Spike Energy Diagnostics (and Similar Techniques)

History, Usefulness & Future Outlook

by

François (Frank) Gagnon

© 2006 by Frank Gagnon

The use of the CMVA logo does not indicate any endorsement by that organization. This paper or its original version was presented at a CMVA event.

October 2006 / Frank Gagnon

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Spike Energy Diagnostics (and Similar Techniques)

History, Usefulness & Future Outlook

by Frank Gagnon, Vibra-K Consultants Ltd.

ABSTRACT

Analysts may already make good use of available HF / ultrasonic functions but at times forget the origin, specifics and significance of these peculiar approaches, as well as potential pitfalls leading to improper diagnostics. This justifies the choice of including a number of trademarked functions in the same paper. They are ALL, in fact, germane to one central concern: high-frequency, stress-wave and acoustic-emission (AE) based diagnostics. Furthermore, they all detect or corroborate the same aspect of our work. History went: NDT Acoustic Emissions technique led to the Shock Pulse Method (SPM). Followed Spike Energy, HFD, Acceleration Enveloping, SEE and PeakVue while in parallel, appeared the Kurtosis Meter and the simple Crest Factor. 1) The Bearing Life Context Once a millwright handles and mounts a rolling-element bearing properly while availability of adequate and clean lubrication is maintained, the probable causes of failure largely disappear, with the notable exception of material fatigue. And even the life-threatening effect of that particular mechanism has been beaten back considerably, as we will see. The bearing’s life depends on proper design and manufacturing practices, and once installed, also must rely on the amicable restraint of the working environment: cleanliness should remain constant, and potential chemical or other types of attacks should be eliminated. From that point forward, life depends on the ability of the elastohydrodynamic (EHD) lubricant film to maintain rolling-elements and races apart, as well as providing some cushioning for cage web, alveoli walls and element Hertzian modulation events. Whether created from oil or grease, the thickness of the film “shield” barely manages to maintain a sufficient separation of the combined “height” of surface imperfections from facing components (such as roller and race). In other words, asperities (surface roughness) can pierce the film thickness. Hydrodynamic Film & Pitting When the one of the spurs pierces through the film, it leaves either indentation or salient point on the opposite surface. Steel will behave like modeling clay: if two pieces are pressed together, the resulting surfaces can

be altered by receiving / losing material to the other piece, although in the case of steel, it will not be through adherence unless the load is immense, but rather through embedding (of one side’s spurs or salient projections into its neighbor’s surface). Race surface pitting or miniature craters arise from the previous mechanism. Bearing Life & Fatigue Damage Bearing life is calculated in function of the environment, taking potential contamination hazards into account, and in virtue of the expected number of cycles of rotation confronted with a combination of radial and axial loads, both static and dynamic. The industrial standard remained B10 or then L10 for decades, and while machinery design engineers remain aware of the two usual targets, most people involved in condition monitoring and reliability lack exposure to the two key numbers: 50,000 or 100,000 hours. Translated back into mundane expected life, that’s respectively 6 or 12 years. Steel shows an inordinate capacity: unlike (most) other materials, if the load-supporting component is made large enough relative to the combined loads it supports, the cyclic loading will not reach failure, in spite of continued in-service exposure. This meant a potential for a permanent bearing, but “permanent” only applies to fatigue. So in spite of increased cost (larger components), they STILL might fail due to contaminant exposure, lubrication problems, etc.

Further research into failure mechanisms improved our comprehension: we now grasp that fatigue occurs where dislocations join up. Inclusions (contaminants within the bearing’s steel) create material imperfections or voids. Rolling (from the load) favors crack propagation from one such void to the next. Successive cycles of passing rolling-elements then favor spalling (dislocation of a metal scale). The conjoining of dissimilar crystalline structures at an interface located within the steel also likely favors void creation. The difference in structure appears due to steel hardening (done through a heat treatment such as quenching; in the case of bearing components, manufacturers typically limit such quenching to surface or “case” hardening). A very hard steel offers a better resistance to deterioration over time, so a hardened “skin” or strata (bainite to perlite) reaches down until the steel crystalline (phase) composition changes to a different composition, still tough, but somewhat more flexible, somewhere below the surface. Such choices largely depend on the end application for the bearing. A “straight” through hardening method leaving the entirety of rings and rolling elements into martensite (another crystalline structure of steel) can also be used. Obviously, a “through” treatment eliminates the potentially troublesome interface area. If the steel contains fewer and smaller contaminant inclusions, and was cast with a care to lower oxygen1 contamination, the end product proves considerably better at enduring without traces of fatigue into a long, productive life: a threefold increase (or sometimes even more) of fatigue life is thus easily reached. Such understanding of bearing failures occurred through experience when analyzing bearings removed under recommendation from the condition monitoring departments of many a plant.

1 Low oxygen levels during smelting also proved a factor in favoring longer bearing service life since this limits the oxidization facilitated by high temperatures. We can equate this to elimination or reduction of rust particle inclusions.

Extensive work is needed to reveal these faults: NDT, cutting, electron microscope inspections of the “slices”, acid etching of surfaces, all told, the type of work performed by a well-equipped materials sciences laboratory. For most plants, this approach can only be obtained when sending the removed bearing to its manufacturer, paying to have the bearing thoroughly examined. This was much more often required before the causes of invisible damage were known.

Figure 1 / Cavities in bearing steel from contaminant inclusion, from Ref (9) Current plant maintenance approaches differ greatly from those of the past: properly interpreted and presented data does support a damaged bearing conclusion. Yet, still seen in some places, often from a transmission of bad habits, the “old” way sometimes persists: a “failing” bearing is mistakenly understood as one that has failed and finds itself as debris. Considerable progress has been made. All the training sold over the past 20 years must bear fruit: while we do want to extract as much life from the bearing as possible, proper asset exploitation should not tempt fate through protracted service once damage becomes evident. Operation prolonged well into the “danger zone” where imminent catastrophic-failure increases in probability makes the risk untenable. Once we identify the principal mechanism causing a bearing’s fatigue spalling, our mental image of incipient defects becomes clear: micro or even nanovoids from contaminants form dislocations or separations located below the material’s surface. These patches of “unglued”

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material grow in size, but should the bearing be removed, still remain hidden from view. Defect size growth implies the spreading of a fracture from one void to another. Voids under load (a passing rolling-element) would tend to compress, causing a (very) minor impact. As voids grow, these impacts or shocks grow in magnitude. There are significant challenges to reliable detection of bearing damage: a bearing sits in some type of housing (pillow block, lodging or other), access to the bearing’s “skin” (outer ring surface) remains scarce (although it has been attempted2), and such can even be qualified as undesirable due to contamination concerns. There can be ever so slight relative movements between the bearing and its seating or surrounding walls. The bearing also transmits dynamic loads through a fluid-barrier. And some bearing components “float”: the criticality of any cage-related vibration is well known, a consequence of its well isolated position from any real transmission path since the cage only touches (we also expect to find lubricant here) the elements which in turn meekly transmit any cage “message” to the raceways (through yet another film of lubricant) and then through the bearing’s support to the outside world. 2) NDT Acoustic Emission The late 60’s brought research into sciences enabling to find the presence of damage in mechanical components. Acoustic Emission (= AE) got its first working committee in 1967. The technique uses a microphone to listen for faint noises arising from material “giving a little” under strain. Example: a storage tank may be sealed hermetically and pressurized while recordings are made to listen in to AE: creaking, pings, pops and other abnormal noises would be indicative of damage. As research moved forth, what tools were available were applied to any

2 Bently Nevada’s REBAM system targets the outer ring of a bearing with a displacement proximity probe. Unfortunately, vibration generated by incipient deterioration can still at times go unseen in this fashion. Installing such a system can be expensive given the prox probe lodging requirement: the pillow block must be drilled and tapped.

number of items. Rolling-element bearings were one of those! Figure 2 / AE Event, Ref (4)

The AE sensor usually covers a target frequency range of 100 kHz to 1MHz. This means capturing events with periods falling in a 1 to 10 μsec range. Shorter period events cycling for an equivalent or longer time would also get measured. AE-based methods have been demonstrated to detect damage as small as 0.25 microns (1/100th of a thousandth of an inch; 0.001” = 25 μmeters). This could otherwise be described as “extremely light” pitting. By the same token, depending on what we seek to isolate from the signal, too much precision can be undesirable for our ends. For example, in an AE context, as far back as 1984, “the... response of the AE sensor was puzzling since the transducer was responding to once-per-ball distorting in the casing at frequencies as low as 1Hz”3 Obviously too much of a good thing! Since micro-modulations are inherent to bearing operation, and considering how much we seek to know, we must still avoid triggering any over-reaction or false alarms. It is largely misunderstood or misstated in literature, perhaps at times in slightly disingenuous fashion, that AE measurements only perceive stress waves. Acoustic emission measurements do perceive strain-linked activity (such as listening in on a tank while it is subjected to internal pressurization), but performing AE measurements on rotating machinery will

3 McFadden, P.D., Smith, J.D., “Acoustic Emission Transducers for the Vibration Monitoring of Bearings at Low Speeds”, 1984 Proceedings of the Institution of Mechanical Engineers, UK

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read / perceive / measure ALL activity falling within its measurement bandwidth. On a running machine, relative to design specifics of course, there are quite a few potential sources of, for example, Fn excitation. Putting it in extremely blunt terms, high-frequency / ultrasonic functions are variations on a theme, but nobody really likes us to put in those terms. 3) The HF / Ultrasonic Functions Shock Pulse Method The wild 70’s gave rise, amongst other things, to the advent of a Shock Pulse Method technology. Its precise bandwidth focus seemed largely empirical4, based on research work likely steeped in Acoustic Emissions5. SKF distributed this technology under the guise of the SPM meter. It was the only condition-monitoring item in the SKF catalog of those days, making exception of such classics as the stethoscope and its faithful companion, the thermometer. In some ways, the SPM item felt and looked “right” to the millwright of that period: akin to a more accurate, instrumented version of the stethoscope (or screwdriver for some), it appeared to perform as a listening device, but reality attained a far greater complexity than what was intuitively imagined by its users. It had borrowed from Acoustic Emissions, and was listening in on “stress waves”, although the expression might not yet have been coined at that point in time.6

4 Arising from experimentation. 5 The timeframe fits, with American AE NDT committees forming in ’67, Shock Pulse getting filed in ’68, patented in ’71 and SPM being born as a corporation in 1970. 6 While we could assume “stress waves”, it would require considerable advances for instrumentation to adequately model their propagation. As an approximate timeline, late 70’s and the 80’s allow ”stress wave” hard science to evolve until dedicated sensors appear in the 90’s. Stress wave velocity CAN be measured, and it has its own NDT approach, involving the use of an impact hammer, and the measure of the frequency or frequencies produced by the impact. Wave propagation will be ALTERED by the presence of a discontinuity or a variation in material density. Most will

The SPM approach measures the mechanical shock speed, measuring the compression wave produced when rolling-element and race interact and with damage or failing lubrication, eventually, collide. When contact occurs, a surface reaction manifests as a compression wave and travels at the indicated speed of sound within the given material. In practice, field evaluation of the signal required a certain degree of sophistication and some manipulation on the user’s part: while a rotating wheel allowed to make sensitivity adjustments in virtue of shaft diameter and RPM (this adjustment likely defines the time unit for SPM’s listening over one a period of a single shaft revolution). Early models also required the operator to “listen in” and set the threshold above which the noise “pops” from bearing shocks and fatigue cracking were no longer heard. This meant a certain amount of subjectivity. With headphones to be worn and values to jot down manually, the contraption was unwieldy and often unpopular. At that time, negativism concentrated on those issues, but the degree of variance introduced by the “listener” rarely influenced measured levels to the point of either exaggerating or obliterating an alarm. The original SPM required RPM and also bearing bore (presumably to fix the proximity of bearing component natural frequencies to the “listening” frequency range and probably correct accordingly: for a given bore, component size can be estimated fairly accurately). Nowadays, the “new” SPM also uses the bearing’s ISO number.

recognize this method as a close relative of FRF (Frequency Response Function) analysis. It is used on museum wood pieces, steel plates, etc.

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The SPM accelerometer’s 32 KHz7 natural frequency would capture what we now call a “stress wave’s shock front”. Given SPM’s first to market status and its aggressive market-resurgence, understanding their approach may prove beneficial for all. A fault-free working bearing (properly designed and selected for its application, under normal loads, adequately lubricated and operating uncontaminated within a reasonably survivable environment) generates friction AE activity (acoustic emission) to the tune of a “carpet value” relative to RPM and shaft size (bearing bore). Empiric testing established a table of such normal noise level expectations, or a quantifiable “Carpet value” measured in dBs (the decibel logarithmic scale here refers to the transducer’s voltage where the reference is 100 μvolt). A brand new bearing entering service already has an expected Shock Pulse value measurable in dB. In the same way as it would to our ear generate a regular, unvarying noise8.

Figure 3 / dB level Progression, Ref (3)

7 One source reports the current design as 36 kHz instead, but this remains unconfirmed. 8 Presumably, the presence of rollers versus balls or double row versus single row would also have an influence. In the case of Spike Energy, we will mention what allowances were made in severity considerations for such variants in configuration.

This baseline / carpet value holds friction noise, but also the modulation noises from elements entering and leaving the load zone, the contacts of elements and cage, the rolling noise of the elements themselves, the occurrence of sliding, normal or not, etc. Even at that point in time, minor noises from impulses will rise above the average carpet noise. The maximum observed excursion reflects the number of shocks from all sources. A phenomenon such as the slight “catching” of an out-of-round imperfection would be much more pronounced and would generate a rise of the maximum rather than in the overall noise. Clashing surface finish protrusions also contribute to the maximum. While some reference sources equate a) the Carpet value to the state of the lubricant and the film it forms while also stating b) the maximum value reflects the actual state-of-health of the bearing, BOTH values evolve over time. This yields not two, but rather, three values: the carpet, the maximum, and the difference between them. Assigning carpet = lube and max = bearing condition can be called a reduction or oversimplification, but it does approach a fair description of reality. It further meshes with Reference (10)’s “From the comparisons of the energy distribution versus frequency within stress wave generating events, it is concluded they are similar with the exception that the equivalent contact time for friction is less than that caused by impacting by a factor of 2-4 times that from impacting. This translates to the frequency band where the dominant energies resides will be higher (factor of 2–4) for friction generated events than those from impacting events.” Emphasis (bold) was added by this writer. Why should the lubrication-linked factor grow in “amplitude” or rise as the maximum does? After all, some bearings are system-fed with circulating oil and do have filtration to remove impurities, contaminants and debris. Obviously, the carpet-noise is not just lubrication related, but close enough. Carpet noise will rise as the population of small deformations or shape alterations “rub” or contact neighboring surfaces.

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The “carpet versus maximum” approach finds a parallel in classic vibration parameters whereas a bearing deterioration progressing from an incipient fault to a serious one will often see: - relatively stable RMS amplitudes, eventually followed by a rise - a contrasting sharp rise of peak amplitudes, followed by a decline - a quick rise and then a fall of the Crest Factor (qv), meaning of the relative values between Pk and RMS. Take note that the original SPM only devolved overall values, but recent versions also offer shock pulse based spectra, not as a diagnostic tool but rather as a bearing-defect frequency confirmation item. The SPM invention was clearly the very first to monitor bearings based on an accelerometer’s signal within a resonant high frequency / ultrasonic band. SPM quantifies the efficiency of lubrication, whereas most other approaches detect failing lubrication, but do so without any great detail. That is a significant nuance. SKF’s SEE (apparently abandoned / no longer supported: option not offered in current products) did yield a lubrication quality value. The ultrasonic detection grease guns that first appeared some 10 years ago fulfill a similar role. Shock Pulse first introduced the simplifying approach of green-yellow-red alarm code later recuperated by numerous vendors. Repetitiveness of the measurement location and possible angularity effects of the hand-held probe already were and might still be issues: such problems have plagued data collection for some time and have, by and large, finally been eliminated through the favored use of sensor magnetic mounting. Analysts immediately recognized, though not always fully embraced, that the SPM meter did something more for them than the mere collection of classic vibration parameters. The concern in the field then became one of having to measure the compulsory and much needed vibration (velocity, acceleration or otherwise) with one instrument while alternating with the SPM unit, or running two different routes on the

same “race track”. Considering the usual anxiety of any purchasing department to spend money, particularly on something that would be used for maintenance, combined with the enthusiasm of doubling one’s data collection workload, the concept was found unsavory. In today’s context where companies wish (as in “wishful thinking”) predictive maintenance personnel to monitor hundreds of machines with vibration while simultaneously applying other techniques, complaints would surely arise... As a note, many companies merely ran SPM tests and managed quite a few “saves” leading to an excellent ROI (return on investment), but that doesn’t mean that desired reliability targets sustainability could be achieved in this fashion alone. SPM’s main advantage, 30 years after its birth, is that its parent company has stuck with it, creating a huge database and refining the process along the way. Former limitations, the absence of the other vibration parameters, have been resolved by offering instrument models that cover the gamut of diagnostic functionality, offering collection of the remainder of normal parameters as well as spectral information. Since SPM confines itself to a very specific frequency area, screw, lobe and other compressor-type OEMs often recommend it as a tool of choice for monitoring their machines. The reason for this preference is simple: “normal” parameter spectral data (such as velocity and acceleration) tend to be highly saturated (contents shows high amplitudes and a dense peak population), making analysis feasible but complex, and thus requiring considerable proficiency, whereas the lubrication analysis and simpler “bearing report” of the SPM seems to provide a more readily usable picture. Prüftechnik currently (or until recently) includes a version of shock pulse measurements in some of its instruments. Since no SPM licensing seems implied or mentioned in available literature, it is likely based on a reworked or recycled shock pulse approach based on the by now expired original patent.

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Stress Waves example, while an accelerometer seeking stress waves should have its primary resonant frequency between 30 KHz and 40 KHz. Several problems may arise should sensor design fail to completely eliminate the occurrence of any secondary resonances from the high-frequency zone of interest since noise contamination from other sources will then 1) affect, and 2) be counted within the stress waves’ amplitude level. This affects measurement accuracy and therefore, undermines repeatability.

Surface disturbance propagation or stress waves remained little known in the late 60’s and early 70’s. Their inclusion out of historical sequence has a lot to do with their capture by the SPM instrument. By definition, a stress wave is an extremely short TRANSIENT phenomenon: an impulse-born wavefront hitting the transducer, whether shock pulse model or otherwise, causing an oscillation of the sensor's mass-piezo internal assembly. The oscillation dampens out quickly. The exact mechanics depend entirely on component design and assembly. Stiffness, mass (and thus, the resulting natural frequency of the assembly) and damping, all may affect response. Peak amplitude will be a function of impact velocity and depending on the exact measurement type, of the material through which the wavefront must travel. As such, they are best described as high-frequency structure borne (ultra)sounds.

How is SWAN technology different from Shock Pulse Method (SPM) and other high-frequency schemes? Relative to SWAN, Shock Pulse Method (SPM) has low diagnostic accuracy, reliability, and not realistic ability for projection of remaining useful life. Shock Pulse Method and demodulation are older, traditional methods of condition monitoring that also base their findings on high-frequency sound to measure energy just as SWAN technology does. However, SWAN technology has distinctive and proven advantages over these technologies and differs in the frequency range used, sensor design, and in signal conditioning. - Swantech website

Any time stress waves are considered, the running parameters (RPM, size, and additionally, lube type9 and even bearing design versus load, although this last one is disputed by some) play a significant role and must be best be documented as well as occasionally compensated in the interpretation bias of data.

The previous statement may be somewhat gratuitous, considering that SPM inventor Söhoel’s patent filing specifically stated a 30 – 40 kHz band, while one of Swantech’s patents (US Pat #6,679,119) states “...it is preferred to detect stress waves in a narrow frequency range such as, but not limited to, 35 kHz to 40 kHz.”

A narrowed frequency range of 35-40 KHz allows us to perceive stress waves from friction and impact sources propagating through machine structures at detectable amplitudes. By the same token, it may be wishful thinking to believe that a mere bandpass filter would suffice in isolating stress wave measurements from the perception, capture or inclusion of other phenomena entering that same frequency zone.

The bandpass filter slope would need to be draconian to make a considerable difference (a 5 kHz difference around a 35 kHz center hardly constitutes an octave or a decade), although the apparent use of the sensor’s Fn amplification range already contributes in limiting its own perception to a narrow sliver of the frequency scale.

Early attempts at detecting / measuring / analyzing stress waves have relied on specially designed and processed accelerometers doubling as stress wave sensors, but shortcomings of both Analog Signal Conditioning (ASC) and Digital Signal Processing (DSP) would obviously favor later dedicated or specialized sensors. For 9 Grease can also play tricks due to its “solid-fluid” nature.

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Crest Factor Simultaneous Development The Crest Factor, highly popular in Europe and currently shown as a sidebar to CSI’s, IMS’ and other vendors’ Time Waveform graphic representations, represents a very basic calculation of peak / RPM amplitudes (whole band). It is preferably calculated on the waveform using the absolute value of peak amplitude (maximum excursion, whether positive or negative). This equals the amplitude maximum if the waveform were rectified. The Crest Factor value, ranging from 1.0 for a square wave, to a more normal 1.41 in the case of a sine wave and higher values as peak activity reaches higher amplitudes over a narrower time period, yields an instantaneous “contents” assessment for the analyst. A tall, narrow peak in a waveform means high amplitude, extremely short duration. This also translates into a negligible RMS value.

Figure 4 / Crest Factor Values Vs Waveform Trending this value for a typical bearing fault scenario would normally show a rise in the Crest Factor value (peak amplitude values increasing while RMS fails to immediately follow suit), and an eventual drop of same. While the parameter can be present in analytical form, no trending of CF can be found on any (current) condition monitoring software package. A logarithmic scale has

sometimes been used to this effect in the past, although it is a bit nonsensical to trend CF in such a fashion. Kurtosis, Five Bands, Six Values As a function, the Kurtosis or 4th statistical moment largely concerns itself with the distribution of “contents” (samples, or peaks) within the “span” (graph, or frequency spectrum). This can be applied to IQ as much as to vibration or political surveys. Key concept: the Kurtosis seeks to describe whether peak or energy contents is evenly, smoothly distributed, or whether it is highly concentrated, with one (or several) spike(s) / dominant peak(s). For vibration, it then becomes “Are there small peaks buttered throughout the entire spectrum, or are there dominant peaks sticking out at specific positions? Where are they relative to the frequency span?” The actual value will also vary according to location of energy concentrations: at the center, upper and lower tails (ends), and the shoulders (between the center and tails). The descriptors are platykurtic or leptokurtic, where this last qualifies a Kurtosis > 3, meaning in our context peaks sticking out of a normal configuration. The Kurtosis method, developed by British Steel and the University of Southampton in the late 70's, calculates the Kurtosis to assess peak distribution within each one of five distinct filtered (bandpassed) frequency bands or “spectral slices”. Some of these bands were wide enough to qualify as “regions”. The Kurtosis was thus calculated for the following spans: 2.5-5 kHz, 5-10 kHz, 10-20 kHz, 20-40 kHz and 40-80 kHz. The Kurtosis values were displayed and stored individually (under b1, b2 for band 1, band 2, etc) as well as summed up in an aggregate “figure of merit” value, reflecting the spreading presence of peaks within spectral higher frequency contents. There were no special provisions to ensure reasonable high-frequency measurement accuracy. The 3rd band, covering 10-20 kHz, would already be in trouble if accurate measurement were the objective. The next two bands, 20-40 kHz and 40-80 kHz, are

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clearly “reaching” but they have been confirmed time and again as regions of key interest. With respect to that last band, and while the attempted measurement was surely deficient to some degree (the accelerometer of that time was incapable of reaching that range linearly), it is nonetheless fascinating to compare the science to the Reference 10 statement to the effect that for stress wave consideration of fatigue cracking, “No specific data is readily available to quantify the equivalent contact time at this time; however, past experiences have suggested the duration (and hence, contact time) of these events is less than that from friction-generated events. They would likely still be in the few μsec range (not the nanosecond range), hence the dominant energy would be in the few kHz range (40–80 kHz range).” Within that context, we presumably count the event duration and ensuing dampening cyclic activity. Did this system function properly? British Steel thought so and used it as the heart of its machinery monitoring efforts for some time. While the science may at first seem slightly complex, little or no interpretation is required, meaning no training on the part of end-users. Why then did it not grab a larger market share? From memory, the meter offered a route system with the velocity or acceleration overalls as well as the Kurtosis. For 1985-1986, it delivered decent value in the $5-10K price range, but was hobbled by lack of spectral measurements (needed for better diagnostics), limited distribution and a rabidly (pun intended) evolving market: the newfangled thing was that our instruments were to keep pace with computer developments (at a bit of a distance, but still). As is often the case for lower sales volume products, too slow a payback likely spelled a limited capacity to redevelop the next generation. Spike Energy Measurement Technique Other companies caught on, and IRD Mechanalysis (eventually Entek IRD, and now RA Entek) sought to emulate the SPM approach. There was a market for this sort of thing, and the field-proven approach

sometimes left classic parameters in a lurch. Completing the measurement capacity of IRD vibration instruments while avoiding the original SPM’s perceived pitfall, which called for a cumbersome switchover from one analyzer to another to complete the full machine behavior picture, IRD prevented the duplication of certain field tasks and Spike Energy completed standard parameters (displ, vel, accel) into a first instance of the “one system does it all” approach. This was of some importance since ISO 2372 vibration standard had unwittingly prejudiced the perception capacity of peak activity by requiring RMS to be the favored overall. Adoption of a peak-peak detector did a lot to compensate for this state of affairs, if and when the function was collected and used judiciously. In Europe, the Crest Factor served this purpose. The new arrival only provided an overall value, based on a high-frequency zone, partly sonic and partly ultrasonic (sound’s threshold = 20 kHz), empirically determined as the 300K – 3M CPM range (5 kHz to 50 kHz). IRD’s standard accelerometer, the IRD 97010, would become one of the workhorses of condition monitoring. The targeted frequency zone (defined as 30 – 40 kHz with a 32 kHz Fn in SPM, as the reader will remember) moved a bit to the 970 transducer’s inner component Fn (natural frequency) of 27 kHz. The overall measurement is collected on the same basis (or same filter) as would be the spectrum and is expressed in units of acceleration “g” with the notation SE to underline the bandpassed nature of this retained or filtered portion of signal contents. In the same way as if you threw out half the contents of this paper, it would be impossible to read the missing pages, the g-

10 The 970 accompanied IRD analyzer models 810, 820, 840 and 880, data collector models 817, 818, 840, as well as the Fast Track, certainly the hottest selling collector of its time, and remained an option for early DataPac purchases. All told, this one sensor got widely distributed for the better part of 20 years.

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SE overall (or spectral contents when an FFT is collected) does not allow a backtracking calculation of acceleration. Once spectra were to be obtained from Spike Energy, a selectable high-pass threshold of 100 Hz, 200 Hz, 500 Hz, 1 kHz, 2 kHz and 5 kHz (the previous standard) appeared. The upper cutoff (or low-pass filter threshold) sits permanently at 65 kHz. Spike Energy’s high-pass filter seeks to reject lower frequency signal components, such as unbalance and misalignment, since amplitudes from gears or bearing defects tend to be much smaller than those of rotor behavior (1X, 2X, 3X RPM, for instance). Larger amplitudes tend to cover up the tinier peaks of impulsive or impacting nature. Spike Energy preserves the severity of defects by holding the peak-to-peak amplitude of the impulses, reflecting the amplitude present in the waveform on the negative side of the signal. Usual acceleration measurements are solely “peak” g’s or m/s2. As a passing note, at least one API standard referred to pk-pk velocity to precisely avoid the possibility of missing key information. Later, when replacements were considered for the 970, the major concerns arose from market-driven economics, with Spike Energy capability taking a remote backseat. What customers want, customers usually get and the inconvenient obligation to use an IRD 970 accelerometer needed to make way for the marketplace’s newly appearing product (not to mention falling sensor price). A range of accelerometers became available, but each one would show a different natural frequency for its internal components, and thus, major discrepancies in gSE measurements could (and did) occur. Whether from lack of damping in the area of concern or from other design peculiarities, one widely distributed accelerometer model just created havoc with widely (wildly) varying Spike Energy amplitudes leading to completely useless amplitudes and incoherent trending.

If the filter width (band pass) varies, the end result (gSE overall) would also change. Many users have observed the sluggish reaction of Spike Energy amplitude, when observed over time (whether with an older analog meter such as the 810, or with a modern LCD screen): unlike the quickly reacting classical parameters, g-SE levels show a “laborious” rise time and SLOW DECAY. This feature is inherent to gSE processing. What it means: cumulative or multiple event impulse energy is required to push the g-SE level up. A period of quiescence is needed to settle back down. The delay prevents amplitude modulation (AM) from imposing their fluctuations as repercussions in gSE amplitude. In recent years, the reactive feature has been further enhanced in becoming adaptive when spectral data is collected: to avoid having a single decay constant that might create a “solid wall” (flatline) in the waveform, the decay constant became proportional to the frequencies manifest within the Spike Energy signal. The damping of internal components also was to have some influence on the resonant response and thus, on the amplitude. The better a peak finds itself centered “into” the response amplification “bell”, the greater the perceived amplitude (from a rise in amplitude response of internal components). Quick overview of Spike Energy, then: - expressed as gSE units11 - extracted from acceleration - using peak-to-peak detection - bandpassed from 5kHz – 50 kHz - later from “user selected” – 65 kHz - sensor internal component Fn MUST be

near center of bandpass - built-in delay in rising or decaying - sensitive to friction & repetitive though

not necessarily periodic, impacts

11 gSE could be called “impulsive” or “impacting” g’s

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changes in perceived amplitude, voiding or hindering the trending capability, an obvious difficulty for variable speed machines given their proliferation in the marketplace (VFDs and a renewed desire for energy savings).

Application & notes - measurement must be trended - easily compromised, but... - good indication of spurious data - sensitive to lubrication issues

- good indication of bearing problems Lower damping means more sensitivity to the previously described “moving frequency” peak issue.

- higher amplitudes for rollers (two ends) - higher amplitudes for double row - first and foremost a DETECTION tool12 The genius of this approach obviously enabled the capture of “something” within a range of frequency that was unattainable for measurement under normal monitoring practice. It grants an overview of what might be going on in that inaccessible region, so in a way, it might be called an impressionistic rendition, or perhaps, “something for nothing”. Figure 5 / Q (resonant amplification factor) Vs. Frequency Match (forcing / natural) for various damping coefficient (zeta) Figure 6 / Tightly Fitted Filter, centered on

sensor Fn, Ref 7 (Patents) If accurate response were a concern for HF / Ultrasonic function, we would almost require a correction curve of amplitude in virtue of frequency, since amplification provided by a lowly-damped sensor internal assembly will also tend to alter the amplitude significantly in relation to Ff/Fn (forcing frequency defect versus natural frequency). As can be seen in Figure 6, a glove-fit of resonant amplification and filter is possible, such as in the case of a narrowly targeted Stress Wave sensor, but hardly feasible on a function such as Spike Energy where the bandwidth covers a much wider range (5 kHz – 65 kHz) and where a high-damping value would limit the function’s efficiency, whereas a low damping value (high amplification) defines a hyper sensitive frequency “area”. Again, centering on a value (sensor component Fn) that we leave, by design, outside of the standard measuring range clashes with desirable features of our accelerometer: the price for accurate high-frequency measurements is time-efficiency (thus, $$$). Consequently, a transducer rated to 25 kHz (requiring rigid mounting) with a 60 kHz Fn probably yields great HF measurements, but likely behaves poorly for quick Spike Energy detection.

Since the frequencies are perceived through a resonant response of the accelerometer’s internal components, the amplitude itself can mean very little EXCEPT when trended (compared to itself) over time. Moving a frequency around within the bandpass, which occurs whenever the machine RPM varies, also moves the generated frequency with relation to the natural frequency. This would lead to

12 The gSE spectrum would be the diagnostic tool.

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Severity A Spike Energy severity chart was eventually empirically developed by the Ford Motor Company. Widely distributed by the trademark holder, the chart showed g-SE amplitude versus SPINDLE (machine tool) shaft speed (FIGURE X) many complaints arose when pulling bearings that failed to SHOW evidence of damage. Of course, we now fully understand that failure mechanics may often hide any VISUAL signs of fatigue. Figure 7 / gSE Severity Chart

Several factors could otherwise have led to erroneous calls: - Failure to trend measurements - Careless or improper measurement practices - Failure to double-check (validating the measurement) - Appearance of other components contaminating the signal13

The prevalent factor of interest when assessing Spike Energy measurements remains the increase of amplitude (and/or appearance of spectral peaks) in an otherwise stable (unvarying) context, meaning the Spike Energy goes up (or peaks appear), and everything else stays

13 Potential contamination from other vibration sources was and remains possible in spite of filtering, given the quantity and nature of potential nearby sources to the subject of interest.

the same. If the measurement is valid, you have a clear case! The reverse, failure to capture an incipient or advanced fault, usually only involves the “immeasurable”: long distances, multiple interfaces, masking secondary source contaminant, etc. Keeping this in mind, assessment of a bearing without available prior (reference) data or trending remains feasible, but doing so requires great care and should be left to seasoned analysts.

While the 970 was still in vogue, this writer’s approach usually set gSE alarm at 0.3 or 0.5 gSE, but this would now depend on the accelerometer used (the current difficulty with both Spike Energy & PeakVue, generic functions sensibly functional with almost any accelerometer). To explain the previous choice, an external resource needs to be more sensitive than an ever-present one, and getting an early warning proved very useful. Obviously, many points called for alarm-level readjustment, also useful when starting a monitoring survey since the “already troubled machines”

are then easier to spot and can be segregated from the naturally noisier units. High Frequency Detection / HFD14

Since Shock Pulse and Spike Energy required “hard-wiring”, the best emulation to get a similar (competitive) result became the simple bandpass applied to acceleration with no further processing. Internal programming came to the fore later. In SKF’s case, HFD was performed on a 5kHz to 60 kHz range, whereas CSI gave themselves the opportunity for variants: “the amplitude of vibration in g's over a broad frequency band from 5 kHz up to 20 kHz or greater”. SKF’s was fairly close to the initial Spike Energy bandpass, but did not offer peak-to-peak or rectified / True Peak

14 “A dynamic high frequency signal from an accelerometer which includes the accelerometer’s resonant frequency. For assessing the condition of rolling element ball or roller bearings.” – SKF Condition Monitoring, Catalog, 2000

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detection. It is a matter of record that SKF and CSI HFD values DID NOT MATCH and were not interchangeable if a program switched from one to the other. As a warning or detection system, HFD offered a reasonable performance. SEE SEE (SKF’s Spectral Emitted Energy): method of monitoring bearings combining high-frequency acoustic emission detection in the 250-350 kHz range with enveloping techniques. Use of a low pass filter fulfilled an essential role identical to what was needed for Spike Energy, conserving low-frequency modulations (enveloped peaks) components to easily link back to known bearing defect frequencies: the enveloped signal (demodulated) can be decomposed using a normal FFT instrument, although the technique obviously implies that peaks remaining in the spectrum found their source in modulations contained within the original (and since altered through filtration) signal. Enveloping / Demodulation Enveloping can be defined as a technique using a less detailed curve to espouse the contour (outer shape) of a denser waveform. Initial efforts likely go back to B&K in the late 70’s, early 80’s. Enveloping is still performed on raw or bandpassed acceleration signals to extract hidden components: curve fitting or molding of the outer shape of the waveform can as readily be done on an unprocessed waveform as a filtered one. The curve or “mold” replaces a waveform. This new waveform is then FFT processed. It is also the universally used technique allowing the production of FFT from a higher frequency contents area back down to a region where defect frequencies may become more apparent. That last region can be defined to extend as high as 3-5X BPFI or 6-7X BPFO (they are roughly equivalent), and also apply universally. The filtered or bandpassed signal is full wave (or half wave) rectified (the negative or lower portion is mirrored to the positive and then eliminated).

The now fully-positive rectified signal is low pass filtered to separate modulation (usually the defect) frequency from its carrier frequency. Low-pass filtering provides an averaging effect on the rectified signal and peaks get smoothed out in the enveloped or demodulated waveform. For gSE, peak-peak values are retained instead of rectified. Certain well established “rules” (of thumb?) apply to enveloping and were initially graven in stone with g-SE spectra, since there were no possibilities of opting out or choosing differently. Under normal circumstances, for best results, desirable separation between band-pass threshold and demodulated FFT spectrum Fmax would be FIVE to ONE. Example: for gSE spectra, initial (Fast Track model) high-pass was set at 5 kHz (300 KCPM) and Fmax at 1kHz (60,000 CPM). The rule was dutifully obeyed. Can the ratio be altered a little or significantly and still yield decent results? A 10:1 ratio can be attempted, or a 2:1 in certain cases of low frequency. Variations are needed in virtue of the variable high-pass threshold shown below.

Figure 8 / Threshold values for gSE spectra

Figure 9 / Appearance of gSE waveform Specifically for g-SE signals, the waveform would not be very revealing since

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rectification and prolonged decay affect the data, altering considerably both digitalization values and visual information (see previous Figure), but the modulations would still get extracted (to their modulating fundamental), whereas PeakVue waveform may still maintain more information. This essentially boils down to the moment in the processing sequence at which the waveform is captured and displayed. PeakVue TWF, seemingly caught before rectification and demodulation, show information differently than Spike Energy TWF displayed after the same two operations have taken place. Enveloping Numerical Analysis In an attempt at further strengthening SEE technology, SKF attempted a breakdown of SEE values into frequency bands, an approach reminiscent of the British Steel Kurtosis meter (qv) of the early 80’s. Given the technology seems to altogether have disappeared from SKF’s online catalog (at least currently), and adding to that the fact that this author has little dealt with it and never in the above specified form, suffice it to say multiple band numerical analysis of enveloping has been attempted. Spike Energy & PeakVue Spectrum Once decay of spike amplitude gets slowed down, the wave generated by an impulse will necessarily end up looking like a triangular wave. While it can be argued that a “quasi peak hold” will cause to appear multiple harmonics of the fundamental, a fundamental representing an impulse creates that very same phenomenon of diminishing amplitude picket-fence harmonics of the fundamental.

Figure 10 / Typical gSE spectrum That has been the cause of oft times harsh criticism of the HF/Ultra functions “It invents things. Spike Energy (or PeakVue) throws in

harmonics that are not there !”15 We can likely agree on that, as long as we remain focused on one single fact of importance: the harmonics are of a little consequence given that the fundamental MUST be present as a frequency modulating contents within a higher frequency band. That is all we need to satisfy the “veracity” obligation. This fact is hard evidence, confirming the presence of an anomaly, whether it is lubrication problem or damage per say remains to be seen. Is the purpose of these Spike Energy &= spectra to complete a full diagnostic based on engineering measurements? Does the amplitude matter much when the observed phenomenon is an indication of ACTUAL DAMAGE? The overall “figure of merit” trend of amplitude detected a problem and/or the spectra spotted an anomaly, is that not enough? If we can FURTHER support / sustain / explore machine behavior using this tool, it is merely an additional benefit! In various locations throughout this paper, the pitfalls and dangers of gSE &= signal contamination or bad measurements are mentioned. It is possible to push the overall upwards, but it is very difficult to introduce through happenstance vibration at a frequency that would exactly match the BPFO, BPFI or other defect frequency. Examples are often given of data where the “problem” can be seen in regular data (vel or accel) as well as HF / Ultra spectra. In fact, such are typically easier to draw parallels between the to type of measurements. Here then is the blatant admission: data for which HF / Ultra is alone in providing detection or indication of abnormal spectral contents is a rarity (albeit NOT a complete impossibility). After all, the data did get extracted from a “normal parameter” source, so given time, patience and a will to manipulate the signal for a while, often in ways that will approach Spike Energy &= methods, we will reach the same result, perhaps in a manner wasteful of resources.

15 The previous are not invention on the part of the author but rather ACTUAL quotes and could readily be assigned to people.

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Sensor Positioning While various authors in the field affirm that positioning or direction changes little in the way of perception of defects when using gSE &=, experience tends to point us in a different direction: a) it may be true for stress waves to propagate in all directions, but they are also within an extremely high-frequency range and those tend to not travel very far, b) stress waves are not the only pertinent activity in this context, c) several conclusive tests had shown a significant rise in gSE amplitude in the horizontal or axial direction while the other directions showed little or no increase in gSE or other amplitude, d) whether the previous occurred from pillow block configuration, or from defect shape and position in relation to bearing design and measurement location, is not known, e) the observation would have been impossible without collection of gSE (or other, as the period dictated) in all directions We seek to monitor activity closely resembling tiny hammer-blows (a ball dropping into a race pothole), and given the expected behavior when such an event occurs (blow-directed motion), direction should remain pertinent. We can presume that in most instances of fatigue, damage will first occur in the load zone, and thus, we can choose a pertinent spot for our measurement, BUT, where load is carried along multiple axes, do try to measure along all of them. Figure 11 / Angular Contact Ball Bearing

Imagine a race fault on an angular-contact ball-bearing (thus made for radial and thrust

loads). These can be used in pairs, front-to-front or back-to-back. Let’s presume excessive angular misalignment has worked out a spall, placing the fault more onto the shoulder (thrust) of the rolling-elements’ support. If it is indeed a tandem, it is a given

that measuring axially would likely capture a higher amplitude on the side of the damaged bearing than on the side of its counterpart. Doppler Laser & Interferometer When writing course notes some 3 or 4 years back, the best laser interferometer conceivably usable within an industrial environment (as opposed to a lab) could deliver a precision of one angstrom in displacement, meaning 1/10,000th of a MICRON (1x 10E-10 meter). In terms of “thousandths of an inch” or Mils, the previous means 1/250,000th part of a Mil. Sub-angstrom precisions can now be achieved to ultra-slow frequencies as well as above the 1 GHz level (think in terms of 0.000-something CPM to 60 Billion CPM). While technology offers the benefit of a precise metrology of these heretofore unmeasured (unmeasurable) vibrations, is it useful? Should I endeavor to mount an interferometer on an inertia-block fitted tripod to capture high-frequencies issuing from a 100 HP electric motor? Is this science-fiction? Since 1994, the “International Conference on Vibration Measurements by Laser Techniques” is held every two years in Ancona, Italy (aivela.org). A laser “sensor” first showed up on the vendor side of vibration conventions circa 1995 (discounting the Hewlett-Packard’s that have been around since the 70’s). Some years ago, an interferometer was the sole purview of R&D, but the cheaper ones are now accessibly priced in the $5K range while others can still reach $18K. From an industrial standpoint, it would be a strange case indeed that might require the use of interferometry. Some years back, a 300,000 RPM experimental spindle on pneumatic bearing forced our hand in this respect. But given the scope of our USUAL condition monitoring concern, what we need is a quick, cheap, uncomplicated routine to see if there appear to be abnormal high-frequency peaks. We are well served by our currently available methods.

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Spike Energy Versus PeakVue Given the description of “prior art” in a patent application by people in the know, “A final method, known as "spike energy detection" or alternatively "Peak Vue", has been used by the assignee of the present application as well as others to generate a measure of the high frequency energy in a vibration signal.” Ref (7), #6,868,348. As can be inferred from the previous, processing may still differ to some degree, as does the moment in time when certain bits of information are captured, but the functions seem very closely related. “PeakVue stands for Peak Value. PeakVue analysis is actually a measure of "stress wave" activity in a metallic component. Stress waves are associated with impact, friction, fatigue cracking, lubrication, etc., and generate faults in various components such as rolling element bearings and gears.” 16

PeakVue roughly adheres to the same approach as Spike Energy. Discrepancies occur not so much in processing as they do in choices of when to capture certain events. PeakVue also offers a selection of band-pass as well as high-pass filters. Condition Monitoring Fallacies & Pitfalls “Immune to or not affected by a rise in amplitudes linked to other phenomena” might be obviously applicable ONLY when the newly appearing or developing phenomenon does not cause the appearance of signal contents (new peaks) within (or very close to) the band-pass. The “very close to” implicates the limitations of the filtering: a band-pass filter is not usually a guillotine. It is of varying efficiency, usually expressed in terms of dB/octave or dB/decade, where dB will be a multiple of 6 (since a reduction of 6dB equates a halving of amplitude) while an octave means “for a doubling of frequency” and a decade signifies for a frequency change of one magnitude (=X10). Example: For a 6dB/octave (halving amplitude per frequency doubling), an amplitude of 0.5 g at 250Hz will be perceived as 0.25 g if the threshold is set at 500 Hz. 16 CSI 2004 End-User Conference Leaflet

How sharp an amplitude rise also affects the outcome: ringing occurs within a bearing when unbalance forces shake things about. Same is true of misalignment. The greater the movement, the more aggravated the ringing becomes and commensurately, the contamination of the Spike Energy signal with a variety of minor natural frequency responses (resonances). In some poorly fitted cases, otherwise tolerable looseness (usually of no consequence) may start acting up and causing impulses between shaft and inner ring, or bearing and pillow block. To some degree, we might say that the “carpet level” rises a bit. Examining the same through an AE lens, severe unbalance, misalignment or other noisemakers can cause alternating-stresses on the bearing and its supporting structure, thus working out a “pinging” effect within the perceivable AE (or other) range. While the previous statement remains true in most cases, meaning a slight increase in unbalance or misalignment related amplitude will usually NOT affect Spike Energy amplitudes overly much, there will be notable exceptions, namely when the rise in amplitude from any source doubles, and/or when the amplitude reaches 0.3 inch/second pk. An attempt at trend weighting was attempted in the past and showed some promise (the author’s own Ref 2), but was not pursued beyond the initial stages, though it was finally assessed that the proper weighting factor hinged on the amplitude root-sum-square of the first three orders of rotation, as in a relation to... ___________________ √(a1x)² + (a2x)² + (a3x)² with variations in virtue of machine specifics: since generation of a wide array of harmonics, such as harmonics of a compression cycle in a lobe-blower (4x, 8x, 12x, 16x, or other series relative to rotor configuration) or similar machine-specific behavior such as blade-pass frequency peaks also needed to be taken into account, the approach proved fairly accurate but impractical unless built-in. Looseness is sometimes erroneously mentioned as another mechanism not likely to affect Spike Energy &=. In fact, some of

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our HF/Ultra functions are excellent at spotting looseness and very often useful in pinpointing its location with accuracy. Again, the lack of transmissibility of high-frequency comes into play. This time, instead of hindering as it usually does, it may serve our purpose. Finding the exact location of looseness is often difficult, but since HF travels with difficulty, the resonant “pings” from rattling components may be easier to pinpoint than the exact source of 1X and/or 2X and/or multiple harmonics of a fundamental. The reader has already seen some of the inherent differences between these functions, hence, no surprises should arise from a statement to the effect that the previous paragraph is entirely relative. The best method to pinpoint looseness relies on amplitude mapping (exploration of the structure while moving the sensor around slowly to find amplitude maxima). Fallacy: “We are collecting acceleration measurements” when Spike Energy &= is collected. A processed / bandpassed peak detection function is NOT the equivalent of acceleration. Fallacy: the reverse of the previous, or “We are collecting Spike Energy measurements” when in fact, acceleration was collected. This honest mistake arose due to potential misunderstanding when switching over to Entek Odyssey software. Basically, the Spike Energy function did not have its usual units assigned but remained as an easily mistaken “g” without the SE appellation. Memory fails as to whether the label was deemed Spike Energy with g’s or Acceleration and then might have had a subheading of Spike Energy. g-SE & Fluid-Film Bearings Fallacy: “High-frequency / demodulation functions serve no purpose with fluid-film bearings”. This assertion was initially made by people who understood that Shock Pulse, Spike Energy, etc, monitored the rolling lubricated contact of race and element. They theorized (or were told, since some vendors had published documents to that effect) that since no contact existed in babbitt applications, the functions would be useless.

Szent-Gyorgyi, a medicine Nobel prize winner, tells us that “A discovery is said to be an accident meeting a prepared mind”, a statement akin to the traditional definition of success; this writer’s confirmation of Spike Energy’s usefulness for fluid-film bearings arose from condition monitoring software “templating” (using in-house sequence of measurements applied indiscriminately to most machines) combined with time compressions (aka a serious rush) for a program start-up. Much tailoring occurred on the other measurements, but since required time for Spike Energy measurement did not really influence total route time allotment, and given the “spurious measurement spotter” advantage, g-SE was collected every time these (several) air-separation plants were monitored. The gSE got trended until one day, the displacement17, velocity, acceleration, and prox-probe obtained signals (trend and FFT spectra) showed nothing, BUT, the Spike Energy shot up! Babbitt? The data was double checked, and was found to be sound. Measuring g-SE properly detected and reported in obvious fashion the sleeve deterioration. This doesn’t guarantee that it always would, but traces of damage in other data (even at the analytical “under the microscope” time, not at the quick detection time) were faint and easily missed. In another similar case, the author appeared confounded when exacting analytical work performed on the basis of a Spike Energy alarm justified inspection of an oxygen compressor sleeve bearing. The “cruel” customer called to complain that the bearing appeared flawless! After leaving this sword of Damocles hanging in the air for a few excruciatingly long seconds (where one imagines responsibility insurance vanishing up in smoke), he added “But we’re pretty happy to have caught a rub of the shaft with the labyrinth seal!” Distance between the

17 Was used as a comparative between case / pedestal vibration and prox probe results. Often revealing. While few people are aware of this, Factory Mutual used to (and may still) require both and have demonstrated cases where pedestal vibration showed more than the Eddy-Current probes.

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end of the sleeve and the outer lip of the seal is roughly ½ ”, so no amount of vibratory measurement exploration would have successfully separated these neighboring potential sources. Over many a training session, much debate has ensued over this particular approach of using Spike Energy for fluid-film bearings. Of course, over the years, the “Don’t bother” school stuck to its guns, but all those who have used it AND come across CLEARLY identified trouble18 tend to smile knowingly. One colleague used an (older) SPM version to do the same thing, with many instances of confirmed positive results. Does this make sense? a) Think oil! Circulation of oil! Shaft-regulated feed in some cases, circulation in others! A fluid we trust to arrive at the proper location, or serious damage will ensue. This could allow “cavitation”. And with it, imploding bubbles acting as excitation for rotor component resonance, and progressive erosion of babbitt surfaces. Does cavitation occur within sleeves? It is a recognized failure mechanism. Would a normal FFT spectrum covering up to 10X RPM detect cavitation? Not likely: amplitudes would likely be hidden if the RPM is high enough for 10X to reach the relevant frequency span, or the frequency span will simply not cover this mechanism. b) Under abnormal circumstances, metal to metal contact might occur, leading to occasional high-frequency noise. c) Fluid-film bearings can support a steam turbine rotor. Steam leaks occur often enough and oil circulation may promote the aspiration of some condensing steam into the oil stream. Water or water-contaminated oil fail miserably at maintaining protective films. Metal might meet metal. The proximity of the leak may itself be found through a rise in Spike Energy.

18 Lest we forget, on some high-powered synchronous motor, centrifugal compressor or steam turbine, 20 years may go by before the sleeve shows distress. Thus, widespread statistical sampling of detectable faults on large-sized turbomachinery tends to require considerable time.

d) Shaft-babbit or shaft-to-particle-to-babbit (particle could be debris, or fatigue spall) contact could occur. In some cases, a whirling rotor (such as crossing a critical speed event or being operated at an RPM causal to quasi-critical deformation, with or without the help of a rub) could have the shaft mildly entering contact. “Isn't SWAN just for rolling-element bearings? No, SWAN technology works well on and has been proven on rolling element and fluid film bearing and all types of gears.” (Swantech Corp. website). Furthermore, diehard skeptics might want to read Barkov (Ref 1) on the possible use of ENVELOPING to detect fluid-film bearing deterioration. While any of these functions may assist in the detection of fluid-film bearing problems, it can be difficult to perform adequate detection and analysis of these bearings due to their frequently deep encasing and lack of readily available transmission pathway to facilitate measurement. Caveats regarding the low capacity for high-frequency propagation over long distances also apply.19

The wary analyst should best support vibration measurement efforts with oil analysis. In many cases, in-depth analysis of vibration data will reveal the presence of a problem, but the experience, knowledge-base and extensive digging required to achieve this result may not be economically viable. On an asynchronous induction motor (the most common industrial beast), the rotor bar pass and slot pass frequency and harmonics, as well as sidebands, all fall within the standardized band-pass of many of these functions. Adjustments to chosen high-pass filtering threshold may concretize (or invalidate) this approach.

19 As a pragmatic example, a passing car with music playing full-blast projects bass or low-frequency noise, not high-pitched sounds.

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On low-speed bearings, the activity arrives at a lower relative velocity of internal components, but the end-result remains very similar. The judicious selection of the high-pass filter will assist considerably in maintaining function usefulness. Occasionally, elimination of any filter may be best when a specific function allows for such measures. For such low speed monitoring applications, Spike Energy tends to have a TINY amplitude, remaining stable (as long as the proper attention is given to the usual details) and trending flatly until a fairly SMALL rise appears. Unlike a higher speed application, this should IMMEDIATELY call for the analyst’s attention. Of course, further investigation must then ideally be pursued, deploying the idealized filter in relation to the sought key frequencies. On DC motors, brushes, springs, brush-holder assemblies and the direct contact of brush and rotor collector can all generate very faint HF detectable by these functions. On pumps, high-frequency activity of cavitation or recirculation affect gSE measurements. Thus, changes in operating conditions drawing pump operation AWAY from BEP (best efficiency point) may lower or boost gSE amplitude. Normally, from a spectral standpoint, this SHOULD only be within random energy (noise floor), but the increased amplitude blade-pass modulation of a perturbed fluid environment can certainly cause unwanted peaks to appear. On geared systems, the question arises whether or not separation exists between the frequency area where bearing defects would appear and the “gearmesh & harmonics” area. Gears share with fluid-film bearings the potential need for oil analysis coverage. It can be incredibly complex to analyze gears, particularly in transmissions (epicyclic gear sets in series). This paper does not propose an extensive discussion of gear diagnostics and HF / ultra spectra. Reference (10) already covers extensive ground on that topic, and although already aged a few years, the paper remains available on the Web. Also be aware that other techniques complete the analytical toolset to fully analyze gears, such as judicious use of the Hilbert transform and

any detection of irregularity. For 2006 CMVA, see Archambault and Saiah. On bearing pillow blocks, where the ongoing battle against corrosion calls for thick coatings, it may be necessary to sand and repaint. A caveat: if the function offers an ADJUSTABLE band-pass, many phenomena can be kicked out of the perceivable range: many frequencies ideally excluded from the band-pass could then be unwittingly included, causing considerable contamination of the signal. Furthermore, the reverse can also become true! Empirical Tricks of the Trade If Spike Energy and, by extension, a number of similar functions seem hypersensitive to certain behaviors, always keep in mind their excuse s found in a partial coverage of the ultrasonic range. Dedicated ultrasound detectors may cover ranges akin to 16 kHz – 100 kHz. Obviously, our vibration techniques cover a large swath of their domain. In a pinch, a “Spike Energy” capable vibration meter fitted with an accelerometer could replace an ultrasonic measurement device. The measured frequency range may not be a perfect fit, but the overlapping section will usually enable performance of accurate ultrasonic source detection routines. However, dedicated instrumentation can now perceive ultrasounds from 20’ away, hardly the case (or a desirable end) for our accelerometers. 4) Conclusion / A Look to the future The elegance of the Shock Pulse, Spike Energy and comparable techniques, combined with demodulation (enveloping) to obtain a spectrum, rests in a quick, inexpensive detection of POSSIBLE activity within a largely inaccessible frequency region, and this without the full measures needed to obtain accurate measurements within said region. There are, and likely will always be, CAVEATS! True, we can now sometimes20 get the exact measurement (special accelerometer, proper mounting, or interferometer targeted at a legible area),

20 Given proper access.

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but not as cheaply and not as readily. Some are better than others, but an analyst accustomed to the workings of one function will likely perform better with the known tool. HF / Ultra functions often provide WARNING of:

- lubrication deficiencies - bearing damage21 (fatigue or wear) - gear damage22 (fatigue or wear) - babbitt damage - oil cavitation (in plain bearings) - pumped-fluid cavitation /

recirculation in pumps (an example) - hints specific to each machine type

or component The volume of vibration data within an extensive predictive program’s scope can easily overwhelm most anyone, but such high-frequency functions underline or render obvious otherwise hard-to-catch “peak amplitude” activity from impacts. Depending on operation set-up, large paper mills (three machines, with refining, pulping, etc) can easily reach 800 to 1200 monitored machines. Unless it is a critical application with huge $$$ outcome or extremely difficult faint signal / far removed measurement point conditions, we do NOT wish to fully analyze23 data for bearings or gears for mere detection purposes: it is prohibitively expensive, and incompatible with current corporate requirements of reduced multitasking manning. Other calculations or simpler functions would likely offer this same benefit, such as trending of the Crest Factor, a simple yet unavailable24 function. Similarly, even a

21 Whether incipient or advanced 22 Same / Whether incipient or advanced 23 Some people still have trouble with the nuance involved between detection and analysis; by definition, analytical diagnostics imply in-depth work, recordings, post-processing, stretching and zooming data, and spending a few hours or days, at times, on a single machine. 24 To the best of this author’s knowledge, not a single vendor offers this simple approach, although the French Movilog and its software package trend a Fault Factor for bearings, likely using the Crest Factor and a bias correction. The

cursory review of waveforms will show SOME of the otherwise missed activity, but few vendor platforms afford the automatic capture of waveforms during routes. Many require considerable more time to deliver waveforms: the lack of forethought in losing something we needed to get to obtain a spectral result is astounding, but is only excusable inasmuch as the discovery of a need for waveforms as an FFT parallel came to us rather late. Frequently, these functions will evidence trouble otherwise unseen in the usually favored linearly-scaled FFT spectrum (at least in North American predictive efforts). There are degrees: logarithmic-scaled spectra will often reveal peaks hidden by the linear display. At the limit, if the signal is quiet and little noise pollutes the noise floor, statements regarding a perfectly healthy bearing’s absence of defect frequencies or modulations can become fallacious. Of course, the amplitudes would then be negligible. HF / Ultra Function or Parameter We can readily grasp the facts: - measurement repeatability can be shaky, but it is not a huge issue, - distance to the source and intervening interfaces will ALWAYS be a problem, - presence of activity or peaks is more important than their amplitude, - reviewing this type of data calls our attention to ongoing phenomena, - functions sometimes detect otherwise unseen events25, - functions sometimes better perceive or reveal concealed / buried events, - the more options a function offers, the greater the knowledge proficiency required to best use it and the easier it is to err in its configuration,

vendor states quasi total independence from bearing bore-size, load and shaft RPM. 25 Admittedly seldom “unmeasured”, although it does happen: events are usually present within the collected analytical, not always detection-oriented, measurements. However, and before the usual bunch derides the comment, the point is to NOT spend hours on end of one’s (or worse, somebody else’s) time to get the job done.

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- a vendor platform without any similar function is now often perceived as deficient; it is lacking or missing an essential component. Giving the inventors their due, these functions or processing techniques have been available for close to 40 years starting with SPM, almost 30 years for Spike Energy, while others celebrate different anniversaries. These functions will long hold a place in our monitoring efforts. Other techniques can be implemented to monitor machines, whether audio or motor-current analysis, but within a vibration context, even post-processing of recorded vibration data is sometimes at a loss and fails to reproduce or emulate HF / Ultra functions. Perhaps a 100 kHz bandwidth recording might suffice, but even then, there may be variations. For that reason, HF / Ultra will likely remain for incipient damage detection even should vibration monitoring disappear (keep in mind that basic detection based on velocity and acceleration may already be replaced by in-depth motor-current analysis, at least to some extent, and that might be completed with a microphone for audio detection, etc.). A final element: perhaps one of the primary reasons for writing this article, an attempt at fortifying our collective memory would prove useful. If we forget that 10, 15 or 20 years ago, such product already existed (and even often worked as promised), the salesman will again sell them to us as brand new. This becomes particularly important at a time when there is considerable change but not necessarily real (condition monitoring) PROGRESS. We are even at times the unwitting victims of corporate regression, loss of memory or even the loss of crucial “recipes”. Feel free to send comments and suggestions to the author by email at fgagnonvib@gmail.com

Trademarks FFT is a trademark of Monsieur Fourier (no lawsuit forthcoming) PeakVue is a trademark of CSI / Emerson Process Management SEE or S.E.E. is a trademark of SKF Condition Monitoring / SKF Reliability Spike Energy and DataPac are trademarks of Rockwell Automation Entek SPM is a trademark of SPM Instrument AB SWAN is a trademark of Swantech References (1) Azovtsev, A., Barkov, A., Carter, D., "Fluid Film Bearing Diagnostics Using Envelope Spectra", Proceedings, 21st Annual Meeting, Vibration Institute, 1996 (2) Gagnon, F., “Making Spike Energy a Better Bearing Diagnostic Tool”, Shock & Vibration Digest, Sep/Oct 1994, Vibration Institute (3) Lundy, James A., “Detecting Lubrication Problems Using Shock Pulse”, Lubrication & Fluid Power, Jan-Feb 2006 (4) Miettinen, J., Andersson, P. “Methods to Monitor the Running Situation of Grease Lubricated Rolling Bearings”, COST 516 Tribology Symposium, Technical Research Centre of Finland, 1989 (5) Unknown, Swantech Corp. website (6) Unknown, Vibration Guide, SKF Reliability, 2000 (7a, 7b, etc) US Patents, #3,554,012, #4,089,055, #4768380, #5,679,900, #6,526,356, #6,553,839, #6,679,119, #6,684,700, #6,868,348, #7,030,046 (8) Xu, Ming, Le Bleu, Julien Jr., “Condition Monitoring of Sealless Pumps Using Spike Energy”, P/PM Technology, Vol. 8, Issue 6, pp. 42-49, December, 1995 (9) Zhang, L., Thomas, BG, “Inclusions in Continuous Casting of Steel”, 24th National Steelmaking Symposium, Mexico, 2003 (10) Berry, JE, Robinson, JC, Walker, JW, “Description of PeakVue and Illustration of its Wide Array of Applications in Fault Detection and Problem Severity Assessment”, CSI & TAC, 2001

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