AIAC-12 Twelfth Australian International Aerospace Congress
Fifth DSTO International Conference on Health & Usage Monitoring – HUMS2007
A Novel Technique of Crack Detection for Helicopter Main
Gearbox Planet Carrier
Wenyi Wang
Air Vehicles Division
DSTO
Fishermans Bend, Melbourne
Australia
Jonathan A. Keller
US Army RDECOM
Aviation Engineering Directorate
Redstone Arsenal, Alabama
USA
Abstract
This paper presents a simple but effective technique of detecting helicopter main gearbox
planet carrier cracking, which occurred in two US Army UH-60A Blackhawks in 2002 and
one US Navy SH-60B Seahawk in 2004. The vibration signal averaged with respect to the
rotation of planet carrier contains the gear mesh components between the planet gears and the
ring gear, which are modulated by the planet passing events. It is expected that a cracked
planet carrier should produce a different modulation pattern to the gear mesh harmonics from
an uncracked planet carrier. Therefore, in the proposed technique, our focus is on the
extraction of the normalised modulation waveforms. We first normalise the averaged signals
to a mean of zero and a standard deviation of one unit, and extract the planet passing
components from the normalised signals. We then generate a Condition Index (CI) from
them. Using the CI, we can differentiate the cracked planet carrier from the uncracked carrier
at 30 percent torque load and above for both the Test-Cell and On-Aircraft data. With further
validation, this technique can be readily implemented into any helicopter health monitoring
system.
1. Introduction
Recently there were three cases of main gearbox planet carrier cracking that occurred in two
UH-60A helicopters of the US Army and one SH-60B helicopter of the US Navy. This paper
presents a simple but effective technique of detecting cracks in planet carrier plates, with
analysis results from two data sets: (1) Test-Cell data generated in a test conducted in the US
Navy’s helicopter transmission test facility (HTTF) in Maryland with a healthy gearbox and a
gearbox with a cracked carrier; and (2) On-Aircraft data generated in four UH-60A
helicopters, one with the cracked carrier and the rest with uncracked planet carriers.
The fundamental principle of the technique is based on the fact that a cracked planet carrier
makes the load sharing of gear mesh different from that of an uncracked carrier, which may
become more significant under higher torque loads. This change of gear mesh load sharing
can have an effect on the amplitudes of the planet passing harmonics.
In the vibration signal averaged with respect to the rotation of planet carrier, the predominant
components are the gear mesh harmonics between the planet gears and the ring gear,
modulated by the planet passing event. It is expected that a cracked planet carrier should
produce a different modulation pattern to an uncracked planet carrier. Therefore, in the
proposed technique, the averaged signals are first normalised to a zero-mean and a unit
standard deviation, and the planet passing harmonics (or the modulation waveforms) are then
extracted from the normalised signals. A Condition Index (CI) based on the standard
deviation of modulation waveform’s 5th
shaft order harmonics (as there are five planet gears)
is calculated and used for trending or plotted against the main gearbox load.
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By comparing the cracked and uncracked conditions using the Test-Cell data, we find that the
CI from the gearbox with the cracked planet carrier progressively decreases as the torque load
is increased from 30 percent to 100 percent rated torque. However, we could not separate the
cracked and uncracked conditions at the 20 percent torque load for both Test-Cell and On-
Aircraft data.
The results presented in the paper show that the proposed technique can be effectively used to
detect a cracked planet carrier provided there is a significant torque load (e.g., 30 percent)
applied to the gearbox. With further validation, this technique can be readily implemented
into helicopter health monitoring systems that have synchronous averaging capability.
2. The UH-60A Test Data and Analyses by Others
There were two UH-60A test data sets used in this paper. The first was the Test-Cell data
generated in a test conducted in the US Navy’s helicopter transmission test facility (HTTF) in
Maryland with a healthy gearbox and a gearbox that had an 8.25cm (3.25”) planet carrier
crack. The test was conducted under a range of torque loads from 20 percent to 100 percent.
The second set was the On-Aircraft data generated by four UH-60A helicopters, one with the
same cracked carrier used in the Test-Cell and the rest with uncracked planet carriers, at 20
percent and 30 percent torque loading only, as 30 percent torque was the maximum safe load
while the helicopters remained on ground.
Figure 1 shows the schematic of the other UH-60A carrier crack, which was 25cm (10”) long.
Figure 2 shows the top view of the Blackhawk’s main transmission gearbox and the sensor
locations.
Fig. 1. The US Army’s UH-60A planet carrier with a 25cm long crack.
3
Fig.2. Blackhawk’s main transmission gearbox and the sensor locations
The main module of the UH-60A main transmission is a two-stage gearbox. The first is a
bevel gear stage with a 17-tooth pinion and an 81-tooth bevel gear, and the second is an
epicyclic stage with a 62-tooth sun gear, five 83-tooth planet gears, a 228-tooth fixed ring
gear and a planet carrier plate. In addition, there is an auxiliary oil pump drive gear with 152
teeth, which rotates with the carrier plate.
The data sets were first analysed by Keller and Grabill [1] using several standard diagnostic
parameters and their modifications. They found that only two of the parameters were capable
of detecting the cracked condition using the Test-Cell data, and no parameter was able to
detect the cracked condition using the On-Aircraft data. Later analysis conducted by Blunt
and Keller [2], through detecting changes to the planet passing modulation of the gear mesh
vibration and changes to the meshing behaviour of the individual planet gears, showed an
improvement on the existing techniques and a reliable detection of cracked condition using
the Test-Cell data.
The data were also widely disseminated and analysed by many researchers. Many existing
and new techniques [3-8] were applied with various degrees of success. Among the new
methods, an impressive approach by Dong et al [3] employed an Advanced-Hidden Markov
model (AHMM) to extract condition indices for the cracked and uncracked conditions. Their
analysis results have shown that the AHMM can be effectively used to identify the cracked
carrier using both Test-Cell and On-Aircraft data. Dong and He [4] further investigated the
Hidden Semi-Markov Model (HSMM), which was applied to the detection of UH-60A planet
carrier crack with excellent results. However, it is believed that the increased computational
complexity is a major drawback of the HSMM. McInerny et al [6] employed a method based
on the spectral energy ratio between the non planet passing residuals and the planet passing
GEARS Input
pinion
Bevel
gear
Sun
gear
No. of
planets
Planet
gears
Ring
gear
Oil pump
drive gear
Tooth No. 17 81 62 5 83 228 152
4
components. This method can produce good results if the frequency band is appropriately
chosen. The data used by McInerny et al were derived from sensor #6, i.e., the Port-Ring
accelerometer.
3. Analytical procedure
In this paper, we propose a simple and yet effective approach to detecting the planet carrier
cracking in a helicopter main gearbox. Firstly, if we look at any planet-carrier signal average
in time domain, we will find five peaks (or humps) associated with the passing of the five
planet gears in the UH-60A main gearbox, and the higher frequency gear mesh vibration
between the planet gears and the ring gear. To further illustrate this, we can extract the low
frequency planet passing component from the averaged signals by a simple envelope analysis.
The enveloped signal shown in Figure 3 represents the modulation waveform of the gear
mesh vibration from an uncracked planet carrier at two different loads. As can be seen, these
modulation waveforms are very dependent on load, i.e., the five peaks are more prominent at
higher load. They should also be highly dependent on the stiffness of the carrier plate (see
Figures 4 and 5). We need to point out that the envelope signals shown in Figures 3, 4 and 5
only contain the low frequency content of modulation waveforms. They are used to illustrate
the effects of loading and cracking on modulations, and will not be used to extract the
condition index for crack detection as they lack the high frequency content.
Fig. 3. Original planet carrier modulation to gear mesh vibration
When the carrier plate develops a crack, its torsional stiffness will change, which will in turn
change the modulation of the gear mesh vibration. One might expect that a condition index
extracted from the modulation waveform of the original vibration signal averages should
reflect the changes of the weakened carrier plate. However, it is very hard to control the test
conditions such that the acquired vibration signals have identical basis for comparison. This is
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especially important for the On-Aircraft data that were acquired from four different
helicopters. In the proposed technique, we first normalise the averaged signals to a mean of
zero and a standard deviation of one unit, to make the comparison basis identical under
different test conditions, i.e., different loading and different aircraft. We need to point out that
the key to differentiating between a cracked and an uncracked carrier plate is the relative
changes in the modulation waveforms, rather than the absolute changes.
Figure 4 is the normalised version of Figure 3. For the uncracked planet carrier, the difference
between the two modulation waveforms is very obvious but their mean values are very
similar. Figure 5 shows the modulation waveforms from a cracked planet carrier with
loadings at 20 percent and 100 percent. Comparing Figure 4 with Figure 5, we find that the
modulation waveforms associated with the cracked carrier differ significantly from those with
the uncracked carrier. With the cracked carrier, the five peaked modulation pattern tends to
disappear, but the mean value does not change significantly at different loads due to the
normalisation.
A simplistic explanation of this could be that a local crack in the carrier plate is weakening
the local gear mesh stiffness between the planet gear adjacent to the crack and the ring gear,
and the weakening is redistributing the load of the affected planet to the other planets. The
flattening of the modulation peaks could be a consequence of this. As the crack propagates, it
could be expected that more planet gears will become affected and the modulation peaks will
be flattened more.
Fig. 4. Normalised planet carrier modulation to gear mesh vibration from an uncracked planet carrier
Based on the above observations, our focus is placed on the difference in the modulation
patterns. Because the five-peaked modulation pattern disappears for the cracked planet carrier,
the harmonics of the 5th
shaft order should diminish as well, which will be more obvious
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under heavy load. Hence, if we can extract a condition index from the 5th
shaft order
harmonics, e.g., the standard deviation of all 5th
shaft order harmonics, we should see a
declining trend of the CI values against load. This forms the basis for the proposed detection
technique. The procedure is outlined in Figure 6. The most important step in the procedure is
the normalisation which allows the relative changes to be tracked.
Fig. 5. Normalised planet carrier modulation to gear mesh vibration from a cracked planet carrier
Fig. 6. A diagram of the proposed planet carrier crack detection technique for helicopter main
transmission gearboxes
Raw
vibration
signal
Reference
tacho
signal
Synchronous
averaging with
respect to the
rotation of planet
carrier
Normalisation to
zero-mean & unit-
standard deviation
Fourier
transform
Extract planet
passing
harmonics
Inverse
Fourier
transform
Calculate
standard
deviations
Condition
Index (CI)
7
4. Analysis results
In this section, we first present a spectral analysis of the epicyclic gearbox vibration. Then,
the analysis results for both the Test-Cell and On-Aircraft data are given. In this paper, we
focus on the analysis of the data acquired by sensor #6 (Port-Ring).
Spectral Analysis
Based on the information given in Section 2 about the UH-60A main gearbox, we expect to
see all the gear mesh harmonics plus bearing vibration and background noise in the spectrum
of any raw signal. Because the fault is on the carrier plate, we need to isolate the vibration
associated with the rotation of the carrier plate. We can achieve this with synchronous
averaging, using the tachometer signal on the output shaft as a rotational reference. In the
spectrum of such an averaged signal, one might expect to see frequency components at the
harmonics of the 228th
shaft order and the 152nd
order, accompanied by modulation sidebands
at 5 shaft orders. In fact, as shown in Figure 7, it is the harmonics of the planet passing
frequency (i.e., multiples of the 5th
shaft order) around the harmonics of the 228th
shaft order
that dominate the spectrum. The harmonics of the 228th
shaft order gear mesh frequency are
actually suppressed (not shown as the dominant components). This phenomenon was
thoroughly explained by McFadden and Smith [9]. The harmonics of the oil pump drive gear
(152nd
shaft order) are also noticeable in Figure 7 as this gear rotates together with the planet
carrier and the vibration induced by this gear is not averaged out.
Fig.7. Spectrum of an averaged signal from Test-Cell accelerometer #6.
Analysis of Test-Cell Data
First, let us take a look at the original signal average to see whether it can lead us to separate
the uncracked and cracked planet carriers. Figure 8 shows a plot of the standard deviation of
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the original Port-Ring signal averages versus the load. Obviously, the curves associated with
the uncracked and cracked carriers are not separated, which means that the overall variations
in planet carrier signal average are not indicative to the carrier fault. However, based on the
discussions given in Section 3, the vibration induced by the passage of the planet carrier
should be indicative to the carrier cracking.
Fig.8. Plot of standard deviations of planet carrier signal averages against gearbox torque load using
the data at Test-Cell accelerometer #6.
With the normalised signal averages of the planet carrier, we now separate the planet passing
components from the gear (i.e., planet gears, ring gear and oil pump drive gear) mesh
components. Figures 9 ~ 11 show the plots of the standard deviations of these separated
components versus load. The fundamental information that we can derive from these plots is
that, with the cracked planet carrier, the standard deviation of:
• the planet passing harmonics decreases with increasing load;
• the ring/planet gear mesh harmonics plus residuals increases with increasing load, which
is probably why the unseparated signal average does not show a monotonic trend; and
• the oil pump drive gear mesh harmonics increases with increasing load.
This is in contrast to the results from the normalised signal averages of the uncracked planet
carrier (the dashed lines in the plots), which are relatively stable as the load increases.
Therefore, any or a combination of the above mentioned measures can be used as the
condition index for detecting a planet carrier crack. Due to the dominance of the planet
passing harmonics in the averaged signals, we have employed the standard deviation (shown
in Figure 9) of these extracted components (transformed back into the time domain) as the
condition index in our study. The process of computing the CI is outlined in Figure 6 of this
paper. However, for consistency and possibly fewer false alarms, the results from all three
plots could be employed together.
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Fig.9. Plot of standard deviation of planet passing harmonics versus torque load using the data at
Test-Cell accelerometer #6.
Fig.10. Plot of standard deviation of ring/planet gear mesh harmonics& residuals versus torque load
using the data at Test-Cell accelerometer #6.
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Fig.11. Plot of standard deviation of oil pump drive gear mesh harmonics versus torque load using the
data at Test-Cell accelerometer #6.
We need to emphasise that the above three standard deviations shown in Figures 9 ~ 11 are
relative to the overall standard deviation of one unit, which is independent of the original unit
(i.e., G for acceleration, or Volt, etc.) of the vibration signals. However, the contributions
from the individual harmonic components may not necessarily sum up to one because of the
phase relationships between the individual components.
Analysis of On-Aircraft Data
The Test-Cell data were acquired under controlled conditions, which improved the ability to
separate the modulation features caused by the carrier crack. However, the On-Aircraft data
were obtained from four different UH-60A helicopters (Aircraft A, B, C and X), in which one
(Aircraft X) had the cracked carrier installed. Because of the structural variability among these
aircraft, identification of the faulty gearbox with the cracked carrier in this data set is far more
difficult than using the Test-Cell data. Furthermore, the loads applied to the aircraft on the
ground could not be more than 30 percent rated load due to safety concerns.
Following the procedure shown in Figure 6, we extracted the CI, as defined by the standard
deviation of the planet passing harmonics, and the result is shown in Figure 12. This figure
shows that the gearboxes with cracked and uncracked carriers can be separated at 30 percent
load, and presumably at other higher loads if they were available. However, we also find that
the variability of CI from all the aircraft with healthy gearboxes at 20 percent load is much
larger, and we cannot separate the healthy and faulty gearboxes at this load. Further, referring
back to Figure 9, we may conclude that the 20 percent load is not sufficiently high to allow an
identification of any faulty gearbox with a cracked planet carrier for both Test-Cell and On-
Aircraft conditions.
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Fig.12. Plot of proposed CI’s versus torque load using the data at On-Aircraft accelerometer #6.
5. Comparison and discussion
Among the techniques presented by other researchers, there is a similar method to our
technique that was discussed by McInerny et al [6]. This method employed the spectral
energy ratio between the non planet passing residuals and the planet passing components.
Using this technique they found the most consistent result was the GM-1 metric (given in
Table II of the paper) from the frequency band around the fundamental ring/planet gear mesh
frequency. The consensus between our approach and McInerny’s method is the fact that the
non-planet passing residuals behave differently from the planet passing components when a
carrier crack is present. However, the technique proposed in this paper differs from the
McInerny’s energy ratio method in the following three aspects:
• There is no need for our technique to select frequency bands for best detection.
• Our technique is based on a time domain normalisation process, which might be
somehow comparable to the usage of ‘ratio’ in McInerny’s method.
• The CI in our technique is drawn from time domain instead of the frequency domain.
Overall, in comparison to other methods, the proposed technique has a unique procedure for
processing both the Test-Cell and the On-Aircraft data. It does not need any subjective
selection of frequency band to demodulate vibration signals and it does not rely on knowledge
about system resonances. Moreover, it is not based on any prescribed model, such as
parametric model (e.g., AR or ARMA model) that needs to estimate model parameters or
statistical model (Markov model) that needs to be trained. The normalisation process is the
key to the successful application of the technique, as it sets a unique comparison basis for data
acquired under different loading conditions and from different aircraft.
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6. Concluding remarks
It has been shown in this paper that the proposed technique can be used to separate the
cracked and uncracked helicopter main gearbox planet carriers provided that there is a
significant load (e.g., 30 percent rated load and above) applied to the gearbox. In conclusion,
this technique is conceptually straightforward and yet effective in detecting planet carrier
cracking. It does not involve subjective judgement, and with further validation, it can be
readily implemented into any helicopter health and usage monitoring system (HUMS) that has
synchronous averaging capability.
Acknowledgement
The authors would like to acknowledge David Blunt, Brian Rebbechi and Albert Wong of
DSTO for their support to the work and comments for the paper.
References
1. J.A. Keller and P. Grabill, “Vibration Monitoring Of UH-60A Main Transmission
Planetary Carrier Fault,” Proceedings of American Helicopter Society 59th
Annual
Meeting, Phoenix, Arizona, USA, 6-8 May 2003.
2. D.M. Blunt and J.A. Keller, “Detection of a Fatigue Crack in a UH-60A Planet Gear
Carrier using Vibration Analysis,” Mechanical System and Signal Processing, Vol.
20(8), pp. 2095-2111, 2006.
3. M. Dong, et al, “Equipment Health Diagnosis and prognosis Using Advanced Hidden
Markov Models,” Proceedings of the 58th
Meeting of the Machinery Failure
Prevention Technology (MFPT) Society, Virginia Beach, Virginia, USA, April 2004.
4. M. Dong and D. He, “Hidden semi-Markov models for machinery health diagnosis
and prognosis,” Transactions of NAMRI/SME (the North American Manufacturing
Research Institution – Society of Manufacturing Engineering), Vol. 32, pp. 199- 206,
2004.
5. B.Q. Wu, et al, “An Approach to Fault Diagnosis of Helicopter Planetary Gears,”
2004 IEEE AUTOTESTCON.
6. S.A. McInerny, et al, “Detection of a Cracked-Planet Carrier,” Proceedings of the 10th
International Congress on Sound and Vibration, Stockholm, Sweden, 7-10 July 2003.
7. P. Sparis and G. Vachtsevanos, “A Helicopter Planetary Gear Carrier Plate Crack
Analysis and Feature Extraction based on Ground and Aircraft Tests,” Proceedings of
the 2005 IEEE International Symposium on Intelligent Control, Limassol, Cyprus,
June 27-29, 2005.
8. A. Saxena, et al, “A Methodology for Analyzing Vibration Data from Planetary Gear
Systems using Complex Morlet Wavelets,” Proceedings of 2005 American Control
Conference, Portland, OR, USA, June 8-10, 2005.
9. P.D. McFadden, and J.D. Smith, “An Explanation for the Asymmetry of the
Modulation Sidebands about the Tooth Meshing Frequency in Epicyclic Gear
Vibration,” Proceedings of the Institution of Mechanical Engineers, Part C:
Mechanical Engineering Science, Vol. 199, No. 1, Jan. 1985, pp. 65-70.
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