RLD Processes and Analyses - Engineering Integrity...

Smarter Thinking.

© MIRA Ltd 2014

Smarter Thinking. © MIRA Ltd 2014

RLD Processes and Analyses

David Ensor – MIRA Ltd]

http://www.ithoughts.co.uk

Smarter Thinking.

© MIRA Ltd 2014

Road Load Data

March 3, 2015 We Deliver Smarter Thinking. 2

Those quantities generated throughout a

product while in its service environment &

having an effect on strength or durability.

Typical measured values include -

Forces

Accelerations

Strains

Displacements

Speeds

etc...

Smarter Thinking.

© MIRA Ltd 2014

Just because we can – Should we?


Analysts & Engineers are requiring MORE

complex measurement data to improve

predictability of Analytical Methods & to

Support Sophisticated Laboratory Testing.

Exponential growth in number of

channels being measured.

Exponential growth in the amount of

information to being extracted from EACH

channel.

Recent exercises have ask MIRA to help analyse & sort out data in

the order of hundreds of thousands of pieces of data, all very long

tests, & covering GBytes of data.

Typical projects now collect 80 – 100 GBytes as standard!!!!!

With all the new techniques, modern kit, & software tools – data still

requires work to make if – time is now the limitation …..

Smarter Thinking.

© MIRA Ltd 2014

Getting the Answer You Want


Spike Removal

Rescaling

Drift & Mean Offset

Noise & Filtering

Drop-outs

Clipped data

Sample Rate Adjustments

Extraction/Deletion of Data

Calculated Channels

XY Display

Nearly always faster & more accurate to collect data again!

Check your data before stripping the vehicle!

Trouble now is the quantity & bulk of data.

E-I-S Software Verification

• You check calibration of transducers

• Do you check calibration of software?

• Do you check veracity of the algorithm?

E-I-S did set up a series of ‘standard’

signals and tests to use.

Smarter Thinking.

© MIRA Ltd 2014

Dodgy Data …..


Some examples of data submitted to MIRA for

analysis!

All of this data was described as checked & verified

by the customer!

Smarter Thinking.

© MIRA Ltd 2014

What about How Many Tests


Very often need to provide a ‘good representation

of an event for analysis or rig test & work out

what is pass/fail criteria.

Should we collect one event?

Should we collect a number?

How many laps/events?

What is the confidence?

How many samples?

How do we know if test is a success?

Correct statistical application as to be taken – determine confidence

levels, design of experiments – more importantly how to set up

project …..

Many times we are asked – “instrument the vehicle, then work out

what can be done with data” …..

When taking data, or measurements how many readings are

needed?

Smarter Thinking.

© MIRA Ltd 2014

Data Analysis Process


Fit

Transducers

Run on

Test Tracks

Look for

Analysis to do

Clean Data

by Eye

Filter Data

as Standard

What we have ! (Typically accelerometers)

Standard! (We always use 35Hz)

Spikes! (Typical freehand)

All of them (Typical high input)

What can we do? (Typical basic plots)

Smarter Thinking.

© MIRA Ltd 2014

Data Analysis ‘Better Practice’


Determine required

result & format

Review the analysis

needed to obtain result

Collect data on

correct surface

Fit transducers

for that data

Determine data specific

to the analysis

Validate data for

required content

Maintain History &

Deliver good results

Check output on

known surface

Check analysis

with known data

Smarter Thinking.

© MIRA Ltd 2014

Of course everyone uses the same coordinates


Smarter Thinking.

© MIRA Ltd 2014

MIRA RLDA Directory Naming

Organises and maintains confidentiality.

Ensures procedures are consistent.

Procedures can be common.

Data is in known areas..

Smarter Thinking.

© MIRA Ltd 2014

Organises procedures

Maintains confidentiality.

Procedure consistency.

Looping on multiple events.

Common naming.

Parsing is easy..

MIRA RLDA File Naming

Smarter Thinking.

© MIRA Ltd 2014

Statistics is important - More than one variability


User

Population

(random)

“X” thousand vehicles per year

Any vehicle can

go to any user

Usage 90%ile

Only 10% exceed this

1 in 10 chance of

exceeding usage

Nu

mb

er

of

Ve

hic

les

Distance

Usage

Distribution

Usage

Target

Failure

Population

(random?)

Fail 10%ile

1 in 10 chance

of fail before

Failure

Distribution

Any vehicle can

fail for any user

Durability

Target

Als

o S

afe

ty C

riti

ca

l

Smarter Thinking.

© MIRA Ltd 2014

Number of readings & Collecting enough data


An experiment checked temp

change of 1deg made difference

of 7/1000s of an inch for the 100

foot chain.

36-inch theodolite weighed over half a

tonne carried by 12 men

One of the 7.5 miles (12 km)

baselines Lambton made over

400 readings with 100’ chain in

57 days across jungle

1843 survey Lambton/Everest set up

line of triangles up the spine of India

over an area of 56,997 square miles

starting from measured baseline. One

such measurement of a 7.19 mile

baseline differed only 3.7 inches from

the value calculated by triangulation.

GPS & laser site measuring have

not got any more accurate

Smarter Thinking.

© MIRA Ltd 2014

Number of Readings! Design of Experiments


Many tester now take just one

vehicle – do one run – change

settings or modify – do another run

and compare the results.

This is a typical request for alternate

fuel tests etc. ONE TEST !

It is now the norm to test only one

vehicle through and ‘hope’ it passes.

There are techniques for providing

the confidence in a result and they

rarely recommend 1 specimen, or

one test run.

http://www.google.co.uk/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=OY92I0BzZc1rEM&tbnid=VFof2i8p9cqQYM:&ved=0CAUQjRw&url=http://jer-skepticscorner.blogspot.com/2010_01_01_archive.html&ei=qZAMVJfNKNbiatn3gLAM&bvm=bv.74649129,d.ZGU&psig=AFQjCNHKDLIZusNREBqRdFF3AsoKLEhNVA&ust=1410195895926617

http://www.google.co.uk/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=OY92I0BzZc1rEM&tbnid=VFof2i8p9cqQYM:&ved=0CAUQjRw&url=http://jer-skepticscorner.blogspot.com/2010_01_01_archive.html&ei=qZAMVJfNKNbiatn3gLAM&bvm=bv.74649129,d.ZGU&psig=AFQjCNHKDLIZusNREBqRdFF3AsoKLEhNVA&ust=1410195895926617

Smarter Thinking.

© MIRA Ltd 2014

Test Samples


Test Sampling

There are standard methods for calculating sample sizes. Actual or projected ‘Sales’ figures for the

population of vehicles to be made will recommended, sample size required mathematically to satisfy

various confidence bands.

It would be usual to offer better than 90% or 95% confidence in a result and within a +/- 5% (10%

Error) band on this. It is rare to find anywhere in the literature on the subject of sampling, any

reference to requirements less than 95% confidence levels.

This implies a large number of samples or lack in confidence.

Test Length

One Sample Just Pass Test

No Confidence

To Be Confident

1 Sample must pass 6 x Test

Test Length

Six Sample Just Pass Test

No Confidence To Be Confident

6 Sample must pass 1.25 x Test

Smarter Thinking.

© MIRA Ltd 2014

Test Failure – Theory v Practice


Total life = Life to Initiate a crack + Life to Grow the crack

Crack initiation Crack growth

Vehicle Life (Stress or SN)

Design life (Strain or EN)

Often much larger than Design Life (Fracture or Crack Growth or

Vehicle designer considers failure is start of a crack <0.5 mm

Most vehicles are designed to a fairly common standard – no cracks in major components inside its Design Life No cracks at all in whole life for any Safety Critical Component

Practice considers failure when broken

New Tank Scrap Vehicle

Smarter Thinking.

© MIRA Ltd 2014

Tracks & Roads RLD - Same data – Enough data


Collect until you have ‘enough’ data – Classify significant sections, continuously average

the classification until it doesn’t change – you now have enough data.

Smarter Thinking.

© MIRA Ltd 2014

Rig Test Time Reduction – Remove “None Event Time” & then Damage Editing


Zero/Start

Stationary

Preliminary Track Section

Vehicle moving & settle

The Event in Track Section

Vehicle moving & test event

Final Track Section

Vehicle moving & re-settle

Zero/End

Stationary

RLD Event Record

As supplied for whole event

Typical Rig Event Extraction – Duty Cycle

Extract vehicle moving and smooth ends

Minimal Rig Extraction – Event only

Extract only event + Lead in/out itself

Time=0 Schedule event start Event only

(can limit fatigue result) Schedule event ends

Time reduced from RLD & vehicle durability work by fixed procedural start/end

conditions, or removal of removal, of approach roads, “zero’ conditions etc.etc

Then we can also apply damage editing techniques

Smarter Thinking.

© MIRA Ltd 2014

Accuracy v Usability


• Should we insist on accuracy?

• What is a useful result?

• Determine confidence in result.

• Has result proven the point?

• Statistical difference (T testing)

Damian Harty explores this

concept well in his Paper

"The Myth Of Accuracy

A common misconception is that

increased complexity leads to

better, more useful results

Smarter Thinking.

© MIRA Ltd 2014


RLD Testing Conditions Loading Instrumentation



Smarter Thinking.

© MIRA Ltd 2014

RLD Test Load Conditions

RLD at ‘worst case’

• What is worst case

• Laden

• GVW

• Unladen

• Plated

• Overload

• Loading from instrumentation

• Typical or Special

• Roof box / Bike racks

• Trailer/Caravan/Boat

• Distribution/Pillion

• Variable (Liquid, People)

• Other ……… etc

Smarter Thinking.

© MIRA Ltd 2014

Some Extremes


People do ask strange things ..

Fig 9: Applying assumed user conditions leads to some over test.

Smarter Thinking.

© MIRA Ltd 2014

Can fixed events test for real world? RLD …

Smarter Thinking.

© MIRA Ltd 2014

How well? Correlate RLD Classification

Smarter Thinking.

© MIRA Ltd 2014


RLD ‘Problems’ & Misconceptions



Smarter Thinking.

© MIRA Ltd 2014

Fo - Outer wheel

force anywhere

along contact patch

length

Spring Damper

Axle Bending Bridge

Strain Gauges

Fi - Inner wheel

force anywhere

along contact patch

length

µ ( Fi + Fo )- Cornering force

r

xi

xo

Measured Bending Moment (Strains) = ( Foxo+ Fi xi ) - µ ( Fi + Fo ) r

WRONG !!!!!

Smarter Thinking.

© MIRA Ltd 2014

Spring Damper

Axle Shear Force

Strain Gauges

Fo - Outer wheel

force anywhere along

contact patch length

Fi - Inner wheel force

anywhere along


µ ( Fi + Fo )- Cornering force

r

xi

xo

Measured Shear (Strains) = Fo+ Fi + a little cross talk from lateral compression.

RIGHT -SHEAR

Smarter Thinking.

© MIRA Ltd 2014

r

Danger of assumptions

• Main test case is based on maximum

constant circle cornering

• Most vehicles can pull 0.8 G or so.

•We can rig test the Z & X loads separately

on a rig

• Z cycles plus X cycles will provide total

damage.

•Is this a good plan?

Spring

Damper

Axle Strain Gauge

F = Wheel force

anywhere along


µ ( F ) = Cornering force

x

r

Smarter Thinking.

© MIRA Ltd 2014

r

Spring

Damper

Axle Strain Gauge

F = Wheel force

anywhere along


µ ( F ) = Cornering force

x

Measured Bending Moment (ie Stress) = Fx - µ F r

Thus if x / r = 0.8 then BM and stress = ZERO

Danger of assumptions

• Remember Muybridge

• Why is this worst case? Only considered

each component separately.

• The real case is the combined vector case.

• In fact from most vehicle proportions

(beam axles) @ 0.8 G or so the bending

moment will be zero!!!!

• Thus, we will artificially create a rig failure

by separating the loading X & Z that would

not actually occur.

r

Smarter Thinking.

© MIRA Ltd 2014

The Accelerometer Trap

You have the accelerometer data

Newton has it that F = ma

We can thus work out the FORCES !!!

All Wheel Bump

Possible that

F = Axle mass x accel

Further Down Road –

Single Wheel Bump

Then possible that

F = ½ Axle mass x accel

And then –

Ripple Under Wheels

Then possible that any

F = Local mass x accel

Smarter Thinking.

© MIRA Ltd 2014


Understanding RLD by Classification Analysis



Smarter Thinking.

© MIRA Ltd 2014

Some Ideas using statistics

Imagine you buy a house near the sea on an 8 m wall

You ask about flooding and damage by freak weather

The builder says average tide height as published by Government are 4 m.

Government tables agree, but also mention range of tides, from 2 m to 6 m.

Locals say waves are usually around 4 m peak to trough

The eco people say RMS ‘average’ for waves is around 6 m

The owner wanting to be helpful says waves have come over the wall.

What could you expect in general and at worse?

Smarter Thinking.

© MIRA Ltd 2014

Taking readings

A short example to give you some ideas …

Lets look at everyday item … the electrical supply.

Take a voltmeter, “poke it” in the socket and look at the result.

On a ‘standard’ setting we can see 240 v. Is this correct? Is it okay?

Reset the voltmeter, to show “peak” and look at the result.

We now get 339 v Is this correct? Is it okay?

Record the voltage and show “average” and look at the result.

We now get 0 v ???? Is this correct? Is it okay?

Reset the meter to show “current” and look at the result.

We see 0 amp, or 1 amp, or 13 amp etc?? Is this correct? Is it okay?

Recheck the meter to another scale and look at the result.

We see 230.6 v at 50 Hz ?? Is this correct? Is it okay?

Smarter Thinking.

© MIRA Ltd 2014

How we view our readings

Most things we want to measure are changing, we need measurements that

take this into account …

It is important to know what and why you are measuring, and use suitable

transducers and take values that are useful …

Statistics - look at the basic info

• Max/Min

• Range

• Mean/Average

• Median

• Mode

• RMS (Root Mean Square)

• Standard Deviation

before we get anywhere near

analysis …… etc

Two signals can give same

statistics so plotting/oscilloscope

can help make sense …

Smarter Thinking.

© MIRA Ltd 2014

Some important RLD classifications


Smarter Thinking.

© MIRA Ltd 2014

Range–Mean Cycle Count (Rainflow is only one algorythm)


Maximum Range RMax

At Mean Level MMean

(1 or minimum count)

Other Ranges R

And Means M

Minimum Mean Level MMax

0 or minimum Range RMin


Maximum Mean Level Mmax



Minimum Range RMin

Most counts

(Approx ½ total points)

Smarter Thinking.

© MIRA Ltd 2014

Why it is a classification


Other Ranges R

And Means M

Minimum Mean Level MMax



Maximum Mean Level Mmax



Minimum Range RMin

Most counts

(Approx ½ total points)

Maximum Range RMax

At Mean Level MMean


Counts outside are

special or anomalies

High counts inside &

peak outside are

unusual cyclic or

resonance etc

Smarter Thinking.

© MIRA Ltd 2014


1

Stage Range (X) Mean (Y) Number (Z)

Whole signal max 9 2 1

Drain & look at next

max 3 0.5 1

Etc 2 0 1

Etc 2 3 1

Last cycle 1 0.5 1

Range–Mean Cycle Count (Non-Rainflow method )

Smarter Thinking.

© MIRA Ltd 2014

A

B

2048 Point buffer extracted from signal

4096 Point buffer extracted from signal

2048 points means a set of buffers each around ½ second These are then used to represent the spectra for 0 – 2500 Hz in 1024 bins. Each point being 2500 / 1024 Hz per point = 2.44 Hz/bin

4096 points means a set of buffers each around 1second These are then used to represent the spectra for 0 – 2500 Hz in 2048 bins. Each point being 2500 / 2048 Hz per point = 1.22 Hz/bin

5000 Hz sampled data has a Nyquist of 2500 Hz Or the highest frequency we can represent in this data

Smarter Thinking.

© MIRA Ltd 2014

134 136 Frequency

Amplitude

134 136 Frequency

Amplitude Example Assuming all frequency inside 135 to 136 Hz bin Area 135 to 136 Hz is still = 3.66 = 3.66 / 1.22 = 3 g Doubled just in changing resolution, but is same spectra power.

1.5 Example Area 134 to 136 Hz = 1.5 x 2.44 = 3.66

3

Smarter Thinking.

© MIRA Ltd 2014


RLD Conditons



Smarter Thinking.

© MIRA Ltd 2014

Some common problems

• Instrumentation

- Fixing of equipment

- Fixing of leads

- Bad shielding

- Earth loops

- Connections

- Power supply +/-

- Disparate devices & power

- Floating zero

- uE offset

- Power requirement

o EV – cannot use vehicle supply

o Starting brownout & pulses

o Noise from EV DC to AC converters

o Signal swamping (rev pulses from tacho sensor etc)

Smarter Thinking.

© MIRA Ltd 2014

© N. Petrone N. Biliato, University of Padova,

2000

Space is always a problem

27 Channels on frame

+ 6 displacement

+ Speed/revs etc

Kit all in seat

Smarter Thinking.

© MIRA Ltd 2014

MIRA Collecting Data Real conditions

Smarter Thinking.

© MIRA Ltd 2014

Loading Conditions


Smarter Thinking.

© MIRA Ltd 2014

Low current draw – Long term data

Through number

of winter /

summer cycles

Measure voltage

& current

Measure usage

poaramters

accels,

operations

Sleep mode in

storage

Quiescent state,

wake on use or

timer.

Small packaging,

but low proce.

Few micro amps

only, to keep AIM

processer alive.

Smarter Thinking.

© MIRA Ltd 2014

Environment, Vibration, Unexpected conditions


Geographical

Mud/water/dust

Temperature/Humidity

Altitude

Electrical

EMC

Other!

Smarter Thinking.

© MIRA Ltd 2014

Various RLD Domains (Time is not everything)

• Set-up considerations (sample rate and filtering)

• Collecting enough data

• Why not collect all data at max sample rate

• Domains

- Time series

- Distance series

- Rotational

- Special

o Triggering

o Temperature

o Envelope

• Classifications for other domains

- Time series (ASD, ADA, JPD, CYH)

- Distance series (ASD, ADA, JPD, CYH)

- Rotational

- Etc

0 500 1000 1500 2000 2500-4

-3

-2

-1

0

1

2

3

4

LHF_Track_Rod(kN) car_c01_0093_037

Seconds

0 5000 1E4 1.5E4-3

-2

-1

0

1

2

3


m

Screen 1

1560 1580 1600 1620

-3

-2

-1

0

1

2

3


Seconds

Sample = 768

Npts = 2.068E6

Max Y = 3.036

Min Y = -3.951

8400 8500 8600 8700

-2

-1

0

1

2


m

Sample = 10

Npts = 1.967E5

Max Y = 2.952

Min Y = -2.798

Screen 3

Vehicle? Surface? Surface?

Smarter Thinking.

© MIRA Ltd 2014

Steering Entropy

Rolling Statistic per Second:

• Provides condition of steering movement during run

• Max , min, mean, RMS & std dev steering movement during each second.

• Entropy is “amount” of steering input (mean variation) & shake (standard deviation or spread) of steering to maintain driving conditions.

• Overall statistics during task provide one of level of assessment.

Mean

Std Dev

Angle

Straight Ahead

Mean

Std Dev Each Second

Smarter Thinking.

© MIRA Ltd 2014

Steering Entropy Visualisation (JPD)

Count number of occurrences steering at angle with amount it ‘shakes’ during task :

• Provides a picture illustrating steering statistic & amount of ‘nervousness’ in steering actions..

• Early days, difficulty providing a single statistic // may be useful using d(Steer Angle) / d(Lat Acc).

Mean Std Dev

Straight Ahead

Mean

Std Dev

Smarter Thinking.

© MIRA Ltd 2014

Assumed Failure – Test the right thing


It is easy to assume that just because we can reproduce a failure, that we have reproduced the process

or mode of failure. Actual causes can be difficult to assess.

Assumption

Actual Mode

Smarter Thinking.

© MIRA Ltd 2014

Analysis : Start + 20 End - 25

Shows change in setting

Drift or offset problem

20 25

Simple Calibrations

This can save large amounts

of time.

Aids credibility!

Smarter Thinking.

© MIRA Ltd 2014

We need to check the initial set-up of the whole system

Tip calculation

Calculate shunt

resistor at

gauge

Physical

calculation

View noise

and accuracy

View noise

and accuracy

Accuracy

Linearity

Noise

Assembly Calibration Checks

Set-up some standard check tests - constant circles

- accel / steady speed / braking

- wheel off - wheels on ground etc

Smarter Thinking.

© MIRA Ltd 2014

The real signal is continuous, but we will sample ...

Assumed signal

Actual signal

Sample points

Theory from Fourier Analysis

- To maintain frequency content, sample at 2 x Nyquist

- To maintain shape and amplitude, sample at 10 x Nyquist

Aliasing Problems

Smarter Thinking.

© MIRA Ltd 2014

1

-1

5170

LH

F.B

ody M

ount (

g)

Time (seconds)

DISPLAY OF test102

2585001 points.

5000 pts/secon

Displayed:

2585001 points.

from pt 1

Full file data:

Max = 0.7812

at 482.9616 seconds

Min = -0.7324

at 467.4204 seconds

Mean = 2.019E-3

S.D. = 0.1401

RMS = 0.1401

40

0

0.779634-0.8284619

Tim

e at level (seconds)

LHF.Body Mount (g)

DISPLAY OF test101

500 points.

310.3 pts/g

Displayed:

500 points.

from pt 1

Full file data:

Max = 31.37

at 0.04809544 g

Min = 4.767E-6

at 0.779634 g

Mean = 1.035

S.D. = 3.019

RMS = 3.189

Other Spatial Problems

Smarter Thinking.

© MIRA Ltd 2014

Other Aliasing Problems

5

-5

86

Strain

(u

E)

Time (Seconds)

DISPLAY OF signals

2.5

0

4000

Am

plitu

de (S

tr (u

E)

Frequency (Hz.)

DISPLAY OF signals

4 Sine waves added together

+/- 2 uE @ 2 Hz

+/- 1 uE @ 5 Hz

+/- 0.5 uE @ 20 Hz

+/- 0.75 uE @ 395 Hz

2.5

0

400

Am

plitu

de (S

tr (u

E)

Frequency (Hz.)

DISPLAY OF signals

4 Sine waves added together

+/- 2 uE @ 2 Hz

+/- 1 uE @ 5 Hz

+/- 0.5 uE @ 20 Hz

+/- 0.75 uE @ 395 Hz

Only interested in 0 - 40 Hz

5

-5

86

Strain

(u

E)

Time (Seconds)

DISPLAY OF alias

13108 points.

409.6 pts/Secon

Displayed:

819 points.

from pt 2459

Full file data:

Max = 3.822

at 0.6079102 Seconds

Min = -4.069

at 2.287598 Seconds

Mean = 2.063E-4

S.D. = 1.705

RMS = 1.705

2.5

0

400

Am

plitu

de (S

tr (u

E)

Frequency (Hz.)

DISPLAY OF alias

Original Title : Strain

WHERE DID +/- 0.75 uE @ 15 Hz COME FROM!

Smarter Thinking.

© MIRA Ltd 2014

The Accelerometer Trap – Again !

You have the accelerometer data

Mathematics says that integrating acceleration twice will

give the displacement

We can thus work out the AMPLITUDES !!!

Smarter Thinking.

© MIRA Ltd 2014

Contact Details


MIRA Ltd

Watling Street,

Nuneaton, Warwickshire,

CV10 0TU, UK

T: +44 (0)24 7635 5000

F: +44 (0)24 7635 8000

www.mira.co.uk

Firstname Secondname Qualifications / Affiliations

Job Title

Direct T: +44 (0)24 7635 5xxx

M: +44 (0)7xxx xxxxxx

E: [email protected]

RLD Processes and Analyses - Engineering Integrity...

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Transcript of RLD Processes and Analyses - Engineering Integrity...