Vibrationdata 1 Non-Gaussian Random Fatigue and Peak Response Unit 36.

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Presentation transcript:

Vibrationdata 1 Non-Gaussian Random Fatigue and Peak Response Unit 36

Introduction Perform a fatigue and peak response analysis for a non-Gaussian random time history base input Compare results to Gaussian time history which matches the PSD of the non-Gaussian case Broadband random, stationary, Gaussian time histories have kurtosis=3 Higher kurtosis time history will be demonstrated Develop critical thinking skills about signal analysis, statistical parameters, fatigue damage, etc

Vibrationdata 3 Statistical Formulas n Skewness = n Kurtosis = n Mean = n Variance = n Standard Deviation is the square root of the variance where Y i is each instantaneous amplitude, n is the total number of points,  is the mean,  is the standard deviation

Non-Gaussian Time History, std dev=10, skewness=0, kurtosis=5, 60 seconds vibrationdata > Generate Signal > random with specified skewness & kurtosis

Non-Gaussian Time History Array name: random_k5 Also, crest factor = 7.1

Non-Gaussian Time History, Close-up View

Non-Gaussian Time History, kurtosis = 5 Resembles witch hat!

Take PSD of Non-Gaussian Time History

PSD of Non-Gaussian Time History Roll-off is due to band limiting

Response to Base Input fn = 600 Hz Q=10 Fatigue exponent b=6.4

SDOF Response to Non-Gaussian Base Input, fn=600 Hz, Q=10

SDOF Response to Non-Gaussian Base Input, Statistics Absolute Peak Response = 115 G, std dev = 21.4 G, Crest Factor = 5.4, kurtosis= 3.15

SDOF Response to Non-Gaussian Base Input, Histogram The histogram approaches a Gaussian shape even though the input is non-Gaussian. See: Central Limit Theorem

Central Limit Theorem For a strongly resonant system subjected to broad band excitation, the central limit theorem makes it possible to establish that the response tends to be Gaussian even if the input is not. This applies when the excitation is not white noise, provided that it is a broad band process covering the resonant peak. - Christian Lalanne

SDOF Response to Non-Gaussian Base Input, Relative Damage Relative Damage = 9.1e+14

Derive Test Spec from PSD of Non-Gaussian Base Input 0.05 G^2/ Hz from 10 to 2000 Hz >> psd_spec =[ ; ] psd_spec = 1.0e+03 * But the PSD spec will assume Gaussian histogram with kurtosis = 3

Synthesize Time History for Test Specification, with Gaussian Histogram

Synthesized Time History for Test Specification

Synthesized Time History for Test Specification, Histogram

SDOF Response to Synthesized Time History for Test Specification

SDOF Response to Synthesized Time History for Test Specification, Statistics Absolute Peak Response = 106 G, std dev = 22.0 G, Crest Factor = 4.8, kurtosis= 3.03

Relative Damage = 9.3e+14 SDOF Response to Synthesized Time History for Test Specification, Relative Damage

Response Parameters by Input Type ParameterNon-GaussianGaussian GRMS Peak G Crest Factor Kurtosis Damage (G^6.4)9.1e+149.3e+14 SDOF System, fn = 600 Hz, Q = 10, b = 6.4 The non-Gaussian base input causes a higher peak acceleration response The Gaussian input yields a slightly higher fatigue damage

Fatigue Damage Spectrum (FDS) The fatigue damage spectrum can be calculated if the natural frequency is unknown Natural frequency is an independent variable The FDS is conceptually similar to the SRS and VRS functions

Calculate the Fatigue Damage Spectrum for the SDOF Response to Non-Gaussian Input

Calculate the Fatigue Damage Spectrum for the SDOF Response to Gaussian Input

Plot the Fatigue Damage Spectra

Comparing Different Environments in Terms of Damage Potential In this example, the kurtosis difference did not really affect the damage level. But may not always be the case! So be careful!