Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data

The response spectra are widely used in the damage assessment of non-Gaussian random vibration environments and the derivation of damage equivalent accelerated test spectrum. The effectiveness of the latter is strongly affected by modal parameter uncertainties, multiple field data processing, and th...

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Main Authors: Fei Xu, Kjell Ahlin, Binyi Wang
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Journal of Sensors
Online Access:http://dx.doi.org/10.1155/2021/3668726
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spelling doaj-b4c9b5ad7eb143fc8f967c5f7fb4b70e2021-09-20T00:29:51ZengHindawi LimitedJournal of Sensors1687-72682021-01-01202110.1155/2021/3668726Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration DataFei Xu0Kjell Ahlin1Binyi Wang2School of Automotive EngineeringProfessor Emeritus Blekinge Tekniska HögskolaNorthwest Institute of Mechanical and Electrical EngineeringThe response spectra are widely used in the damage assessment of non-Gaussian random vibration environments and the derivation of damage equivalent accelerated test spectrum. The effectiveness of the latter is strongly affected by modal parameter uncertainties, multiple field data processing, and the nonsmooth shape of the derived power spectral density (PSD). Optimization of accelerated test spectrum derivation based on dynamic parameter selection and iterative update of spectrum envelope is presented in this paper. The extreme response spectrum (ERS) envelope of the field data is firstly taken as the limiting spectrum, and the corresponding relationship between damping coefficient, fatigue exponent, and damage equivalent PSD under different test times is constructed to achieve the dynamic selection of uncertain parameters in the response spectrum model. Then, an iterative update model based on the weighted sum of fatigue damage spectrum (FDS) error is presented to reduce the error introduced by the nonsmooth shape of the derived PSD. The case study shows that undertest can be effectively avoided by the dynamic selection of model parameters. The weighted error is reduced from 80.1% to 7.5% after 7 iterations. Particularly, the error is close to 0 within the peak and valley frequency band.http://dx.doi.org/10.1155/2021/3668726
collection DOAJ
language English
format Article
sources DOAJ
author Fei Xu
Kjell Ahlin
Binyi Wang
spellingShingle Fei Xu
Kjell Ahlin
Binyi Wang
Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data
Journal of Sensors
author_facet Fei Xu
Kjell Ahlin
Binyi Wang
author_sort Fei Xu
title Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data
title_short Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data
title_full Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data
title_fullStr Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data
title_full_unstemmed Optimization of Damage Equivalent Accelerated Test Spectrum Derivation Using Multiple Non-Gaussian Vibration Data
title_sort optimization of damage equivalent accelerated test spectrum derivation using multiple non-gaussian vibration data
publisher Hindawi Limited
series Journal of Sensors
issn 1687-7268
publishDate 2021-01-01
description The response spectra are widely used in the damage assessment of non-Gaussian random vibration environments and the derivation of damage equivalent accelerated test spectrum. The effectiveness of the latter is strongly affected by modal parameter uncertainties, multiple field data processing, and the nonsmooth shape of the derived power spectral density (PSD). Optimization of accelerated test spectrum derivation based on dynamic parameter selection and iterative update of spectrum envelope is presented in this paper. The extreme response spectrum (ERS) envelope of the field data is firstly taken as the limiting spectrum, and the corresponding relationship between damping coefficient, fatigue exponent, and damage equivalent PSD under different test times is constructed to achieve the dynamic selection of uncertain parameters in the response spectrum model. Then, an iterative update model based on the weighted sum of fatigue damage spectrum (FDS) error is presented to reduce the error introduced by the nonsmooth shape of the derived PSD. The case study shows that undertest can be effectively avoided by the dynamic selection of model parameters. The weighted error is reduced from 80.1% to 7.5% after 7 iterations. Particularly, the error is close to 0 within the peak and valley frequency band.
url http://dx.doi.org/10.1155/2021/3668726
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AT kjellahlin optimizationofdamageequivalentacceleratedtestspectrumderivationusingmultiplenongaussianvibrationdata
AT binyiwang optimizationofdamageequivalentacceleratedtestspectrumderivationusingmultiplenongaussianvibrationdata
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