Study of Multi-axis Load Spectrum Edition Method Based on the Wavelet Transform to the Accelerated Durability Test of the Vehicle Components

The multi-axis load spectrum edition based on the wavelet transform to the vehicle component accelerated durability test is introduced. And a modified resampling method is proposed to preprocess the acquisited load spectrum. Some peak and valley points of the load spectrum are ignored in the general...

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Veröffentlicht in:Ji xie gong cheng xue bao 2018, Vol.54 (10), p.156
1. Verfasser: ZHENG, Guofeng
Format: Artikel
Sprache:eng
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Zusammenfassung:The multi-axis load spectrum edition based on the wavelet transform to the vehicle component accelerated durability test is introduced. And a modified resampling method is proposed to preprocess the acquisited load spectrum. Some peak and valley points of the load spectrum are ignored in the general resampling method. And these neglecting points will lead to the damage calculation error of the load spectrum. The modified resampling method eliminates the error of damage calculation through reassign the neglected peak and valley points. After the resampling, wavelet decomposition is conducted to the load spectrum. The high frequency wavelet component is obtained by the load spectrum wavelet transformation. And the envelope damage identification method is used to identify the damage contribution parts of the load spectrum by setting a threshold value to the high frequency wavelet component. The shorten load spectrum is obtained by organizing the most the damage contribution parts identified before. The edition load spectrum based on the wavelet transform edition method has the similar parameters including pseudo-damage, mean value, root mean square and kurtosis as well as the energy to the original spectrum. It is illustrated that the edited load spectrum has the same effect to the original one. The proposed load spectrum edition method can be used in the accelerated durability test research of all the vehicle components.
ISSN:0577-6686
DOI:10.3901/JME.2018.10.156