scholarly journals A critical analysis of the Mises stress criterion used in frequency domain fatigue life prediction

2016 ◽  
Vol 10 (38) ◽  
pp. 177-183 ◽  
Author(s):  
Adam Niesony
Keyword(s):  
Fatigue Life ◽  
Frequency Domain ◽  
Critical Analysis ◽  
Life Prediction ◽  
Fatigue Life Prediction ◽  
Stress Criterion

scholarly journals Durability Analysis for Coil Spring Suspension Based on Strain Signal Characterisation

2018 ◽  
Vol 7 (3.17) ◽  
pp. 104
Author(s):  
Chin Chuin Hao ◽  
Shahrum Abdullah ◽  
Ahmad Kamal Ariffin ◽  
Salvinder Singh Karam Singh
Keyword(s):  
Fourier Transform ◽  
Fatigue Life ◽  
Frequency Domain ◽  
Time Domain ◽  
Life Prediction ◽  
Energy Content ◽  
Fatigue Life Prediction ◽  
Coil Spring ◽  
Time Frequency ◽  
Strain Signal

This paper aims to predict the durability of an automobile coil spring by characterising the captured strain data. The load histories collected at coil spring are often presented in time domain but time domain cannot provide sufficient information for fatigue life prediction. The objective of this study was to characterise the strain signal in time domain, frequency domain and time-frequency domain for fatigue life prediction. The signal obtained in time domain was used to predict the fatigue life of the coil spring through Rainflow cycle counting technique and models of strain-life relationships. In frequency domain, fast Fourier transform revealed that the frequency components in the strain signal ranged between 0-5 Hz. The frequencies can be further categorised into two ranges: 0-0.3 Hz and 1-2 Hz. Power spectral density confirmed that the frequencies with high energy content were 0-5 Hz and the total energy content in the signal is 4.0872x103 µɛ2. Short time Fourier transform can identify the local time and frequency properties of the signal but it has a limitation in time-frequency resolutions. Wavelet transform can provide a better time-frequency resolutions and it confirmed that the transients in the time domain had frequency range of 1-2 Hz. In summary, this study revealed different possible approaches of signal processing in fatigue life assessment of automotive components as guidance for the selection of suitable approach based on the type of information needed for the analysis.  

Accurate Prediction of Fatigue Life under Random Loading

2014 ◽  
Vol 891-892 ◽  
pp. 1347-1352
Author(s):  
Norio Takeda ◽  
Tomohiro Naruse
Keyword(s):  
Fatigue Life ◽  
Frequency Domain ◽  
Prediction Accuracy ◽  
Life Prediction ◽  
Stress Amplitude ◽  
Fatigue Life Prediction ◽  
Random Loading ◽  
Power Spectral ◽  
Mechanical Products ◽  
As Stress

This study focuses on the method of predicting the fatigue life of materials subjected to random loading. Since random stress caused by random loading is rigorously expressed in the frequency domain as stress power spectral density (PSD), fatigue life should be predicted using stress PSD. We propose two adjustment methods of improving the accuracy of fatigue life prediction using stress PSD in the frequency domain. The method proposed by Dirlik is widely used for predicting the fatigue life in the frequency domain; however, it overestimates fatigue damage caused by large stress amplitude when the slope of the fatigue resistance curve is large. To prevent this overestimation, we applied our two adjustment methods to fatigue life prediction for typical random stresses observed on mechanical products. As a result, the adjustment methods worked well in improving prediction accuracy. Lightweight and reliable products can be therefore designed by applying the proposed methods to the evaluation of fatigue life under random loading.

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