scholarly journals Fatigue Life Prediction of Long-Life Pavement Using Frequency-Domain Analysis

2017 ◽  
Vol 19 (6) ◽  
pp. 80
Author(s):  
Baoli Wei ◽  
Chengchao Guo ◽  
Can Cui
Keyword(s):  
Fatigue Life ◽  
Frequency Domain ◽  
Life Prediction ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Fatigue Life Prediction ◽  
Long Life

Fatigue Reliability Analysis Including Super Long Life Regime

2010 ◽  
Vol 118-120 ◽  
pp. 17-26 ◽  
Author(s):  
Yong Xiang Zhao
Keyword(s):  
Fatigue Life ◽  
Reliability Analysis ◽  
Life Prediction ◽  
Reliability Assessment ◽  
Cyclic Stress ◽  
Fatigue Life Prediction ◽  
Fatigue Reliability ◽  
Stress Strain ◽  
Structural Fatigue ◽  
Long Life

For an engineering structure with an actual fatigue life over that corresponding to a so-called fatigue limit, appropriate reliability assessment and fatigue life prediction are essential for developing the structure and sustaining its high quality in service. Basic clues are explored. A competition fatigue initial mechanism is shown to provide a requirement of material primary quality management. Affordable deduced material and structural probabilistic S-N curves are presented by fitting into material mid-and-long life S-N data and fatigue limits and, then, comparing to structural fatigue limits. Random cyclic stress-strain relations are depicted for constructing random stressing history of structures. Reliability assessment and fatigue life prediction are established to synthetically consider the interference of applied stresses deduced from the random cyclic stress-strain relations and capacity strengths derived from the structural S-N relations with an expected life. Affordable and appropriate method has been then developed to realize the reliability assessment and fatigue life prediction including the super long life regime. Availability of the present method has been indicated through a reliability analysis to the velocity related reliabilities and fatigue lives of a railway axle.

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.  

Automotive Component Fatigue Life Estimation by Frequency Domain Approach

2005 ◽  
Vol 297-300 ◽  
pp. 1776-1783 ◽  
Author(s):  
Do Hyun Jung ◽  
Sung In Bae
Keyword(s):  
Fatigue Life ◽  
Frequency Domain ◽  
Time Domain ◽  
Motor Vehicle ◽  
Local Strain ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Life Estimation ◽  
Fatigue Life Estimation

Time domain approach with S-N approach and local strain approach were used for fatigue life estimation. But these days, using PSD (Power Spectral Density) method is highlighted, because of short amount of time in measurement and analysis. Especially, PSD method is useful for analysis of fatigue failure which is caused by vibration damage, also FRF (Frequency Response Function) is useful for efficient prediction of fatigue life when the same product is employing different motor vehicle or test condition. In order to estimate fatigue life of compressor for air conditioning, time domain analysis and frequency domain analysis were performed and the results were compared. As a result, results of analysis in frequency domain and time domain were similar. With this, there is recognition of decreasing the period of measuring and analysis in PSD analysis. Moreover, in case of FRF pursued of a part, using FRF is applicable at fatigue life prediction in different testing condition. There was investigated an analysis method with curtailed analysis period by FRF.

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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