The probabilistic analysis of fatigue crack effect based on magnetic flux leakage

M. Ahmad, A. Arifin, S. Abdullah, W. Jusoh, S. Singh
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引用次数: 3

Abstract

In this paper, probabilistic analysis on the fatigue crack effect was investigated by applying the Metal Magnetic Memory (MMM) method, based on Self-Magnetic Leakage Field (SMLF) signals on the surface of metal components. The precision of MMM signals is essential in identifying the validity of the proposed method. The tension-tension fatigue test was conducted using the testing frequency of 10 Hz with 4 kN loaded, and the MMM signals were captured using the MMM instrument. As a result, a linear relationship was observed between the magnetic flux leakage and cyclic loading parameter, presenting the R-squared value at 0.72-0.97. The 2P-Weibull distribution function was used as a probabilistic approach to identify the precision of the data analysis from the predicted, and experimental fatigue lives, thereby showing that all points are placed within the range of a factor of 2. Additionally, the characteristics of PDF, CDF, failure rate and failure probability data analysis were plotted and described. Therefore, a 2P-Weibull probability distribution approach is determined to be an appropriate method to determine the accuracy of data analysis for MMM signals in a fatigue test for metal components.
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基于漏磁的疲劳裂纹效应概率分析
本文基于金属构件表面的自漏磁场信号,应用金属磁记忆(MMM)方法对疲劳裂纹效应进行了概率分析。MMM信号的精度是确定该方法有效性的关键。测试频率为10 Hz,载荷为4 kN,进行拉伸-拉伸疲劳试验,并利用MMM仪器采集MMM信号。结果表明,漏磁与循环加载参数呈线性关系,r平方值为0.72 ~ 0.97。使用2P-Weibull分布函数作为概率方法,从预测和实验疲劳寿命中识别数据分析的精度,从而表明所有点都位于因子2的范围内。此外,还绘制和描述了PDF、CDF的特征、故障率和故障率数据分析。因此,确定2P-Weibull概率分布方法是确定金属构件疲劳试验中MMM信号数据分析精度的合适方法。
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来源期刊
International Journal of Reliability and Safety
International Journal of Reliability and Safety Engineering-Safety, Risk, Reliability and Quality
CiteScore
1.00
自引率
0.00%
发文量
1
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