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为及时准确地确定钻具疲劳损伤及应力集中位置,确定疲劳损伤程度,对42CrMo钢缺口试件进行拉扭疲劳试验及磁记忆在线检测。试验中实时采集磁记忆信号的切向分量,分析其梯度变化趋势,并提取Hp(x)max,Hp(x)sub,Kmax,Ksub等4个磁记忆信号特征参量,研究这4个特征参量在整个疲劳循环过程中的变化规律,并比较在线卸载与在线加载检测各特征参量的异同。试验结果表明,在整个疲劳过程中,各磁记忆信号特征参量具有不同的变化规律,很好地诠释了材料的拉扭疲劳过程,表征出不同疲劳阶段材料的应力集中程度。
In order to timely and accurately determine the fatigue damage and stress concentration location of drilling tools and determine the degree of fatigue damage, tensile fatigue test and magnetic memory online testing of 42CrMo steel notched specimens were carried out. In the experiment, the tangential components of magnetic memory signals were collected in real time, and the trend of gradient was analyzed. The four magnetic memory signal parameters Hp (x) max, Hp (x) sub, Kmax and Ksub were extracted to study the four characteristic parameters In the entire fatigue cycle of the law of variation, and online load detection and online comparison of the characteristics of the different parameters. The experimental results show that the characteristic parameters of the magnetic memory signals have different variation rules throughout the fatigue process, and the fatigue and torsional fatigue of the material are well interpreted, and the stress concentration of the material in different fatigue stages is characterized.