基于K熵和关联维数的金属疲劳损伤过程的声发射信号特征分析
发布时间：2019-05-12 11:49
【摘要】：深化对金属疲劳损伤过程中声发射信号的特征认识,是运用声发射信号对金属结构损伤过程进行监测预测的重要基础热点问题。针对金属疲劳损伤经历裂纹萌生阶段、裂纹缓慢扩展阶段、裂纹快速扩展阶段、临近破坏等四个阶段产生大量的声发射信号,采用K熵和关联维数等混沌特征量来分析海量的声发射信号;通过对45号钢试件进行三点弯曲疲劳试验、测试得到试件疲劳损伤过程的声发射信号,分别估算不同时间段所产生声发射信号的K熵和关联维数,分析结果表明金属疲劳损伤过程的声发射信号具有混沌特征,其K熵和关联维数的变化趋势与金属疲劳损伤过程的四个阶段具有较清晰的对应关联,表明K熵和关联维数可以较好的揭示金属疲劳损伤过程的动力学特性,这将为运用声发射信号实现金属结构疲劳损伤在线监测及预测提供了一种新思路。
[Abstract]:Deepening the understanding of the characteristics of acoustic emission signals in the process of metal fatigue damage is an important basic hot issue in monitoring and predicting the damage process of metal structures by using acoustic emission signals. A large number of acoustic emission signals are generated in four stages of metal fatigue damage: crack initiation stage, slow crack propagation stage, fast crack propagation stage and near failure stage. K entropy and correlation dimension are used to analyze a large number of acoustic emission signals. Through three-point bending fatigue test of 45 steel specimen, the acoustic emission signal of fatigue damage process of 45 steel specimen is obtained, and the K entropy and correlation dimension of acoustic emission signal produced in different time periods are estimated respectively. The analysis results show that the acoustic emission signal of metal fatigue damage process has chaotic characteristics, and the variation trend of K entropy and correlation dimension has a clear correlation with the four stages of metal fatigue damage process. It is shown that K entropy and correlation dimension can reveal the dynamic characteristics of metal fatigue damage process, which will provide a new idea for on-line monitoring and prediction of metal structure fatigue damage by using acoustic emission signal.
【作者单位】： 广西大学机械工程学院;广西科技大学汽车与交通学院;长沙理工大学工程车辆安全性设计与可靠性技术湖南省重点实验室;
【基金】：国家自然科学基金(51365006;51445013;51105045) 广西制造系统与先进制造技术重点实验室课题(14-045-15S05)
【分类号】：TG115.57
本文编号：2475369
[Abstract]:Deepening the understanding of the characteristics of acoustic emission signals in the process of metal fatigue damage is an important basic hot issue in monitoring and predicting the damage process of metal structures by using acoustic emission signals. A large number of acoustic emission signals are generated in four stages of metal fatigue damage: crack initiation stage, slow crack propagation stage, fast crack propagation stage and near failure stage. K entropy and correlation dimension are used to analyze a large number of acoustic emission signals. Through three-point bending fatigue test of 45 steel specimen, the acoustic emission signal of fatigue damage process of 45 steel specimen is obtained, and the K entropy and correlation dimension of acoustic emission signal produced in different time periods are estimated respectively. The analysis results show that the acoustic emission signal of metal fatigue damage process has chaotic characteristics, and the variation trend of K entropy and correlation dimension has a clear correlation with the four stages of metal fatigue damage process. It is shown that K entropy and correlation dimension can reveal the dynamic characteristics of metal fatigue damage process, which will provide a new idea for on-line monitoring and prediction of metal structure fatigue damage by using acoustic emission signal.
【作者单位】： 广西大学机械工程学院;广西科技大学汽车与交通学院;长沙理工大学工程车辆安全性设计与可靠性技术湖南省重点实验室;
【基金】：国家自然科学基金(51365006;51445013;51105045) 广西制造系统与先进制造技术重点实验室课题(14-045-15S05)
【分类号】：TG115.57
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，本文编号：2475369
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