摘要
针对观缆车主轴系统难以拆卸的特点,将声发射检测技术应用于观缆车轴承的故障诊断中,提出一种经验模态分解(Empirical mode decomposition,EMD)与近似熵相结合的观缆车轴承故障诊断方法.即利用观缆车试验台对滚动轴承无故障、内圈故障和滚动体故障进行模拟,采集其声发射信号.通过EMD方法将获取的声发射信号分解为若干个本征模态函数(Intrinsic mode function,IMF)分量,然后利用能量和相关系数法选取IMF分量,最后对筛选的IMF分量进行近似熵计算.实验结果表明,该方法能够有效判断观缆车滚动轴承是否存在故障.
Aiming at the difficulty of disassembling the main spindle of the ferris wheel,the acoustic emission(AE)detection technology was applied to the fault diagnosis of the ferris wheel bearing.A fault diagnosis of the ferris wheel bearing based on empirical mode decomposition(EMD)and aproximate entropy(ApEn)was proposed.The rolling bearing fault-free,the inner ring fault and the rolling element fault were simulated by the ferris wheel test bench.The acoustic emission signals were collected.The acoustic emission signals of the rolling bearing were decomposed into several intrinsic mode function(IMF)components by the EMD algorithm.Then the IMF components were selected by using the energy and correlation coefficient method.Finally,the approximate entropy of IMF components was calculaed.The results showed that the method can effectively detect the ferris wheel bearing fault.
作者
金榕舜
沈功田
王强
张君娇
JIN Rongshun;SHEN Gongtian;WANG Qiang;ZHANG Junjiao(College of Quality and Safety Engineering,China Jiliang University,Hangzhou 310018,China;China Special Equipment Inspection and Research Institute,Beijing 100029,China)
出处
《中国计量大学学报》
2018年第4期417-423,共7页
Journal of China University of Metrology
基金
国家重点研发计划项目(No.2016YFF0203104)
关键词
声发射
经验模态分解
近似熵
故障诊断
acoustic emission
EMD
approximate entropy
fault diagnosis
作者简介
金榕舜(1993-),男,浙江省临海人,硕士研究生,主要研究方向为无损检测技术.E-mail:jinrongshun@qq.com;通信联系人:沈功田,男,研究员.E-mail:shengongtian@csei.org.cn
