信号特征提取方法在球磨机故障诊断中的应用  

Application of Signal Feature Extraction Method in Ball Mill Fault Diagnosis

作　　者：李名莉 焦欣欣[1] LI Mingli;JIAO Xinxin(Institute of Electromechanical Automation,Henan Polytechnic University,Nanyang 473000)

机构地区：[1]河南工业职业技术学院机电自动化学院

出　　处：《计算机与数字工程》2019年第10期2622-2626,共5页Computer & Digital Engineering

摘　　要：球磨机运行现场工矿复杂,为对球磨机进行故障监测与诊断,在研究中对球磨机的故障信号进行小波分解和Hilbert小波包络谱分析,找出奇变点对应的频率,诊断出故障部位,最后通过特征向量和欧氏距离的计算,证明了方法的有效性。Ball mill running field is complex,for ball mill fault monitoring and diagnosis,wavelet decomposition and Hilbert wavelet envelope spectrum analysis are applied in the study of the ball mill fault signal,the frequency corresponding is found out to the singularity pointand diagnose the fault location.Finally,through the calculation of eigenvector and Euclidean distance,the effectiveness of the method is proved.

关 键 词：故障诊断 小波分解 Hilbert小波包络谱 特征向量 欧氏距离 

分 类 号：TP23[自动化与计算机技术—检测技术与自动化装置]