文章摘要
基于MCKD和teager能量算子的滚动轴承复合故障诊断
Composite fault diagnosis of rolling bearing based on MCKD and Teager energy operator
投稿时间:2018-06-17  修订日期:2018-07-29
DOI:
中文关键词: 复合故障  MCKD  能量算子  故障诊断
英文关键词: Composite failure  MCKD  energy operator  fault diagnosis
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)、内蒙古自治区自然科学基金
作者单位邮编
齐咏生* 内蒙古工业大学 010051
刘飞 内蒙古工业大学 010051
高学金 北京工业大学 
李永亭 内蒙古工业大学 
刘利强 内蒙古工业大学 
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中文摘要:
      滚动轴承是旋转机械的主要部件之一,由于其工作环境的复杂多变,导致其频繁的出现故障,且大部分情况下是多种故障复合的情况。针对这一问题,提出一种基于改进最大相关峭度解卷积(MCKD)和teager能量算子混合的滚动轴承复合故障诊断方法。该方法通过粒子群寻优算法(PSO)对不同类型故障情况下MCKD的影响参数(L和M)进行寻优,设置与故障类型相对应的解卷积周期,以相关峭度最大化进行MCKD算法迭代运算,优化滤波器系数,改进的MCKD算法减少了噪声的干扰,然后利用teager能量算子具有检测信号瞬态冲击方面的优势,对信号的teager能量进行频谱分析实现复合故障特征提取。最后利用西楚大学轴承数据和轴承故障模拟实验台对该算法进行验证,结果表明该方法能有效从滚动轴承单一和复合故障中提取故障特征信息,准确识别出故障类型。
英文摘要:
      Rolling bearing is one of the main parts of rotating machinery, because of its complex and changeable working environment, it causes frequent failure and many kinds of fault compound. In order to solve this problem, a composite fault diagnosis method of rolling bearing based on improved maximum correlated kurtosis deconvolution (MCKD) and Teager energy operator is proposed. In this method, particle swarm optimization (PSO) is used to optimize the MCKD parameters (L and m) of different types of faults, to set up the deconvolution period corresponding to the fault type, to calculate the MCKD algorithm with the maximum correlation kurtosis, and to improve the filter coefficients, The improved MCKD algorithm can reduce the noise interference to a great extent, and then use the Teager energy operator to detect the transient impact of the signal, and analyze the Teager energy spectrum to realize the compound fault extraction and diagnosis. Finally, the method is validated by using the bearing data of Case Western Reserve University and the bearing fault simulator, and the results show that it can effectively extract fault feature information from single and compound fault of rolling bearing and identify the fault type accurately.
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