TT变换结合计算阶比跟踪的滚动轴承时变微弱故障特征提取

发布时间：2018-02-11 10:42

本文关键词： TT变换计算阶比跟踪奇异值分解滚动轴承变转速故障诊断　出处：《中国电机工程学报》2017年20期 　论文类型：期刊论文

【摘要】：为解决变转速工况滚动轴承微弱故障特征难以提取的问题,提出了时时(time-time,TT)变换结合计算阶比跟踪(computed order tracking,COT)的滚动轴承时变微弱故障特征提取方法。首先对变转速状态的轴承微弱故障信号进行时时变换,得到反映故障信号二维时时特征的TT变换矩阵。为消除TT变换矩阵的冗余性,提出了基于峭度准则的奇异值分解(singular value decomposition,SVD)方法对TT变换矩阵降噪。然后对降噪后的TT变换矩阵实施TT反变换,获取滚动轴承时变故障特征增强信号。最后对增强信号进行COT分析得到其包络阶比谱,从而提取滚动轴承的故障特征阶次。对仿真信号和实验测试信号进行分析验证,均实现了滚动轴承变转速工况故障类型的精确识别,分析效果优于包络阶比谱方法,证明了该方法的有效性。
[Abstract]:In order to solve the problem that it is difficult to extract the weak fault features of rolling bearings under variable speed conditions, A method of extracting time-varying weak fault feature of rolling bearing based on time-time TTT transform combined with computed order tracking method is proposed. Firstly, the weak fault signal of bearing in variable speed state is transformed from time to time. In order to eliminate the redundancy of the TT transform matrix, a TT transform matrix reflecting the two-dimensional characteristics of the fault signal is obtained. A singular value decomposition (SVD) method based on kurtosis criterion is proposed to reduce the noise of TT transform matrix. Finally, the envelope order spectrum of the enhanced signal is obtained by COT analysis, and the fault feature order of the rolling bearing is extracted. The simulation signal and the experimental test signal are analyzed and verified. The fault types of rolling bearings under variable speed conditions are accurately identified. The analysis results are superior to the envelope order ratio spectrum method, and the effectiveness of this method is proved.
【作者单位】：华北电力大学能源动力与机械工程学院;
【基金】：国家自然科学基金项目(51307058,51475164) 河北省自然科学基金项目(E2014502052) 中央高校基本科研业务费专项资金资助项目(2017XS134)~~
【分类号】：TH133.33

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