海军航空工程学院,海军航空工程学院 飞行器检测与应用研究所,海军航空工程学院,海军航空工程学院
TN911.23；TP206.3
国家部委预研基金资助(9140A27020214JB1446)
Department of Aircraft Engineering,Naval Aeronautical and Astronautical University,YanTai Shandong,Institute of Aircraft Detection and Application,Naval Aeronautical and Astronautical University,Yantai Shandong,Department of Aircraft Engineering,Naval Aeronautical and Astronautical University,YanTai Shandong,Department of Aircraft Engineering,Naval Aeronautical and Astronautical University,YanTai Shandong
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轴承故障振动信号具有非平稳、非线性特征，且可视为多个调幅-调频分量的叠加，单分量的包络蕴含了轴承的故障特征。局部特征尺度分解可将振动信号准确分解为多个内禀尺度分量之和，某些分量能清晰反映轴承的运行状态，根据包络谱可进行故障诊断。为了准确筛选有用分量，提出了基于滑动峭度相关性准则的分量筛选方法。首先，对信号进行局部特征尺度分解，得到若干个内禀尺度分量；然后，对分量和原始信号分别计算滑动峭度，生成时间序列；最后，依据分量滑动峭度序列与原始信号滑动峭度序列的互相关系数筛选有用分量。通过轴承内圈故障数据分析发现：有用分量与非有用分量之间的滑动峭度互相关系数比互相关系数差异明显，区分度更大，有益于分量的分类、筛选。
In order to process the roller bearing fault vibration signals, aiming at determining the effective components of local characteristic-scale decomposition(LCD), a new method based on sliding kurtosis correlation coefficients was proposed. Firstly, the vibration signal was decomposed into some intrinsic mode components (ISC) by LCD. Secondly, the sliding kurtosis of every ISC and the original signal were calculated. At last, the effective components were selected by the sliding kurtosis correlation coefficients. The analysis of the bearing fault data shows that the method can realize the determining effective components of LCD effectively.
引用本文
崔伟成,许爱强,李伟,孟凡磊.基于滑动峭度相关性准则的局部特征尺度分解分量筛选方法计算机测量与控制[J].,2016,24(10).
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- 收稿日期:2016-05-05
- 最后修改日期:2016-05-25
- 录用日期:2016-05-26
- 在线发布日期: 2016-11-09
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