机械密封端面接触状态的声发射监测研究

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摘要有效监测机械密封的端面接触状态有助于对密封失效做出早期预警。针对密封声发射信号难以降噪的问题，提出基于神经网络粒子滤波和最小二乘支持向量机的声发射建模方法。首先通过机械密封的端面膜厚测量，研究声发射能量在密封启动过程中的变化规律；接着利用人工神经网络构建信号的状态空间，再通过粒子滤波算法对状态空间滤波降噪；最后从滤波信号中提取特征，并利用最小二乘支持向量机构建机械密封端面接触状态的检测模型。实验数据证明该方法能有效实现机械密封端面状态的无损检测，具有良好的工业前景。

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关键词 ：密封端面接触, 声发射, 粒子滤波, 状态监测, 最小二乘支持向量机

Abstract：

Monitoring the contact state of seal end faces would help to the early warning of the seal failure. For the problem of the difficulty in seal signal denoising, a new approach based on particle filter with artificial neural network (ANN-PF) and least square support vector machine (LS-SVM) is presented for acoustic emission (AE) modeling. Following the measurement of seal film thickness, variations of the AE energy during the seal startup are studied first. Then Elman ANN is used to build the dynamic state space (DSS) of the AE signal and PF is used for signal filtering. Finally, multiple features are extracted and a classification model based on LS-SVM is constructed for state monitoring. Experimental data shows that the proposed method can detect the seal face contact effectively and non-destructively, and has a wide industrial prospect.

Key words： seal face contact acoustic emission particle filter state monitoring least square support vector machine

收稿日期: 2015-06-19 出版日期: 2016-04-15

引用本文:

李晓晖1，傅攀1，曹伟青1，陈侃2. 机械密封端面接触状态的声发射监测研究[J]. 振动与冲击, 2016, 35(8): 83-89.
Li Xiao-hui 1 Fu Pan 1 Cao Wei-qing 1 Chen Kan 2 . The study of acoustic emission monitoring for contact state of seal end faces. JOURNAL OF VIBRATION AND SHOCK, 2016, 35(8): 83-89.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2016/V35/I8/83

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