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一种基于支持向量机预测器模型的转子系统故障诊断方法
引用本文:于德介,陈淼峰,程军圣,杨宇.一种基于支持向量机预测器模型的转子系统故障诊断方法[J].中国机械工程,2006,17(7):696-699.
作者姓名:于德介  陈淼峰  程军圣  杨宇
作者单位:湖南大学,长沙,410082
基金项目:中国科学院资助项目;广东省博士启动基金
摘    要:提出了一种基于支持向量机回归预测模型的转子系统故障诊断方法。分别对转子系统振动信号建立支持向量机回归预测模型,利用回归预测模型对振动测试信号进行预测,计算各支持向量机回归预测模型的预测信号与真实信号的误差并计算信噪比,通过比较各预测信号的信噪比来判断转子系统的工作状态和故障类型。实验结果表明,该方法能够有效地应用于转子系统的故障诊断。

关 键 词:回归  预测  支持向量机  故障诊断  转子系统
文章编号:1004-132X(2006)07-0696-04
收稿时间:2005-04-18
修稿时间:2005-04-18

Fault Diagnosis Approach for Rotor Systems Based on Support Vector Machine Predictive Model
Yu Dejie,Chen Miaofeng,Cheng Junsheng,Yang Yu.Fault Diagnosis Approach for Rotor Systems Based on Support Vector Machine Predictive Model[J].China Mechanical Engineering,2006,17(7):696-699.
Authors:Yu Dejie  Chen Miaofeng  Cheng Junsheng  Yang Yu
Affiliation:Hunan University, Changsha, 410082
Abstract:A fault diagnosis approach for rotor systems based on support vector machine predictive model was proposed. Firstly, the SVMs regression for predictive model of the vibration signals of a rotor system was established. Then, the support vector machine models were used to predict some time series of vibration signals and the values of SNR were calculated. By comparing the values of SNR, the conditions and fault patterns of a rotor system can be identified. Practical examples demon strate that the SVMs predictive model can be applied to rotor system fault diagnosis effectively.
Keywords:regression  prediction  support vector machine  fault diagnosis  rotor system
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