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基于小波包分形的瓦斯传感器故障诊断方法
引用本文:陈宏,邓芳明,吴翔,付智辉.基于小波包分形的瓦斯传感器故障诊断方法[J].传感器与微系统,2016(11):26-29.
作者姓名:陈宏  邓芳明  吴翔  付智辉
作者单位:1. 华东交通大学 轨道交通学院,江西 南昌,330013;2. 华东交通大学 电气与自动化工程学院,江西 南昌,330013
基金项目:国家自然科学基金资助项目(21265006);江西省科技支撑计划资助项目(20161BBE50076,20161BBE50077)
摘    要:针对瓦斯传感器的故障诊断问题,提出一种基于小波包分形的瓦斯传感器故障诊断方法。使用3层小波包对故障信号进行分解和重构,获得不同频带的重构信号,计算各个重构信号的分形维度,并构成对应的故障特征向量。以此作为输入向量来训练支持向量机(SVM),完成故障的诊断。实验结果表明:该方法能有效地提取传感器的故障特征,提高了传感器故障诊断的准确率,可有效地应用于瓦斯传感器的故障诊断。

关 键 词:瓦斯传感器故障诊断  小波包变换  分形分析  支持向量机

Gas sensor fault diagnosis method based on wavelet package fractal analysis
CHEN Hong,DENG Fang-ming,WU Xiang,FU Zhi-hui.Gas sensor fault diagnosis method based on wavelet package fractal analysis[J].Transducer and Microsystem Technology,2016(11):26-29.
Authors:CHEN Hong  DENG Fang-ming  WU Xiang  FU Zhi-hui
Abstract:Aiming at fault diagnosis problem of gas sensor,a gas sensor fault diagnosis method based on wavelet package fractal analysis is proposed. Fault signals are decomposed and reconstructed by using three-level wavelet package,reconstructed signals of different frequency bands are achieved. Compute fractal dimension of each reconstructed signal,and compose corresponding fault feature vectors. Inputting these fault vectors to train SVM to achieve fault diagnose. Experimental result shows that the proposed method extract effectively features of fault of sensor and increase of fault diagnosis,which can be applied to fault diagnosis of gas sensor effectively.
Keywords:gas sensor fault diagnosis  wavelet package transform  fractal analysis  support vector machine (SVM)
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