传感技术学报Issue(4)：512-517,6.DOI:10.3969/j.issn.1004-1699.2014.04.017
基于SVM和RBFN的汽车主动降噪系统传感器故障诊断
Sensor Fault Diagnosis of the Automobile Active Noise Control System Based on SVM and RBFN
摘要
Abstract
The normal operation of the automobile active noise control system depends on multiple sensors. Once there is any sensor failure, it will severely affect the noise reduction effect. In order to guarantee the automobile active noise control system's performance,a sensor fault diagnosis system based on support vector machines( SVM) and radial basis function networks(RBFN)is put forward. The SVM model monitors sensor fault,meanwhile the RBFN models locate the fault sensor and reconstruct its signal based on the information redundancy between each sensor. Simulation results prove that the proposed diagnosis system could effectively diagnose any sensor fault in the automobile active noise control system as well as reconstruct fault sensor's signal. Compared to the conventional au-tomobile active noise control system,introducing the proposed diagnosis system provides higher reliability of noise reduction.关键词
故障诊断/信号预测/支持向量机/径向基神经网络/信号重构/汽车主动降噪系统Key words
fault diagnosis/signal prediction/support vector machines/radial basis function networks/signal recon-struction/automobile active noise control分类
信息技术与安全科学引用本文复制引用
赛吉尔呼,戴盛芳,董爱华,苗清影..基于SVM和RBFN的汽车主动降噪系统传感器故障诊断[J].传感技术学报,2014,(4):512-517,6.基金项目
国家自然科学基金青年基金项目(61304158) （61304158）
