摘要
针对电力电子整流装置故障诊断方法中的故障特征提取和故障识别两个关键技术,提出一种基于主元分析和支持向量机相结合的三相整流装置故障诊断方法,首先对故障信号进行主元分析并提取相应的故障特征,然后构造支持向量机分类器实现对故障类型的识别。三相桥式可控整流电路晶闸管故障诊断仿真结果表明,该方法能准确对电力电子电路故障进行类型的识别和故障元的定位,对噪声具有鲁棒性,且算法简单,在解决电力电子电路故障问题上有很好的工程实用价值。
For fault feature extraction and fault identification, a novel method based on principal component analysis and support vector machines were presented for fault diagnosis of three-phase rectifiers, in which the prin- cipal component analysis of fault signal is used to extract the features corresponding to various fault, then fault types are identified through the pattern recognition classifier based on support vector machines. The simulation result of fault diagnosis of a thyristor in a three-phase full-bridge controlled rectifier showed that the method can make an accurate identification of fault types as well as the location of the fault elements for power electronics circuits, and it has an excellent performance for noise robustness and calculation complexity. Therefore, it is quite practically valuable in the solution to the fault problems for power electronics rectifiers.
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2013年第1期171-176,共6页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(51179074)
集美大学李尚大学科建设基金(ZC2011006)
关键词
支持向量机
主元分析
故障诊断
三相整流装置
support vector machine
principal component analysis
fault diagnosis
three-phase rectifiers