摘要
在详细介绍小波包和特征熵的基础上,提出了一种基于振动信号的断路器机械故障诊断新方法。该方法首先在振动信号小波包分解的第3层各节点重构信号,并提取包络;而后利用包络信号的分段能量,计算小波包一特征熵向量;最后将正常状态和待测状态下所得向量之间的欧氏距离作为诊断参量。对某少油断路器无负载开断振动信号的分析证实,该方法检测断路器故障简单、准确,能同时在时域和频域检测断路器状态的变化。
A new method to diagnose faults for high voltage circuit breakers is presented in the paper based on the introduction of wavelet packet and characteristic entropy. Firstly, the vibration signal is decomposed by the three-layer wavelet packet, and eight signals of each junction at the third level are reconstructed. Secondly, the vector is extracted from the envelopes of reconstructed signals. Finally the Euclidean distance between the vectors of normal state and fault state is used as a characteristic parameter for fault diagnosis. Experiment results demonstrate that the proposed method can easily and accurately diagnose breaker faults and detect the state change of circuit breakers in time domain and frequency domain at the same time.
出处
《电力系统自动化》
EI
CSCD
北大核心
2006年第14期62-65,共4页
Automation of Electric Power Systems
关键词
高压断路器
故障诊断
小波包
特征熵
high voltage circuit breaker
fault diagnosis
wavelet packet
characteristic entropy
