小波包频带能量分解在断路器机械状态监测中的应用

基于小波包原理,将断路器操作振动信号分解到独立的频带内,不同频带内信号能量的变化反映了断路器机械运行状态的改变.提取主要的频带能量作为断路器状态监测的特征向量,并根据试验结果确定了不同状态下能量特征向量的容差范围,从而实现了不同机械状态的简单分类,为断路器的机械状态监测提供了相应的量化依据.试验模拟了ZN12-35型真空断路器4种不同的合闸同期性状态,采用单个加速度传感器在机构箱上获取合闸时的触头振动信号.该信号经过小波包频带能量分解后,可以将各种合闸同期性状态分类集中在复平面中明显区分的不同区域内,从而验证了该方法在断路器机械状态监测中的有效性.重复试验表明,在保证监测系统稳定的前提下,该方法具有较高的状态监测准确率.

Application of Frequency Band Energy Decomposition Using Wavelet Packet in Condition Monitoring of Circuit Breakers

Based on the algorithm of wavelet packets, the vibration signals during the operation of circuit breakers were decomposed into the individual frequency bands. The variations of the signal energy in these bands reflect the different mechanical conditions of circuit breakers. Main energy ingredients were extracted to form the eigenvector for condition monitoring and the tolerance range of the eigenvector was determined by the test results under each condition. These tolerance ranges supplied the quantified standard for condition monitoring of the circuit breaker,and a simple classification of the mechanical conditions was implemented consequently. The vibration signals of a ZN12-35 type vacuum circuit breaker under specific closing simultaneity were recorded from a single vibration sensor mounted on the mechanism box. After the wavelet packet decomposition, different closing simultaneities distributed in the individual areas of a complex plane can be apparently distinguished, which verifies the feasibility of the proposed method applied to the condition monitoring of circuit breakers. The repeated tests indicate that the wavelet packet decomposition has a high monitoring accuracy based on a stable measurement system.