摘要
提出了基于小波包改进算法的电机故障信号压缩和重构方法 ,取定误差限后 ,通过选择分解阶数并自动优化调节每个节点的阈值来获得尽可能大的压缩比。分析了小波包分解尺度空间系数v1不压缩和压缩 2种方案 ,以及小波包完全分解和基于熵值的最优分解下各压缩指标随尺度的变化情况 ,并比较了不同小波的压缩效果。分析结果表明 ,提出的方法在获得较大压缩比的同时又能不失真地重构原信号 ,并有效地减少小波包分解和重构的计算量 ,是一种有效的电机故障信号的压缩和重构方法。
A new method for compression and reconstruction of faults signals of electric machines based on the improved fast algorithms of wavelet packets (WP) are presented in this paper.The error limitation is selected , the best compression rate can be obtained by selecting decomposition orders and adjusting the threshold of every node. The compression indices changed with decomposition orders are analyzed under the different methods that the coefficients of scale space ( v 1 ) can be compressed and not compressed , and the whole decomposition and optimal decomposition based on “entropy”.The evident results show that the computing loads of the WP can be reduced greatly , and the effective compression and reconstruction without distortion can be obtained using the method proposed in this paper.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2001年第1期25-29,共5页
Proceedings of the CSEE
基金
国家自然科学基金项目! (5 0 0 7770 0 8)
广东省自然科学基金项目! (980 6 0 8)
关键词
电机
故障信号
小波包算法
电力系统
滤波器
wavelet packets
compression and reconstr uction
faults signals of the electric machi
