摘要
在实际的故障分析中通常不是利用故障暂态信号的全部频带信息 ,而是利用其部分频带信息来解决问题 ,因此提出了针对电力系统故障信号压缩的特殊要求 ,即对于所要解决问题有重要价值的频带信息无损压缩 ,对不重要的频带信息可以失真压缩 ,即保频带压缩。在此基础上提出了基于小波包变换、Huffman编码方法和矢量量化相结合的故障数据压缩算法 ,首先利用小波包变换将故障信号分解成各个频带的信息 ,选择有重要信息的频带采用自适应 Huffman无损压缩算法 ,而对于其他频带数据信息 ,采用矢量量化压缩算法。通过仿真测试 ,该算法较好地满足了故障暂态信号的压缩要求 。
In practical application of fault analysis in power system, not all the information of frequency bands is needed for signal processing. So according to the application characteristic of the fault analysis of power system, this paper uses lossless compression for the useful frequency band signal and lossy compression for the unimportant frequency band signal. A data compression method is proposed for fault transient signal according to the special requirements of the power system. Firstly, wavelet package transform is employed to decompose the fault signal into information of various frequency bands. Then adaptive Huffman lossless compression method is used for the frequency of important information and vector quantification algorithm is employed for the other frequency information. The simulation test shows that the method proposed has a good compression rate and wide potential in application.
出处
《电力系统自动化》
EI
CSCD
北大核心
2003年第1期45-48,共4页
Automation of Electric Power Systems
