基于小波变换的热工信号多尺度相关性分析  

Analysis on Multi-scale Correlation of Thermal Signal Based on Wavelet Transform

作　　者：郝祖龙[1] 刘吉臻[1] 常太华[1] 田亮[1] 

机构地区：[1]华北电力大学自动化系,北京市昌平区102206

出　　处：《中国电机工程学报》2010年第14期109-114,共6页Proceedings of the CSEE

基　　金：国家自然科学基金项目(50776030);国家863高技术基金项目(2007AA04Z163)~~

摘　　要：针对传统的热工信号相关性分析无法兼顾整体趋势相关性和局部波动相似性分析的不足,利用小波变换的多分辨率分析思想,提出从不同频率尺度来研究信号的相关性。通过小波变换的多层分解与重构得到不同频率范围内的信号分量,依据同一频率信号的波动相似性,计算相关系数来定量描述该尺度下信号间的关联程度。对某600MW机组数据进行实例分析,表明该方法不仅可以定量分析信号低频趋势的相关性强弱,同时也能够挖掘出高频波动相似性强的信号,从而拓展了热工相关信号的挖掘范围。In order to overcome the insufficiency of correlation information for overall tendency and local fluctuation in the analysis of traditional thermal signals, a new wavelet multi-resolution strategy with correlation in different frequency ranges was proposed. Firstly, components of different frequency ranges were obtained via multi-level wavelet decomposition and reconstruction. Then, correlation coefficients were calculated based on the assumption of fluctuation similarity among components in the same frequency range, which can be used to describe the correlation degree of those components. The proposed method was utilized in the data analysis procedure of a 600 MW thermal unit. The result shows that the correlation level of frequency tendency in a low frequency range can be calculated by quantitative analysis; and signals with strong similarity in high frequency range can be mined. Thus, mining ranges of related thermal signals are widened by the proposed method.

关 键 词：热工信号 数据挖掘 多尺度相关 波动相似性 小波变换 

分 类 号：TK39[动力工程及工程热物理—热能工程]