基于小波变换的信号奇异度指标计算方法

摘要

Wavelet transform signal singularity detection research mainly appearse on the mutation point test, sound source localization and singular intermittent judgments. Aiming at the shortfall about the acoustic emission (AE) signals accurate positioning in the airspace, the signal singular degree of index calculation method based on wavelet transform was put forward to conduct singularity detection of acoustic emission signal. The method first used the wavelet transform to multi-scale analysize the actual acquisition of AE signal. The calculation of singular index identified the occurring time and location of mutations. Project examples showed that the signal singular degree of index calculation method operated in the AE signal singularity detection was of the error with only a difference of a sample point location,and there were no cumulative errors, where db3,sym2 coifl wavelet basis was more suitable for the detection of AE distortion signal.%小波变换在信号奇异性检测的应用研究主要表现在突变点测试、声源定位、奇异间断点判断方面.针对声发射信号在时空域准确定位中存在的问题,提出基于小波变换的信号奇异度指标计算方法对声发射信号进行奇异性检.该方法采用小波变换对实际采集的声发射信号进行多尺度分析,通过对奇异度指标的计算来确定突变发生的时间和位置.工程实例表明:小波变换的信号奇异度指标计算方法在声发射信号奇异性检测的误差仅相差一个采样点的位置,且不存在累计误差,其中db3、sym2、coifl小波基更适合声发射畸变信号的检测,为煤岩体受压损伤破坏全过程的检测提供了有效的思路.