小波包变换在金属磁记忆信号处理中的应用研究

金属磁记忆技术是对金属部件进行早期损伤检测行之有效的方法.针对磁记忆信号中存在干扰磁场,不利于应力集中区特征信号的识别的问题,运用小波包分解重构的滤波方法。小波包将信号分解到各个不同的频段,截取感兴趣的频段,再重构信号,达到降低干扰信号的目的。仿真分析验证了该方法的可行性。通过对实测磁记忆信号进行小波包分解重构,使得应力集中区的特征更易识别,取得了较好的效果,降低了误判的几率。

Application of Wavelet Packet Transform in Metal Magnetic Memory Signal Processing

The metal magnetic memory technique is very effective in early damage detection for metal parts. However, information of disturbing magnetic fields also exists in the magnetic memory signals so that the characteristic signals in the stress concentration area can not be recognized easily. This paper puts forward a new filtering method based on wavelet packet decomposition and reconstruction. Wavelet packet decomposes signals according to different frequency ranges. The goal to filter the disturbing signals can be achieved through intercepting the interested frequency ranges and reconstructing signals. Simulation analysis verifies the feasibility of this method. Then, this method is used to decompose and reconstruct actual magnetic memory signals and a preferable effect is gained. It makes the signal characters in stress concentration area more clear and depresses the probability of damage misjudgment.