摘要
根据小波系数的相关分析理论,提出了基于双树复小波变换的小波相关滤波法。该方法根据相邻层小波系数的相关性,通过迭代过程自适应地进行滤波,能够在达到良好降噪效果的同时保留微弱故障特征信息。对降噪后的信号进行希尔伯特包络分析便可准确得到故障特征频率。试验信号分析与工程应用结果表明,该方法能够有效提取强背景噪声下的齿轮箱轴承早期故障特征信息。
The conventional wavelet denoising method based on the simple threshold principle cannot always successfully extract the weak fault feature from the vibration signal with strong background noise,as the noise of different layers is individually estimated.Inspired by the fact that the wavelet transform coefficients of adjacent layers have some similarities where the signal is singular,a new method based on dualtree complex wavelet transform and correlation filter is proposed.The method is an interactive process in which its parameters are adaptively selected and the noise can be efficiently reduced.More important,the faint component that is expected to be extracted will be retained.The defect frequency can be accurately found by the envelope demodulation analysis.As an improvement to the conventional wavelet transform domain correlation filter,it takes full advantage of dual-tree complex wavelet transform.Experimental and engineering application examples show the method′s effectiveness in incipient gearbox fault diagnosis.
出处
《振动．测试与诊断》
EI
CSCD
北大核心
2016年第1期138-144,203,共7页
Journal of Vibration,Measurement & Diagnosis
基金
国家自然科学基金资助项目(51375020)
北京市教委科研计划资助项目(KM201310005013)
北京市属高等学校青年拔尖人才培育计划
先进制造技术北京市重点实验室开放基金
北京工业大学基础研究基金资助项目(X4001011201301)
关键词
双树复小波变换
相关滤波
降噪
齿轮箱
早期故障诊断
dual-tree complex wavelet transform
correlation filtering
denoising
gearbox
incipient fault diagnosis
