摘要
为解决设备故障检测和故障预报中某些微弱振动信号难以提取出来的问题,在介绍谐波小波变换的优良特性及其基本原理的基础上,给出了谐波小波变换的实现技术.在不减少信息点数的情况下,用谐波小波变换成功地对微弱振动信号实现了频域提取与时域重构,并且实现了强噪声下微弱周期振动信号的频域提取.通过算例和工程实例,说明谐波小波方法在微弱信号的频域提取能力和精度上明显优于基于二进分解的小波方法和傅里叶分析方法,且在混有强噪声的信号提取中消除了二进小波包仍然存在的噪声泄漏,同时也显示了谐波小波变换的频域保相特性.
Some weak vibration signals are very useful for equipment inspection and fault forecast but are difficult to extract by Fourier transform or dyadic wavelet transform. In comparison with dyadic wavelet, harmonic wavelet has such excellent properties as being easy to construct, simple expression, phase holding characteristic and clear relation with Fourier transform. It is found that the weak partial signal can effectively be extracted by harmonic wavelet transform in frequency domain and can easily be reconstructed. Moreover, the weak cycle signal can be extracted from strong noise by harmonic wavelet transform in frequency domain. Computation and engineering results show that the extraction ability of weak signal and the extraction precision of harmonic wavelet transform in frequency domain are higher than those of dyadic wavelet transform and Fourier analysis method. The noise leak problem in weak signal extraction by dyadic wavelet package and Fourier transform is eliminated by harmonic wavelet transform.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2004年第1期51-55,共5页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(1 9972 0 2 9)
山东省自然科学基金资助项目 (Y2 0 0 0A0 1 )
关键词
微弱信号
振动信号
谐波小波
提取
Frequency domain analysis
Signal filtering and prediction
Vibrations (mechanical)
Wavelet transforms
