摘要
提出了利用小波多分辨率分析技术进行多重并发故障检测的方法。根据信号分解重构后的时间位置不变这一事实,将信号进行多尺度的小波分解,并根据奇变信号和噪声信号小波变换后的系数差异,采用软阈值法,对其高频分量进行去噪重构,根据重构后的故障信号高频分量在不同尺度上的特征,对其进行故障特征提取,并将不同尺度上的故障特征进行综合,获得并发故障各自特征,进而可以实现对多重并发故障的检测和识别。对一电网信号分析的仿真结果证实了该方法的正确性和可行性。
A composite fault detection method based on wavelet multiresolution analysis is presented. According to the fact that the position of a signal in time field is invariable after it is reconstructed, wavelet analysis is applied to decompose the signal in multiple - level and reconstruct its high - frequency components after soft threshold de-noising. The threshold of denosiing is decided by the difference between the wavelet coefficient modules of a broken signal and those of a noise. The features of the fault signal will be shown in different levels, so that the faults can be detected and distinguished by the integrated features of the variant levels. The validity of the composite fault detection method has been demonstrated by simulation.
出处
《计算机仿真》
CSCD
2005年第6期197-200,共4页
Computer Simulation
关键词
故障检测
小波分析
多分辨率分析
去噪重构
Fault detection
Wavelet analysis
Multiresolution analysis
Denoising and reconstruction
