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基于小波变换的信号奇异性检测原理,提出了信号奇异点的定位及奇异性程度的检测方法,并利用Matlab仿真平台,对故障信号实例进行了仿真和分析。仿真结果表明,与传统的Fourier分析方法相比,该方法是一种简单、有效的检测方法,特别在非平稳信号的监测和机械故障诊断领域。利用此方法可以比较精确地判断出信号发生的奇异点时刻以及奇异程度的大小,并且边缘效应要小得多。
Based on the principle of signal singularity detection based on wavelet transform, a method of detecting signal singularities and detecting the degree of singularities is proposed. The examples of fault signals are simulated and analyzed by Matlab simulation platform. The simulation results show that the proposed method is a simple and effective method for the detection of non-stationary signals and mechanical fault diagnosis, compared with the traditional Fourier analysis method. This method can be more accurately determine the signal singular point of time and the size of the degree of singularity, and the edge effect is much smaller.