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An Improved Algorithm of Wavelet Denoising and Its Application In Bearing Fault Diagnosis

机译:一种改进的小波去噪算法及其在轴承故障诊断中的应用

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This paper combined advantages of traditional Donoho threshold denoising algorithm and modulus maxima reconstruction denoising algorithm, proposed an improved wavelet denoising algorithm, which not only can filter white noise, but also can filter the residual color noise in low frequency band at the same time, so that it can be precisely' denoised. Decomposing signal by wavelet transform, using the Donoho threshold alogrithm principle to denoise, based on the decomposed signal, according to the. .modulus maxima reconstruction algorithm principle, improve the selection of preset signal power value, then denoising and reconstruct signal. Through the algorithm improvemet, it can be accurately to signal denoising and can overcome the defect of large calculation amount by using modulus maxima algorithm denoising. Through analysis and process the simulation signals and the experimental acquisition vibration signals, the results shows that the improved algorithm denoising effect is better than traditional denoising algorithm.
机译:本文综合了传统的Donoho阈值去噪算法和模数最大重建去噪算法的优点,提出了一种改进的小波去噪算法,这不仅可以过滤白噪声,还可以同时过滤低频带中的残留色噪声,所以它可以精确地'去噪。根据的,通过小波变换分解信号,根据该信号,使用Donoho阈值alogrithm原理基于分解信号来表示。 。模范最大重建算法原理,改善预设信号功率值的选择,然后去噪和重建信号。通过算法改进,可以准确地发出信号去噪,可以通过使用模数最大算法去噪来克服大计算量的缺陷。通过分析和处理模拟信号和实验采集振动信号,结果表明,改进的算法的去噪效果优于传统的去噪算法。

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