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Early Detection of Rolling Bearing Defect by Demodulation of Vibration Signal Using Adapted Wavelet

机译:自适应小波解调振动信号早期检测滚动轴承缺陷。

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Vibratory analysis allows us to interpret the fundamental conditions of rotating machines. This interpretation is useful in the diagnosis of defects. Many studies implement advanced processing tools for mechanical detection of defects in individual components. Among these processes, wavelet demodulation is a powerful tool for signal processing. This technique requires the use of a traditional wavelet, such as a Morlet wavelet, which is defined by two parameters: Decrease and frequency. However, this determination is hard to do. Moreover, the processing required is very expensive in computing time, which prevents instantaneous follow-up. This paper suggests a new form of wavelet, which is adapted to shock response, and a methodology for its use in which the parameters are determined automatically.
机译:振动分析使我们能够解释旋转机械的基本条件。这种解释对缺陷的诊断很有用。许多研究实施了先进的加工工具,用于机械检测单个组件中的缺陷。在这些过程中,小波解调是用于信号处理的强大工具。该技术需要使用传统的小波,例如Morlet小波,它由两个参数定义:减少和频率。但是,这种确定很难做到。而且,所需的处理在计算时间上是非常昂贵的,这阻止了即时的跟进。本文提出了一种适用于冲击响应的小波新形式,以及一种可以自动确定参数的方法。

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