Feature extraction of machine sound using wavelet and its application in fault diagnosis

Jing Lin 20f

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Feature extraction of machine sound using wavelet and its application in fault diagnosis

机译：基于小波的机器声音特征提取及其在故障诊断中的应用

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Machine sound always carries information about the working of the machine. But in many cases, the sound has a very low SNR. To obtain correct information, the background noise has to be removed or the sound must be purified. A de-noising method is given in this paper and is successfully used in feature sound extraction. We can easily diagnose a machine using the purified sound. This de-noising method is based on the wavelet technique and uses the Morlet wavelet as the mother wavelet, because its time-frequency resolution can be adjusted to adapt to the signal to be analyzed. The method is used for extracting the sound of some vehicle engines with different types of failure. The feature sound is extracted successfully.

机译：机器声音始终会携带有关机器工作的信息。但是在许多情况下，声音的信噪比非常低。为了获得正确的信息，必须消除背景噪音或必须净化声音。给出了一种去噪方法，并成功地用于特征声音的提取中。我们可以使用纯净的声音轻松诊断机器。这种降噪方法基于小波技术，并使用Morlet小波作为母小波，因为可以调整其时频分辨率以适应要分析的信号。该方法用于提取某些具有不同故障类型的汽车发动机的声音。功能声音已成功提取。

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《NDT & E international》 |2001年第1期|p.25-30|共6页
作者
Jing Lin 20f;
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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类工业通用技术与设备;金属的分析试验（金属材料试验）;
关键词
Fault diagnosis; Wavelet; Feature extraction;

机译：故障诊断;小波特征提取;

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Feature extraction of machine sound using wavelet and its application in fault diagnosis

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