A FAULT DIAGNOSIS METHOD BASED ON WAVELET APPROXIMATE ENTROPY FOR FAN

机译：基于小波近似熵的风扇故障诊断方法

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The vibration signal of the fan is a typical non-stationary time-varied signal with chaotic characteristic.Approximate entropy is able to take description of disorder or irregularity in the motion systems.This paper introduces approximate entropy as a tool to describing the fan conditions.A threshold filtering algorithm based on the wavelet for reducing noise is introduced.Utilizing the above method, the vibration signals of the fan under different working conditions are analyzed.The result shows that the approximate entropy is able to identify the conditions of the fan with faults compared with the normal condition, thereby providing an effective technology for condition monitoring and fault diagnosis of mechanical equipment.

机译：风扇的振动信号是典型的具有混沌特性的非平稳时变信号。近似熵能够描述运动系统的无序或不规则性。本文介绍近似熵作为描述风扇状态的工具。提出了一种基于小波的降噪阈值滤波算法，利用上述方法对不同工况下的风机振动信号进行了分析，结果表明近似熵能够识别出故障风机的状态。与正常情况相比，为机械设备的状态监测和故障诊断提供了有效的技术。

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《Proceedings of the 2007 International Conference on Machine Learning and Cybernetics》|2007年|P.519-523|共5页
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作者
JIN TIAN; JUN-JIE GU; XUE-ZHI PENG; ZHI-MING QIN;
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原文格式 PDF
正文语种
中图分类计算技术、计算机技术;
关键词
Fault diagnosis; Wavelet coefficient; Approximate entropy; Fan;

机译：故障诊断;小波系数;近似熵;风扇;
入库时间 2022-08-26 14:56:14

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A FAULT DIAGNOSIS METHOD BASED ON WAVELET APPROXIMATE ENTROPY FOR FAN

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