基于小波分析的大型振动筛侧板裂纹故障诊断研究

Q. Zhu, Han Wang
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引用次数: 0

摘要

本文以大型振动筛侧板裂纹为研究对象。利用小波分析理论,在Matlab中对侧板振动信号进行降噪处理,提取小波包能量特征。同时,将故障特征输入遗传神经网络进行识别。实际制造应用表明,基于小波分析的大型振动筛侧板裂纹故障诊断系统具有较高的故障识别能力、分类精度和速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Side Panel Crack Fault Diagnosis Research of Large-scale Vibrating Screen Based on Wavelet Analysis
The paper takes side panel cracks of large-scale vibrating screen as research object. The side panel vibration signals have been de-noised and the wavelet packet energy feature has been extracted in Matlab with wavelet analysis theory. Meanwhile, the fault characteristics is sent to genetic neural network for identification. The practical manufacturing application shows that this kind of side panel crack fault diagnosis system of large-scale vibrating screen based on wavelet analysis has high fault recognition ability, classification precision and speed.
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