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| 摘要: |
| 针对电气设备运行环境复杂这一特点,提出将声波分析技术应用到其故障诊断中,可克服高电压和强电磁场给故障检测带来的诸多难题.设计了基于声波识别的电气设备故障诊断专家系统的总体方案,故障诊断系统由信号采集、特征提取、状态识别和诊断决策4个部分组成,简要介绍了各部分的工作原理:阐述了一种使用分层阈值处理声音信号的消噪算法,将该方法与传统消噪方法作对比,证明了该算法在对非平稳信号分析中具有较高的精确性.给出小波包提取电气设备实测声波信号特征向量的算法,以此作为知识获取和推理的依据,为电气设备运行状态诊断专家系统的实现奠定了基础. |
| 关键词: 声波信号分析 故障诊断 分层阈值消噪 小波包 特征提取 专家系统 |
| DOI： |
| 分类号:TM07 |
| 基金项目: |
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| Electrical equipment fault diagnosis based on acoustic wave signal analysis |
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PAN Liangliang1 2 ZHAO Shutao1 LI Baoshu1
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| Abstract: |
| As the running environment of electrical equipment is complex,the acoustic wave recognition technology is used in its fault diagnosis to avoid the problems brought by high voltage and powerful electromagnetic field.A general expert system of electrical equipment fault diagnosis is designed,which is composed of four parts:signal acquisition,feature extraction,state recognition and decision-making.Its working principle is introduced.A layered threshold de-noising algorithm of acoustic signals is presented,whi... |
| Key words: acoustic signal analysis fault diagnosis layered threshold de-noising wavelet packet feature extraction expert system |
