| 基于小波分析的大型齿轮箱低速轴故障诊断 |
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| 引用本文： | 高立新,韩金顺,张建宇,丁庆新,崔玲丽,CUI Lingli.基于小波分析的大型齿轮箱低速轴故障诊断[J].北京科技大学学报,2005,27(3):342-346. |
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| 作者姓名： | 高立新 韩金顺 张建宇 丁庆新 崔玲丽 CUI Lingli |
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| 作者单位： | 1. 北京工业大学先进制造技术重点实验室,北京,100022
2. 北京第一机床厂,北京,100022 |
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| 基金项目： | 国家高技术研究发展计划(863计划)
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北京市科委科研项目
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北京工业大学校科研和教改项目
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北京市重点实验室基金 |
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| 摘 要： | 针对大型齿轮箱低速轴故障信息难以提取的问题,采用小波分析方法对故障数据进行处理以实现信号在时/频域的局域性分析,将其无冗余、无泄漏地分解到一组具有紧支撑性的小波基上.文中采用小波分层突变系数作为判别故障隐患的特征值,并对该特征值进行趋势分析.结果表明:小波变换能有效捕捉冲击信号的时域特征和故障发生的时间历程,用小波分层突变系数所做的趋势图能有效地预测故障发展趋势,避免突发故障.
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| 关 键 词： | 小波分析 齿轮箱 诊断 特征提取 趋势图 小波分析 大型齿轮箱 低速轴 故障诊断 wavelet analysis based large diagnosis 突发故障 故障发展 预测 趋势图 时间历程 发生 时域特征 冲击信号 小波变换 结果 特征值 故障隐患 |
| 修稿时间： | 2005年1月12日 |
Fault diagnosis of low-speed shafts in large gearboxes based on wavelet analysis |
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| Gao Lixin,HAN Jinshun,Zhang Jianyu,DING Qingxin,ZHUO Li,CUI Lingli.Fault diagnosis of low-speed shafts in large gearboxes based on wavelet analysis[J].Journal of University of Science and Technology Beijing,2005,27(3):342-346. |
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| Authors: | Gao Lixin HAN Jinshun Zhang Jianyu DING Qingxin ZHUO Li CUI Lingli |
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| Abstract: | Aimed at the difficulty to extract the fault information of a low speed shaft in a large gearbox, wavelet analysis was used to realize the local analysis of signals in a time and frequency domain simultaneously. The signals were dissembled to a sieres of compactly supported wavelet bases non-redundantly and without leaking. The saltation coefficient of wavelet analysis was regarded as a characteristic value to predict a sudden accident and the changing trend of the coefficient was figured out. The results showed that wavelet transform could capture the characteristics in a time domain and the evolvement procedure of a fault. The trend graph of the coefficient could effectively predict the development trend of a fault and avoid a sudden accident. |
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| Keywords: | wavelet analysis gearbox fault diagnosis characteristic extraction trend graph |
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