| 连续小波变换识别水轮机故障信号孤立奇异点 |
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| 引用本文： | 孙涛,黄天戍,孙颖慧,黄绵华,王宁芳.连续小波变换识别水轮机故障信号孤立奇异点[J].哈尔滨工业大学学报,2003,35(1):106-109. |
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| 作者姓名： | 孙涛 黄天戍 孙颖慧 黄绵华 王宁芳 |
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| 作者单位： | 1. 武汉大学,电子信息学院,湖北,武汉,430072
2. 山东电力设备厂设计室,山东,济南,250022 |
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| 摘 要： | 针对低频振动信号，给出一种故障信息识别的有效方法。选择双正交样条小波作为基小波，将多尺度分析及孤立奇异点的检测运用到水轮机房轴径向摆度分量信号的故障识别中。结果表明，利用连续小波变换系数模极大值（WTMM）的多尺度分析、根据WTMM曲线的长度、强度及其Lipschitz指数可以定位孤立奇异点；运用最小二乘算法估算李氏指数，即可估算故障点的奇异性程度并取得了很好的诊断效果。
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| 关 键 词： | 水轮机 故障信号 连续小波变换 模极大值曲线 孤立奇异点 消失矩 故障识别 故障诊断 |
| 文章编号： | 0367-6234(2003)01-0106-04 |
| 修稿时间： | 2001年12月5日 |
Recognition of isolated singularity points of hydroelectric generators fault signals based on CWT |
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| SUN Tao ,HUANG Tian shu ,SUN Ying hui ,HUANG Mian hua,WANG Ning fang.Recognition of isolated singularity points of hydroelectric generators fault signals based on CWT[J].Journal of Harbin Institute of Technology,2003,35(1):106-109. |
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| Authors: | SUN Tao HUANG Tian shu SUN Ying hui HUANG Mian hua WANG Ning fang |
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| Affiliation: | SUN Tao 1,HUANG Tian shu 1,SUN Ying hui 2,HUANG Mian hua,WANG Ning fang 1 |
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| Abstract: | As for low frequency vibrating signal, an effective method of identifying fault information is put forward. With biorthogonal spline wavelet selected, fault points of the main shaft of hydroelectric generator can be recognized, using MRA(multi resolution analysis ) theory of CWT (continuous wavelet transform) and isolated singularity points detecting. A perfect method is designed that positions the isolated singularity points and estimates theirs singularity degree, basing on WTMM (wavelet transform maximal modulus), MRA of wavelet transform and Least Square Algorithm, taking account of the length, intensity, and Lipschitz exponent of WTMM curves. |
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| Keywords: | continuous wavelet transform wavelet transform modulus isolated singularity points varnishing moments |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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