Support Vector Classification for Fault Diagnostics of an Electrical Machine

机译：电机故障诊断的支持向量分类

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摘要

Support vector classification (SVC) is applied to fault diagnostics of an electrical machine. Numerical magnetic field analysis is used to provide virtual measurement data from healthy and faulty operation of an electrical machine. Power spectra estimates of a stator current of the motor are calculated with Welch's method, and SVC is applied to distinguish healthy spectrum from faulty spectra. Results are promising. Most of the faults can be classified correctly.

机译：支持向量分类（SVC）用于电机的故障诊断。数值磁场分析用于提供来自电机正常运行和故障运行的虚拟测量数据。使用韦尔奇（Welch's）方法计算电机定子电流的功率谱估计值，并应用SVC区分正常谱和故障谱。结果是有希望的。大多数故障可以正确分类。

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来源
《2002 6th International Conference on Signal Processing Proceedings (ICSP'02) Vol.2; Aug 26-30, 2002; Beijing, China》|2002年|p.1719-1722|共4页
会议地点 Beijing(CN);Beijing(CN)
作者
Sanna Poeyhoenen; Marian Negrea; Antero Arkkio; Heikki Hyoetyniemi; Heikki Koivo;
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作者单位

Helsinki University of Technology, Laboratory of Control Engineering, P.O.Box 5400, 02015 HUT, Finland;

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原文格式 PDF
正文语种 eng
中图分类无线电电子学、电信技术;
关键词
support vector classification; fault diagnostics; electrical machine; finite element analysis;

机译：支持向量分类；故障诊断；电机；有限元分析;

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4. Support vector classification for fault diagnostics of an electrical machine [C] . Poyhonen, S., Negrea, . 2002

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8. Support Vector Machines in Fault Diagnostics of Electrical Motors;Licentiate thesis [R] . Poeyhoenen, S. 2002

机译：支持向量机在电机故障诊断中的应用;许可论文

Support Vector Classification for Fault Diagnostics of an Electrical Machine

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