Broken Rotor Bars Fault Detection in Induction Motors Using Park's Vector Modulus and FWNN Approach
文献类型：会议论文
| 作者 | Guo QJ(郭前进); Li XL(李晓利); Yu HB(于海斌) ; Hu W(胡为); Hu JT(胡静涛)
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| 出版日期 | 2008 |
| 会议名称 | 5th International Symposium on Neural Networks |
| 会议日期 | September 24-28, 2008 |
| 会议地点 | Beijing, China |
| 关键词 | Fault Detection Induction Motors Park's Vector Modulus FWNN |
| 页码 | 809-821 |
| 中文摘要 | In this paper a new integrated diagnostic method based on the current Park's Vector modulus analysis and fuzzy wavelet neural network classifier is proposed for the diagnosis of rotor, cage faults in operating three-phase induction motors. Detection of broken rotor bars has long been an important but difficult job in the detection area of induction motor faults. The characteristic frequency components of a faulted rotor in the stator current spectrum are very close to the power frequency component but by far less in amplitude, which brings about great difficulty for accurate detection. In order to overcome the shortage of broken rotor bars characteristic components being submerged by the fundamental one in the spectrum of the stator line current, Park's Vector modulus(PVM) analysis is used to detect the occurrence of broken rotor bar faults in our work. Simulation and experimental results are presented to show the merits of this novel approach for the detection of cage induction motor broken rotor bars. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | ADVANCES IN NEURAL NETWORKS - ISNN 2008, PT 2, PROCEEDINGS
 |
| 会议录出版者 | SPRINGER-VERLAG |
| 会议录出版地 | BERLIN |
| 语种 | 英语 |
| ISSN号 | 0302-9743 |
| ISBN号 | 978-3-540-87733-2 |
| WOS记录号 | WOS:000260605100092 |
| 源URL | [http://ir.sia.cn/handle/173321/8069]  |
| 专题 | 沈阳自动化研究所_工业信息学研究室_工业控制系统研究室 |
| 推荐引用方式 GB/T 7714 | Guo QJ,Li XL,Yu HB,et al. Broken Rotor Bars Fault Detection in Induction Motors Using Park's Vector Modulus and FWNN Approach[C]. 见:5th International Symposium on Neural Networks. Beijing, China. September 24-28, 2008. |
入库方式： OAI收割
来源：沈阳自动化研究所
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