|本期目录/Table of Contents|

[1]刘沛津,高雪波,孙昱.三相电流主分量融合的电机故障图形诊断方法[J].电机与控制学报,2017,21(06):75-82.[doi:10.15938/j.emc.2017.06.010]
 LIU Pei-jin,GAO Xue-bo,SUN Yu.Graphic diagnosis method of motor faults based on components fusion of three phase currents PCA[J].,2017,21(06):75-82.[doi:10.15938/j.emc.2017.06.010]
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三相电流主分量融合的电机故障图形诊断方法(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
21
期数:
2017年06
页码:
75-82
栏目:
出版日期:
2017-06-01

文章信息/Info

Title:
Graphic diagnosis method of motor faults based on components fusion of three phase currents PCA
作者:
?刘沛津 高雪波 孙昱
?( 西安建筑科技大学机电工程学院,陕西西安710055)
Author(s):
?LIU Pei-jin GAO Xue-bo SUN Yu
?( School of Mechanical and Electrial Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,China)
关键词:
异步电机 三相电流主分量分析法 融合图形 状态识别判据 故障严重度指标
Keywords:
asynchronous motor three phase currents principal component analysis fusion figure criteria of state identification fault severity index
分类号:
TM 343
DOI:
10.15938/j.emc.2017.06.010
文献标志码:
A
摘要:
为了在线快捷有效检测识别电机运行状态,并准确诊断交流电机常见故障,将图形融合方法与主分量分析方法( PCA) 相结合,充分利用电机三相定子电流信号实现了电机故障的图形化在线检测方法。应用主分量分析法将三维电流状态空间样本进行降维并在二维平面内实现主分量的
图形化融合,定义了电机正常、定子匝间短路、转子断条等不同运行状态下的状态识别实用判据,并针对主分量融合图形定义了故障严重度指标。通过理论分析及电机故障试验,论证了所提诊断方法对电机常见定子匝间短路及转子断条故障检测及诊断的直观性、准确性及载荷变化的鲁棒性,为电机及其拖动系统的故障诊断提供新的思路和方法。
Abstract:
?In order for on-line efficient detection and accurate diagnosis of common faults of AC motors,an approach is presented. Dimension of current data sample matrix were reduced by using principal component analysis( PCA) algorithm and formed 2-D figure. Practical,useful criteria of state identification was defined for the normal condition,stator winding inter-turn short circuit fault,rotor broken bar fault of motor. At the same time,fault severity index of motor was defined too. The characteristic of intuitive,accuracy
and robustness of the fault diagnosis algorithm was verified by way of theoretical analysis and fault motor experiments. The method provides a new thought and method for fault diagnosis of motors and driving systems.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2014 - 11 - 28
基金项目: 国家自然科学基金( 50575168) ; 国家工程实验室开放基金( 2013G1502047) ; 西安建筑科技大学校级重点基金( JC1316)
作者简介: 刘沛津( 1971—) ,女,博士,副教授,研究方向为机电系统监测及故障诊断;
高雪波( 1990—) ,男,硕士研究生,研究方向为机电系统监测及故障诊断;
孙昱( 1986—) ,男,博士研究生,研究方向为机电系统监测及故障诊断。
更新日期/Last Update: 2017-08-24