双余度永磁无刷直流电机绕组故障诊断研究 -- 西北工业大学,2014,32(1):93-97
论文:2014,Vol:32,Issue(1):93-97
引用本文:
付朝阳, 刘景林, 张晓旭. 双余度永磁无刷直流电机绕组故障诊断研究[J]. 西北工业大学
Fu Zhaoyang, Liu Jinglin, Zhang Xiaoxu. Research on Winding Fault Diagnosis of Dual-Redundancy Permanent Magnet Brushless DC Motor[J]. Northwestern polytechnical university

双余度永磁无刷直流电机绕组故障诊断研究
付朝阳, 刘景林, 张晓旭
西北工业大学 自动化学院, 陕西 西安 710072
摘要:
双余度永磁无刷直流电机具有可靠性高、体积小、重量轻等优点,但绕组之间的耦合性对故障诊断提出了更高要求。针对双余度永磁无刷直流电机常见的绕组故障,包括绕组开路和绕组短路,选择相电流作为故障分析信号,通过拆分定子槽,改变控制电路的方式,建立了电机的绕组故障有限元仿真模型。根据故障信号和小波函数的特点,分别采用Daubechies3和coif5小波函数对故障信号进行特征提取。结果表明:在小波分解高频部分的第2层,信号有明显突变,并由此确定coif5小波函数进行故障特征检测。采用coif5小波函数对相电流d2分解系数进行了能量特征提取,得到了各相短路时的故障特征向量。建立了基于PNN神经网络的故障诊断模型,对故障样本进行了诊断,诊断结果准确率100%,验证了所用方法的有效可行。
关键词:    无刷直流电机    电枢绕组    故障分析    特征提取   
Research on Winding Fault Diagnosis of Dual-Redundancy Permanent Magnet Brushless DC Motor
Fu Zhaoyang, Liu Jinglin, Zhang Xiaoxu
Department of Automatic Control, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
Dual-redundancy permanent magnet brushless DC motor has the advantages of high reliability,small volume,light weight. But the two windings cause fault diagnosis to be difficult. According to the winding faults,including winding open-circuit and winding short circuit,phase current is chosen to be the fault analysis signal. Based on the method of splitting the stator slot and changing the control circuit,the motor winding fault simulation finite element model is established. According to the characteristic of fault signal and the wavelet functions,this paper uses daubechies3 and coif5 wavelet function for fault signal feature extraction. The results and their analysis show preliminarily that the signal has a significant change in the second layer of high frequency part and that the coif5 wavelet function is better. The d2 decomposition coefficients of phase current were features extracted by coif5 wavelet function and the fault feature vector is obtained. The fault diagnosis model is established based on PNN neural network. The fault samples were detected by the model. The diagnosis accuracy is 100% and it proves that the method is effective and feasible.
Key words:    brushless DC motors    electric windings    failure analysis    feature extraction   
收稿日期: 2013-04-28     修回日期:
DOI:
基金项目: 陕西省自然科学基金(2013JQ7035);航空科学基金(2013ZC53045)资助
通讯作者:     Email:
作者简介: 付朝阳(1981-),西北工业大学讲师、博士,主要从事永磁电机设计与控制及智能控制理论与应用的研究。
相关功能
PDF(859KB) Free
打印本文
把本文推荐给朋友
作者相关文章
付朝阳  在本刊中的所有文章
刘景林  在本刊中的所有文章
张晓旭  在本刊中的所有文章

参考文献:
[1] 王巍, 郭宏, 李艳明, 于凯平.电气双余度无刷直流电动机转子极弧系数研究[J].电机与控制学报, 2009, 13(6): 862-866 Wang Wei, Guo Hong, Li Yanming, Yu Kaiping. Research on Rotor Pole Arc of Electrical Dual-redundancy Brushless DC Motor[J]. Electric Machines and Control, 2009, 13(6): 862-866 (in Chinese)
[2] Guo Hong, Wang Wei, Xing Wei, Li Yanming. Design of Electrical/Mechanical Hybrid 4-Redundancy Brushless DC Torque Motor [J]. Chinese Journal of Aeronautics, 2010, 23: 211-215
[3] 马瑞卿, 刘卫国, 解恩.双余度无刷电动机位置伺服系统仿真与试验[J].中国电机工程学报, 2008, 28(18): 98-103 Ma Ruiqing, Liu Weiguo, Xie En. Simulation and Test of Position Servo System Based on Dual-Redundancy BLDCM[J]. Proceedings of the CSEE, 2008, 28(18): 98-103 (in Chinese)
[4] 王巍, 郭宏, 李艳明. 电气/ 机械混合四余度无刷直流力矩电动机绕组短路分析[J].航空学报, 2010, 31(5): 975-982 Wang Wei, Guo Hong, Li Yanming. Analysis of Winding Short-Circuit in Electrical/Mechanical Hybrid 4-Redundancy Brushless DC Torque Motor[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(5): 975-982 (in Chinese)
[5] Li Shichao, Shi Xiuhua, Cui Haiying. Diagnosis Based on Genetic Algorithms Wavelet Neural Network in Dual-Redundancy Brushless DC Motor[J]. Journal of Vibration Measurement & Diagnosis, 2009, 29(2): 223-226