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[1]刘扬,张振海.小波神经网络的无刷直流电机转子位置检测方法[J].武汉工程大学学报,2014,(10):66-70.[doi:103969/jissn167428692014010014]
 LIU Yang,ZHANG Zhen hai.Rotor position detection method of brushless direct current motor based on wavelet neural network[J].Journal of Wuhan Institute of Technology,2014,(10):66-70.[doi:103969/jissn167428692014010014]
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小波神经网络的无刷直流电机转子位置检测方法(/HTML)
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《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
期数:
2014年10期
页码:
66-70
栏目:
机电与信息工程
出版日期:
2014-10-30

文章信息/Info

Title:
Rotor position detection method of brushless direct current motor based on wavelet neural network
文章编号:
16742869(2014)010006605
作者:
刘扬1 张振海2
1.集美大学诚毅学院 ,福建 厦门 361021;2.兰州交通大学自动化与电气工程学院,甘肃 兰州 730070
Author(s):
LIU Yang1 ZHANG Zhenhai2
1.Jimei University Chengyi College, Xiamen 361021,China;2.School of Automation and Electrical Engineering, Lanzhou Jiao Tong University, Lanzhou 730070,China
关键词:
无刷直流电机自适应小波神经网络遗传算法
Keywords:
brushless direct current motor adaptive wavelet neural network genetic algorithm
分类号:
TP273
DOI:
103969/jissn167428692014010014
文献标志码:
A
摘要:
位置检测与换相准确与否,对无刷直流电机的运行有非常关键的影响.在分析反电动势过零检测原理的基础上得出线反电动势过零点与电机换相点及线反电动势与线电压之间的关系,从而得到线电压与转子位置之间的关系.由于电机运行过程中的参数变化及系统的非线性特征,直接通过线电压准确获得转子位置比较困难,因此构建了一个以三个线电压为输入,转子电角度为输出的自适应小波神经网络模型,并采用遗传算法优化小波神经网络结构。仿真实验证明,该方法辨识转子位置精度高,自适应性强,并能有效地控制电机换向.
Abstract:
The accuracy of position detection and commutation is very critical for the operation of the brushless direct current motor(BLDCM). Aimed at BLDCM rotor position detection, the relationship between motor back electromotive force zero crossing point and motor commutation point as well as the relationship between line back electromotive force and line voltage was derived based on analysis of back electromotive force zero crossing detection principle, so the relationship between line voltage and motor point was established. However, because of the motor parameters variation during operation and nonlinear characteristics of the system, it is more difficult to obtain accurate rotor position through the line voltage directly. So the adaptive wavelet neural network model was proposed using line voltage as input and the rotor electrical angle as output, and genetic algorithm was also adopted to optimize wavelet neural network structure. Finally simulation and experiment show that the method has high precision to identify the rotor position, and controls the motor commutator effectively with strong adaptability.

参考文献/References:

[1]夏长亮,文德,范娟.基于RBF 神经网络的无刷直流电机无位置传感器控制[J].电工技术学报, 2002, 17 (3 ): 2629. XIA Changliang, WEN De, FAN Juan.Based on RBF neural network position sensorless control for brushless DC motors[J]. Transactions of China Electrotechnical Society, 2002, 17 (3): 2629. (in Chinese)[2]程启明, 王勇浩. 基于小波神经网络的控制方法及其应用研究[J].工业仪表与自动化装置, 2004(5): 69. CHENG Qiming, WANG Yonghao .A study on the control method and its application based on wavelet neural network[J]. Industrial Instrumentation and Automation, 2004(5): 69. (in Chinese)[3]李天舒,刘军.无刷直流电动机的反电势过零检测法研究[J].微电机,2007(3):3436.LI Tianshu ,LIU Jun. Brushless dc motor the back emf of the zero test study [J]. Journal of Micromotor, 2007 (3) : 3436.(in Chinese)[4]李自成,程善美,秦忆.线反电动势检测无刷直流电机转子位置方法[J].电机与控制学报,2010,12(14):96100.LI Zicheng, CHEN Shanmei,QIN Yi. Line counter electromotive force detection rotor position method for brushless dc motor [J]. Journal of Motor and Control, 2010, 12 (14) : 96100.(in Chinese)[5]JANG G H,PARK J H, CHANG J H. Position detection and startup algorithm of a rotor in a sensorless BLDC motor utilizing inductance variation[J]. IEE Proc Electr Power Appl, 2002, 149(2): 137142. [6]OGASAWARA S, AKAGI H. An approach to position sensorless drive for brushlesss DC motors[J]. IEEE Trans Ind Application, 1991, 27(5): 928933.[7]赵学智,邹春华.小波神经网络的参数初始化研究[J]. 华南理工大学学报:自然科学版, 2003, 31 (2): 7779. ZHAO Xuezhi, ZOU Chunhua. Research on the initialization of paramete rs of wavelet neural networks[J]. Journal of South China University of Technology:Natural Science Edition, 2003, 31 (2): 7779. (in Chinese)[8]韦鲲,任军军,张仲超.一种新的直流无刷电机的无传感器控制方法[J].电力电子技术,2004,38(3): 70 73.WEI Kun,REN Junjun,ZHANG Zhongchao. A new sensorless control method for brushless dc motor[J]. Power Electronic Technology,2004,38(3): 70 73.(in Chinese)

相似文献/References:

[1]杨海燕,兰宝华.基于PSOWNN的无刷直流电机转子位置检测方法[J].武汉工程大学学报,2010,(01):93.
 YANG Hai yan,LAN Bao hua.A new position detection based on PSOwavelet neural network method for brushless DC motors[J].Journal of Wuhan Institute of Technology,2010,(10):93.

备注/Memo

备注/Memo:
收稿日期:20140616基金项目:甘肃省自然科学基金资助项目(0916RJZA039)作者简介:刘扬(1980),女,陕西宝鸡人,讲师,硕士,研究方向:控制理论与控制工程.
更新日期/Last Update: 2014-11-22