永磁直线同步电机垂直提升系统故障征兆获取策略研究
|
摘要
永磁直线同步电机及其伺服系统具有高效、节能等显著优点,在我国已取得了成功的开发和应用,已越来越受到重视。由于“分段式永磁直线电动机驱动的矿井提升系统”是一项新的研究课题,有许多问题有待解决,其中提升系统的运行安全就是亟待解决的关键问题之一。电机在发生故障前会出现某些征兆,其直接参数和间接参数都会在某种程度上呈现出一定的变化趋势,通过检测这些参数,以达到抑制故障发生,达到安全运行的目的。
本文以分段式永磁直线电机提升系统为研究对象,通过对其结构、运行原理的分析,研究了系统在发生各种故障时引起的参数变化趋势和主要特征参数的获取策略,建立了以TMS320F2812和传感器测试技术相结合的故障征兆检测系统。该系统既可以完成现场的实时监测,又可以完成连续的参数分析。该系统由硬件电路和软件部分组成。硬件部分包括电压、电流、气隙、速度、绝缘、无位置传感器功率角检测模块,模拟信号调理电路,A/D转换电路,开关量采集模块,通讯模块。软件设计包含了数据采集,SCI初始化,监控程序设计。实验结果表明本设计可以满足实际要求、误差较小,可应用于实际系统。本监测系统为以后研制更大规模的管理系统迈出了具有基础性和开拓性的一步,其成果具有先进性和潜在的经济效益。
Permanent magnet linear synchronous motor and servo system with high efficiency, energy-saving and other significant advantages, it has made a successful development and application in our country ,and gets more and more attention. the“sectional permanent magnet linear motor drive for mine transportation system”is a new research project, so many issues is still to be resolved, in which the operation stability is the key issues. Some signs will be shown before failure of the motor, its direct and indirect parameters would have some tendency, we can restrain failures by parameters detecting.
In this paper, sub-type permanent magnet linear motor lift system as the research object, through analysis of its structure and operation principle, researching these parameters’changes when the system occurs failures.Based on the TMS320F2812 and sensor technology established the test monitoring system. The system not only can complete the on-site real-time monitoring, but also complete a continuous parameter analysis.The system is constituted by Hardware and software. Hardware is composed by voltage, current, air gap, speed, insulation modules, without position sensor power angle detection module, analog signal conditioning circuits, A/D conversion circuit, the switch volume acquisition module, communication module. Software design includes data acquisition, SCI initialization, monitoring program design. Experimental results show that this design can meet the practical requirements; less error can be applied to practical applications. The monitoring system for the future development of more large-scale management system has taken the foundation and ground-breaking step, the results have advanced and the potential economic benefits.Experimental results show that this design can meet the practical requirements, less errors, it can be applied to practical applications. The monitoring system has taken the foundation and ground-breaking step for the future development of more large-scale management system, the results have advanced and the potential economic benefits.
本文以分段式永磁直线电机提升系统为研究对象,通过对其结构、运行原理的分析,研究了系统在发生各种故障时引起的参数变化趋势和主要特征参数的获取策略,建立了以TMS320F2812和传感器测试技术相结合的故障征兆检测系统。该系统既可以完成现场的实时监测,又可以完成连续的参数分析。该系统由硬件电路和软件部分组成。硬件部分包括电压、电流、气隙、速度、绝缘、无位置传感器功率角检测模块,模拟信号调理电路,A/D转换电路,开关量采集模块,通讯模块。软件设计包含了数据采集,SCI初始化,监控程序设计。实验结果表明本设计可以满足实际要求、误差较小,可应用于实际系统。本监测系统为以后研制更大规模的管理系统迈出了具有基础性和开拓性的一步,其成果具有先进性和潜在的经济效益。
Permanent magnet linear synchronous motor and servo system with high efficiency, energy-saving and other significant advantages, it has made a successful development and application in our country ,and gets more and more attention. the“sectional permanent magnet linear motor drive for mine transportation system”is a new research project, so many issues is still to be resolved, in which the operation stability is the key issues. Some signs will be shown before failure of the motor, its direct and indirect parameters would have some tendency, we can restrain failures by parameters detecting.
In this paper, sub-type permanent magnet linear motor lift system as the research object, through analysis of its structure and operation principle, researching these parameters’changes when the system occurs failures.Based on the TMS320F2812 and sensor technology established the test monitoring system. The system not only can complete the on-site real-time monitoring, but also complete a continuous parameter analysis.The system is constituted by Hardware and software. Hardware is composed by voltage, current, air gap, speed, insulation modules, without position sensor power angle detection module, analog signal conditioning circuits, A/D conversion circuit, the switch volume acquisition module, communication module. Software design includes data acquisition, SCI initialization, monitoring program design. Experimental results show that this design can meet the practical requirements; less error can be applied to practical applications. The monitoring system for the future development of more large-scale management system has taken the foundation and ground-breaking step, the results have advanced and the potential economic benefits.Experimental results show that this design can meet the practical requirements, less errors, it can be applied to practical applications. The monitoring system has taken the foundation and ground-breaking step for the future development of more large-scale management system, the results have advanced and the potential economic benefits.
引文
[1]基于嵌入式系统的异步电机故障检测系统
[2]基于FPGA永磁同步直线电机性能检测系统的实现
[3]可编程控制器在中小型电动机检测中的应用
[4]基于DSP永磁同步电动机系统信号检测软件实现研究
[5]基于196单片机的开关磁阻电机性能检测系统设计方案
[6]《Hooper CW and Hill RJ.Detection of Rotor Positon Stepping and Switched Motors By Monitoring of Current Wave for ms》
[7]《Improved Digital Current Control Methods in Switched Reluctance Motor Drives》
[8]《Flux and Torque Control of Switched Reluctance Machine》
[9]《Optimum geometry for torque ripple minimization of switched reluctance motors》
[10]《Rotor Position Sensing in Switched Reluctance Motor Drives by Measuring Mutually Induced Voltages》
[11]叶云岳.直线电机原理与应用[M].北京:机械工业出版社,2000年.
[12]郭庆鼎,王成元.直线交流伺服系统的精密控制技术[M].北京:机械工业出版社,2000年
[13]符曦.高磁场永磁式电动机及其驱动系统[M].北京:机械工业出版社,1997年
[14]沈标正.电机故障诊断技术[M].北京:机械工业出版社,2001年
[15]王福忠,袁世鹰.永磁直线同步电动机的智能故障诊断研究[J]. The 7th World Congress on Intelligent Control and Automation(IEEE), June 25-27, 2008 Chongqing China.
[16]焦留成,袁世鹰.垂直运动永磁直线同步电动机运行特性分析[J].中国电机工程学报,2002,22(4):37-40.
[17]王国贞,王福忠,袁世鹰.基于模糊小波神经网络的永磁直线同步电机故障诊断[J].煤矿机械,2007,128(11):170-172.
[18]冯爱伟,高英杰,韩有顺.基于信息融合技术的电机故障诊断[J].传感器与微系统,2006,25(1):19-21.
[19]胡冠林,李娟,罗勇. D-S证据理论信息融合在故障诊断中的应用[J].计算机与数字工程,2007,l35(8):151-153.
[20]田刚,电机故障的小波MRA诊断技术.国外电子测量技术[J],2005, Vol.24,No.20:19-21
[21]黄红梅,胡寿松.基于在线学习RBF神经网络的故障预报[J].南京航空航天大学学报,2007,39(2):249-252.
[22]王福忠,焦留成,袁世鹰.基于神经网络永磁直线同步电动机提升系统动态模型建立与仿真,系统仿真学报[J]. 2002,14(9):1249-1254.
[23]余佩琼,陆亿红,王涌.永磁直线同步电动机无位置传感器控制系统的研究[J].中国电机工程学报,2007,27(24):53-57.
[24]钱存元,韩正之,邵德荣.直线同步电机动子位置检测研究[J].中国电机工程学报,2006,26(15):129-133.
[25]秦峰,贺益康.两种高频注入法的无传感器运行研究[J].中国电机工程学报,2005,25(5):116-121.
[26]谢宝昌,任永德,刘文瑛.无传感器电机位置检测策略综述[J].微电机,2000,33(5):29-31.
[27]文永明,沈传文,苏彦民.基于无位置传感器的永磁电机控制技术综述[J].微电机,2002,35(6)32-35.
[28]冬雷,李永东.无速度传感器异步电动机极低转速下的磁通位置观测[J].电工技术学报,2001,16(5)20-23.
[29] S. Vaez-Zadeh and A. Hassanpour Isfahani, Enhanced Modeling of Linear Permanent-Magnet Synchronous Motors[J]. IEEE TRANSACTIONS ON MAGNETICS, 2007, 43(1):p. 33-39.
[30] Jang J H, Sul S K, Ha J 1. Sensorless drive of surface-mounted permanent-magnet motor by high-frequency signal injection based on magnetic saliency[J]. IEEE Trans. on industry Applications, 2003, 39(4):p.1031-1038.
[31] Jang J H, Ha J I. Analysis of permanent-magnet machine for sensorless control based on h igh-frequency signal injection [J]. IEEE Tarns . on Industry Appilcaitons, 2004, 40(6):p.1595-1604.
[32] Jeong Y, Lorenz R D, Jahns T M, et al. Initial rotor position estimation of an interior permanent magnet synchronous machine using carrier-frequency injection methods [J].IEEE Trans. on Industry Applications, 2005, 41(1):p.38-45.
[33] Kuhlmann.D, Handschin, E.,Hoffmann, W. ANN based fault diagnosis system ready for practical application[J]. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications, 1999,vol.7, No.1:P29-39.
[34] Zidani,Fatiha,Benbouzid, Mohamed EI Hachermi,Diallo, Demba,etal.Induction Motor StatorFaults Diagnosis by a Current Concordia Pattern-Based Fuzzy Decision System[J]. IEEE Transactions on Energy Conversion, 2003,18(4):p.469-475.
[35] Bayir, Raif,Bay, Omer Faruk. Serial wound starter motor faults diagnosis using artificial neural network[J]. Proceedings of the IEEE International Conference on Mechatronics 2004, ICM'04, Proceedings of the IEEE International Conference on Mechatronics 2004, ICM'04:p.194-199.
[36] Alexandru, Monica. Analysis of induction motor fault diagnosis with fuzzy neural network. [J]Applied Artificial Intelligence, 2003, 7(2):p.105-133.
[37] Zhuang, Zhe-Min,Xiao, Wen-Hui,Cao,Qin. Fault detection of a synchronism motor based on genetic neural networks[J]. Journal of Test and Measurement Technology, 2004, 18(4):p.377-380.
[38] Briz F. Degner M W, Diez A, etal. Measuring, modeling and decoupling of saturation-Induced saliencies in carrier-signal injection based sensorless AC dirves[J].IEEE Trans.on Industry Applications, 2001, 37(5):p.1356-1364.
[39] Briz F,Degner M W. Diez A,etal. Staitc and dynamic behavior of saturation-induced saliencies and their effect on carrier-signal-based sensorless AC drives[J]. IEEE Trans. On Industry Applications, 2002, 38(3):p.670- 678.
[40] Fenton W G, McGinnity T M , Maguire L P. Fault diagnosis of electronic systems using intelligent techniques: a review[J].IEEE Transactions on Systems, Man , and Cybernetics– Part C: Applications and Reviews , 2001, 31(3):p.269-281.
[41] Lin, F.J., Wai, R.J., and Hong, C.M. Hybrid supervisory control using recurrent fuzzy neural network controller for tracking periodic inputs[J], IEEE Trans. Neural Netw, 2001, Vol.12: p.68–90
[2]基于FPGA永磁同步直线电机性能检测系统的实现
[3]可编程控制器在中小型电动机检测中的应用
[4]基于DSP永磁同步电动机系统信号检测软件实现研究
[5]基于196单片机的开关磁阻电机性能检测系统设计方案
[6]《Hooper CW and Hill RJ.Detection of Rotor Positon Stepping and Switched Motors By Monitoring of Current Wave for ms》
[7]《Improved Digital Current Control Methods in Switched Reluctance Motor Drives》
[8]《Flux and Torque Control of Switched Reluctance Machine》
[9]《Optimum geometry for torque ripple minimization of switched reluctance motors》
[10]《Rotor Position Sensing in Switched Reluctance Motor Drives by Measuring Mutually Induced Voltages》
[11]叶云岳.直线电机原理与应用[M].北京:机械工业出版社,2000年.
[12]郭庆鼎,王成元.直线交流伺服系统的精密控制技术[M].北京:机械工业出版社,2000年
[13]符曦.高磁场永磁式电动机及其驱动系统[M].北京:机械工业出版社,1997年
[14]沈标正.电机故障诊断技术[M].北京:机械工业出版社,2001年
[15]王福忠,袁世鹰.永磁直线同步电动机的智能故障诊断研究[J]. The 7th World Congress on Intelligent Control and Automation(IEEE), June 25-27, 2008 Chongqing China.
[16]焦留成,袁世鹰.垂直运动永磁直线同步电动机运行特性分析[J].中国电机工程学报,2002,22(4):37-40.
[17]王国贞,王福忠,袁世鹰.基于模糊小波神经网络的永磁直线同步电机故障诊断[J].煤矿机械,2007,128(11):170-172.
[18]冯爱伟,高英杰,韩有顺.基于信息融合技术的电机故障诊断[J].传感器与微系统,2006,25(1):19-21.
[19]胡冠林,李娟,罗勇. D-S证据理论信息融合在故障诊断中的应用[J].计算机与数字工程,2007,l35(8):151-153.
[20]田刚,电机故障的小波MRA诊断技术.国外电子测量技术[J],2005, Vol.24,No.20:19-21
[21]黄红梅,胡寿松.基于在线学习RBF神经网络的故障预报[J].南京航空航天大学学报,2007,39(2):249-252.
[22]王福忠,焦留成,袁世鹰.基于神经网络永磁直线同步电动机提升系统动态模型建立与仿真,系统仿真学报[J]. 2002,14(9):1249-1254.
[23]余佩琼,陆亿红,王涌.永磁直线同步电动机无位置传感器控制系统的研究[J].中国电机工程学报,2007,27(24):53-57.
[24]钱存元,韩正之,邵德荣.直线同步电机动子位置检测研究[J].中国电机工程学报,2006,26(15):129-133.
[25]秦峰,贺益康.两种高频注入法的无传感器运行研究[J].中国电机工程学报,2005,25(5):116-121.
[26]谢宝昌,任永德,刘文瑛.无传感器电机位置检测策略综述[J].微电机,2000,33(5):29-31.
[27]文永明,沈传文,苏彦民.基于无位置传感器的永磁电机控制技术综述[J].微电机,2002,35(6)32-35.
[28]冬雷,李永东.无速度传感器异步电动机极低转速下的磁通位置观测[J].电工技术学报,2001,16(5)20-23.
[29] S. Vaez-Zadeh and A. Hassanpour Isfahani, Enhanced Modeling of Linear Permanent-Magnet Synchronous Motors[J]. IEEE TRANSACTIONS ON MAGNETICS, 2007, 43(1):p. 33-39.
[30] Jang J H, Sul S K, Ha J 1. Sensorless drive of surface-mounted permanent-magnet motor by high-frequency signal injection based on magnetic saliency[J]. IEEE Trans. on industry Applications, 2003, 39(4):p.1031-1038.
[31] Jang J H, Ha J I. Analysis of permanent-magnet machine for sensorless control based on h igh-frequency signal injection [J]. IEEE Tarns . on Industry Appilcaitons, 2004, 40(6):p.1595-1604.
[32] Jeong Y, Lorenz R D, Jahns T M, et al. Initial rotor position estimation of an interior permanent magnet synchronous machine using carrier-frequency injection methods [J].IEEE Trans. on Industry Applications, 2005, 41(1):p.38-45.
[33] Kuhlmann.D, Handschin, E.,Hoffmann, W. ANN based fault diagnosis system ready for practical application[J]. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications, 1999,vol.7, No.1:P29-39.
[34] Zidani,Fatiha,Benbouzid, Mohamed EI Hachermi,Diallo, Demba,etal.Induction Motor StatorFaults Diagnosis by a Current Concordia Pattern-Based Fuzzy Decision System[J]. IEEE Transactions on Energy Conversion, 2003,18(4):p.469-475.
[35] Bayir, Raif,Bay, Omer Faruk. Serial wound starter motor faults diagnosis using artificial neural network[J]. Proceedings of the IEEE International Conference on Mechatronics 2004, ICM'04, Proceedings of the IEEE International Conference on Mechatronics 2004, ICM'04:p.194-199.
[36] Alexandru, Monica. Analysis of induction motor fault diagnosis with fuzzy neural network. [J]Applied Artificial Intelligence, 2003, 7(2):p.105-133.
[37] Zhuang, Zhe-Min,Xiao, Wen-Hui,Cao,Qin. Fault detection of a synchronism motor based on genetic neural networks[J]. Journal of Test and Measurement Technology, 2004, 18(4):p.377-380.
[38] Briz F. Degner M W, Diez A, etal. Measuring, modeling and decoupling of saturation-Induced saliencies in carrier-signal injection based sensorless AC dirves[J].IEEE Trans.on Industry Applications, 2001, 37(5):p.1356-1364.
[39] Briz F,Degner M W. Diez A,etal. Staitc and dynamic behavior of saturation-induced saliencies and their effect on carrier-signal-based sensorless AC drives[J]. IEEE Trans. On Industry Applications, 2002, 38(3):p.670- 678.
[40] Fenton W G, McGinnity T M , Maguire L P. Fault diagnosis of electronic systems using intelligent techniques: a review[J].IEEE Transactions on Systems, Man , and Cybernetics– Part C: Applications and Reviews , 2001, 31(3):p.269-281.
[41] Lin, F.J., Wai, R.J., and Hong, C.M. Hybrid supervisory control using recurrent fuzzy neural network controller for tracking periodic inputs[J], IEEE Trans. Neural Netw, 2001, Vol.12: p.68–90