为了减小电机驱动系统中未知干扰对逆变器开路故障诊断的影响,提出了一种基于扩展观测器ESO(extended state observer)和混合逻辑动态MLD(mixed logic dynamic)模型的逆变器开路故障快速诊断方法。通过分析开关管在正常工作和故障状态...为了减小电机驱动系统中未知干扰对逆变器开路故障诊断的影响,提出了一种基于扩展观测器ESO(extended state observer)和混合逻辑动态MLD(mixed logic dynamic)模型的逆变器开路故障快速诊断方法。通过分析开关管在正常工作和故障状态下的电流流向路径,建立了逆变器的混合逻辑动态模型,并设计了一种电压扩展观测器。根据观测器的观测电压和实际系统输出电压之间的相电压残差进行故障检测,通过故障相残差与正常两相残差之间的数值关系来定位故障相和故障管。该方法有效减小了系统中未知干扰和不确定因素对逆变器故障诊断的影响,提高了故障诊断率。最后,通过Matlab/Simulink仿真验证了该方法的正确性和有效性。展开更多
In a permanent magnet synchronous generator(PMSG)system,conversion systems are major points of failure that create expensive and time-consuming problems.Fault detection is usually used to achieve a steady system.This ...In a permanent magnet synchronous generator(PMSG)system,conversion systems are major points of failure that create expensive and time-consuming problems.Fault detection is usually used to achieve a steady system.This paper presents a full analysis of a PMSG system for wind turbines(WT)and proposes a fault detection method using correlation features.The proposed method is motivated by the balance among the three-phase currents both before and after an opencircuit fault occurs in a converter of the PMSG system.It is unnecessary to analyze the output waveforms of a converter during fault detection.In this study,two correlation features of stator currents,the mean and covariation,are extracted to train an artificial neural network(ANN),thereby enhancing the performance of the proposed method under different wind speed conditions.Moreover,additional sensors and the collection of a massive amount of data are not required.Model simulations of an ideal inverter and a PMSG system are conducted using PSCAD software.The simulation results show that the proposed method can detect the locations of faulty switches with a diagnostic rate greater than 99.4%for the ideal inverter,and the PMSG drives settings at different wind speeds.展开更多
文摘为了减小电机驱动系统中未知干扰对逆变器开路故障诊断的影响,提出了一种基于扩展观测器ESO(extended state observer)和混合逻辑动态MLD(mixed logic dynamic)模型的逆变器开路故障快速诊断方法。通过分析开关管在正常工作和故障状态下的电流流向路径,建立了逆变器的混合逻辑动态模型,并设计了一种电压扩展观测器。根据观测器的观测电压和实际系统输出电压之间的相电压残差进行故障检测,通过故障相残差与正常两相残差之间的数值关系来定位故障相和故障管。该方法有效减小了系统中未知干扰和不确定因素对逆变器故障诊断的影响,提高了故障诊断率。最后,通过Matlab/Simulink仿真验证了该方法的正确性和有效性。
文摘In a permanent magnet synchronous generator(PMSG)system,conversion systems are major points of failure that create expensive and time-consuming problems.Fault detection is usually used to achieve a steady system.This paper presents a full analysis of a PMSG system for wind turbines(WT)and proposes a fault detection method using correlation features.The proposed method is motivated by the balance among the three-phase currents both before and after an opencircuit fault occurs in a converter of the PMSG system.It is unnecessary to analyze the output waveforms of a converter during fault detection.In this study,two correlation features of stator currents,the mean and covariation,are extracted to train an artificial neural network(ANN),thereby enhancing the performance of the proposed method under different wind speed conditions.Moreover,additional sensors and the collection of a massive amount of data are not required.Model simulations of an ideal inverter and a PMSG system are conducted using PSCAD software.The simulation results show that the proposed method can detect the locations of faulty switches with a diagnostic rate greater than 99.4%for the ideal inverter,and the PMSG drives settings at different wind speeds.
基金韩国国际合作项目(Development of Embedded Software and System for Automobile Electronics)重庆市科技攻关计划项目(CSTC+2 种基金2006AB2026)"面向汽车ABS嵌入式系统的专用开发平台及其应用"国家863计划项目(2006AA11A107-2)节能与新能源汽车-"长安混合动力汽车标定系统开发"国家863计划重点资助项目(2004AA1Z2380)"面向汽车电子控制的嵌入式系统开发平台及其应用"
