基于参数估计模型的对转永磁无刷直流电机实时故障诊断方法

无刷直流电机可靠性高,但在过载、过热等条件下,会造成电机性能降低;在电动力船舶推进系统中,由于速度闭环负反馈作用,这些故障常常无法及时发现,因此在电机运行过程中及时发现故障具有十分重要的应用价值。论文把参数估计技术应用于对转无刷直流电机故障实时诊断,建立了对转无刷直流电机驱动对转螺旋桨时的实时辨识模型,通过测量电机电压、电流和电机转速,得到电机的绕组电阻、反电势系数和转动惯量参数以及螺旋桨负载的力矩系数,通过观察参数的实时变化,监控电机的工作状态。这种以微分方程为基础的最小二乘方法不影响电机正常工作。仿真结果表明该方法可以完成对转无刷直流电机驱动对转螺旋桨时的故障诊断。

Real-Time Fault Detection of Anti-Directional-Twin-Rotary BrushLess DC Motor (BLDCM) Using Least Squares Parameter Estimation

Aim.The introduction of the full paper reviews Refs.2 through 4 and then proposes the research mentioned in the title.Sections 1 through 4 explain our research.Much of section 1 briefs what is available in the open literature but there is some contribution by us,particularly eqs.(10) and(16).Sections 2 briefs least squares parameter estimation.In sections 3,Figs.4(a) through 4(e) give simulation results.Section 4,utilizing the above-mentioned simulation results,gives a 7-step procedure for real-time fault d...