摘要
微型永磁步进电机作为电子阀核心器件,其运行状态对电子阀能否正常执行操作有着直接影响。为了准确掌握电机剩余寿命情况,提出了一种考虑个体差异Wiener过程的剩余寿命预测方法。首先通过分析电机性能退化失效过程,选取相电流有效值作为性能退化特征量;其次由于同型号多台电机同时参与实验,建立考虑个体差异Wiener过程的电机性能退化模型并基于EM算法进行参数估计;最后,设计一种将启停次数作为电机剩余寿命参考的实验,并与基于传统Wiener过程的预测结果进行对比。实验结果表明所提方法平均预测误差下降了3.74%,具有更高的预测精度。
As the core device of the electronic valve,the operating state of the micro permanent magnet stepping motor has a direct impact on whether the electronic valve can perform operations normally.In order to accurately grasp the remaining useful life of the motor,a prediction method considering individual differences in the Wiener process is proposed.Firstly,by analyzing the failure process of motor performance degradation,the effective value of phase current is selected as the characteristic quantity of performance degradation.Secondly,due to the simultaneous participation of multiple motors of the same model in the experiment,a motor performance degradation model considering the individual differences in the Wiener process is established,and parameter estimation is carried out based on the EM algorithm.Finally,the number of starting and stopping times is designed as the reference of the motor′s remaining useful life in the experiment and compared with the prediction results based on the traditional Wiener process.The experimental results show that the average prediction error of the proposed method decreases by 3.74%,which has a higher prediction accuracy.
作者
杨超群
段书用
杨天豪
李珊瑚
Yang Chaoqun;Duan Shuyong;Yang Tianhao;Li Shanhu(State Key Laboratory of Reliability and Intelligence of Electrical Equipment(Hebei University of Technology),Beichen District,Tianjin 300401,China;Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province(Hebei University of Technology),Beichen District,Tianjin 300401,China)
出处
《电子测量技术》
北大核心
2024年第4期104-112,共9页
Electronic Measurement Technology
基金
国家自然科学基金(52175222)
国家自然科学基金(51907049)项目资助。
关键词
微型永磁步进电机
WIENER过程
EM算法
剩余寿命预测
micro permanent magnet stepper motor
Wiener process
EM algorithm
remaining useful life prediction
