Permanent magnet synchronous machines position sensor failure identification using sequence mining

Safa Aloui Dkhil, M. Bennani, H. B. A. Sethom
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引用次数: 1

Abstract

In recent years, Permanent Magnet Synchronous Motors (PMSMs) are increasingly used in industrial applications, automotive, aerospace, robotics, etc. However, this type of actuator can be affected by faults and failures which make it operate in severe conditions. An undetected fault in the PMSM-based system may lead to high repair costs or even catastrophic failure. Therefore, each fault must be detected and isolated at early stages to avoid its extensive effects on the motor. PMSM sensors are sensitive to many types of faults, such as the total loss of the position/speed information.This paper shows the efficiency of sequence mining and data dependency analysis to identify faults localization at design time. The detection of the position sensor failure has been carried out from gathering the PMSM currents data.
基于序列挖掘的永磁同步电机位置传感器故障识别
近年来,永磁同步电机(PMSMs)越来越多地应用于工业、汽车、航空航天、机器人等领域。然而,这种类型的执行器可能会受到故障和故障的影响,使其在恶劣条件下运行。在基于pmsm的系统中,未被发现的故障可能导致高昂的维修成本甚至灾难性的故障。因此,必须在早期阶段检测和隔离每个故障,以避免其对电机的广泛影响。永磁同步电动机传感器对许多类型的故障都很敏感,例如位置/速度信息的完全丢失。本文展示了序列挖掘和数据依赖分析在设计阶段识别故障定位的有效性。通过采集永磁同步电机电流数据,实现了位置传感器故障的检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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