Accurate Demagnetization Faults Detection of Dual-Sided Permanent Magnet Linear Motor Using Enveloping and Time-Domain Energy Analysis

摘要

In this article, dual-sided permanent magnet linear motors (DPMLM) have been wildly applied in linear motion occasions such as high-precision laser cutting machines. This article researches a new way for accurate demagnetization fault detection of DPMLM, and this proposed method based on signal enveloping and time-domain energy analysis can be suitably used in some typical industrial occasions such as motor batch demagnetization inspection before delivery and periodic maintenance. First, three magnetic signals in motor air-gap region are selected as demagnetization fault index, and finite element analysis (FEA) is used to obtain these signals. Second, complex continuous wavelet transform (CCWT) is introduced to preprocess the fault signal and extract signal envelop for next-step fault feature extraction. Comparison experiments show that CCWT is better than frequently used extreme value and Hilbert-Huang transform methods. Then, Teager-Kaiser energy operator (TKEO) is applied to detect time-domain energy of fault signal envelop as fault feature. In addition to this, Hanning window is used to optimize TKEO to enhance fault feature and help with the accurate detection of demagnetization fault. Finally, motor prototype is manufactured for actual experiment and the results under different noise environments can certify the effectiveness and robustness of this proposed method.