基於馬達電流訊號分析法開發之軸承故障診斷技術
Other Title
A Diagnostic Approach for Bearing Faults Using Motor Current Signal Analysis
Journal
機械工業雜誌
Journal Issue
508
Start Page
16
End Page
23
ISSN
0255-0075
Date Issued
2025-07
Author(s)
Abstract
軸承是旋轉機械中的重要元件，其故障可能導致設備停機甚至更嚴重事故。以「振動訊號分析」作為軸承故障診斷法雖然常見，但存在成本高昂且易受環境雜訊干擾的問題。本研究提出一種基於馬達電流訊號分析之軸承故障診斷方法，利用永磁同步馬達內部固有的電流訊號進行故障辨識。並透過三相電流同步與快速傅立葉轉換，使得雜訊降低以有效提取故障特徵頻率。該方法已在一套小型永磁同步馬達平台上獲得驗證。實驗結果顯示，該方法可在低負載與低轉速條件下準確診斷軸承故障，並具有低成本與易於實現等優勢。
Bearings are critical components in rotating machinery, and their failures may lead to equipment downtime or even more severe accidents. Although vibration signal analysis is a commonly used method for bearing fault diagnosis, it suffers from high implementation costs and vulnerability to environmental noise. This study proposes a bearing fault diagnosis method based on motor current signal analysis, which utilizes the inherent current signals within a Permanent Magnet Synchronous Motor (PMSM) to identify faults. By applying three-phase current synchronization and Fast Fourier Transform (FFT), the proposed method effectively suppresses noise and extracts fault characteristic frequencies. The approach was experimentally validated on a small-scale PMSM platform. Results demonstrate that the method can accurately diagnose bearing faults under low-load and low-speed conditions, while offering advantages such as low cost and ease of implementation.
Subjects
預兆式診斷系統
初期故障診斷
馬達電流訊號分析
Prognostic Management System (PMS)
Early Fault Diagnosis (EBD)
Motor Current Signature Analysis (MCSA)
Type
journal article