電気学会論文誌D(産業応用部門誌)
Online ISSN : 1348-8163
Print ISSN : 0913-6339
ISSN-L : 0913-6339
論文
電流徴候解析によるモータ診断とその高精度化
三好 将仁金丸 誠安原 裕登宮内 俊彦
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2022 年 142 巻 2 号 p. 119-124

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Feature values of the current are rapidly becoming online indicators of faults in motors and load equipment. Diagnosis by analysis of the stator currents is called motor current signature analysis (MCSA). Compared with vibration analysis, this method can be applied without sensors, and additional long wiring. MCSA detects incidents peculiar to motors, such as bearing failures and rotor bar faults, before breakdown. In this study, we introduce relationships between the failures and current features. The MCSA sometimes has difficulty in identifying anomalies and there is the possibility of false-positive results; hence, we propose some solutions to these problems.

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