電流徴候解析によるモータ診断とその高精度化

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2022/02/01

タイトル(英語): Application and Amelioration of Motor Current Signature Analysis

著者名: 三好　将仁（三菱電機（株）先端技術総合研究所），金丸　誠（三菱電機（株）先端技術総合研究所），安原　裕登（三菱電機（株）受配電システム製作所），宮内　俊彦（三菱電機（株）受配電システム製作所）

著者名(英語): Masahito Miyoshi (Advanced Technology R&D Center, Mitsubishi Electric Co.), Makoto Kanemaru (Advanced Technology R&D Center, Mitsubishi Electric Co.), Yuto Yasuhara (Power Distribution System Center, Mitsubishi Electric Co.), Toshihiko Miyauchi (Power Distribution System Center, Mitsubishi Electric Co.)

キーワード: 誘導機，ベアリング診断，状態基準保全，電流徴候解析，誤検知　　induction motor，bearing diagnosis，condition based maintenance，motor current signature analysis，false positive

要約(英語): 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.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.142 No.2 （2022）

本誌掲載ページ: 119-124 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/142/2/142_119/_article/-char/ja/