Non-intrusive current-based fault detection of electro-mechanical actuators with brushed DC motors

• Autorzy: Hanuš Ondřej , Smid Radislav

Identyfikatory

DOI

10.24425/mms.2022.140040

• Języki publikacji: EN

Abstrakty

EN

This paper proposes data-based fault detection methods for an electromechanical actuator (EMA) with a brushed DC motor. The jam and winding short faults are considered in the study as the most prominent EMA faults. The fault detection is based on evaluating the properties of the motor current, considering the basic electromechanical parameters of EMAs. The main advantages are a non-intrusive approach utilising a commonly accessible motor current measurement, simple configurability, and the ability to detect faults under varying operation modes of EMA, including changes of speed, load, or movement profiles. The proposed methods have been evaluated with a custom testing system, and the results have proven the performance of the proposed approach to detect faults under varying operating conditions in industrial applications.

Słowa kluczowe

EN

Electro-mechanical Actuator; EMA; Fault Detection and Diagnostics; FDD; jam; winding short

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2022
• Tom: Vol. 29, nr 3
• Strony: 505--523
• Opis fizyczny: Bibliogr. 17 poz., rys., tab., wykr., wzory

Twórcy

autor

Hanuš Ondřej

• Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Measurement, Technicka 2, 166 27 Prague, Czech Republic

autor

Smid Radislav

• Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Measurement, Technicka 2, 166 27 Prague, Czech Republic

Bibliografia

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Uwagi

1. This work was supported in part by the Grant Agency of the Czech Technical University in Prague, under grant no. SGS21/063/OHK3/1T/13 and in part by Technology Agency of the Cech Republic, project no. TH04010237.

2. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).