Fault detection in robots based on discrete wavelet transformation and eigenvalue of energy
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Department of Electrical Engineering, University of Biskra,Biskra, Algeria
College of Engineering, Royal University for Women,Bahrain
Department of Electrical Engineering, University of Mohamed Boudiaf, M’Sila, Algeria
Submission date: 2023-06-07
Final revision date: 2023-09-18
Acceptance date: 2023-10-13
Online publication date: 2023-10-23
Publication date: 2023-10-23
Corresponding author
Saloua Ouarhlent   

Department of Electrical Engineering, University of Biskra,Biskra, Algeria
Diagnostyka 2023;24(4):2023407
This article addresses the problem of fault detection in robot manipulator systems. In the production field, online detection and prevention of unexpected robot stops avoids disruption to the entire manufacturing line. A number of researchers have proposed fault diagnosis architectures for electrical systems such as induction motor, DC motor, etc..., utilizing the technique of discrete wavelet transform (DWT). The results obtained from the use of DWT coefficient analysis in the field of diagnosis are very encouraging. Inspired by previous work, The objective of this paper is to present a methodology that enables accurate fault detection in the actuator of a 2 DOF robot arm to avoid system performance degradation; a partial reduction in joint torque constitutes the actuator fault, resulting in a deviation from the desired end-effector motion. The actuator fault detection is carried out by analysing the torques signals using DWT. The stored energy at each level of the DWT contains information which can be used as a fault indicator. The Matlab/Simulink simulation on the manipulator robot demonstrates the effectiveness of the proposed technique.
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