Detection of the Misalignment Fault in Non-Electric Rotating Machines Through the Current Signal of a Brushless Direct Current Motor

Ehsani-Seresht, Abbas; Bolourian, Ali; RoshanFekr, Reza

doi:10.22075/mseee.2023.28937.1121

Detection of the Misalignment Fault in Non-Electric Rotating Machines Through the Current Signal of a Brushless Direct Current Motor

Document Type : Research Article

Authors

Abbas Ehsani-Seresht ¹

Ali Bolourian ¹

Reza RoshanFekr ²

¹ Department of Mechanical Engineering, Hakim Sabzevari University, Sabzevar, Iran

² Department of Electrical Engineering, Hakim Sabzevari University, Sabzevar, Iran

10.22075/mseee.2023.28937.1121

Abstract

One of the most common causes of vibration in rotating machines is the misalignment fault. The Motor Current Signature Analysis (MCSA) is an excellent method for the detection of the misalignment fault on those electric machines whose current signals are practically available. This paper aims to extend the application of the MCSA method to non-electric rotating systems for the detection of the misalignment fault between the driver machine and the driven machine. For this, a small brushless direct current (BLDC) motor was connected to the driver machine. Then, by using the Fast Fourier Transform and Wavelet Packet Transform the current signal of the BLDC motor was analyzed to detect the misalignment fault. In addition, a fault detection indicator was provided using the energy of the current signal. For the evaluation of the proposed method, an experimental setup was provided. The driver machine of the setup was an induction machine. So, it was possible to investigate the misalignment fault through both the BLDC motor and the induction motor. The results showed that the misalignment fault can be detected by the current signal of the BLDC motor as well as the current signal of the driver machine.

Keywords

Condition monitoring

Fault detection

Fast Fourier Transform

Wavelet packet transform

Subjects

Power System

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