Open AccessCurrent Signature Analysis for Diagnostics in Motor Bars under Locked Rotor Condition
Author(s) -
Michael Hrelrison F. da Silva,
Paula Cristina Pereira da Costa
Publication year - 2021
Publication title -
international journal of electrical and electronic engineering and telecommunications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.171
H-Index - 6
ISSN - 2319-2518
DOI - 10.18178/ijeetc.10.5.362-368
Subject(s) - induction motor , rotor (electric) , fast fourier transform , hilbert transform , signature (topology) , computer science , operability , discrete wavelet transform , wavelet , control theory (sociology) , discrete fourier transform (general) , transformation (genetics) , engineering , control engineering , wavelet transform , fourier transform , fourier analysis , short time fourier transform , artificial intelligence , algorithm , mathematics , reliability engineering , electrical engineering , voltage , mathematical analysis , geometry , control (management) , chemistry , telecommunications , biochemistry , spectral density , gene
Three-phase induction motors are widely used in industrial electric applications. To ensure their operability, efforts have been made mainly in the detection of rotor faults. This work aims to detect rotor faults in induction motors through of Motor Current Signature Analysis (MCSA) under locked rotor condition. In this configuration, the procedure is most suitable for drives where the motor operates intermittently, with a short operating stroke or variable speed. This paper proposes a methodology and presents a comparison of consolidated signal processing techniques such as Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), and Discrete Hilbert Transform (DHT) applied on the conventional input currents and components of Park transformation in a case study. The objective is to define which of the techniques is the most robust in the process of identifying broken bars in the induction motor for the proposed methodology.