Loading

Detection of Air gap Eccentricity Fault of Three Phase Induction Motor by Fast Fourier Transform using ARM Microcontroller
B. Rajagopal1, S. Singaravelu2

1B. Rajagopal, Department of Electrical Engineering, Annamalai University, Annamalai Nagar, Chidambaram, (Tamil Nadu), India.
2Dr. S. Singaravelu, Department of Electrical Engineering, Annamalai University, Annamalai Nagar, Chidambaram, (Tamil Nadu), India.

Manuscript received on 20 September 2015 | Revised Manuscript received on 30 September 2015 | Manuscript published on 30 September 2015 | PP: 8-16 | Volume-4 Issue-4, September 2015 | Retrieval Number: D1475094415©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Induction machines are the backbones of many industrial processes due to its robustness and reliability. Online fault diagnostics of induction motor is important, and its real function is to attempt to recognize the development of faults at an early stage, which are highly useful preventive rescue especially in high power applications. Among various faults occurred in induction motors, eccentricity faults are of significant importance as they produce secondary effects that can lead to a major fault to a motor. Using different signal processing and mathematics techniques, the stator current signals of a motor can be analyzed, interpreted and faults inside the motor can be identified. It is observed that the fault frequencies for different faults of induction motor are unique. This paper investigates on detection of air gap eccentricity fault in three phase cage induction using modulated motor stator current.. MCSA (Motor Current Signature Analysis) technique using FFT (Fast Fourier Transform) approach is utilized in this research work to identify air gap eccentricity fault of induction motor under different loading conditions. Hence, in this paper RISC (Reduced Instruction Set Computing) based ARM (Advanced RISC Machine) architecture controller (LPC2148 from NXP) for current signature analysis is developed to analyze the air gap eccentricity fault. An experimental setup, using the ARM based data acquisition board and PC based analysis software is also developed and results are given for air gap eccentricity fault
Keyword: Induction motor, MCSA, FFT, Air gap Eccentricity fault, ARM controller.

Scope of the Article: Knowledge Engineering Tools and Techniques