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Mathematical Modelling and IoT Enabled Instrumentation for Simulation & Emulation of Induction Motor Faults.

Authors :
Ayyappan, G. S.
Ramesh Babu, B.
Srinivas, Kota
Raja Raghavan, M.
Poonthalir, R.
Source :
IETE Journal of Research. Apr2023, Vol. 69 Issue 4, p1829-1841. 13p.
Publication Year :
2023

Abstract

Simulation and emulation of electric motor faults are particularly useful to study, test, and evaluate the motor condition monitoring products based on the motor current signature and vibration analysis. Many researchers have proposed and developed several DAQ & computer-based simulation tools. This paper aims to develop a system to simulate and emulate the maximum types of faults which can occur in a three-phase induction motor. In this paper, an embedded system based induction motor fault simulator and the emulator is proposed and developed. The focus of this paper is to model the induction motor faults mathematically based on the motor current signature and vibration frequency spectrum, which are theoretically derived and proved by the early generation researchers and engineers. The novelty of the proposed approach is a cost-effective, portable, and handy tool for field evaluation of the motor condition monitoring products. This paper presents the hardware and software development for making a stand-alone motor faults simulator and emulator. The system employs a powerful high-end and powerful embedded system INTEL ATOM Minnow Board, which is built around E3826, Dual Core, and 1.46 GHz processor. A dedicated 4-channel Direct Digital Synthesizer (DDS) with 12-bit resolution along with software generates all three-phase induction motor faults for both MCSA and vibration analysis. The simulated and emulated faults signals are compared and evaluated against the Standards with the help of a digital storage oscilloscope. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03772063
Volume :
69
Issue :
4
Database :
Academic Search Index
Journal :
IETE Journal of Research
Publication Type :
Academic Journal
Accession number :
163409399
Full Text :
https://doi.org/10.1080/03772063.2021.1875272