6533b7d0fe1ef96bd125af48

RESEARCH PRODUCT

Broken rotor bars detection via Park's vector approach based on ANFIS

Hossein HassaniZuolong WeiHamid Reza KarimiJafar Zarei

subject

EngineeringAdaptive neuro fuzzy inference systemRotor (electric)business.industryStatorANFIS; broken rotor bars; fault diagnosis; Park's transformation; Electrical and Electronic Engineering; Control and Systems EngineeringCoordinate vectorfault diagnosisFault (power engineering)Fault detection and isolationlaw.inventionlawControl theoryControl and Systems EngineeringTime domainElectrical and Electronic EngineeringbusinessANFISbroken rotor barsPark's transformationInduction motor

description

Many attempts have been made on fault diagnosis of induction motors based on frequency and time domain analysis of stator current. In this paper, first the Park's vector transformation and frequency analysis for fault detection of induction motors are introduced. Then a smart approach using Adaptive Neuro Fuzzy Inference System (ANFIS) is proposed. This approach uses the time domain features derived from the Park's vector transformation of stator current. By the proposed method, a partial break including 5 mm crack on a bar, one broken bar and two broken bars using experimental data are investigated. It will be shown that features derived from Park's vector compared to features obtained from a phase current, have better results.

yearjournalcountryeditionlanguage
2014-06-01
10.1109/isie.2014.6864999http://hdl.handle.net/11311/1028742