Neural Network Used to Stator Winding Interturn Short-Circuit Fault Detection in an Induction Motor Driven by Frequency Converter

2013 ◽  
Author(s):  
Atila Girao de Oliveira ◽  
Ricardo Silva The Pontes ◽  
Claudio Marques de Sa Medeiros
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Induction Motor ◽  
Short Circuit ◽  
Frequency Converter ◽  
Stator Winding ◽  
Short Circuit Fault

scholarly journals Induction Motor Stator Interturn Short Circuit Fault Detection in Accordance with Line Current Sequence Components Using Artificial Neural Network

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Gayatridevi Rajamany ◽  
Sekar Srinivasan ◽  
Krishnan Rajamany ◽  
Ramesh K. Natarajan
Keyword(s):  
Neural Network ◽  
Fault Detection ◽  
Induction Motor ◽  
Short Circuit ◽  
Positive Sequence ◽  
Negative Sequence ◽  
Three Phase ◽  
Sequence Components ◽  
Negative Sequence Current ◽  
Short Circuit Fault

The intention of fault detection is to detect the fault at the beginning stage and shut off the machine immediately to avoid motor failure due to the large fault current. In this work, an online fault diagnosis of stator interturn fault of a three-phase induction motor based on the concept of symmetrical components is presented. A mathematical model of an induction motor with turn fault is developed to interpret machine performance under fault. A Simulink model of a three-phase induction motor with stator interturn fault is created for extraction of sequence components of current and voltage. The negative sequence current can provide a decisive and rapid monitoring technique to detect stator interturn short circuit fault of the induction motor. The per unit change in negative sequence current with positive sequence current is the main fault indicator which is imported to neural network architecture. The output of the feedforward backpropagation neural network classifies the short circuit fault level of stator winding.

Diagnostics of Stator Winding Faults in a Three-Phase Asynchronous Motor Using Park’s Vector Analysis

Vestnik MEI ◽  
2021 ◽  
pp. 69-74
Author(s):  
Muhammad Deeb ◽  
◽  
Gassan Ibragim ◽  
Talal Assaf ◽  
◽  
...  
Keyword(s):  
Induction Motor ◽  
Short Circuit ◽  
Asynchronous Motor ◽  
Vector Model ◽  
Stator Winding ◽  
Stator Windings ◽  
Stator Current ◽  
Experimental Part ◽  
Three Phase ◽  
Short Circuit Fault

The study addresses the problem of detecting a short circuit fault in the three-phase induction motor winding by monitoring the stator current Park vector (Lissajous curves). Park's vector model is implemented using the Matlab software package. The experimental part of the study was carried out on an 11 kW three-phase induction motor. The Lissajous curves obtained for a healthy motor and a motor with short-circuited turns under various load conditions were compared with each other. The obtained results have demonstrated the effectiveness of the proposed method for detecting interturn short circuit faults in the three-phase stator windings of induction motors.

Short Circuit between Turns in Stator Winding of Induction Machine Fault Detection and Diagnosis

2013 ◽  
Vol 416-417 ◽  
pp. 565-571 ◽  
Author(s):  
Youcef Soufi ◽  
Tahar Bahi ◽  
H. Merabet ◽  
S. Lekhchine
Keyword(s):  
Induction Motor ◽  
Low Cost ◽  
Short Circuit ◽  
Induction Machine ◽  
Fault Detection And Diagnosis ◽  
Operating Conditions ◽  
Stator Winding ◽  
Detection And Diagnosis ◽  
Abnormal Operating Conditions ◽  
Short Circuit Fault

The induction motor is one of the most used electric machines in variable speed system in the different field of industry due to its robustness, mechanical strength and low cost. Despite these qualities, the induction machine is subjected during its operation to a number of constraints of various natures (electrical, mechanical and environmental). This paper focuses on the diagnosis and the detection of the short circuit fault between turns in the stator winding of an induction machine, based on analyzing the evolution of the stator current in each stator phase, using tools based both on motor current spectral analysis and Park vector approach. A study by simulation was presented. The obtained results show that the considered methods can effectively diagnose and detect abnormal operating conditions in induction motor applications. Therefore, they clearly show the possibility of extracting signatures and the application of these techniques offered reliable and satisfactory results for the diagnosis and detection of such fault.

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