Diagnosis and classification of stator winding insulation faults on a three-phase induction motor using wavelet and MNN

2016 ◽  
Vol 23 (5) ◽  
pp. 2543-2555 ◽  
Author(s):  
N. Rama Devi ◽  
D. V. S. S. Siva Sarma ◽  
P. V. Ramana Rao
2021 ◽  
Vol 29 (3) ◽  
pp. 869-883
Author(s):  
Majid Hussain ◽  
Dileep Kumar Soother ◽  
Imtiaz Hussain Kalwar ◽  
Tayab Din Memon ◽  
Zubair Ahmed Memon ◽  
...  

2021 ◽  
Author(s):  
Ang Joey

<p>The induction motor is considered the workhorse of the industry as it is used in most of the engineering applications. It is essential to ensure a safe and reliable operation of the induction motor in every system. Among the various types of induction motor faults, stator winding insulation fault accounts for a high percentage of it. As such, being able to detect early stages of insulation faults within the equipment using the method proposed in this paper would prove to be useful in providing timely maintenance. The proposed method in this paper is the non-intrusive impedance extraction method for online stator winding fault detection of induction motor. By observing the health condition of the motor in relation with its impedance, early stages of faults can be detected and rectified. Hence, eliminating potential safety hazards, reducing motor downtime as well as lowering the cost of maintenance. Experimental results shown will prove the reliability and accuracy in which the method proposed would provide. At the same time, its installation and removal are less complicated as compared to other methods hence is cost and time efficient.<b></b></p>


This paper adopted a thermal network method (TNM) based on Motor-CAD with MATLAB/Simulink software, and finite element method (FEM) based on Motor- CAD with Flux2D software, to estimate the stator winding temperature of a totally enclosed fan-cooled (TEFC), squirrel cage, three-phase induction motor. The three software packages were adopted successfully with a good agreement among their results resulting in preferring using Motor-CAD in obtaining results, and using Flux2D with MATLAB to validate these results. The success of triple-software methodology will give the induction motor designer a well-validated tool in attaining a safe motor operation without exceeding the maximum allowable stator winding temperature rise, and without using an experimental test based on an expensive manufacturing motor.


2020 ◽  
Vol 2 (1) ◽  
pp. 32
Author(s):  
Guilherme Lucas ◽  
Marco Rocha ◽  
Bruno Castro ◽  
José Leão ◽  
André Andreoli

Three-phase induction motors (TIMs) play a key role in industrial production lines. Due to their robustness and versatility, TIMs are commonly used to drive different devices like fans, conveyors, sieves, and compressors. However, these devices are often exposed to mechanical and electrical faults. Among them, failures in stator winding insulation lead to severe damage to the TIMs and can cause operational interruptions. Therefore, several approaches have been developed to monitor electrical faults in induction motors. The acoustic emission (AE) stands out as an efficient non-invasive technique (NIT) for TIM diagnosis. In this work, the AE analysis was applied to detect winding insulation faults and identify which electrical phase was affected. To achieve this proposal, a TIM was subjected to insulation faults in each of the three electrical phases, and the acoustic signals were acquired by four piezoelectric sensors attached to the motor. These signals were processed using a new technique, which calculates the energy of a specific range of the signal spectrum and assigns the energy values of each piezoelectric sensor to a coordinate axis (x, y). By ploting the values for each fault condition, this technique allows the detection of insulation faults and correctly identifies the affected phase by clustering the resulting values. Finally, the proposed methodology presented satisfactory results in winding insulation diagnosis.


Vestnik MEI ◽  
2021 ◽  
pp. 69-74
Author(s):  
Muhammad Deeb ◽  
◽  
Gassan Ibragim ◽  
Talal Assaf ◽  
◽  
...  

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.


Sign in / Sign up

Export Citation Format

Share Document