scholarly journals Predictive Maintenance Applied to Three phase Induction Motors

2019 ◽  
Vol 4 (2) ◽  
pp. 71-88
Author(s):  
Fatma Zohra DEKHANDJI ◽  
Salah Eddine HALLEDJ ◽  
Oussama ZABOUB
Keyword(s):  
Supply Voltage ◽  
Induction Machines ◽  
Operating Conditions ◽  
Predictive Maintenance ◽  
Ground Fault ◽  
Simulink Simulation ◽  
Three Phase ◽  
Process Failure ◽  
Safety And Reliability ◽  
Voltage Phase

Induction machines are widely used in industry. The operating conditions may sometimes lead the machine into different fault situations. The machine should be shut down when a fault is experienced to avoid complete process failure and for the safety of the workers. The predictive maintenance consists of scheduling maintenance activities only when a functional failure is detected. The advantages of predictive maintenance are accepted in many industries because of its efficiency in fault detection during early stages and thus reducing unscheduled down time. It increases productivity, improves quality and provides the feeling of safety and reliability to staff. The main types of external faults experienced by these motors are over loading; single phasing, unbalanced supply voltage, phase reversal, ground fault, under voltage and over voltage. MATLAB/SIMULINK simulation is used in this work for the detection and analysis of the faults on induction motor.

Electrical fault diagnosis in induction motors using local extremes analysis

2016 ◽  
Vol 22 (3) ◽  
pp. 321-332 ◽  
Author(s):  
Paulo Cezar Monteiro Lamim Filho ◽  
Fabiano Bianchini Batista ◽  
Robson Pederiva ◽  
Vinicius Augusto Diniz Silva
Keyword(s):  
Induction Motors ◽  
Short Circuit ◽  
Induction Machines ◽  
Time Sequence ◽  
Content Type ◽  
Three Phase ◽  
Unbalanced Voltage ◽  
Voltage Phase ◽  
Detection And Diagnosis ◽  
Original Time

Purpose – The purpose of this paper is to introduce an algorithm based only on local extreme analysis of a time sequence to further the detection and diagnosis of inter-turn short circuits and unbalanced voltage supply using vibration signals. Design/methodology/approach – The upper and lower extreme envelopes from a modulated and oscillatory time sequence present a particular characteristic being of, theoretically, symmetrical versions with regard to amplitude reflection around the time axis. Thus, one may say that they carry the same characteristics in terms of waveforms and, consequently, frequency content. These envelopes can easily be built by an interpolation process of the local extremes, maximums and minimums, from the original time sequence. Similar to modulator signals, they contain more detailed and useful information about the required electrical fault frequencies. Findings – Results show the efficiency of the proposed algorithm and its relevance to detecting and diagnosing faults in induction motors with the advantage of being a technique that is easy to implement in any computational code. Practical implications – A laboratory investigation carried out through an experimental setup for the study of faults, mainly related to the stator winding inter-turn short circuit and voltage phase unbalance, is presented. Originality/value – The main contribution of the work is the presentation of an alternative tool to demodulate signals which may be used in real applications like the detection of faults in three-phase induction machines.

Identificación de polaridad de los devanados en un motor trifásico de 6 terminales

2019 ◽  
pp. 13-19
Author(s):  
José Luis Viramontes-Reyna ◽  
Josafat Moreno-Silva ◽  
José Guadalupe Montelongo-Sierra ◽  
Erasmo Velazquez-Leyva
Keyword(s):  
Low Cost ◽  
Voltage Reference ◽  
Three Phase ◽  
Voltage Phase ◽  
The Law ◽  
And Control

This document presents the results obtained from the application of the law of Lens to correctly identify the polarity of the windings in a three-phase motor with 6 exposed terminals, when the corresponding labeling is not in any situation; Prior to identifying the polarity, it should be considered to have the pairs of the three windings located. For the polarity, it is proposed to feed with a voltage of 12 Vrms to one of the windings, which are identified randomly as W1 and W2, where W1 is connected to the voltage phase of 12 Vrms of the signal and W2 to the voltage reference to 0V; by means of voltage induction and considering the law of Lens, the remaining 4 terminals can be identified and labeled as V1, V2, U1 and U2. For this process a microcontroller and control elements with low cost are used.

scholarly journals Comprehensive Parameters Identification and Dynamic Model Validation of Interior-Mount Line-Start Permanent Magnet Synchronous Motors

Machines ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Luqman S. Maraaba ◽  
Zakariya M. Al-Hamouz ◽  
Abdulaziz S. Milhem ◽  
Ssennoga Twaha
Keyword(s):  
Mathematical Model ◽  
Permanent Magnet ◽  
High Efficiency ◽  
Experimental Tests ◽  
Induction Machines ◽  
Test Methods ◽  
Operating Conditions ◽  
Test Method ◽  
Permanent Magnet Synchronous Motors ◽  
Synchronous Motors

The application of line-start permanent magnet synchronous motors (LSPMSMs) is rapidly spreading due to their advantages of high efficiency, high operational power factor, being self-starting, rendering them as highly needed in many applications in recent years. Although there have been standard methods for the identification of parameters of synchronous and induction machines, most of them do not apply to LSPMSMs. This paper presents a study and analysis of different parameter identification methods for interior mount LSPMSM. Experimental tests have been performed in the laboratory on a 1-hp interior mount LSPMSM. The measurements have been validated by investigating the performance of the machine under different operating conditions using a developed qd0 mathematical model and an experimental setup. The dynamic and steady-state performance analyses have been performed using the determined parameters. It is found that the experimental results are close to the mathematical model results, confirming the accuracy of the studied test methods. Therefore, the output of this study will help in selecting the proper test method for LSPMSM.

scholarly journals Mutual Information and Meta-Heuristic Classifiers Applied to Bearing Fault Diagnosis in Three-Phase Induction Motors

2020 ◽  
Vol 11 (1) ◽  
pp. 314
Author(s):  
Gustavo Henrique Bazan ◽  
Alessandro Goedtel ◽  
Marcelo Favoretto Castoldi ◽  
Wagner Fontes Godoy ◽  
Oscar Duque-Perez ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Mutual Information ◽  
Induction Motors ◽  
Operating Conditions ◽  
Industrial Systems ◽  
Bearing Fault Diagnosis ◽  
Bee Colony ◽  
Three Phase ◽  
C4.5 Decision Tree ◽  
The Time Domain

Three-phase induction motors are extensively used in industrial processes due to their robustness, adaptability to different operating conditions, and low operation and maintenance costs. Induction motor fault diagnosis has received special attention from industry since it can reduce process losses and ensure the reliable operation of industrial systems. Therefore, this paper presents a study on the use of meta-heuristic tools in the diagnosis of bearing failures in induction motors. The extraction of the fault characteristics is performed based on mutual information measurements between the stator current signals in the time domain. Then, the Artificial Bee Colony algorithm is used to select the relevant mutual information values and optimize the pattern classifier input data. To evaluate the classification accuracy under various levels of failure severity, the performance of two different pattern classifiers was compared: The C4.5 decision tree and the multi-layer artificial perceptron neural networks. The experimental results confirm the effectiveness of the proposed approach.

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