Non-invasive condition monitoring of induction motors
Condition monitoring of induction motor has been widely researched over recent years due to its ability to monitor operating characteristics and the health status of induction motor. Various methods have been used to monitor induction motors such as thermal monitoring and vibration analysis. This re...
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Nanyang Technological University
2020
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sg-ntu-dr.10356-1393892023-07-07T18:35:16Z Non-invasive condition monitoring of induction motors Rayyan Fairuz See Kye Yak School of Electrical and Electronic Engineering ekysee@ntu.edu.sg Engineering::Electrical and electronic engineering Condition monitoring of induction motor has been widely researched over recent years due to its ability to monitor operating characteristics and the health status of induction motor. Various methods have been used to monitor induction motors such as thermal monitoring and vibration analysis. This report introduces an alternative method which is to use an inductive coupling method to extract in-circuit impedance of an induction motor. This method allows for an online measurement of the system under test (SUT) preventing any unnecessary shutdowns. These unnecessary shutdowns may incur a loss of revenue for relevant industries that depends heavily on induction motor operations. Two sets of experiments were conducted, the first experiment was to examine the accuracy of the proposed method by simulating various SUT using a resistor, inductor, and capacitor (RLC) network. The next experiment was to detect incipient stator faults such as turn to turn faults in an induction motor. This proposed method measures the impedance of the stator winding of an induction motor to identify abnormalities. In addition, this method allows for an accurate in-circuit impedance measurement without the influence of load change, speed variation as well as bearing and rotor faults. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-19T06:14:02Z 2020-05-19T06:14:02Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/139389 en A2162-191 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Rayyan Fairuz Non-invasive condition monitoring of induction motors |
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Condition monitoring of induction motor has been widely researched over recent years due to its ability to monitor operating characteristics and the health status of induction motor. Various methods have been used to monitor induction motors such as thermal monitoring and vibration analysis. This report introduces an alternative method which is to use an inductive coupling method to extract in-circuit impedance of an induction motor. This method allows for an online measurement of the system under test (SUT) preventing any unnecessary shutdowns. These unnecessary shutdowns may incur a loss of revenue for relevant industries that depends heavily on induction motor operations. Two sets of experiments were conducted, the first experiment was to examine the accuracy of the proposed method by simulating various SUT using a resistor, inductor, and capacitor (RLC) network. The next experiment was to detect incipient stator faults such as turn to turn faults in an induction motor. This proposed method measures the impedance of the stator winding of an induction motor to identify abnormalities. In addition, this method allows for an accurate in-circuit impedance measurement without the influence of load change, speed variation as well as bearing and rotor faults. |
author2 |
See Kye Yak |
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See Kye Yak Rayyan Fairuz |
format |
Final Year Project |
author |
Rayyan Fairuz |
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Rayyan Fairuz |
title |
Non-invasive condition monitoring of induction motors |
title_short |
Non-invasive condition monitoring of induction motors |
title_full |
Non-invasive condition monitoring of induction motors |
title_fullStr |
Non-invasive condition monitoring of induction motors |
title_full_unstemmed |
Non-invasive condition monitoring of induction motors |
title_sort |
non-invasive condition monitoring of induction motors |
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Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/139389 |
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1772825725770924032 |