A survey of testing and monitoring methods for stator insulation systems in induction machines

2008 ◽  
Author(s):  
S. Grubic ◽  
J. M. Aller ◽  
B. Lu ◽  
T. G. Habetler
Keyword(s):  
Induction Machines ◽  
Monitoring Methods ◽  
Insulation Systems

scholarly journals Fusion of Vibration and Current Signatures for the Fault Diagnosis of Induction Machines

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Meng-Kun Liu ◽  
Minh-Quang Tran ◽  
Peng-Yi Weng
Keyword(s):  
Wavelet Packet ◽  
Induction Machines ◽  
Fault Detection And Isolation ◽  
Support Vector ◽  
Monitoring Methods ◽  
Time Frequency ◽  
Isolation Techniques ◽  
Level Sensor ◽  
Common Signal ◽  
Air Compressors

Induction machines are widely used in the industry as one of the major actuators, such as water pumps, air compressors, and fans. It is necessary to monitor and diagnose these induction motors to prevent any sudden shut downs caused by premature failures. Numerous fault detection and isolation techniques for the diagnosis of induction machines have been proposed over the past few decades. Among these techniques, motor current signature analysis (MCSA) and vibration analysis are two of the most common signal-based condition monitoring methods. They are often adopted independently, but each method has its strengths and weaknesses. This research proposed a systemic method to integrate the information received from the vibration and current measurements. We applied the wavelet packet decomposition to extract the time-frequency features of the vibration and current measurements and used the support vector machines as classifiers for the initial decision-making. The significant features were identified, and the performances of several classifiers were compared. As a result, the decision-level sensor fusion based on the Sugeno fuzzy integral was proposed to integrate the vibration and current information to improve the accuracy of the diagnosis.

INSULATION SYSTEMS ENGINEERING

1984 ◽  
Vol 45 (C1) ◽  
pp. C1-615-C1-617
Author(s):  
H. Becker ◽  
P. G. Marston
Keyword(s):  
Systems Engineering ◽  
Insulation Systems

The influence of ultrasound signal parameters on sonoluminescence light intensity

2013 ◽  
Vol 62 (4) ◽  
pp. 605-612
Author(s):  
Marek Szmechta ◽  
Tomasz Boczar ◽  
Dariusz Zmarzły
Keyword(s):  
Acoustic Emission ◽  
Acoustic Waves ◽  
Power Transformer ◽  
Electrical Power ◽  
Partial Discharges ◽  
Research Project ◽  
Insulation Systems ◽  
Secondary Phenomenon ◽  
New Research ◽  
The Relationship

Abstract Topics of this article concern the study of the fundamental nature of the sonoluminescence phenomenon occurring in liquids. At the Institute of Electrical Power Engineering at Opole University of Technology the interest in that phenomenon known as secondary phenomenon of cavitation caused by ultrasound became the genesis of a research project concerning acoustic cavitation in mineral insulation oils in which a number of additional experiments performed in the laboratory aimed to determine the influence of a number of acoustic parameters on the process of the studied phenomenona. The main purpose of scientific research subject undertaken was to determine the relationship between the generation of partial discharges in high-voltage power transformer insulation systems, the issue of gas bubbles in transformer oils and the generated acoustic emission signals. It should be noted that currently in the standard approach, the phenomenon of generation of acoustic waves accompanying the occurrence of partial discharges is generally treated as a secondary phenomenon, but it can also be a source of many other related phenomena. Based on our review of the literature data on those referred subjects taken, it must be noted, that this problem has not been clearly resolved, and the description of the relationship between these phenomena is still an open question. This study doesn’t prove all in line with the objective of the study, but can be an inspiration for new research project in the future in this topic. Solution of this problem could be a step forward in the diagnostics of insulation systems for electrical power devices based on non-invasive acoustic emission method.

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