NDLI: Knowledge based technique to enhance the performance of neural network based motor fault detectors

Content Provider	IEEE Xplore Digital Library
Author	Bo Li Goddu, G. Mo-Yuen Chow
Copyright Year	1997
Description	Author affiliation: Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA (Bo Li)
Abstract	The monitoring and fault detection of motors is a very important and difficult topic. Neural networks can often be trained to recognize motor faults by examining the performance of certain motor measurements. Unfortunately, several weaknesses exist for neural networks when used in this application. Examples of these shortcomings are that they can take a considerable time to train, often have less than desirable accuracy and generally are very dependent on the choice of training data. Although neural networks can recognize the nonlinear relationships that exist between motor measurements and motor faults, all aspects of the neural network fault detector performance can be improved if appropriate heuristics can be used to preprocess the input-output training relationship. This paper presents a novel approach of applying knowledge based modeling techniques to preprocess the training data and significantly improve the overall performance of the neural network based motor fault detector.
Starting Page	1113
Ending Page	1118
File Size	665962
Page Count	6
File Format	PDF
ISBN	0780339320
DOI	10.1109/IECON.1997.668441
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-11-14
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Fault detection Electrical fault detection Artificial neural networks Training data Mathematical model Nonlinear dynamical systems Artificial intelligence Machine intelligence Feedforward neural networks
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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