DocumentCode
1555998
Title
Reliability improvement and economic benefits of online monitoring systems for large induction machines
Author
Siyambalapitiya, D.J.Tilak ; McLaren, Peter G.
Author_Institution
Sri Lanka Electricity Board, Colombo, Sri Lanka
Volume
26
Issue
6
fYear
1990
Firstpage
1018
Lastpage
1025
Abstract
Microprocessor-based monitoring systems are being developed for the regular analysis of large induction machine variables and to predict possible fault conditions, so that preventive maintenance can be organized in a cost-effective manner. A method for the evaluation of the improvement of machine reliability made by such monitoring systems is presented. An economic and financial analysis to examine the viability of a condition monitoring system for a large machine using comprehensive rotor, stator, and other parameter measurements is developed. In two case studies, the costs of design, construction, mounting, and operation of condition monitoring systems are discussed, and estimates are made at current costs. These costs are balanced against the costs avoided in cases of unexpected machine failures, lost production, and repairs. Cost estimates for repairs and downtime are made using published information from previous reliability surveys on electrical machines. Information is presented for different machine sizes, which will indicate any relevance of the machine size when evaluating monitoring systems
Keywords
asynchronous machines; computerised monitoring; economics; microcomputer applications; power engineering computing; reliability; economic benefits; fault conditions; financial analysis; induction machines; microprocessor based monitoring systems; online monitoring systems; parameter measurements; preventive maintenance; rotor; stator; Chemical industry; Condition monitoring; Coolants; Electrical fault detection; Induction machines; Industry Applications Society; Instruments; Power generation; Rotors; Stators;
fLanguage
English
Journal_Title
Industry Applications, IEEE Transactions on
Publisher
ieee
ISSN
0093-9994
Type
jour
DOI
10.1109/28.62371
Filename
62371
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