NDLI: Soft computing applications in equipment maintenance and service

Content Provider	IEEE Xplore Digital Library
Author	Bonissone, P.P. Goebel, K.
Copyright Year	2001
Description	Author affiliation: GE Corp. Res. & Dev., Niskayuna, NY, USA (Bonissone, P.P.)
Abstract	We present methods and tools from the soft computing domain, which are used within the diagnostics and prognostics framework to accommodate imprecision of real systems. Soft computing (SC) is an association of computing methodologies that includes as its principal members fuzzy, neural, evolutionary and probabilistic computing. These methodologies enable us to deal with imprecise, uncertain data and incomplete domain knowledge typically encountered in real-world applications. We outline the advantages and disadvantages of these methodologies and show how they can be combined to create synergistic hybrid SC systems. We conclude with a description of three successful SC case study applications to equipment diagnostics: 1) prediction of paper web breakage in a paper mill using neural nets and induction trees; 2) a method for automated tuning of a raw mix proportioning controller in cement plants; and 3) adaptive classification for gas turbine anomalies.
Sponsorship	Int. Fuzzy Syst. Assoc.
Starting Page	2752
Ending Page	2757
File Size	548164
Page Count	6
File Format	PDF
ISBN	0780370783
DOI	10.1109/NAFIPS.2001.943660
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-25
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer applications Contracts Condition monitoring Artificial intelligence Fuzzy logic Space technology Research and development Paper mills Neural networks Automatic control
Content Type	Text
Resource Type	Article

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