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Content Provider | IEEE Xplore Digital Library |
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Author | Eklund, N.H.W. Goebel, K.F. |
Copyright Year | 2006 |
Description | Author affiliation: One Res. Circle, New York (Eklund, N.H.W.; Goebel, K.F.) |
Abstract | Accurate detection of faults and prediction of equipment remaining useful life result in considerable economic benefit to industry due to avoidance of unscheduled downtime and costly secondary damage. This paper described an approach to improving the performance of fault detection schemes that operate on time series data by fusing the results of an ensemble of classifiers that operate on the raw data. A meta-feature is designed to provide an indication of the historical state of other classifiers in the system, and to aid in fusion by allowing the individual classification results to be discounted appropriately. This meta-feature is shown to provide a substantial performance increase for fusion schemes. Data from actual aircraft engine/airframe systems are used to assess the performance of the approach. |
Starting Page | 3223 |
Ending Page | 3230 |
File Size | 1037487 |
Page Count | 8 |
File Format | |
ISBN | 0780394909 |
DOI | 10.1109/IJCNN.2006.247308 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2006-07-16 |
Publisher Place | Canada |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Costs Fault detection Equipment failure Power generation economics Economic forecasting Industrial economics Aircraft propulsion Turbines Job shop scheduling Power generation |
Content Type | Text |
Resource Type | Article |
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