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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Reuter, Matthias Bohlmann, Sabine |
| Copyright Year | 2012 |
| Description | Author affiliation: Department of Modeling and Simulation, TU-Clausthal/CUTEC Institute GmbH, Clausthal-Zellerfeld, Germany (Reuter, Matthias; Bohlmann, Sabine) |
| Abstract | In this paper we present a tool, supervising a multi-cut aggregate working in the German factory for pipeline production Salzgitter Mannesmann Line Pipe GmbH by CI-based methods. To achieve this aim we use special pre-processing strategy of the DLS-Spectra and topological closed SOMs used as “unsharp classifiers in a defined range” by using the principle of “Computing with Activities (CWA)”. We will show that this strategy leads to an early detection of machinery faults, creeping trends of wear effects and sudden uprising of so far unknown sensor states. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 830682 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467344975 |
| ISSN | 21544824 |
| e-ISBN | 9781889334479 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-06-24 |
| Publisher Place | Mexico |
| Access Restriction | Subscribed |
| Rights Holder | TSI Press |
| Subject Keyword | Aggregates Production Market research Neural networks Protocols Neurons Steel CI - Based Monitoring Supervising MultiCut Aggregates CWA Closed SOMs Early Detection of Machinery Faults by Neural Nets DLS-Spectra |
| Content Type | Text |
| Resource Type | Article |
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