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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Martin, J.A. Santos, H.M. Farias, G. Duro, N. Sanchez, J. Dormido, R. Dormido-Canto, S. Vega, J. |
| Copyright Year | 2007 |
| Description | Author affiliation: UCM, Madrid (Martin, J.A.; Santos, H.M.) |
| Abstract | Measurements in long pulse devices like ITER require the use of intelligent techniques to detect interesting events and anomalous behaviors within a continuous data flow. This detection will trigger the execution of some experimental procedures such as: increasing sampling rates, starting data sampling in additional channels or notifying the event to other diagnostics. In a first approach, an interesting event can be any non-average behavior in the expected temporal evolution of the waveforms. Therefore, a model of the signals is needed. In this work, a model that represents each type of plasma signal is obtained by means of fuzzy inference systems (FIS) which are generated by applying adaptive neuro-fuzzy techniques. The purpose of this neuro-fuzzy modeling is to identify patterns of these groups of data to produce a concise representation of a signal. Previously the signals have been preprocessed and a new dynamic clustering strategy based on a partitioning method has been applied to obtain the clusters. Off-line analyses have been applied to bolometric signals of the fusion device TJ-II Stellator with encouraging results. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 596056 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424408290 |
| DOI | 10.1109/WISP.2007.4447626 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-10-03 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pulse measurements Event detection Dynamic clustering fuzzy models Plasma devices Fluid flow measurement Plasma diagnostics Signal processing Plasma measurements Sampling methods Signal analysis neuro-fuzzy identification Plasma waves fusion plasma signals |
| Content Type | Text |
| Resource Type | Article |
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