Signal trend identification with fuzzy methods.
Conference
·
OSTI ID:11931
A fuzzy-logic-based methodology for on-line signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of on-line signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one.
- Research Organization:
- Argonne National Lab., IL (US)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- W-31109-ENG-38
- OSTI ID:
- 11931
- Report Number(s):
- ANL/RE/CP-99798; TRN: US0102294
- Resource Relation:
- Conference: IEEE International Conference on Information, Intelligence and Systems, Washington, DC (US), 11/01/1999--11/03/1999; Other Information: PBD: 19 Aug 1999
- Country of Publication:
- United States
- Language:
- English
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