DocumentCode :
3379665
Title :
Magnetic flowmeter neural-wavelet diagnostics system
Author :
Gao, R. ; Eryurek, E. ; Tsoukalas, L.H.
Author_Institution :
Purdue Univ., West Lafayette, IN, USA
fYear :
1999
fDate :
1999
Firstpage :
149
Lastpage :
154
Abstract :
Magnetic flow meters (magmeters) are instruments for measuring the velocity of flow in many industrial fields. The signal that comes from a magmeter is noisy and conventional techniques are often not effective enough in dealing with noisy situations. Neural networks have proven capabilities for data handling in noisy circumstances. A novel approach based on wavelet-neural networks is presented. The stability, accuracy and response time characteristics of the presented neural-wavelet approach have been tested and the results are found to be highly promising
Keywords :
flowmeters; neural nets; noise; signal processing; velocity measurement; wavelet transforms; data handling; flow velocity measurement; industrial fields; magmeters; magnetic flow meters; magnetic flowmeter neural-wavelet diagnostics system; neural network; neural-wavelet approach; noisy situations; response time; wavelet-neural networks; Data handling; Delay; Fluid flow measurement; Instruments; Magnetic field measurement; Magnetic noise; Neural networks; Stability; Testing; Velocity measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Intelligence and Systems, 1999. Proceedings. 1999 International Conference on
Conference_Location :
Bethesda, MD
Print_ISBN :
0-7695-0446-9
Type :
conf
DOI :
10.1109/ICIIS.1999.810246
Filename :
810246
Link To Document :
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