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