Rb Neural Networks in the Em Measurements of Flow through Partially Filled Pipes
نویسندگان
چکیده
A novel way of measuring a portion of the pipes crosssection Þlled with liquid (PPCSFWL) and ßow-rate of liquid through partially Þlled pipes, based on electromagnetic method, is proposed. The technique developed is valid for laminar ßow and cylindric pipes. The measuring method, based on nonlinear relationships between the PPCSFWL and the measured signals, is developed and utilizes an optimally designed radial basis neural network to model these nonlinear relationships.
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