Coal gas measuring method by utilization of BP neural network

Abstract

The invention relates to a coal gas flow measuring method by utilizing BP NN (technology). A three-layer BP NN is selected as a prototype; a three-layer BP NN model is built to predict the coal gas flow; the method mainly includes the following three steps: 1) collecting sample data: selecting settlement data (including temperature, pressure, pressure difference and flow) with accurate history as a sample; 2) training a BP network: inputting the sample data in the step 1) into the three-layer BP network, training the network, comparing a coal gas flow value inputted by the network with a corresponding sample value until the mean square error for training the network reaches the requirements and confirming the important parameters of weight and the threshold of the network; 3) measuring the coal gas flow: inputting the collected coal gas temperature, pressure and pressure difference into the BP network trained in the step 2) during production prediction, thus being capable of predicting the coal gas flow value. The coal gas flow measuring method applies the BP NN technology into measuring the goal gas flow, thus solving the nondeterminacy problem of flow complementing.

Description

technical field [0001] The invention relates to gas flow metering technology, in particular to a gas metering method based on BP (Back Propagation) neural network ANN (Artificial Neural Networks). Background technique [0002] With the development of market economy and the advancement of science and technology, the requirements for measurement accuracy are getting higher and higher. No matter what kind of flowmeter is used and what kind of fluid is measured, compensation measures are often required to improve the accuracy of measurement. [0003] The so-called flow compensation is the correction of the systematic error of the flowmeter reading. Most of the system errors of flow detection devices are caused by changes in fluid properties and conditions (such as temperature, pressure, composition, and flow range, etc.), and the scale relationship between the output signal of the flowmeter and the measured flow can only be based on a specific process condition. To determine, ...

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Problems solved by technology

[0006] The purpose of the present invention is to overcome the above-mentioned shortcoming, provide a kind of gas flow metering method using neural network (technology), can solve the problem of compensation uncertainty in the gas flow metering process, improve the accuracy of gas flow metering

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