Gas pipeline leakage positioning experimental device and method based on RBF neural network

Abstract

The invention belongs to the technical field of gas pipeline leakage positioning and particularly relates to a gas pipeline leakage positioning experimental device and method based on an RBF neural network. The gas pipeline leakage positioning experimental method comprises the steps that a pressure sensor is installed at the tail end of a gas transmission pipeline, and five equal-precision acoustic emission sensors are installed on one side of a preset leakage point at equal intervals; leakage signals collected by five channels under different leakage pressure are subjected to feature extraction and processing, and the maximum peak value, the (3, 0) node wavelet packet energy and the power spectrum peak value corresponding to the leakage feature frequency of the leakage signal of each channel are obtained to construct feature vectors under the different leakage pressure; and after being subjected to normalization processing, the feature vectors serve as the input of the RBF combined neural network, the leakage positioning value L serves as the output of the RBF combined neural network, and an RBF combined neural network pipeline leakage positioning model is built under the different pressure, so that gas pipeline leakage point positioning and error analysis are achieved.

Description

technical field [0001] The invention belongs to the technical field of gas pipeline leakage location, in particular to an RBF neural network-based gas pipeline leakage location experiment device and method. Background technique [0002] With the increasingly serious energy crisis and environmental problems, Carbon Capture and Storage (CCS) technology is considered to be the most effective way to deal with global warming and reduce greenhouse gases. CCS technology is to separate the carbon dioxide produced by industry and energy industry, and then transport it to the seabed or underground and other places isolated from the atmosphere through carbon storage means. The use of pipelines to transport captured CO2 is currently recognized as the most economical and reliable way, but leakage problems often occur during the transportation process. Therefore, finding a suitable leak location method can locate the leak point in time and improve the safety of the carbon dioxide deliver...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem of difficult gas pipeline leakage location, the present invention proposes an experimental device and method for gas pipeline leakage location based on RBF neural network

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