Gas pipeline leak location experiment device and method based on rbf neural network
A technology of gas pipeline and neural network, which can be used in measurement devices, pipeline systems, gas/liquid distribution and storage, etc., and can solve the problems of gas pipeline leakage location and gas pipeline leakage
Inactive Publication Date: 2018-04-10
NORTH CHINA ELECTRIC POWER UNIV (BAODING) +1
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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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[0025] The embodiments will be described in detail below in conjunction with the accompanying drawings.
[0026] like figure 1 As shown, the gas pipeline leak location experimental device based on RBF neural network of the present invention comprises: a compressor connected in sequence, a filter, a first ball valve, a high-pressure buffer tank, a gas-liquid separator, a second ball valve, a first substrate pipeline, The simulated leakage unit, the second base pipeline, the third ball valve, and the recovery tank; the base pipeline and the simulated leakage unit are connected by flanges, and the simulated leakage unit is sealed in the protective cover. The simulated leakage unit is a straight pipeline, one end of which is There is a leak point, and five equal-precision acoustic emission sensors are installed at equal intervals on the other side of the leak point. A temperature sensor and a pressure sensor are installed at the end of the simulated leak unit. The simulated leak u...
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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...
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IPC IPC(8): F17D5/06F17D3/01F17D1/02G01M3/24
CPCF17D1/02F17D3/01F17D5/06G01M3/243
Inventor 韩晓娟赵泽昆蔡丽娟刘大贺
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)