Natural gas pipeline leakage detection method based on LSTM recurrent neural network

Abstract

The invention provides a natural gas pipeline leakage detection method based on an LSTM recurrent neural network. The natural gas pipeline leakage detection method comprises the following steps: step1, collecting pipeline leakage audio data; step 2, performing feature extraction on the audio data by adopting an improved Mel-frequency cepstral coefficient MFCC method; step 3, constructing a natural gas pipeline leakage detection model based on a long-term and short-term memory LSTM recurrent neural network; and step 4, carrying out training and parameter optimization on the pipeline micro-leakage detection model, and verifying the robustness of the model. Compared with the prior art, the natural gas pipeline leakage detection method provided by the invention has the technical effects or advantages: in a parameter optimization process of the pipeline leakage detection model, according to the natural gas pipeline leakage detection method based on the LSTM recurrent neural network, the pipeline state can be detected, the accuracy of pipeline leakage detection is improved, sufficient reaction time is provided, the possibility of safety accidents is reduced, and the natural gas pipelineleakage detection method has certain theoretical research value and wide application prospects.

Description

technical field [0001] The invention relates to the field of pipeline tightness detection and detection, in particular to a natural gas pipeline leakage detection method based on an LSTM cycle neural network. Background technique [0002] Natural gas is a safe, clean and efficient green energy, so natural gas and related industries are the best choice for environmental protection and sustainable economic development. Natural gas energy adopts long-distance pipeline transportation, which connects various regions through pipelines to form a complex and large-scale pipeline transportation network system. Pipeline transportation has the characteristics of low cost, high safety, and resource conservation, but it does not mean that it is risk-free. Therefore, the safety of pipeline transportation is an important assessment index for ensuring gas pipeline facilities. [0003] Natural gas pipelines carry heavy transportation tasks, but there are the following problems: in the pipe...

AI Technical Summary

Problems solved by technology

[0003] Natural gas pipelines carry heavy transportation tasks, but there are the following problems: in the pipeline construction, the defects of pipeline quality, welding process and construction damage; as the service life of the pipeline grows longer, the pipeline itself is affected by external natural factors and human factors , there will be corrosion

Most of the existing research is to use the negative pressure wave method to realize the leak detection through the time difference between the change of the pressure signal and the negative pressure wave generated by the leak point. This method is aimed at the low recognition rate of small leak detection, and the effect is not as expected. Effect

In the face of problems such as the complexity and stability of the pipeline transportation network system, it is impossible to efficiently and accurately detect the leakage of the pipeline in real time, and further in-depth research is needed

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