@article{Wang_Lin_Shen_2022, title={Developing and Implementing an AI-Based Leak Detection System in a Long-Distance Gas Pipeline}, volume={7}, url={https://ojs.imeti.org/index.php/AITI/article/view/8904}, DOI={10.46604/aiti.2022.8904}, abstractNote={<p>This research proposes an artificial intelligence (AI) detection model using convolutional neural networks (CNN) to automatically detect gas leaks in a long-distance pipeline. The change of gap pressure is collected when leakage occurs in the pipeline, and thereby the feature of gas leakage is extracted for building the CNN model. The gas leak patterns in the long-distance pipeline are analyzed. A pipeline detection model based on AI technology for automatically monitoring the leaks is proposed by extracting the feature of gas leakage. This model is tested by collecting gas pressure data from an existing natural gas pipeline system starting from Mailiao to Taoyuan in Taiwan. The testing result shows that the reduced model of leak detection can be used to detect the leaks from the upstream and downstream pipelines, and the AI-based pipeline leak detection system can obtain a satisfactory result.</p>}, number={3}, journal={Advances in Technology Innovation}, author={Wang, Te-Kwei and Lin, Yu-Hsun and Shen, Jian-Yuan}, year={2022}, month={Jun.}, pages={169–180} }