Pipeline transportation is an efficient, convenient and environment-friendly transportation mode, especially in the transportation of gas and liquid. It has become one of the five transportation means parallel to railway, highway, aviation and water transportation. However, due to inevitable aging, corrosion and man-made damage, pipeline leakage occurs frequently, resulting in serious economic losses and environmental pollution. Therefore, the real-time automatic detection of pipeline leakage has become an important research topic in the world. There are many methods for pipeline leakage detection. Generally speaking, they can be divided into three categories: information-based method, model-based method and knowledge-based method. Among them, knowledge-based methods have attracted widespread attention from the industry in recent years, mainly focusing on the application of neural networks and expert systems, but these methods have some shortcomings in general. Due to the interference of pressure noise in the pipe, the collected pressure data are inaccurate. The traditional leak detection algorithm is based on the negative pressure wave formed by the pressure in the pipe. With the development and application of computer technology, signal processing, pattern recognition, artificial intelligence and other disciplines, software-based pipeline leak detection technology has become one of the most popular methods because of its advantages of sensitivity, low cost, simplicity and easy operation.
Research on Leakage Detection Technology of Long-distance Natural Gas Pipeline Based on Cost Optimization
ECITech 2022 - The 2022 International Conference on Electrical, Control and Information Technology ; 2022 ; Kunming, China
ECITech 2022 ; 4
2022-01-01
4 pages
Conference paper
Electronic Resource
English
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