Buried gas pipeline leakage risk degree prediction system

Abstract

The invention belongs to the technical field of gas pipeline maintenance, and particularly relates to a buried gas pipeline leakage risk prediction system. The buried gas pipeline leakage risk prediction system comprises a plurality of acquisition nodes, a processor module and a cloud server, each acquisition node acquires a stress value and a PH value of a corresponding position of a buried gas pipeline and uploads the stress value and the PH value to the processor module, and the processor module uploads the corresponding stress values and the PH values to the cloud server so as to judge thedanger degree of the buried gas pipeline; and the cloud server sends a judgment result of the danger degree of the buried gas pipeline back to the processor module. According to the buried gas pipeline leakage risk prediction system, the defects of high subjectivity and high randomness of manual judgment and early warning of the leakage risk of the buried gas pipeline according to monitoring datacan be overcome, advanced protection and predictive maintenance of a leakage accident of the buried gas pipeline are facilitated, and the predictive maintenance has better economical efficiency; andmeanwhile, the labor cost for maintaining the buried gas pipeline is reduced.

Description

technical field [0001] The invention belongs to the technical field of gas pipeline maintenance, and in particular relates to a leakage risk prediction system of buried gas pipelines. Background technique [0002] The leakage of buried gas pipelines cannot be found intuitively and obviously, especially if a small amount of leakage occurs, it is even more difficult to find. When a leak occurs, a series of secondary disasters such as an explosion are likely to occur, resulting in serious personal casualties and property losses. Buried pipelines are concealed projects with 24-hour uninterrupted operation and other characteristics. Daily inspections can only ensure "surface" safety, but little is known about the internal situation, resulting in insufficient information and difficult management. Ultrasonic real-time monitoring of gas pipeline data can only be used for overhead pipelines, and cannot obtain sufficient information for buried pipelines. [0003] At present, the com...

AI Technical Summary

Problems solved by technology

Due to the use of a large amount of manpower such as experts, this method has a large workload, high labor cost, and poor economy; at the same time, it also has the problems of strong subjectivity and large randomness.

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