Abnormity detection method and device for low-pressure gas pipeline and medium

By obtaining the current gas consumption and historical gas consumption of the low-pressure gas pipeline user cluster, determining the abnormal cluster and conducting gas abnormality detection, the problem of low detection efficiency in the existing technology is solved, and efficient abnormal detection and predicted cause analysis are achieved.

CN119691652APending Publication Date: 2025-03-25SHANDONG SYNTHESIS ELECTRONICS TECH
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Patent Information

Application Number
CN202411867016.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-18
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

The existing low-pressure gas pipeline abnormality detection method monitors the gas usage data of all users in real time, resulting in huge and complex data volume and low detection efficiency.

Method used

By obtaining the actual value of the current gas consumption of the user cluster and the predicted value of the historical gas consumption, the abnormal cluster is determined, and the users in the abnormal cluster are detected by gas consumption abnormality, reducing the calculation amount and improving detection efficiency.

Benefits of technology

Through the prediction and abnormal detection of user clusters, the calculation amount is significantly reduced, the abnormal detection efficiency is improved, and the prediction cause of gas abnormalities is determined through the knowledge graph, which improves the processing efficiency and the accuracy of the knowledge graph.

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Abstract

The invention discloses a low-pressure gas pipeline anomaly detection method, equipment and a medium, belongs to the technical field of gas safety, and is used for solving the technical problems that the existing low-pressure gas pipeline anomaly detection method is used for monitoring gas consumption data of all users, the monitored data volume is huge and complex, and the detection efficiency is relatively low. The method comprises the following steps: acquiring an actual value of current gas consumption of a user cluster; determining a predicted value of the current cluster gas consumption of the user cluster; when the difference value between the actual value and the predicted value exceeds a preset difference value threshold value, determining the user cluster as an abnormal cluster; acquiring user current gas consumption data of any user in the abnormal cluster; and determining whether any user is a target user with abnormal gas consumption or not based on the current gas consumption data of any user. According to the method, the anomaly detection efficiency is improved.
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