A method and system for leak diagnosis of flexible pipes

By synchronously acquiring pressure and displacement information in flexible pipelines, constructing joint feature vectors, and using an isolated forest model for real-time leak detection, the problems of slow response and high false positives in traditional methods are solved, enabling rapid leak identification and safe response of flexible pipelines under large displacement conditions.

CN122129654APending Publication Date: 2026-06-02TIANJIN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TIANJIN UNIV
Filing Date
2026-01-22
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

In urban gas, industrial media transportation, fire water supply and electromechanical pipelines of seismic isolation buildings, traditional pipeline leakage monitoring methods have long response cycles and low positioning accuracy, making it impossible to detect hidden leaks in a timely manner. Furthermore, diagnostic methods based on long sequence prediction are difficult to achieve real-time judgment at edge terminals, and cannot meet the safety requirements under large displacement conditions.

Method used

By synchronously acquiring pressure information from pipeline pressure measurement points and displacement information from the hinge area, a joint pressure-displacement feature vector is constructed. Real-time anomaly detection is performed using an isolated forest model, and combined with a failure probability model and reinforcement learning strategy, rapid leak determination and safety policy triggering are achieved.

Benefits of technology

It enables rapid identification and safe response to leaks in flexible pipelines under large displacement conditions, reduces misjudgments and delays, improves the timeliness and accuracy of leak detection, and shortens the accident handling time.

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Abstract

This invention discloses a leakage diagnosis method and system for flexible pipelines, relating to the field of pipeline engineering technology. The method simultaneously acquires pressure information from at least one pressure measurement point and displacement information from at least one hinge area on the pipeline, and splices them in real time to form a pressure-displacement joint feature vector at the same moment. The joint feature vector is then input into an isolated forest model to calculate the anomaly score at that moment. When the anomaly score meets preset anomaly conditions, a leakage risk is determined, and a corresponding safety strategy is triggered. The isolated forest model uses historical joint feature vectors under normal operating conditions as a baseline and completes the determination based on the current single-frame joint feature vector. This method eliminates the need for prediction and manual thresholding, enabling rapid and accurate leakage diagnosis.
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