Pipeline monitoring early warning system based on distributed coaxial-cable electric grid strain sensor

Abstract

The present invention discloses a pipeline monitoring early warning system based on a distributed coaxial-cable electric grid strain sensor, and relates to the technical field of stress and strain monitoring and pipeline deformation monitoring systems. The system comprises a distributed coaxial-cable electric grid strain sensor, a distributed interrogator, a monitoring system substation, a cloud server and a remote monitoring center workstation. The distributed interrogator is in data connection with the distributed coaxial-cable electric grid strain sensor, the monitoring system substation isin data connection with the distributed interrogator, the monitoring system substation is configured to transmit data to the cloud server through a GPRS transmission module, and the remote monitoringcenter workstation is in data connection with the cloud server through an Internet. The pipeline monitoring early warning system achieves wide-range, full-coverage and low-cost real-time pipeline monitoring early warning in its true sense so as to avoid generation of large-scale damaging and secondary disaster caused by geological disaster and improve the practicability.

Description

Technical field: [0001] The invention relates to a pipeline monitoring and early warning system based on a distributed coaxial cable grid strain sensor, and relates to the technical fields of stress and strain monitoring and pipeline deformation monitoring systems. Background technique: [0002] Long-distance pipelines have a long operating distance and inevitably need to pass through areas with dense distribution of geological hazards. The problems faced by geological disasters such as pipeline landslides are very serious. Especially for long-distance pipelines laid in mountainous areas, the problem of pipeline landslide disasters has emerged rapidly and is becoming more and more serious. Geological disasters have become one of the main risk sources for safe operation of pipelines. [0003] Geological disasters refer to geological effects (phenomena) formed under the action of natural or human factors that cause damage and loss to human life, property and the environment. ...

AI Technical Summary

Problems solved by technology

Domestic and foreign technologies mostly use traditional resistance strain gauges, vibrating wire strain gauges, fiber Bragg grating strain gauges, etc. Traditional strain gauges have a small range and a short gauge length, and the range is generally 0.3% or 3000µε, which cannot meet the monitoring needs of large-strain pipelines in special areas; The gauge length is generally ≤200mm, which is "point" strain measurement or "local" strain measurement, which can only monitor a little strain or a small local strain within the gauge length, and cannot reflect the overall strain of the pipeline; there are BOTDR distributed optical fiber pipeline strain monitoring at home and abroad It is reported in papers and materials, but there are few practical engineering applications, and the construction survival rate and practicability need to be verified.

[0006] To sum up, the main indicators and shortcomings of the current geological disaster pipeline monitoring technology at home and abroad are as follows: 1) The strain sensor for pipeline deformation monitoring: the range is small, generally the maximum is 0.3% (3000µε), and the traditional strain gauge range is low, which cannot meet the requirements. Large strain monitoring needs for pipelines passing through geological disaster areas; 2) Short gauge length ≤ 200mm, for point strain measurement or local strain measurement, can only monitor a little strain or a small local strain within the gauge distance, and cannot reflect the overall situation of the pipeline; 3) 1. The anti-corrosion layer needs to be destroyed during installation, and the survival rate of engineering construction is low. Most monitoring systems are damaged due to insufficient range of strain sensors, resulting in system failure and failure to operate normally.

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