A Bridge Stress Detection System

Abstract

The invention provides a bridge stress detection system, which comprises a stress detection server, a bridge detection management terminal and a sensor network, and is characterized in that the sensornetwork comprises a plurality of effective grids, and each effective grid is provided with a stress sensor to form a sensor matrix corresponding to the effective grid; the stress detection server comprises a management module and a stress estimation module, the stress estimation module comprises a plurality of estimation models, a bijection relation exists between each estimation model and a corresponding effective grid, and the estimation models only acquire data acquired by stress sensors in a range corresponding to the effective grids and output estimation results; and the bridge detectionmanagement terminal is used for interacting with the management module, issuing a management instruction to the management module and receiving push information sent by the management module. According to the invention, the detection efficiency is improved.

Description

technical field [0001] The invention relates to the field of bridge detection, in particular to a bridge stress detection system. Background technique [0002] Routine periodic inspections of bridge inspections include bridge deck system inspections, superstructure inspections and substructure inspections. The usual method is manual inspection. However, the labor cost of manual inspection is too high, and the detection results are limited by the individual level of manual labor, making it difficult to obtain stable detection results. However, it is impossible to detect bridges manually in real time, and it is impossible to predict the risk of bridge cracks. Increasing the inspection frequency may be able to detect bridge crack risks in time, but the detection cost will further increase. Contents of the invention [0003] In order to solve the above technical problems, the present invention proposes a bridge stress detection system. The present invention is specifically ...

AI Technical Summary

Problems solved by technology

However, the labor cost of manual inspection is too high, and the detection results are limited by the individual level of manual labor, making it difficult to obtain stable detection results

However, it is impossible to detect bridges manually in real time, and it is impossible to predict the risk of bridge cracks. Increasing the frequency of inspections may be able to detect bridge crack risks in time, but the detection cost will further increase

Images