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A Method for Early Prediction of Bridge Stress

A stress and bridge technology, applied in the field of bridge stress prediction in advance, can solve the problems of increasing inspection frequency, difficulty in obtaining detection results, and inability to detect bridges

Active Publication Date: 2020-11-13
杭州鲁尔物联科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

Method used

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  • A Method for Early Prediction of Bridge Stress
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Embodiment Construction

[0014] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0015] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate ...

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Abstract

The invention provides a bridge stress early estimation method, which comprises the following steps of: determining a plurality of effective grids on the lower surface of a bridge, and arranging a stress sensor on each effective grid to form a sensor matrix corresponding to the effective grid; for any effective grid, executing the following steps: acquiring stress data acquired by a sensor matrixcorresponding to the effective grid, wherein each piece of stress data comprises the position of a sensor for collecting the stress data; transmitting the stress data to an estimation model corresponding to the effective grid; and obtaining a stress estimation result output by the estimation model, wherein the stress estimation result is used for prompting the estimated stress at the position of the sensor of the stress data. According to the invention, the labor cost is remarkably saved.

Description

technical field [0001] The invention relates to the field of bridge detection, in particular to a bridge stress prediction method in advance. 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 prediction method in advance. The present in...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20G06N3/02G06N3/08G01L5/00G06F119/14
CPCG01L5/00G06N3/02G06N3/08G06F30/20G06F2119/14
Inventor 宋杰张亮董梅胡辉
Owner 杭州鲁尔物联科技有限公司
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