Engineering structure damage remote monitoring and early warning method and system

Abstract

The invention discloses an engineering structure damage remote monitoring and early warning method and system, and the method comprises the steps: carrying out the vulnerability analysis of an engineering structure according to the existing engineering investigation data at the early stage of the operation of the engineering structure, and arranging a vibration sensor at a vulnerable part; duringoperation, collecting a power response signal; performing frequency domain integration and wavelet packet energy spectrum analysis on the dynamic response signal, establishing a quantitative evaluation damage criterion, and judging a structural damage position and a damage degree; in the later maintenance period, establishing a quantitative visual three-dimensional structure damage image by calling the structure damage data stored in the operation period; and meanwhile, adopting a multi-layer neural network algorithm to analyze the structural damage data, predicting the remaining service lifeof the engineering structure, and when the remaining service life is smaller than a set threshold value, triggering an alarm immediately. Therefore, accurate dynamic real-time monitoring of the damagedegree of the structure and instant early warning before failure of the engineering structure are realized, and theoretical and technical guarantee is provided for operation and maintenance of the engineering structure.

Description

technical field [0001] The invention relates to the field of engineering structure damage, in particular to a remote monitoring and early warning method and system for engineering structure damage. Background technique [0002] China is one of the countries with the most severe geological disasters due to its many types, wide distribution, and great harm. Sudden geological disasters such as collapses, landslides, and debris flows occur frequently, especially in the operation and maintenance of engineering structures in the southwest mountainous area, where construction is difficult. , High cost, such as bridges and other structures are often arranged in valleys and mountainous terrain areas, which have the characteristics of high disaster occurrence rate, complex causes of disasters, wide impact areas, and high damage intensity. With the improvement of the level of transportation lines, many tall and steep slopes will inevitably appear due to the terrain constraints of the c...

AI Technical Summary

Problems solved by technology

[0003] In recent years, the maintenance of engineering structures is mainly based on manual on-site observation and structural bearing capacity tests, lacking quantitative, real-time and accurate damage detection methods

The manual on-site observation method is a rough visual inspection by on-site technicians, comprehensively assessing the structure score according to the damage status of each part, and finally determining the maintenance measures according to the relevant maintenance specifications or procedures. This method is highly subjective and cannot detect hidden parts and initial damage. , even more powerless for complex structures

However, the structural bearing capacity test is difficult to make a detailed evaluation of the damage state of the structure, and cannot fully reflect the damage accumulation of the structure.

In response to the above pain points, some technicians have used signal analysis methods to carry out research work on structural damage monitoring, but there are still some deficiencies. For example, in order to ensure accurate collection of structural damage signals, sensors are often installed in vulnerable parts of the structure. However, since engineering structures are located in different types of geological regions, potential geological hazards have different impact forms, scales, and impact energies on structures, resulting in differences in structural damage locations and damage degrees; for structural damage monitoring, only damage identification methods are proposed. There is no consideration for the sensor layout in the early stage of engineering structure construction and how to use damage data for efficient maintenance in the later stage of engineering structure operation; for the existing signal monitoring damage methods, most of them propose damage criteria for the local positions monitored by sensors, and the damage indicators are quantified. At the same time, it has not yet been able to combine with the damage theory of concrete structures to propose a judgment standard for the overall damage degree of the structure; most of the current research stays at the analysis and judgment of the damage signal, and has not yet carried out the damage data after processing. Deep excavation to obtain effective information of engineering structures at a deeper level, such as the remaining service life of the structure, etc.

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