Machine vision-based building structure crack detection and repair method

Abstract

The embodiment of the invention discloses a machine vision-based building structure crack detection and repair method, which includes: (1) building structure image acquisition by machinery equipment; (2) image feature value extraction; (3) monitored building stress analysis; (4) intelligent monitored building repair. The invention introduces machine vision into structure health monitoring to establish a real-time and high-efficiency intelligent detection and repair measure. The method can make up for certain deficiencies in structure health monitoring and promote the development of the structure health monitoring and repair field toward intelligentization, and the wavelet analysis method is used for extracting crack feature values. By carrying out finite element analysis on the extracted feature values, such as width and distribution range, the method can find out the relation between cracks and structure health and quantitatively classify the cracks, thus increasing the intelligentization degree of structure monitoring, and the method has profound significance for the development of building disaster prevention and mitigation and civil engineering toward intelligentization.

Description

technical field [0001] The invention relates to the field of civil engineering automation, in particular to a method for detecting and repairing cracks in building structures and an intelligent robot applying the method. Background technique [0002] With the development of the economy, people have higher and higher requirements for the safety of building structures, so they pay special attention to the damage of structures. In a building structure system, failure can be considered as a parameter of unfavorable factors affecting the working of the structure. The damage starts from the damage of the material. With the use of the structure, the damage will gradually accumulate. In the process, the sudden situation will aggravate this change. When it increases to a certain extent, it will cause the overall failure of the structure. . After the building structure is put into use, under normal use, it will be continuously eroded by the environment, and its small damage will gra...

AI Technical Summary

Problems solved by technology

There are still many defects in the existing SHM (structural health monitoring) system, such as system reliability, data storage and transmission, environmental impact and noise impact, etc.

These defects will affect the reliability of the results, and some errors will occur when processing the collected data. Therefore, the existing monitoring methods often cannot make people get more intuitive monitoring results, and consume a lot of manpower and material resources. not real-time information

Images