Building structure defect detection system based on machine vision

By combining dual-modal detection with visible light and depth thermal imaging data, and using dynamic cognitive kernel modules for cross-validation and iterative refinement, the problem of false alarms and missed detections in building structure defect detection systems under complex textures and uneven lighting environments has been solved. This has resulted in a highly reliable and accurate defect identification system with self-optimization capabilities.

CN121600407APending Publication Date: 2026-03-03CHONGQING JIAOTONG UNIV
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Patent Information

Application Number
CN202511871014.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-12
Publication Date
2026-03-03

AI Technical Summary

Technical Problem

Existing machine vision-based building structural defect detection systems struggle to accurately identify minute structural defects in complex textures and uneven lighting environments, resulting in high false alarm and false negative rates and failing to provide reliable structural safety assessments.

Method used

The system employs a visible light camera unit and a depth thermal imaging acquisition unit to acquire dual-modal data. It combines a dynamic cognitive kernel module for cross-validation and iterative refinement, optimizes feature extraction through adaptive attention weight maps and feature selection parameters, and optimizes the model by combining an offline training library, thereby achieving accurate differentiation between real defects and pseudo-features.

Benefits of technology

It effectively reduces false alarms and missed detections, improves the reliability and accuracy of detection in complex environments, and forms an intelligent detection system with self-optimization and closed-loop verification, providing reliable technical support for building structural health monitoring.

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Abstract

The invention discloses a building structure defect detection system based on machine vision, and relates to the technical field of building quality detection and machine vision, the building structure defect detection system comprises an image acquisition module, an image processing module, a feature analysis module and a decision output module; the image acquisition module comprises a visible light shooting unit and a depth thermal image acquisition unit. The visible light shooting unit is used for acquiring visible light image data of the surface of the building component. According to the building structure defect detection system based on machine vision, through bimodal data fusion of visible light and a depth thermal image, and in combination with a cross validation and cyclic refining mechanism of a dynamic cognitive nucleus, interference of complex textures and uneven illumination on the surface of a building on defect identification is effectively overcome. The system can accurately distinguish real defects from surface false features, greatly reduces false alarm and leak detection phenomena, and improves the detection reliability and accuracy of fine structure defects in a complex engineering environment.
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