A cast-in-place floor crack construction control method and system based on image processing

By identifying defects in cast-in-place floor slabs and predicting crack risks through image processing, and dynamically adjusting construction parameters, the problem of construction parameter mismatch in existing technologies is solved, enabling refined control and quality assurance in cast-in-place floor slab construction.

CN121582151BActive Publication Date: 2026-06-26HUBEI LUQIAO GRP MUNICIPAL CONSTR ENG CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HUBEI LUQIAO GRP MUNICIPAL CONSTR ENG CO LTD
Filing Date
2025-11-07
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing technologies struggle to correlate the quantitative assessment of static defects in cast-in-place floor slab construction with the prediction of dynamic crack risks, leading to a mismatch in construction parameters, an inability to achieve real-time quality feedback and control, and a high risk of quality defects.

Method used

Image processing technology is used to identify honeycomb, delamination and crack defects on the surface of cast-in-place floor slabs, quantify their area proportion, regional dispersion and crack width and direction, use the defect degree analysis model to predict crack risk value, and dynamically adjust the pouring speed and vibration intensity to achieve fine control.

Benefits of technology

It enables multi-dimensional and refined assessment of the structural condition of cast-in-place floor slabs, improves the accuracy of crack risk prediction and dynamic control of construction parameters, and ensures construction quality and safety.

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Abstract

The present application relates to the floor pouring construction monitoring technical field, specifically relates to a kind of cast-in-place floor crack construction control method and system based on image processing.The present application is combined to identify three key defects of honeycomb defect, stratification defect and crack defect, and respectively quantifies its area proportion, area discrete degree and direction weighted influence degree, realizes the multi-dimension, fine evaluation of cast-in-place floor structure state, significantly improves the accuracy and comprehensiveness of subsequent pouring section crack risk prediction.
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