Wall crack detection system based on block chain and BIM

Abstract

The invention discloses a wall crack detection system based on a block chain and a BIM. The system comprises a wall crack segmentation encoder, a wall crack segmentation decoder, a wall crack depth first encoder, a wall crack depth second encoder, a full connection layer, a wall crack area estimation unit and a wall crack grade estimation unit. The system further comprises a computing cluster, allnodes in the computing cluster load parameters required by the wall crack detection deep neural network, for image data sent by the image acquisition unit, a wall crack detection block chain privatechain is configured in the computing cluster, network reasoning is executed, and a wall crack grade estimation result is obtained and sent to the building information model. By utilizing the method and the device, in wall crack detection, the result feedback is diversified, and the practicability of the detection result, the precision of the detection result and the safety performance in the dataprocessing process are improved.

Description

technical field [0001] The invention relates to the technical fields of blockchain, artificial intelligence, BIM, and smart construction sites, and in particular to a wall crack detection system based on blockchain and BIM. Background technique [0002] Due to the complex site environment of the construction site, the unbalanced ratio of cement and concrete will produce messy cracks. After solidification, different degrees of shrinkage of the wall surface will produce vertical cracks. If the surface is judged as unqualified, it will cause economic losses, and there will be great safety hazards. It can be seen that it is very necessary to perform crack detection on the walls under construction in the construction site. For buildings that have been put into use, they need to be repaired according to the problems and status of the building in order to maintain a longer service life. The state of the wall can directly reflect the existing problems of the building. Therefore, i...

AI Technical Summary

Problems solved by technology

However, due to the fact that the detection is under natural light conditions, there are many external environment interferences, and its feature selection is not accurate enough, resulting in low detection robustness, which cannot meet the needs of practical applications.

Moreover, the hardware clusters used for computing are easy to leak information and have low security performance

Therefore, the existing field of wall crack detection has the problems of low detection accuracy, poor practicability of detection results, single result feedback, and low safety performance.

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