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Automatic crack detection using AI

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last updated:Sep 23, 2021

東設土木コンサルタント
東設土木コンサルタント
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Automatic detection of cracks in concrete walls using AI.

Automatically detects cracks from high-resolution images and estimates crack width automatically. It can accurately detect cracks without misidentifying dirt or seams. Civil engineers can create high-precision inspection data simply by checking the crack detection results output by AI. 【Main Features】 - This crack detection AI conducts Deep Learning using cracks extracted by civil engineers as training data. - By having engineers create deformation records based on automatic detection results, significant reductions in man-hours can be achieved. - Detection can be performed with consistent quality. - Compatible with the deformation development diagram creation and management support software "CrackDraw21" for data integration. *For more details, please refer to the PDF document or feel free to contact us.

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Automatic crack detection using AI

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basic information

【Automatic Detection of Anomaly Types】 - Cracks in concrete surfaces 【Detection Accuracy】 - 99% (601 out of 605 locations): Detection accuracy after verification of AI detection results by engineers * Published in the Ministry of Land, Infrastructure, Transport and Tourism trial results NETIS (New Technology Information System) * For more details, please refer to the PDF document or feel free to contact us.

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Applications/Examples of results

【Purpose】  ・Inspection of concrete structures 【Examples of Achievements】  ・Bridges (deck slabs, piers), etc. *For more details, please refer to the PDF document or feel free to contact us.

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  • 自動検知結果の一例.jpg

    An example of automatic crack detection using AI.

  • 人との比較.jpg

    Comparison of Engineer and AI Automatic Detection Results

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東設土木コンサルタント

東設土木コンサルタント

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Tosetsu Civil Engineering Consultant Co., Ltd. has been engaged in the maintenance and management of facilities for hydroelectric power generation, such as dams, and civil engineering structures for thermal and nuclear power generation, including intake and discharge channels, through investigations, surveys, measurements, analyses, and diagnostics. Additionally, we have developed systems that capture images of tunnel walls using vehicles equipped with digital cameras while driving through tunnels, as well as systems that efficiently inspect marine structures from ships while controlling the ship's motion.

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