China's fatigue testing machine industry
2026-06-23 20:55:54
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The integration of China's fatigue testing machine industry and AI has achieved
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The integration of China's fatigue testing machine industry and AI has achieved a systematic transition from detection assistance to decision-making intelligence. Relying on deep learning and multimodal sensing technology, the 'Tiangongyan' AI vision system developed by AVIC Strength Institute can autonomously identify micro cracks in aircraft structures, with a detection efficiency improvement of over 300% and a false detection rate of less than 0.5%; Huace Testing has built an AI evaluation and generative reporting system, which enables automatic analysis of testing data and minute level generation of reports, reducing manual intervention by 80%. In the experimental process, enterprises such as Wanchen and Shenglin integrated machine vision and industrial robots to complete automatic sample clamping, closed-loop loading, and 7 × 24-hour unmanned testing, increasing the annual production capacity of a single device by four times. In terms of cutting-edge research, the Shanghai University team has integrated Physics Information Neural Network (PINN) with experimental data to achieve a prediction error of less than 8% for fatigue life of metal materials, breaking through the limitations of traditional S-N curve models. At the policy level, the 'Guidelines for the Construction of National Intelligent Manufacturing Standard System (2024 Edition)' clearly includes AI intelligent equipment as a key direction, and Chongqing has released the first 'Evaluation Standard for AI Radiation Testing of Pressure Equipment' (DB50/T 1807-2025) in China, promoting technology from pilot to standardized. AI is transforming fatigue testing machines from 'force value recorders' to 'material health diagnostic centers', supporting the full lifecycle reliability verification of high-end equipment.
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shanghai caite international trade co.,ltd
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