A new fatigue crack detection system was developed utilizing IoT and statistical analysis techniques. Strain distributions on structural members are statistically compared between health and diagnosis conditions. It was designed to detect fatigue crack initiations and propagations as abnormal. Data acquisition transfer system and automatic fatigue crack detection system were built using IoT techniques and cloud server platform. Users can see the detection results with real time chart application software in their office on demand. Two examples of demonstration experiments are shown with their data and analysis results. Fatigue crack was detected in one of the experiments in realistic working conditions. Robust crack detection method and IoT remote monitoring system were developed, and verified possessing high detection accuracy on realistic machinery.
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YASUDA et al. (2017) studied this question.
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