Abstract
Humans have been conducted the nondestructive inspection by hammering sound of the infrastructure construction up to now, in this study, the objective is fully automated it using machines. Among them, diagnostic apparatus automation is especially difficult. We therefore considered a system for generating a discriminator using machine learning and aimed at automation of diagnosis by performing the quality determination by the machine. Then, we made the sounding hammer with rotary solenoid and designed software for integration to run recording, analysis and diagnosis by Python. After that, the system was found to it is a useful by experiments at a bridge pier.
Published Version
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