인공지능 머신러닝을 이용한 체인 스프라켓 드라이브 시스템의 건전성 감시 장치

초록

A chain sprocket drive (CSD) system consists of parts such as chains, sprockets, gears, bearings, and rotating shafts. The purpose of this study is to develop a health monitoring system that uses deep learning artificial intelligence (AI) technology to diagnose defects in the CSD system in advance to prevent complete failures due to such defects. In this study, eight types of defects were arbitrarily fabricated and combined to build a CSD system. Deep AI machine learning algorithms were developed to classify and diagnose the eight types of defects. The eight types of defects were mainly limited to bearing parts, gear parts, and rotary shaft parts. Sprocket or chain defects were excluded from the eight types of defects. Finally, an AI machine was successfully developed and applied for diagnosing defects in the CSD system.

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