해상크레인 윈치 감속기의 기계학습기반 실시간 상태모니터링 시스템 개발

Abstract

This study introduces development examples of monitoring system for winch equipment, the main equipment of floating cranes. The detail process was introduced to develop a system that can acquire sensor data in real time, monitor operating conditions and fault diagnosis. The proposed monitoring system is designed for winch equipment, which is a key equipment of the offshore crane. The system was developed for bearing part, which frequently causes failures in the winch equipment. In addition, we would like to introduce a relatively low-cost H/W configuration to facilitate application in small and medium-sized industries. The monitoring methods have been implemented by applying the method of Na？ve Bayes classification based on the method of supervised learning.