DTW 기반 추진 전동기 잔여수명 예측 알고리즘 개발 사례연구

Abstract

Recently, more detailed fault diagnosis is being performed by analyzing the current status and changes of equipment through condition monitoring data obtained through various sensor data. In addition to fault diagnosis, attempts to predict the remaining useful life (RUL) in the event of a fault are being studied in various ways. RUL prediction is very important as a key indicator that can be used as a reference for equipment replacement time, cost reduction, and accident prevention. In this study, we propose a method for predicting the remaining life of equipment by extracting an abnormal pattern based on data collected from a ship's propulsion motor. To this end, the dynamic time warping (DTW) algorithm, which is a nonlinear pattern matching technique, and a method applying KNN were presented, and their effectiveness was examined through a simple case study.