선박 추진용 2행정 저속엔진의 고장모드 데이터 개발 및 LSTM 알고리즘을 활용한 특성인자 신뢰성 검증연구

• Published in: 大韓造船學會 論文集 Vol. 60; no. 2; pp. 95 - 109
• Main Authors: 박재철(Jae-Cheul Park), 권혁찬(Hyuk-Chan Kwon), 김철환(Chul-Hwan Kim), 장화섭(Hwa-Sup Jang)
• Format: Journal Article
• Language: Korean
• Published: 대한조선학회 2023
• Subjects: Condition Based Maintenance(상태 기반 유지관리); Maritime autonomous surface ship(자율운항선박); Reliability verification(신뢰성 검증); Exploratory data analysis(탐색적 데이터 분석); Failure mode DB(고장모드 데이터베이스); 2-stroke low speed engine(2행정 저속엔진); 2
• ISSN: 1225-1143; 2287-7355
• DOI: 10.3744/SNAK.2023.60.2.95

In the 4th industrial revolution, changes in the technological paradigm have had a direct impact on the maintenance system of ships. The 2-stroke low speed engine system integrates with the core equipment required for propulsive power. The Condition Based Management (CBM) is defined as a technology that predictive maintenance methods in existing calender-based or running time based maintenance systems by monitoring the condition of machinery and diagnosis/prognosis failures. In this study, we have established a framework for CBM technology development on our own, and are engaged in engineering-based failure analysis, data development and management, data feature analysis and pre-processing, and verified the reliability of failure mode DB using LSTM algorithms. We developed various simulated failure mode scenarios for 2-stroke low speed engine and researched to produce data on onshore basis test_beds. The analysis and pre-processing of normal and abnormal status data acquired through failure mode simulation experiment used various Exploratory Data Analysis (EDA) techniques to feature extract not only data on the performance and efficiency of 2-stroke low speed engine but also key feature data using multivariate statistical analysis. In addition, by developing an LSTM classification algorithm, we tried to verify the reliability of various failure mode data with time-series characteristics.