摘要
为提升船舶装备力量,增强船舶电站的续航能力,搭建一套船用柴油发电机组试验系统。采集大量系统运行数据,运用统计学方法分析这些数据的特性,并采用层次分析法对柴油发电机进行健康评分计算。在此基础上,对异常数据进行分析,并研究一种基于机器学习的故障识别算法,形成一套柴油发电机组健康诊断系统,实现对柴油发电机组运行状态的实时诊断。
In order to improve the performance of marine equipment and increase the cruising ability of marine power generators,an experimental system for marine diesel generator set is developed.Huge amount of system operational parameters are collected.The data characteristics are analyzed using statistical analysis method,and the health of generator set is scored using the analytic hierarchy process(AHP).On this basis,the abnormal data are analyzed to develop a fault recognition algorithm based on machine learning,and a health diagnostic system is then set up,which can realize the real-time fault diagnosis of the generator set.
作者
赵俊超
汪佳彪
艾麦提布拉丁
王起硕
毛冬麟
ZHAO Junchao;WANG Jiabiao;Aimaiti Bulading;WANG Qishuo;MAO Donglin(Shanghai Marine Equipment Research Institute,Shanghai 200030,China)
出处
《船舶与海洋工程》
2021年第6期31-37,共7页
Naval Architecture and Ocean Engineering
关键词
柴油发电机组
故障预测
机器学习
健康诊断
diesel engine generator set
fault prediction
machine learning
health diagnosis
