The application of data mining for marine diesel engine fault detection

Yongzhi Chen, Yonghua Yu, Zhangming Peng
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引用次数: 2

Abstract

Early fault detection for marine diesel engines is very important to ensure reliable operation throughout the course of their service. An early fault detection method is introduced in this paper based on the thermal parameters, and a fault predication system for marine diesel engine is developed based on abnormal data mining technology, which acquires the thermal parameters of the diesel engine from the local safety, alarm and control system through field bus, manages the data by database, and predicts the operation condition through statistic and data miming technology. It is found that the abnormal data mining is effective to fault detection at the early stage.
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数据挖掘在船用柴油机故障检测中的应用
船用柴油机的早期故障检测对于保证柴油机在整个服役过程中的可靠运行具有重要意义。本文介绍了一种基于热参数的早期故障检测方法,并基于异常数据挖掘技术开发了船用柴油机故障预测系统,该系统通过现场总线获取柴油机本地安全、报警和控制系统的热参数,通过数据库对数据进行管理,并通过统计和数据挖掘技术对柴油机运行状态进行预测。发现异常数据挖掘对早期故障检测是有效的。
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