DocumentCode :
2542607
Title :
The application of data mining for marine diesel engine fault detection
Author :
Chen Yongzhi ; Yu Yonghua ; Peng Zhangming
Author_Institution :
Sch. of Energy & Power Eng. of Wuhan, Univ. of Technol., Wuhan, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
1430
Lastpage :
1433
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.
Keywords :
data mining; diesel engines; fault diagnosis; marine systems; reliability; safety; abnormal data mining technology; alarm system; control system; data management; fault predication system; field bus; local safety; marine diesel engine fault detection method; reliable operation; statistic technology; thermal parameters; Data mining; Data models; Databases; Diesel engines; Fault detection; Temperature distribution; Testing; Data Mining; Database; Fault Detection; Marine Diesel Engine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
Type :
conf
DOI :
10.1109/FSKD.2012.6233807
Filename :
6233807
Link To Document :
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