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