Machine learning-based wear fault diagnosis for marine diesel engine by fusing multiple data-driven models

2020 ◽  
Vol 190 ◽  
pp. 105324 ◽  
Author(s):  
Xiaojian Xu ◽  
Zhuangzhuang Zhao ◽  
Xiaobin Xu ◽  
Jianbo Yang ◽  
Leilei Chang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fault Diagnosis ◽  
Diesel Engine ◽  
Data Driven ◽  
Marine Diesel Engine ◽  
Multiple Data ◽  
Marine Diesel

Physical and Data-Driven Models Hybridisation for Modelling the Dynamic State of a Four-Stroke Marine Diesel Engine

2021 ◽  
pp. 145-193
Author(s):  
Andrea Coraddu ◽  
Miltiadis Kalikatzarakis ◽  
Gerasimos Theotokatos ◽  
Rinze Geertsma ◽  
Luca Oneto
Keyword(s):  
Diesel Engine ◽  
Data Driven ◽  
Dynamic State ◽  
Marine Diesel Engine ◽  
Marine Diesel

Applied Research of BP Neural Network in Remote Marine Diesel Engine Fault Diagnosis System

2012 ◽  
Vol 548 ◽  
pp. 444-449 ◽  
Author(s):  
Xin Gang Song ◽  
Yu Na Miao ◽  
Qiang Ma ◽  
Xiao Jie Guo
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Diesel Engine ◽  
Bp Neural Network ◽  
Marine Diesel Engine ◽  
Gas Temperature ◽  
Data Simulation ◽  
Marine Diesel ◽  
Exhaust Gas Temperature ◽  
Matlab Programming

In order to detect and diagnose abnormal conditions of marine diesel engine and ensure its normal functioning, the present study adopts the BP neural network and related algorithms to determine the remote fault diagnosis process. Taking the design of exhaust gas temperature remote monitoring sub-system as an example, MATLAB programming was used for data simulation and verification. The applying of the system on board a real ship shows that it has a high working rate, a reliable and safe storage mode and a self- adaptive process.

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