scholarly journals An Intelligent Fault Diagnosis Scheme Based On PCA-BP Neural Network for the Marine Diesel Engine

Author(s):  
Sibo Wang ◽  
Jin Wang ◽  
Xuewen Ding
2012 ◽  
Vol 548 ◽  
pp. 444-449 ◽  
Author(s):  
Xin Gang Song ◽  
Yu Na Miao ◽  
Qiang Ma ◽  
Xiao Jie Guo

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.


2013 ◽  
Vol 281 ◽  
pp. 105-111 ◽  
Author(s):  
Yong Shi ◽  
Lian Yu Zhang ◽  
Jun Sun ◽  
Hong Guang Zhang

Marine diesel engine is of characteristics of non-linear and time-invariant, so it is difficult to be controlled with traditional PID controller. An adaptive controller based on back-propagation (BP) neural networks was put forwarded for marine diesel engine speed control system, where two neural networks are proposed to control the position loop and speed loop. The adaptive controller was improved was improved via introducing relative error in target evaluation function of the BP neural network, and obtain sensitivity function of diesel engine output with respect to its input using a differential equation. The controller has self-learning and adaptive capacity. It can also optimize the PID controller parameters online. The controller was experimentally evaluated on rack position actuator of marine diesel engine simulated based on a diesel hardware-in-loop system of dSPACE. Finally, tests on a diesel engine demonstrated that the controller can satisfy the transient and steady demands of speed regulation system.


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