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

Abstract:

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.

• Periodical: Advanced Materials Research (Volume 548)
• Pages: 444-449
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.548.444
• Online since: July 2012
• Authors: Xin Gang Song, Yu Na Miao, Qiang Ma, Xiao Jie Guo
• Keywords: BP Neural Network (BPNN), Diesel Engine, Fault Diagnosis, Vessel

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