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Soft Measurement of Methane Slip Concentrations for Diesel/Natural Gas Dual-Fuel Low-Speed Marine Engines
DOI:10.13949/j.cnki.nrjgc.2024.03.012
Key Words:long short-term memory(LSTM) neural network  mutual information  soft measurement  methane slip  dual-fuel engine
Author NameAffiliationPostcode
ZHAO Guoxu School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuhan 430063 China 430063
HU Lei School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuhan 430063 China
Key Laboratory of Marine Power Engineering and Technology of the Ministry of Transport Wuhan 430063 China 
430063
YU Yonghua School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuhan 430063 China
Key Laboratory of Marine Power Engineering and Technology of the Ministry of Transport Wuhan 430063 China 
430063
SHI Xiaodong China Shipbuilding Power Engineering Institute Co. Ltd. Shanghai 200129 China 200129
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Abstract:In order to eliminate the impact of the delay between measured data on the real-time and soft measurement of methane slip concentration monitoring process for marine dual-fuel low-speed engines, a soft measurement method of methane slip concentrations for dual-fuel low-speed marine engines based on long short-term memory(LSTM) neural network and mutual information (MI) was proposed. Auxiliary variable selection and variable time delay calculation were performed using mutual information. The preprocessed data was imported into the LSTM model to predict the methane slip concentration. Finally, the historical data from a methane slip processing system of a dual-fuel low-speed engine was used to test the performance of the proposed model. The experimental results show that the model based on LSTM and mutual information has good predictive ability. The method is proved to be effective by experiments, which can provide an effective method for monitoring the methane slip concentrations for dual-fuel low-speed marine engines.
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