Prediction of marine main engine exhaust temperature changing trend based on GA-BP model

WANG Xin-quan; SUN Pei-ting; ZOU Yong-jiu; LI Guo-long

doi:10.16411/j.cnki.issn1006-7736.2015.03.013

Journal of Dalian Maritime University >

2015 , Vol. 41 >Issue 3: 73 - 76

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2015.03.013

Prediction of marine main engine exhaust temperature changing trend based on GA-BP model

WANG Xin-quan ,
SUN Pei-ting ,
ZOU Yong-jiu ,
LI Guo-long

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（1.Marine Engineering College, Dalian Maritime University, Dalian 116026,China；2. DSIC, Dalian 116000,China）

Received date: 2015-05-25

Revised date: 2015-07-01

Online published: 2015-07-02

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Abstract

A time series prediction model was established based on BP neural network, and initial weights and threshold values were optimized by using genetic algorithm(GA) .The proposed model was verified by real examples, and result shows that the mean deviation of the two groups of GA-BP model is 0.39 ℃ and 0.74 ℃ respectively. The model is accurate and reliable, and can be used for prediction of marine main engine exhaust temperature changing trend.

Key words： marine main engine; exhaust temperature; trend prediction; BP neural network; genetic algorithm

Cite this article

WANG Xin-quan , SUN Pei-ting , ZOU Yong-jiu , LI Guo-long . Prediction of marine main engine exhaust temperature changing trend based on GA-BP model[J]. Journal of Dalian Maritime University, 2015 , 41(3) : 73 -76 . DOI: 10.16411/j.cnki.issn1006-7736.2015.03.013

References

[1]赵小兰,郭永尚,徐济仁,等.船舶监控数据分析技术的发展与现状[J].中国造船,2012,53(4):198-206.
ZHAO Xiao-lan,GUO Yong-shang,XU Ji-ren,et al. Development and current situation of ship monitoring data analysis technology [J]. Shipbuilding of China,2012,53(4):198-206. (in Chinese)
[2]甘辉兵,任光,张均东.基于数据挖掘的船舶机舱监控系统[J].中国造船,2011,52(4):214-220.
GAN Hui-bing,REN Guang,ZHANG Jun-dong. Monitored control system for ship engine room based on data mining [J]. Shipbuilding of China,2011,52(4):214-220. (in Chinese)
[3]马剑,吕琛,陶来发,等.船舶主推进系统故障预测与健康管理设计[J].南京航空航天大学学报.2011,43 (增):119-124.
MA Jian,LV Chen,TAO Lai-fa,et al. Design of prognostics and health management for marine main propulsion system [J]. Journal of Nanjing University of Aeronautics & Astronautics,2011,43 (S):119-124.(in Chinese)
[4]姜兴家.基于B/S的船舶远程监控系统的设计与实现[D].大连:大连海事大学,2010.
JIANG Xing-jia. The design and implementation of ship remote monitoring system based on B/S [D].Dalian: Dalian Maritime University,2010.(in Chinese)
[5]臧军.船舶柴油机故障诊断系统的研制[D].北京:中国舰船研究院,2011.
ZANG Jun. Development of fault diagnosis system for marine diesel engine [D]. Beijing:China Ship Research and Development Academy,2011.(in Chinese)
[6]丁刚,徐敏强,侯立国.基于过程神经网络的航空发动机排气温度预测[J].航空动力学报,2009,24(5): 1035-1039.
DING Gang，XU Min-qiang，HOU Li-guo. Prediction of aero engine exhaust gas temperature using process neural net work [J]. Journal of Aerospace Power,2009,24(5):1035-1039. (in Chinese)
[7]于广滨,丁刚,姚威,等.基于支持过程向量机的航空发动机排气温度预测[J].电机与控制学报,2013,17(8): 30-36.
YU Guang-bin,DING Gang,YAO Wei,et al. Aero engine exhaust gas temperature prediction using support process vector machine [J]. Electric Machines and Control,2013,17(8): 30-36. (in Chinese)
[8]李松,罗勇,张铭锐. 遗传算法优化BP神经网络的混沌时间序列预测[J]. 计算机工程与应用,2011(29): 52-55.
LI Song,LUO Yong,ZHANG Ming-rui. Prediction method for chaotic time series of optimized BP neural network based on genetic algorithm[J]. Computer Engineering and Applications,2011(29): 52-55. (in Chinese)
[9]李松,刘力军,解永乐.遗传算法优化BP神经网络的短时交通流混沌预测[J].控制与决策,2011,26(10): 1581-1585.
LI Song,LIU Li-jun,XIE Yong-le. Chaotic prediction for short-term traffic flow of optimized BP neural network based on genetic algorithm[J]. Control and Decision,2011,26(10): 1581-1585. (in Chinese)
[10]艾红,周东华.动态系统的故障预测方法[J].华中科技大学学报:自然科学版,2009,37(增1):222-225.
AI Hong,ZHOU Hua-dong. Fault prediction approach for dynamic system[J]. Journal of Huazhong University of Science and Technology :Natural Science Edition, 2009,37(S1):222-225. (in Chinese)

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