Differential Evolutionary Modeling with Residual Correction and Down-load Characteristic Analysis for Marine Turbocharged Unit

Abstract

Abstract:

Abstract： For the modeling and operation characteristic analysis of marine turbocharged unit, an improved differential evolutionary modeling method with residual correction was designed in this paper. This method adopted the differential evolution algorithm to identification model parameters based on the mechanistic model of turbocharged unit, and then used the residuals of original data and model outputs to correct errors, which avoided the deviation caused by experience or experimental data under ideal state. Simulation experiments were conducted based on this model and existing supercharged model to studied the dynamic characteristics of turbocharged unit in pastdown load process. The comparsion of the simulation result with the original data proved that the differential evolution algorithm with residual correction could automatically generate dominant model that met realtime and accuracy requirements in a given model space and parameter ranges. Further analysis of simulation results showed that there was ignificant lag of turbocharged unit in the pastdown load process.

Key words: turbocharging unit, differential evolutionary, residual modification, down-load characteristics

CLC Number:

NI He,XIAO Hang,ZENG Fanming,SUN Fengrui. Differential Evolutionary Modeling with Residual Correction and Down-load Characteristic Analysis for Marine Turbocharged Unit[J]. Journal of Shanghai Jiaotong University, 2015, 49(05): 620-625.

References

［1］李章, 张宁, 刘翔源, 等．船用增压锅炉装置［M］．北京: 海潮出版社，2009.

［2］Haryanto A, Hong K S．Modelling and simulation of an oxyfuel combustion boiler system with flue gas recirculation［J］．Computers and Chemical Engineering, 2011, 35(1): 2540．

［3］胡继敏, 金家善. 船用增压锅炉系统动态数学模型的建立［J］. 计算机与数字工程, 2012, 34(1): 5054.

HU Jimin, JIN Jiashan. Dynamic mahematical model of marine supercharged boiler system［J］. Computer and Digital Engineering, 2012, 34(1): 5054.

［4］刘云生, 冯永明, 陈华清, 等. 增压锅炉与涡轮增压机组匹配特性仿真分析［J］. 舰船科学技术, 2012, 34(1): 5054.

LIU Yunsheng, FENG Yongming, CHEN Huaqing, et al. Simulation analysis of cooperation relationship between supercharged boiler and turbincharger unit［J］. Ship Science and Technology, 2012, 34(1): 5054.

［5］韩静, 姜任秋, 孙宝芝,等. 船用增压锅炉的热平衡计算方法研究［J］. 工程热物理学报, 2004, 25(S): 173175.

HAN Jing, JIANG Renqiu, SUN Baozhi, et al. Research on heat calculation method of the marine supercharged boiler［J］. Engineering Thermophysics, 2004, 25(S): 173175.

［6］李彦军. 船用增压锅炉的增压机组和热平衡计算［J］. 哈尔滨工程大学学报, 2007, 28(8): 867869.

LI Yanjun. Calculating heat balance for a turbocharged unit of a marine supercharged boiler［J］. Journal of Harbin Engineering University, 2007, 28(8): 867869.

［7］刘宝杰, 邹正平, 严明, 等. 叶轮机计算流体动力学技术现状与发展趋势［J］. 航空学报, 2002, 23(5): 394404.

LIU Baojie, ZOU Zhengping, YAN ming, et al. Present status and future development of CFD inurbomachinery［J］. ACTA Aeronau Ticaet Sinica, 2002, 23(5): 394404.

［8］张智博, 郑洪涛, 李雅军. 基于特征参数准则的舰船燃机燃烧室贫熄预测［J］. 哈尔滨工程大学学报, 2014, 35(2): 177183.

ZHANG Zhibo, ZHENG Hongtao, LI Yajun. Prediction of lean blowout on marine gas turbine combustor based on featureparametercriterion［J］. Journal of Harbin Engineering University, 2014, 35(2): 177183.

［9］王俊国. 基于神经网络的建模方法与控制策略研究［D］. 武汉: 华中科技大学计算机学院, 2004.

［10］Storn R, Price K. Differetial evolution: A simple and efficient heuristic for global optimization over continuous spaces ［J］. Journal of Global Optimization, 1997, 11(4): 341359.

［12］武志峰. 差异演化算法及其应用研究［D］. 北京: 北京交通大学自动化学院, 2009.

［13］董文永, 李元香. 二次演化建模在实时仿真中的应用［J］. 计算机研究和发展, 2002, 39(10): 12611268.

DONG Wenyong, LI Yuanxiang. A new method of evolutionary modeling used in realtime simulation［J］. Journal of Computer Research and Development, 2002, 39(10): 12611268.

［14］倪何, 肖航, 曾凡明, 等. 基于基元级计算的汽轮机级间集总参数建模［J］. 系统仿真学报, 2014, 26(2): 912.

NI He, XIAO Hang, ZENG Fanming, et al. Segmented lumped parameter modeling of steam turbine based on cascad calculation［J］. Journal of System Simulation, 2014, 26(2): 912.

［15］陈航, 郑群, 邓庆峰, 等．某大型舰船主汽轮机的建模与动态仿真［J］．热能动力工程, 2012, 27(3): 282286．

CHEN Hang, ZHENG Qun, DENG Qingfeng, et al. Dynamic modeling and simulation of a certain type large ship marine turbine ［J］．Thermal Power Engineering, 2012, 27(3): 282286．

［16］倪何, 程刚, 孙丰瑞. 热工流体网络简易模块化建模方法［J］. 系统仿真学报, 2009, 21(12): 35363541.

NI He, CHENG Gang, SUN Fengrui. Simple modular modeling method of thermofluid network［J］. Journal of System Simulation, 2009, 21(12): 35363541.

［17］Hong T, Ni H, Cheng G. Fullscale mathematical model and simulation of marine natural recirculation drumboiler［C］∥International Conference on Advances in Computational Modeling and Simulation. Kunming, China:SpringerVerlag Press 2011: 834843.

［11］Shiakolas P S, Koladiya D, Kebrle J. On the optimum synthesis of sixbar 1inkages using differential evolution and the geometric centroid of precision positions technique ［J］. Mechanism and Machine Theory, 2005, 4(3): 319335.

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