基于残差修正的涡轮增压机组差异演化建模与降负荷特性分析

摘要/Abstract

摘要：

摘要：针对船用增压锅炉涡轮增压机组的建模与运行特性分析问题，提出了一种基于差异演化算法和残差修正的演化建模方法.在涡轮增压机组机理模型的基础上，采用差异演化算法辨识模型参数，利用原始数据和所建模型的残差进行修正，避免了采用经验值或理想状态下的实验数据作为模型参数所造成的偏差，在所建模型和已有增压锅炉涡轮增压机组模型的基础上进行仿真实验，研究了涡轮增压机组在快速降负荷过程中的动态特性，并通过仿真结果与原始数据的对比验证了其可靠性.结果表明：在给定的模型空间和参数范围内，采用残差修正的差异演化算法能够自动生成同时满足实时性和精度要求的显性模型；通过对仿真结果分析发现，相对于锅炉，涡轮增压机组在快速降负荷过程中出现了明显滞后的现象，甚至可能导致锅炉熄火.

关键词: , 涡轮增压机组, 差异演化, 残差修正, 降负荷特性

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

中图分类号:

倪何，肖航，曾凡明，孙丰瑞. 基于残差修正的涡轮增压机组差异演化建模与降负荷特性分析[J]. 上海交通大学学报（自然版）, 2015, 49(05): 620-625.

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.

参考文献

［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.

[1]	王聚团, 戚晓宁, 黄志明. 水下生产管汇测试技术及其改进研究[J]. 海洋工程装备与技术, 2022, 9(2): 43-49.
[2]	袁振钦, 邹科, 孙亚峰, 刘刚, 屈衍, 李居跃. 基于时域分析法的动态电缆疲劳分析[J]. 海洋工程装备与技术, 2022, 9(2): 50-55.
[3]	王娟, 杨明旺, 郑茂尧, 刘凌云, 赵立君. 高强钢在大型半潜式平台组块建造中的应用[J]. 海洋工程装备与技术, 2022, 9(1): 27-31.
[4]	陈欣, 赵晓磊, 王立坤, 肖德明, 张腾月. 深水大型吸力锚建造技术研究[J]. 海洋工程装备与技术, 2022, 9(1): 32-36.
[5]	尹彦坤, 易涤非. 半潜式生产平台船体结构关键节点工程临界评估[J]. 海洋工程装备与技术, 2022, 9(1): 52-57.
[6]	ZHANG Shengfa (张胜发), TANG Na (唐纳), SHEN Guofeng (沈国峰), WANG Han (王悍), QIAO Shan (乔杉). Universal Software Architecture of Magnetic Resonance-Guided Focused Ultrasound Surgery System and Experimental Study[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(4): 471-481.
[7]	MA Qunsheng (马群圣), CEN Xingxing (岑星星), YUAN Junyi (袁骏毅), HOU Xumin (侯旭敏). Word Embedding Bootstrapped Deep Active Learning Method to Information Extraction on Chinese Electronic Medical Record[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(4): 494-502.
[8]	KONG Xiangqiang (孔祥强), MENG Xiangxi (孟祥熙), LI Jianbo (李见波), SHANG Yanping (尚燕平), CUI Fulin (崔福林) . Comparative Study on Two-Stage Absorption Refrigeration Systems with Different Working Pairs[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(2): 155-162.
[9]	ZHUANG Weimin (庄蔚敏), WANG Pengyue (王鹏跃), AO Wenhong (熬文宏), CHEN Gang (陈刚) . Experiment and Simulation of Impact Response of Woven CFRP Laminates with Different Stacking Angles[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(2): 218-230.
[10]	安庆升, 孙立东, 武秋生. 碳纤维增强复合材料发射筒设计研究[J]. 空天防御, 2021, 4(2): 13-.
[11]	ZHOU Xuhui (周旭辉), ZHANG Wenguang (张文光), XIE Jie (谢颉). Effects of Micro-Milling and Laser Engraving on Processing Quality and Implantation Mechanics of PEG-Dexamethasone Coated Neural Probe[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(1): 1-9.
[12]	HUANG Ningning (黄宁宁), MA Yixin (马艺馨), ZHANG Mingzhu (张明珠), GE Hao (葛浩), WU Huawei (吴华伟). Finite Element Modeling of Human Thorax Based on MRI Images for EIT Image Reconstruction[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(1): 33-39.
[13]	WANG Xianjin, GAO Xu, YU Kuigang . Fixture Locating Modelling and Optimization Research of Aluminum Alloy Sidewall in a High-Speed Train Body[J]. J Shanghai Jiaotong Univ Sci, 2020, 25(6): 706-713.
[14]	QIAO Xing, MA Dan, YAO Xuliang, FENG Baolin. Stability and Numerical Analysis of a Standby System[J]. J Shanghai Jiaotong Univ Sci, 2020, 25(6): 769-778.
[15]	WU Jin, MIN Yu, YANG Xiaodie, MA Simin . Micro-Expression Recognition Algorithm Based on Information Entropy Feature[J]. Journal of Shanghai Jiao Tong University(Science), 2020, 25(5): 589-599.