[1]田松峰,吴昭延,王子光,等. 基于神经网络的凝汽器污垢热阻预测模型[J].热力发电,2018,(预出版):1-5.[doi:10.19666/j.rlfd.201807145]
 TIAN Songfeng,WU Zhaoyan,WANG Ziguang,et al.Prediction model of condenser fouling thermal resistance based on neural network[J].Thermal Power Generation,2018,(预出版):1-5.[doi:10.19666/j.rlfd.201807145]
点击复制

 基于神经网络的凝汽器污垢热阻预测模型

参考文献/References:

 [1] Walker M E, Safari I, Theregowda R B, et al. Economic impact of condenser fouling in existing thermoelectric power plants[J]. Energy, 2012, 44(1): 429-437.
[2] 钟达文, 曾辉, 孟继安, 等. 凝汽器性能的数值模拟与布管原则[J]. 工程热物理学报, 2014, 35(1): 123-127.
ZHONG Dawen, ZENG Hui, MENG Ji’an, et al. Numerical simulation of power plant condenser performance and roles for tube arrangement[J]. Journal of Engineering Thermophysics, 2014, 35(1): 123-127.
[3] 杨家技, 黄汝广. 凝汽器清洁程度监测方法研究与应用[J]. 发电设备, 2014, 28(1): 27-29.
YANG Jiaji, HUANG Ruguang. Study and application of condenser cleanness monitoring methods[J]. Power Equipment, 2014, 28(1): 27-29.
[4] 曾申富, 张莉, 屈彬彬. 凝汽器管束布置修正系数随负荷变化的数值计算[J]. 汽轮机技术, 2017, 59(3): 169-172.
ZENG Shenfu, ZHANG Li, QU Binbin. The numerical calculation of the tube bundle arrangement correction factor with the change of the condenser load[J]. Turbine Technology, 2017, 59(03):169-172.
[5] FAN Shaoshen, ZHONG Qingchang. Prediction of fouling in condenser based on fuzzy stage identification and chebyshev neural network[J]. Measurement Science Review, 2013, 13(2) :94-99.
[6] 王建国, 汪勇华. 基于灰色神经网络的凝汽器水侧清洁系数预测[J]. 热力发电, 2013, 42(9): 95-99.
WANG Jianguo, WANG Yonghua. Gray neural network based prediction of water side clean coefficient of condenser tubes[J]. Thermal Power Generation, 2013, 42(9): 95-99.
[7] 王建国, 林乐平. 粒子群算法与径向神经网络相结合的凝汽器真空预测模型[J]. 热力发电, 2015, 44(10): 72-76.
WANG Jianguo, LIN Leping. A vacuum value prediction method for steam condensers using RBF neural network optimized by particle swarm algorithm[J]. Thermal Power Generation, 2015, 44(10): 72-76.
[8] 肖洪闯, 葛晓霞, 李扬. 基于广义回归神经网络的凝汽器故障诊断[J]. 电站辅机, 2018, 39(2): 15-18.
XIAO Hongchuang, GE Xiaoxia, LI Yang. Fault diagnosis of condenser based on generalized regression neural network[J]. Power Station Auxiliary Equipment, 2018, 39(2): 15-18.
[9] Reuter H C R, Owen M, Goodenough J L. Experimental evaluation of the temporal effects of paint-based protective films on composite fouling inside admiralty brass and titanium steam surface condenser tubes[J]. Applied Thermal Engineering, 2017, 126: 引用起止页码?.
[10] 张利平, 陈浩天, 王伟锋, 等. 应用PSO算法改进Elman神经网络的双压凝汽器真空预测[J]. 热力发电, 2015, 44(3): 53-57.
ZHANG Liping, CHEN Haotian, WANG Weifeng, et al. Application of PSO algorithm-modified elman neural network in vacuum prediction for dual-pressure condensers[J].Journal of Thermal Power Generation, 2015, 44(3): 53-57.
[11] 葛晓霞, 肖洪闯, 嵇卫, 等. 基于果蝇算法优化广义回归神经网络的凝汽器真空预测[J]. 汽轮机技术, 2018, 60(3): 208-212.
GE Xiaoxia, XIAO Hongbiao, JI Wei, et al. Vacuum pediction of condenser based on generalized regression neural network optimized by fruit fly algorithm[J]. Turbine Technology, 2018, 60(3): 208-212.
[12] 赵希梅, 金鸿雁. 基于Elman神经网络的永磁直线同步电机互补滑模控制[J]. 电工技术学报, 2018, 33(5): 973-979.
ZHAO Ximei, JIN Hongyan. Complementary sliding mode control for permanent magnet linear synchronous motor based on Elman neural network[J].Transactions of China Electrotechnical Society, 2018, 33(5): 973-979.
[13] 孟蓉歌, 张春化, 梁继超. 改进粒子群优-Elman算法在发动机曲轴脉宽预测中的应用[J]. 中国机械工程, 2018, 29(7): 766-770.
MENG Rongge, ZHANG Chunhua, LIANG Jichao. Applications of advanced PSO-Elman in engine crankshaft pulse width predictions[J]. China Mechanical Engineering, 2018, 29(7): 766-770.
[14] 皮骏, 黄江博. 基于IPSO-Elman神经网络的航空发动机故障诊断[J]. 航空动力学报, 2017, 32(12): 3031-3038.
PI Jun, HUANG Jiangbo. Aero-engine fault diagnosis based on IPSO-Elman neural network[J]. Journal of Aerospace Power, 2017, 32(12): 3031-3038.
[15] 王雷, 徐治皋, 司风琪. 基于支持向量回归的凝汽器清洁系数时间序列预测[J]. 中国电机工程学报, 2007(14): 62-66.
WANG Lei, XU Zhizhen, SI Fengqi. Time series prediction of condenser cleanness coefficient based on support vector regression[J]. Proceedings of the CSEE, 2007(14): 62-66.

相似文献/References:

[1]测试.测试[J].热力发电,2013,(03):1.
  测试[J].Thermal Power Generation,2013,(预出版):1.
[2]张利平,陈浩天,王伟锋,等.应用PSO算法改进Elman神经网络的双压凝汽器真空预测[J].热力发电,2015,(03):53.
 ZHANG Liping,CHEN Haotian,WANG Weifeng,et al.Application of PSO algorithm-modified Elman neural network in vacuum prediction for dual-pressure condensers[J].Thermal Power Generation,2015,(预出版):53.
[3]陈海平,谢 天,杨博然,等. 火电厂烟气水分及余热陶瓷膜法回收实验[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201803032]
 CHEN Haiping,XIE Tian,YANG Boran,et al. Ceramic membrane method for water and waste heat recovery from flue gas of thermal power plant[J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201803032]
[4]肖俊峰,李晓丰,胡孟起,等. 燃气轮机污染物排放影响因素相关性分析[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201804088]
 XIAO Junfeng,LI Xiaofeng,HU Mengqi,et al. Research on the correlation between influencing factors and pollutant emission of a heavy-duty gas turbine[J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201804088]
[5]汪淑军,姚 伟,张喜来,等. 准东煤一维炉燃烧结渣特性试验研究[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201804121]
 WANG Shujun,YAO Wei,ZHANG Xilai,et al. Experimental study on slagging characteristics of zhundong coal burning on a one dimensional furnace [J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201804121]
[6]张贵泉,刘永兵,文慧峰,等. Incoloy800H合金晶间腐蚀敏化条件研究[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201805112]
 ZHANG Guiquan,LIU Yongbing,WEN Huifeng,et al. Research on intergranular corrosion sensitization conditions for Incoloy800H alloy[J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201805112]
[7]杨 琛,薛 铮,方彦军,等. 塔式太阳能镜场三轴支撑定日镜控制装置[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201803062]
 YANG Chen,XUE Zheng,FANG Yanjun,et al. Tower solar mirror field of the three-axis support heliostat control device[J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201803062]
[8]张雪慧,魏 博,马 瑞,等. 准东地区粉煤灰改性做高碱煤缓焦剂的熔融性能评估[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201805097]
 Zhang Xuehui,Wei Bo,Ma Rui,et al. The Evaluation of Fusion Characteristics on the High Alkali Coal Slagging Inhibitor by Modified Fly Ash from Zhundong Area[J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201805097]
[9]余兴刚,李 旭,蒋北华,等. 汽轮机变工况模型的简便建立方法及应用[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201806123]
 YU Xinggang,LI Xu,JIANG Beihua,et al. A simple method to construct variable condition model for steam turbine and its application[J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201806123]
[10]邱振波,张立杰,胡伟,等.基于信息通信技术的燃气轮机远程预警技术研究及应用[J].热力发电,2018,(预出版):1.[doi:10.19666/j.rlfd.201804129]
 QIU Zhenbo,ZHAGN Lijie,HU Wei,et al. Research and application of gas turbine remote early warning technology based on ICT[J].Thermal Power Generation,2018,(预出版):1.[doi:10.19666/j.rlfd.201804129]

备注/Memo

 田松峰(1966—),男,教授,博士,主要研究方向为电站设备节能与监测。

更新日期/Last Update: 2018-09-17