黑犬黑犬97
电气工程及其自动化毕业设计(东北电力大学毕业论文) 2009 年 03 月 19 日 星期四 16:22 论文主要内容包括 1.摘要 2.英文翻译 3.原始资料 4.计算书 5.说明书 6.参考文献 7.图纸 简单区域电力网络系统的一次或二次设计毕业论文 目录: 第一章. 设计依据 第二章. 原始资料 第三章 接入系统设计 第四章 地方供电系统设计 第五章 主变选择(包括抽头选择或调整方式设计) 第六章 主接线设计(包括所用电设计) 第七章 短路电流计算 第八章 设备选择 第九章 继电保护配置 [正文]: 第一章.设计依据 根据××大学电气工程及自动化专业毕业任务书 第二章.原始资料 为了满足工农业生产发展的需要,经上级批准,决定新建 110KV 盐北变电所。 一. 设计资料 (一) 新建的盐北变电所各电压级负荷数据,回路,同时率等见表 3。 盐北变电所每年负荷增长率 5%,需考虑五年发展规划 变电所总负荷 s110=K 1(s35+s10) (1+5%) (二) 新建的盐北变电所,受电方案有两种: (1)从 110K 盐城东郊变受电距离 30KM(本课题做)(2)从 110KV 灌南变受电距离 35KM(本课题不 ; 做) ,电力系统接线图见图 1 (三) 电力系统,各厂、所、输电线等主设备技术参数见表 1、2、3、4、5。 (四) 其它原始资料: 所址:地形地势平坦、土址电阻率为 ×10 欧?厘米,所址高于百年一遇最高洪水位。所 址所在地气候,平均气温 15℃,最高气温 35℃,最低气温-15℃。 交通:紧靠国家二级公路,进所公路 公里。 水源:变电所附近有河流供方方便,水量充足。 二.设计内容 (一) 接入系统设计: 确定接入系统输电线路回路数及导线截面。 (二) 地区供电系统设计: 根据地区负荷性质及供电距离,确定供电线路数及导线截面。 (三) 通过技术、经济比较,确定变电所主变压器台数及容量、型号、规格。 (四) 通过电压计算、选择主变分接头或调压方式。 (五) 根据所确定的主变方案和进出线回路数,通过技术分析、论证,确定待建变电所的 主接线。 (六) 确定待建变电所的所用电方案(所用变压器台数、型号、容量和自用电接线型式, 所用电负荷按 变电所容量计) 。 (七) 电气设备选择 1. 为选择电器设备和继电器保护整定需要,计算三相短路电流。 2. 选择变电所电气一次设备(断路器、隔离开关、PT、CT、母线、避雷器及中性点接地 设备) 。 (八) 继电保护 根据继电保护要求,确定变电所各元件继电保护配置。 ...... [摘要]: 本设计说明书是根据毕业设计任务书的要求,结合“电气设备”“电力系统暂态分析”“电 、 、 力系统稳态分析”“继电保护”“电气工程专业毕业设计指南”等有关书籍而制定的,是我 、 、 三年大学学习的总结。 三年中,在授课老师的指导下,学到了很多的知识,对我的学习生涯和社会实践生活有很大 的促进使我不断的挑战自我、充实自己,不仅思想上有了大的收获,知识上也有质的突破。 同时也注重于将所学习的知识运用与实际工作中 ,增强了处理分析问题的能力。 这次设计的新建 110KV 变电所本着为国民经济各个部门提供充足的电能,最大限度地满足 用户的用电需要,保证供电的可靠性,保证良好的电能质量,提高电力系统运行经济性的原 则进行设计。是针对接入系统设计:确定接入系统输电线路回路数及导线截面。地区供电系 统设计: 根据地区负荷性质及供电距离, 确定供电线路数及导线截面。 通过技术、 经济比较, 确定变电所主变压器台数及容量、 型号、 规格。 通过电压计算、 选择主变分接头或调压方式。 根据所确定的主变方案和进出线回路数,通过技术分析、论证,确定待建变电所的主接线。 确定待建变电所的所用电方案(所用变压器台数、型号、容量和自用电接线型式,所用电负 荷按 变电所容量计) 。电气设备选择:为选择电器设备和继电器保护整定需要,计算三 相短路电流。选择变电所电气一次设备(断路器、隔离开关、PT、CT、母线、避雷器及中 性点接地设备) 。继电保护根据继电保护要求,确定变电所各元件继电保护配置。 Prolegomenon This design explains is basis of graduate design assignment book, combine bear on book that 《electric equipment》 、 《electric system steady condition analyzing》 、 《relay safeguard》 、 《electric engineering specialty enchiridion of graduate design》,this is my summarize of three years in university . In three years, depend on teachers go to supervise, acquire many knowledge, promote me that learning 、 work and live, ceaseless challenge me and enrich me, not only my inwardly harvest and that go up knowledge. Likewise pay attention to in the work. This time design of 110KV substation tenet that in order to afford ample electricity of country every department, ensure power supply, ensure power supply finer quality, and promote electric system economy. This time design of running system design (fix on transmit electricity circuitry loops of running system and section of circuitry); fix on number that mains transformer of substation, and capability 、type、specification; compute voltage、choose tap place, compare economy and technology; fix on power supply blue print of substation; compute electrical current of three route short circuit ; choose electric equipment (breaker、seclusion switch、PT、CT、 generatrix、arrester、grounding equipment )and relay safeguard , fix on relay safeguard configure of substation. [参考文献]: 1.《发电厂电气部分课程设计参考资料》 水力电力出版社 2.《电力系统设计设备参考资料》 河海大学出版社 3.《电力系统稳态分析》 水力电力出版社 4.《电力系统暂态分析》 水力电力出版社 5.《电力工程设计手册》 水力电力西北电力设计院 6.《发电厂电气部分》 水力电力出版社 7.《电力系统继电保护原理》 水力电力出版社 8.《电力系统课程设计及毕业参考资料》 中国电力出版社
景德镇瓷器
[1]ROVITHAKIS G A. Stable adaptive neuro-control design via Lyapunov function derivative estimation [ J ]. Automatica, 2001 37 (8):1213- 1221.[2]王源,胡寿松,吴庆宪.一类非线性系统的自组织模糊CMAC神经网络重构跟踪控制[J].控制理论与应用,2003,20(1):70-77.(WANG Yuan, HU Shousong, WU Qingxian. Adaptive reconfigurable tracking control of a class of nonlinear systems based on self-organizing fuzzy CMAC neural networks [ J ]. Control Theory & Applications, 2003,20(1 ) :70 - 77. )[3]LEWIS F L, YESILDIREK A, LIU K. Multilayer neural net robot controller:structure and stability proofs [ J]. IEEE Trans on Neural Networks, 1996,7(2) :388 - 399.[4]金波,俞亚新.一种自适应CMAC神经元网络控制器及其在水轮调速器中的应用[J].控制理论与应用,2002,19(6):905-908.( JIN Bo, YU Yaxin. Adaptive CMAC controller for hydraulic turbine speed governor [ J ]. Control Theory & Applications, 2002, 19 (6):905 - 908. )[5]CHEN F C, KHALIL H K. Adaptive control of nonlinear systems using neural networks [J]. Int J Control, 1992,55(6): 1299 - 1317.[6]牛玉刚,邹云,杨成梧.基于神经网络的一类非线性系统自适应跟踪控制[J].控制理论与应用,2001,18(3):461-464.( NIU Yugang, ZOU Yun, YANG Chengwu. Neural network-based adaptive tracking control for a class of nonlinear systems [ J]. Control Theory & Application, 2001,18 ( 3 ): 461 - 464. )[7]李翔,陈增强,袁著祉.非最小相位非线性系统的简单递归神经网络控制[J].控制理论与应用,2001,18(3):456-460.(LI Xiang,CHEN Zengqiang, YUAN Zhuzhi. Simple recurrent neural network control for non-minimum phase nonlinear system [ J ]. Control Theory &Application ,2001,18(3) :456 - 460. )[8]CHEN S, BILLINGS S A, GRANT P M. Recursive hybrid algorithm for nonlinear system identification using radial basis function networks [J]. Int J Control, 1992,55(5): 1050 - 1070.[9]BROWN M, HARRIS C J. Neurofuzzy Adaptive Modeling and Control [M].Hertfordshire: Prentice Hall International (UK) Limited,1994.[10]LIN C T, LEE G C S. Neural Fuzzy Systems-A Neuro-fuzzy Synergism to Intelligent Systems [M].New York: Prentice Hall Inc. ,A Simon & Schuster Company, 1996.[11]GE S S, LEE T H, HARRIS C J. Adaptive Neural Network Control of Robotic Manipulators [ M]. Singapore: World Scientific, 1998.[12]孙富春,孙增圻,张钹.机械手神经网络稳定自适应控制的理论与方法[M].北京:高等教育出版社,2004.(SUN Fuchun, SUN Zengqi, ZHANG Bo. Theory and Approaches for Stable Adaptive Control of Robotic Manipulators Using Neural Networks [M]. Beijing: Higher Education Press,2004. )[13]WIDROW B. The original adaptive neural net broom-balancer[ C ]//Proc of IEEE Int Symposium on Circuits and Systems. Piscataway,NJ:IEEE Press, 1987:351 - 357.[14]ALBUS J approach to manipulator control:the cerebellar model articulation controller (CMAC) [ J]. J of Dynamics Systems,Measurement and Control, 1975,97 ( 3 ): 220 - 227.[15]HOPFIELD J J, TANK D W. Computing with neural circuits: A model [ J]. Science, 1986,233:625 - 633.[16]RUMELHART D E, MCCLELLAND J L. Parallel Distributed Processing : Explorations in the Microstructure of Cognition [ M]. Cambridge, MA: MIT Press, 1986.[17]WANG Jeen-Shing, LEE G C S. Self-adaptive recurrent neuro-fuzzy control of an autonomous underwater vehicle [ J ]. IEEE Trans on Robotics and Automation, 2003,19 ( 2 ): 283 - 295.[18]DIAO Yixin, PASSINO K M. Adaptive neural/fuzzy control for interpolated nonlinear systems [ J ]. IEEE Trans on Fuzzy Systems,2002,10(5) :582 - 595.[19]达飞鹏,宋文忠.基于模糊神经网络的滑模控制[J].控制理论与应用,2000:17(1):128-132.(DA Feipeng,SONG Wenzhong. Sliding mode control based on the fuzzy neural networks [ J ]. Control Theory & Applications, 2000,17(1):128- 132.)[20]DENG Hui, SUN Fuchun, SUN Zengqi. Observer-based adaptive controller design of flexible manipulators using time-delay neurofuzzy networks [J]. J of Intelligent and Robotic Systems,2002,34(34) :453 - 466.[21]LIU Huaping, SUN Fuchun, HE Kezhong, et al. Controller design and stability analysis for fuzzy singularly perturbed systems [ J]. Acta Automatica Sinica ,2003,29(4) :494 - 500.[22]胡寿松,周川,胡维礼.基神经网络的模型跟随鲁棒自适应控制[J].自动化学报,2000,26(5):623-629.(HU Shousong, ZHOU Chuan, HU Weili. Model-following robust adaptive control based on neural networks [ J ]. Acta Automatica Sinica ,2000,26(5) :623 - 629. )[23]PARTRICIA Melin, OSCAR Castrilio. Intelligent adaptive control of non-linear dynamical systems with a hybrid neuro-fuzzy-genetic approach [C]//Proc of IEEE Int Conf on Systems, Man, and Cybernetics. Piscataway,NJ: IEEE Press, 2001:1508 - 1513.[24]LEE Ching-hung,LIN Yu-hing,LAI Wei-yu. Systems identification using type-2 fuzzy neural network (type-2 FNN) systems [C]//Proc of 2003 IEEE Int Symposium on Computational Intelligence in Robotics and Automation. Piscataway, NJ: IEEE Press, 2003:1264 -1269.[25]PARTRICIA M, OSCAR C. A new method for adaptive model-based control of nonlinear plants using type-2 fuzzy logic and neural networks [C]//Proc of IEEE Int Conf on Fuzzy Systems. Piscataway,NJ: IEEE Press, 2003: 420 - 425.[26]MENDELAND J M, BOB John R I. Type-2 fuzzy sets made simple [J]. IEEE Trans on Fuzzy Systems,2002,10(2): 117 - 127.[27]Ezhov A A, Khromov A G, Berman G P. Analog quantum neuron for functions approximation [ C ]//Proc of Int Joint Conf on Neural Networks. Piscataway,NJ: IEEE Press, 2001,2:1577 - 1582.[28]SANNER R M, SLOTINE J J E. Stable adaptive control and recursive identification using radial Gaussian networks [ C ]//Proc of IEEE Conf on Decision and Control. Piscataway, NJ: IEEE Press,1991:2116-2123.[29]POLYCARPOU M M, IOANNOU P S. Identification and control of nonlinear systems using neural network models: design and stability analysis EE-Report 91 - 09 - 01 [ R ]. Los Angeles: University of Southem California, 1991.[30]SANCHEZ E N, BERNAL M A. Adaptive recurrent neural control for nonlinear system tracking [ J ]. IEEE Trans on Systems, Man,and Cybernetics, Part B: Cybernetics, 2000,30( 6 ): 886 - 889.[31]SUN Fuchun, LI HanXiong, LI Lei. Robot discrete adaptive control based on dynamic inversion using dynamical neural networks [ J ].Automatica, 2002,38 ( 11 ): 1977 - 1983.[32]SANNER R M, SLOTINE J J E. Structurally dynamic wavelet networks for the adaptive control of uncertain robotic systems [ C ]//Proc of the 34 th IEEE Conf on Decision and Control. Piscataway,NJ: IEEE Press, 1995: 2460 - 2467.[33]POLYCARPOU M M. Stable adaptive neural control scheme for nonlinear systems [ J]. IEEE Trans on Automatic Control, 1996,41(3) :447 - 451.[34]SUN Fuchun, SUN Zengqi, WOO Pengyun. Neural network-based adaptive controller design of robot manipulators with an observer [ J]. IEEE Trans on Neural Networks ,2001,12( 1 ) :54 - 67.[35]NARENDRA K S, PARTHASARATHY K. Identification and control of dynamical systems using neural networks [ J ]. IEEE Trans on Neural Networks, 1990,1(1) :4 - 27.[36]ROVITHAKIS G A. Tracking control of multi - input affine nonlinear dynamical systems with unknown nonlinearities using dynamical neural networks [ J]. IEEE Trans on Systems, Man, and Cybernetics-Part B: Cybernetics, 1999,29(2): 179 - 189.[37]GE S S, LI G Y, LEE T H. Adaptive NN control for a class of strictfeedback discrete-time nonlinear systems [ J ]. Automatica, 2003,39(5) :807 - 819.[38]JAGANNATHAN S, LEWIS F L. Multilayer discrete-time neural-net controller with guaranteed performance [ J ]. IEEE Trans on Neural Networks, 1996,7 ( 1 ): 107 - 130.[39]SUN Fuchun, SUN Zengqi, WOO Pengyan, Stable neural networkbased adaptive control for sampled-data nonlinear systems [ J]. IEEE Trans on Neural Networks, 1998,9(5) :956 - 968.[40]CHENG C M, REES N W. Stability analysis of fuzzy multivariable systems: vector Lyapunov function approach [ J]. IEE Proceeding of Control Theory, 1997,144(5) :403 - 412.[41]SUN Fuchun, SUN Zengqi, FENG Gang. An adaptive fuzzy controller based on sliding mode for robot manipulators [ J ]. IEEE Trans on Systems, Man, and Cybernetics- Part B: Cybernetics,1999,29(5) :661 - 667.[42]TANAKA K, WANG H O. Fuzzy Control Systems Design and Analysis-A Linear Matrix Inequality Approach [M] .New York:John Wiley & Sons, Inc. ,2001.[43]TANIGUCHI T, TANAKA K, WANG H O. Fuzzy descriptor systems and nonlinear model following control [ J ]. IEEE Trans on Fuzzy Systems, 2000,8 (4): 442 - 452.[44]WU S J, LIN C T. Optimal fuzzy controller design: local concept [J] .IEEE Trans on Fuzzy Systems,2000,8(2): 171 - 185.[45]WU S J, LIN C T. Discrete-time optimal fuzzy controller design:global concept approach [ J]. IEEE Trans on Fuzzy Systems, 2002,10(1) :21 - 38.[46]CAO S G, REES N W, FENG G. H∞ control of uncertain fuzzy continuous - time systems [ J ]. Fuzzy Sets and Systems, 2000,115 (2):171 - 190.
Electric Automation 电气自动化ELECTRIC AUTOMATION DEVICE AND METHOD FOR ADJUSTING THE
第一篇:PLC对电气自动化控制的应用论文 引言 随着高新技术的发展,自动化系统逐渐应用到工业生产领域。PLC技术的应用,不仅解决了传统电气控制系统内部结构复杂,
转眼间大学生活即将结束,毕业生要通过最后的毕业论文,毕业论文是一种比较正规的、比较重要的检验学生学习成果的形式,毕业论文我们应该怎么写呢?以下是我整理的电气自动
电气工程自动化工程控制体系则是社会工业化发展的关键,是其应用和功能表达的按钮和键盘 。下文是我为大家搜集整理的关于电气工程自动化专科毕业论文的内容,欢迎大家阅读
随着我国科学技术的不断发展,电气工程及其自动化系统的建设与发展在人们的生活中也有很大的作用。下面是我为大家整理的电气工程及其自动化专业 毕业 论文,供大家参