摘要
本文以锅炉常见故障为对象,通过分析锅炉故障的特点,提出了基于贝叶斯网络的专家系统。对贝叶斯网络理论进行了论述,分别研究了贝叶斯网络的基础理论及贝叶斯网络的网络推理方法。在专家系统的数据库设计中用面向事件的方法来表示浅知识,用面向对象的贝叶斯网络来表示锅炉故障中的不确定知识,在专家系统的推理机种引入了贝叶斯网络团树精确推理方法。建立了一个故障诊断专家系统,并用实例证明了系统在锅炉故障诊断中的有效性。
By analyzing the failure of the characteristics of the boiler, this article considers boiler fault as the common object , then make a expert system based on Bayesian network. We have a discussion on Bayesian network theory, To study the basis of a Bayesian network theory and Bayesian inference methods network of networks. In the expert system database ,using Event-Oriented method to represent the shallow knowledge and using Object-Oriented Bayesian network to represent the knowledge of uncertainty of the failure of boiler, in the expert system inference engine, using Bayesian network group tree accurate method of reasoning. Building a fault diagnosis expert system ,using a example to proof the usefulness of this system in boiler fault diagnosis.
引文
[1]李录平,等.火电机组故障诊断技术的现状与展望.电力情报,1997, (3)
[2]阮跃,等.大型电站状态监测与故障诊断专家系统的研究.电站系统工程,1997 ,(13)
[3]王道平,张义忠.故障智能诊断系统的理论与方法.北京:冶金工业出版2001
[4]刘启元,张聪等.信度网近似推理算法(上)[J].计算机科学,2001,28(1):70-73
[5]李刚.知识发现的图模型方法[D].中国科学院软件研究所,2001:10-18
[6]张培先,董泽,刘吉臻.智能故障诊断技术的发展及应用.山西电力,2001,(3)
[7]叶春等.混合神经网络在汽轮机在线性能分析中的应用研究.动力工程. 1999.Vol.19 .No.5
[8]徐敏等.欧美大型旋转机械监测诊断技术发展近况与综述第四届全国机械设故障诊断学术会议论文集.杭州,1994
[9]李勇等.汽轮机运行性能诊断技术及其应用科学出版社.1999
[10]马国宪等.电站锅炉故障诊断专家系统的研究和应用.动力工程. 1992.Vol.12.No2
[11] Chow M Y et al.. Methodology for on-line incipient fault detection in single-phase squirrel-coge induction motors using artificial neural networks .IE EE Trans On Energy Conversion.1991.
[12] King I J.Chow et al.Plant diagnostics relies on AI transmissions from remote site.Power.1988.No12
[13]华斌,周建中,喻菁.贝叶斯网络在水电机组故障诊断中的应用研究.华北电力大学学报,2004,31(5):33-36
[14] WolbrechtE,AmbrosioBD,PasschB.Monitoring and Diagnosis of A Multi-stage Manufacturing Process Using Bayesian Networks. Artificial Intelligence for Engineering,Design and Manufacturing,2000,14(2): 53-67
[15]王华伟,周经伦.基于贝叶斯网络的复杂系统故障诊断.计算机集成制造系统,2004,10(2),230～234
[16] Jensen FV. Bayesian Network Basics.AISB Quarterly,1996,94:9～22
[17] Charniak E. Bayesian Networks without Tears. AI Magazine,1991,12(4):50～63
[18] Pearl J. Graphical Models for Probabilistic and Causal Reasoning. In: The Computer Science and Engineering Handbook. Kluwer Academic Publishers, 1997:697～714
[19]华斌.贝叶斯网络在水电机组状态检修中的应用研究. [博士学位论文].武汉:华中科技大学,2004
[20]李炜,伦淑娴.设备故障诊断技术的现状及其发展.甘肃工业大学学报199(82)
[21]罗锦,孟晨,苏振中.故障诊断技术的发展和展望.自动化与仪器仪表,2003(2)
[22]关惠玲,等.设备故障诊断专家系统原理及实践.北京:机械工业出社,2000
[23]陈媛,杨武.系统级故障诊断方法概述计算机应用研究,1999,(2)
[24]刘一,智能故障诊断方法研究及应用.[硕士学位论文].昆明:昆明理工大学2003
[25]李凡,邹凡.电力设备故障诊断专家系统.电脑与信息技术,1998(1)
[26]王广盛.工业锅炉运行故障诊断.工业锅炉,1998(1)
[27]冯冬青,姚志红.锅炉运行故障在线诊断研究.郑州工业大学学报,1997(1)
[28]何洁月,张南翔.电厂故障诊断系统设计与实现.工业控制计算机,1998(3)
[29]张尧庭,杜劲松.人工智能中的概率统计方法.北京:科学出版社,1998
[30] Stephenson TA. An Introduction To Bayesian Network Theory And Usage .ID IAP-R R00-03,Feb,2000
[31] Kim J11, Pearl. A Computation Model for Causal and Diagnostic Reasoning in Inference Systems .Proceedings of the 8th International Joint Conference on A1,LosAngeles ,1983,190-193
[32] Jensen FV .An Introduction to Bayesian Networks .UCL Press Ltd ,London, 1996
[33] Charniak1 :.Bayesian Networks without Tears. A l Magazine, 1991.12(4):50-63
[34]陈希孺.概率论与数理统计.合肥:中国科学技术大学出版社,2000
[35]史忠植.知识发现.北京:清华大学出版社,2002
[36]胡小建,杨善林,马溪骏,基于联结树的贝叶斯网的推理结构及构造算法[J].系统仿真学报,2004,16(11):25-26,59-64
[37]张宏辉,唐锡宽.贝叶斯推理网络在大型旋转机械故障诊断中的应用[J].机械科学与技术,1996,25(2):43-46
[38] Pearl J. Belief Networks revisited. Artificial Intelligence,1993,59(1):49-56
[39] Pearl J. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo, CA,1988
[40] Suermondt H, Cooper G. Probabilistic Infererce in Multiply Connected Belief Networks Using Loop Cutsets. Internationnal Journal of Approximate Reasoning,1990,4(4):283-3-6
[41] Pearl J. Fusion, Propagation, and Structuring in Belief Networks. Artificial Intelligence, 1986,29(9):241-288
[42] Lauritzen S L, Dawid A P, Larsen B N, et al. Independence properties of directed markov fields. Networks,1990,20
[43] Shachter R D. Probabilistic Inference and Influence Diagrams. Operations Research, 1988,36:589-605
[44] Shachter R D,D'Ambrosio B, DelFabero B. Symbolic Probabilistic Inference in Belief Networks. Proceedings Eighth National Conference on AI,1990,126-131
[45] Li Zhaoyu, D'Ambrosio B. Efficient Inference in Bayesian Networks As A Combinatorial Optimization Problem. International Journal of Approximate Reasoning ,1994
[46] Dechter R. Bucket Elimination: Aunifying Framework for Probabilistic Inference Proc. 12th Conference on Uncertainty in Artificial Intelligence. Porland, OR, 1996: 211-219
[47] Lepar V ,Shenoy PP .A Comparison of Lauritzen and Spiegelhalter, Hugin and Shafer and Shenoy Architectures for Computing Marginals of Probability Distributions. Proc On Uncertainty in artificial Intelligence, Morgan Kaufmann Publishers, San Francisco, CA, 1998: 328-337
[48] Jensen F, Jensen F V Dittmer SL . From Influence Diagram to Junction Tree. The 10th Conference on Uncertainty in Artificial Intelligence,1994
[49] Madsen A L, Jensen F V. Lazy Propagation in Junction Tree. Proc. Of the Fourteenth Conf. On Uncertainty in Artificial Intelligence, Morgan Kaufmann Publishers, 1998: 362-369
[50] Madsen A L, Jensen F V. A Junction Tree Inference Based on Lazy Evaluation. The Proc. Of the Fourteenth Conf. On Uncertainty in Artificial Intelligence, Morgan Kaufmann Publishers, San Francisco, CA, 1998: 362-369
[51] Skaanning C, ensen F V, Kjarulff U. Printer Troubleshooting Using Bayesian Networks. Industrial and Engineering Applications of Artificial Intelligence and Expert Systems(IEA/All)2000, New Orleans, USA, June, 2000
[52]王双成,林土敏,陆玉昌.用Bayesian网络处理不完整数据的问题分析.清华大学学报(自然科学版),2000,40(9):65-68
[53]李俭川,胡笃庆,秦国军,温熙森.基于故障树的贝叶斯网络建造方法与故障诊断应[J]计算机工程与应用,2003(24):225-228
[54]覃秋梅,张师超一类贝叶斯网络的线性推理计算机科学1999,26(10):67-70
[55] Pearl J. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo, CA, 1988
[56] Coper G F.”The Conputational Complexity of Probabilistic Inference Using Bayesian Belief Networks.”Artificial Intelligence. 1990, 42: 393-405
[57] Neal R M. Probabilistic Inference Using Markov Chain Monte Carlo Methods: Technical Report C RGIR-93-11. Department of Computer Science,University of Toronto. 1993
[58] Henrion M. Search-based Methods to Bound Diagnostic Probabilities in Very Large Belief Nets. Proc. Seventh Workshop on Uncertainty in Artificial Intelligence Los angeles, CA, 1991
[59] Poole D. Average-case Analysis of A Search Algorithm for Estimating Prior and Posterior Probabilities in Bayesian Networks with Extreme Probabilities, Proc. Thirteenth International Joint Conference1993:606-612on Artificial Intelligence, France, August
[60] Poole D. The Use of Conflicts in Searching Bayesian Networks: Technical Report. Department of Computer Science, University of Britis Columgia,March 1993
[61]王军,周伟达.贝叶斯网络的研究与进展.电子科技,1999,11(8):6～7
[62]宋光雄,何永勇,褚福磊.汽轮机振动故障诊断知识信息服务系统.电力系统自动化,2006,17(1):78～82
[63] Geiger D, Heckerman D. A Characterization of The Dirichlet Distribution with Applicable to learning Bayesian Networks. Proceedings of Eleventh Conference on Uncertainty in Artificial Intelligence, Montrcal, QU, 1995: 196-207
[64]胡玉胜,涂序彦,崔晓瑜等.基于贝叶斯网络的不确定性知识的推理方法.计算机集成制造系统-CIMS,2001,7(12):65～68
[65]邢永康,沈一栋.学习信度网的结构.计算机科学,2000, 27 (10): 83-87
[66] Robinson R W. Counting Unlabeled Acyclic Digraphs. In C. H. C. Little, editor, Combinatorial Mathematics V, volume 622 of Lecture Notes in Mathematics, Australia ,1977: 239-273
[67] Friedman N .Learning Belief Networks in the Presence of Missing Values and Hidden Variables. Proceedings of the 14th International Conference on Machine Learning (ICMU97),Morgan Kaufmann, San Francisco,1997
[68] Heckerman D, Mamdani A, Wellman M P. Real-world Applications of Bayesian Networks. Communications of the ACM,19 95.38(3): 24-30
[69] Stephenson T A. An introduction to Bayesian network theory and usage. ID IA P2RR 00203. Zurich:DaleMoll Institute, 2000.
[70] Cooper Greg F, Herskovits E. A Bayesian Method for the induction of probabilistic networks from data. Machine Learning, 1992, 9: 309～347
[71]李俭川,陶利民,胡茑庆,等.设备智能故障诊断和维修支持技术的研究.仪器仪表学报,2002,23(3):244～245
