基于FPN推理的多Agent网络故障诊断系统模型的研究
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摘要
信息技术的高速发展给人们带来了极大的方便,但与此同时,发展中的信息网络也给人们提出了挑战,主要体现在网络设备复杂化使网络管理变得复杂,网络的经济效益越来越依赖网络的健壮运行。网络故障诊断的重要性越来越突出,网络故障诊断技术的研究,特别是网络的智能诊断技术研究已成为目前一个重要的研究领域。
目前,基于多Agent的故障诊断系统能够有效的提高故障诊断的灵活性,加快诊断速度。在传统的多Agent诊断系统中,故障诊断过程往往采用案例与专家系统相结合的推理方式。基于规则的专家系统具有规则表现形式易读、知识变更容易,解释方便、推理过程简单等优点,但是存在知识获取困难及逻辑推理的组合爆炸问题。模糊Petri网是基于模糊产生式规则的良好建模工具,可以很好的描述网络故障的动态产生和传播过程。因此,本文提出一种基于FPN推理的多Agent网络故障诊断模型,即在模块化的多Agent诊断模型中,使用模糊Petri网推理算法进行网络故障诊断专家系统的推理,结合实例给出推理结果的可信度,并对系统性能进行了分析。
本文的主要研究工作如下:
(1)分析了模糊Petri网推理机制,探讨了模糊Petri网构建过程中的约简方法,研究了模糊petri网推理算法。
(2)提出基于FPN推理算法的网络故障诊断方法,并将FPN推理算法嵌入多Agent诊断模块中,设计出一个基于多Agent的网络故障诊断系统模型,详细描述了系统模型中各组成部分的作用和各个模块的工作原理。
(3)从JAVA语言角度,对系统各模块功能进行了设计。针对网络故障实例,进行故障诊断推理,最后进行了性能分析。
The high speed developed information technique bring people tremendous convenience, but at the same time, the information network in the development also put forward a challenge to people, which the network equipments' complication makes the network management become more complicated, the economic performance of network depends on the stabilize movement of network more and more. The research of the network fault diagnosis, especially intelligent diagnosis, has become an important field currently.
Currently, fault diagnosis system based on multi-agent can raise the vivid of fault diagnosis effectively and release the diagnosis time. In the traditional multi-agent diagnosis system, fault diagnosis often uses the reasoning method that combining the case and the expert system. The expert system based on the rule has the advantage that the rule is easy to read, the changing, explaining and the reasoning is easy, but it has the problem, for example: the difficult to get the knowledge, the explosion during the logic reasoning. The fuzzy petri net (FPN) is a model tool based on the fuzzy rule, it can distribute the fault state creation and speed of the network. Therefore, this article puts forward a kind of network fault diagnosis model, which using fuzzy petri net reasoning diagnose the network fault in the model based on the multi-agent, it get the credibility during an example and analyze the system function.
The researches of this thesis include:
(1) To analyze the backward reasoning algorithm and discuss the method of simplifying a FPN model to reduce the calculation complexity.
(2) The FPN reasoning is embedded into the diagnosis module of the mobile agent. The network fault diagnosis method based on fuzzy petri net reasoning is proposed. The function of the components and the working principle of the module are minutely illuminated.
(3) The model is descripted using Java language. Taking a network fault for example, the diagnosis reasoning is circulated. At last the performance is analyzed.
目前,基于多Agent的故障诊断系统能够有效的提高故障诊断的灵活性,加快诊断速度。在传统的多Agent诊断系统中,故障诊断过程往往采用案例与专家系统相结合的推理方式。基于规则的专家系统具有规则表现形式易读、知识变更容易,解释方便、推理过程简单等优点,但是存在知识获取困难及逻辑推理的组合爆炸问题。模糊Petri网是基于模糊产生式规则的良好建模工具,可以很好的描述网络故障的动态产生和传播过程。因此,本文提出一种基于FPN推理的多Agent网络故障诊断模型,即在模块化的多Agent诊断模型中,使用模糊Petri网推理算法进行网络故障诊断专家系统的推理,结合实例给出推理结果的可信度,并对系统性能进行了分析。
本文的主要研究工作如下:
(1)分析了模糊Petri网推理机制,探讨了模糊Petri网构建过程中的约简方法,研究了模糊petri网推理算法。
(2)提出基于FPN推理算法的网络故障诊断方法,并将FPN推理算法嵌入多Agent诊断模块中,设计出一个基于多Agent的网络故障诊断系统模型,详细描述了系统模型中各组成部分的作用和各个模块的工作原理。
(3)从JAVA语言角度,对系统各模块功能进行了设计。针对网络故障实例,进行故障诊断推理,最后进行了性能分析。
The high speed developed information technique bring people tremendous convenience, but at the same time, the information network in the development also put forward a challenge to people, which the network equipments' complication makes the network management become more complicated, the economic performance of network depends on the stabilize movement of network more and more. The research of the network fault diagnosis, especially intelligent diagnosis, has become an important field currently.
Currently, fault diagnosis system based on multi-agent can raise the vivid of fault diagnosis effectively and release the diagnosis time. In the traditional multi-agent diagnosis system, fault diagnosis often uses the reasoning method that combining the case and the expert system. The expert system based on the rule has the advantage that the rule is easy to read, the changing, explaining and the reasoning is easy, but it has the problem, for example: the difficult to get the knowledge, the explosion during the logic reasoning. The fuzzy petri net (FPN) is a model tool based on the fuzzy rule, it can distribute the fault state creation and speed of the network. Therefore, this article puts forward a kind of network fault diagnosis model, which using fuzzy petri net reasoning diagnose the network fault in the model based on the multi-agent, it get the credibility during an example and analyze the system function.
The researches of this thesis include:
(1) To analyze the backward reasoning algorithm and discuss the method of simplifying a FPN model to reduce the calculation complexity.
(2) The FPN reasoning is embedded into the diagnosis module of the mobile agent. The network fault diagnosis method based on fuzzy petri net reasoning is proposed. The function of the components and the working principle of the module are minutely illuminated.
(3) The model is descripted using Java language. Taking a network fault for example, the diagnosis reasoning is circulated. At last the performance is analyzed.
引文
[1] Jacobson V, Nichols K, Poduru K.An Expedited Forwarding PHB. IETF Internet RFC 2598,1999
[2] 马平,王英敏,张建等.基于遗传优化神经网络的故障诊断研究[J].微计算机信息,2007. 23(10): 142-143
[3] 赵文清,朱永利,张小奇等.粗糙集理论在电为变压器故障诊断中的应用[J].仪器仪表学报,2006. 27(6): 1722-1723
[4] 杨奎河,单甘霖,赵玲玲.最小二乘支持向量机在故障诊断中的应用[J].计算机科学, 2007. 34(1): 289-291
[5] 程涛.基于移动 Agent 的网络故障管理系统的研究与实现[D].硕士论文学位论文,合肥:合肥工业大学,2007 年
[6] 何永勇,褚福磊,陈真勇.基于多 Agent 的分布式故障智能诊断原型系统研究[J].计算机工程与科学,2002,24(1):88-92
[7] R.P16sch, R. Weinreich.An Agent-Based Environment for Remote Diagnosis, Supervision and Control[C]. In:Proceedings of the International Computer Science Conference, ICSC99, Hongkong, 1999,Dec.13-15,
[8] 黎洪生,刘俊刚,王为东.基于多 Agent 的远程故障诊断系统架构研究[J].计算机应用,2001,21(8):9-10
[9] 李祯,倪天倪.基于 Agent 的智能决策支持系统模型的研究及应用[J].计算机工程, 2002,28(5): 120-122
[10] 赵林度.多 Agent 诊断任务的执行与评价策略[J].管理工程学报,2003,17(2): 86-89
[11] 夏敬华,陆宝春,张卫,等.多 Agent 诊断系统的几个问题研究[J].系统工程理论与实践, 2000,2: 21-27
[12] 朱平,黄文虎,姜兴谓.基于 Agent 卫星故障诊断系统的开发研究[J].空间科学学报,1999,19(1): 76-81
[13] 李琦,王坚,张浩,等.Multi-agent 技术在远程诊断与维护系统中的应用[J].计算机工程, 2002,28(2): 137-139
[14] Looney C.G. Fuzzy Petri nets and application [C]. In: Tzafestas S.G. et al Fuzzy Reasoning in Information, Decision and Control Systems. Norwell, MA: Kluwer Academic Publishers, 1994,511-527.
[15] 林闯. 随机Petri模型的精化设计[J].软件学报,2000,11(1):104-109
[16] 乐晓波,庹清,何小飞,汪琳.时间Petri 网应用及其分析技术[J].吉首大学学报, 2001, 22(3): 65-68
[17] K.Jensen. An Introduction to the Theoretical Aspects of Coloured Petri nets [M]. Computer Science 1994,230-272.
[18] 袁崇义.Petri网原理与应用[M].北京:机械工业出版社,2005
[19] 蒋昌俊.Petri网的行为理论及其应用[M].北京:高等教育出版社,2003
[20] 鲍培明.基于BP网络的模糊Petri网的学习能力[J].计算机学报,2004, 27(5): 695-702
[21] 贾立新等.采用模糊Petri网的形式化推理算法及其应用[J].西安交大学报, 2003, 37(12): 1263-1266
[22] 李夏.基于 Petri 网的故障诊断技术研究及其在液压系统中的应用[D].博士学位论文,上海:同济大学,2006
[23] M. Gao, M. - C. Zhou. Fuzzy reasoning Petri nets for demanufacturing process decision. Electronics and the Environment[C]. In: Proceedings of the 2001 IEEE International Symposium, 2001,7-9:167-172
[24] 鲍培明.模糊 Petri 网模型的反向推理算法[J].南京师范大学学报,2003,3 (3):21-25
[25] Shyi-Ming Chen. Fuzzy backward reasoning using fuzzy Petri nets[C]. In: Systems, Man and Cybernetics, Part B, IEEE Transactions, 2000,30 (6): 846-856
[26] Shyi-Ming Chen, Jyh-Sheng Ke, Jin-Fu Chang. Knowledge representation using fuzzy Petri nets[C]. In: Knowledge and Data Engineering, IEEE Transactions, 1990,2(3): 311-319
[27] E.C.C.Tsang, D.S.Yeung, J.WT Lee. Learning capability in fuzzy Petri nets[C]. In: Systems, Man, and Cybernetics, 1999. IEEE SMC Conference Proceedings, 1999,3(12-15): 355-360
[28] R.P Brent. Fast training algorithms for multilayer neural nets. Neural Networks[C]. In: IEEE Transactions, May 1991,2(3): 346-354
[29] Wen Yu, F.Lara-Rosano. Dynamic knowledge inference and learning under adaptive fuzzy Petri net framework[C]. In: Systems, Man and Cybernetics, Part C, IEEE Transactions, 2000,30(4): 442-450
[30] C.G. Looney. Fuzzy Petri nets for rule-based decisionmaking[C]. In: Systems, Man and Cybernetics, IEEE Transactions,1988,18(1):178-183
[31] 江志斌.Petri 网及其在制造系统建模与控制中的应用[M].北京:机械工业出版社,2004
[32] 黄玉燕,詹素华.故障诊断的模糊 Petri 网模型[J].集美大学学报(自然科学版),2002,7(3):237-241
[33] 王蓓蓓等.基于模糊 Petri 网的知识表示方法在变压器故障诊断专家系统中的应用[J].电力系统及其自动化学报,2003,15(1):74-77
[34] 王楠等.基于粗糙集理论与模糊 Petri 网络的油浸电力变压器综合故障诊断[J].中国电机工程学报,2003,23(12):127-132
[35] 王建元,纪延超.模糊 Petri 网络知识表示方法及其在变压器故障诊断中的应用[J].中国电机工程学报,2003,23(1):121-125
[36] Shyi-Ming Chen. Weighted Fuzzy Reasoning Using Weighted Fuzzy Petri Nets[C]. In: IEEE Transactions on Knowledge and Data Engineering, 2002,14 (2): 386-397
[37] Meimei Gao, Zhiming Wu, MengChu Zhou. A Petri net-based formal reasoning algorithm for fuzzy production rule-based systems. Systems, Man, and Cybernetics, 2000 IEEE International Conference, 2000, 4 (8-11): 3093-3097
[38] 谭旭.模糊 Petri 网在网络故障诊断中的应用研究[硕士论文]长沙:长沙理工大学,2005 年
[39] Shyi-Ming Chen. Fuzzy backward reasoning using fuzzy Petri nets[C]. In: Systems, Man and Cybernetics, Part B, IEEE Transactions, 2000,30 (6): 846-856
[40] 赵龙文,候义斌.多 AGENT 系统及其组织结构[J].计算机应用研究,2000,(7): 12-14
[41] 周立柱,赵洪彪.Internet 环境中的软件 Agent[J].计算机科学, 1999,(3): 24-28
[42] 颜跃进,李舟君,陈跃新.多 Agent 系统体系结构[J].计算机科学, 1999, 28(5): 32-36
[43] Jennings N R, Sycara K, Wooldridge M. A roadmap of agent research and development. Autonomous Agents and Multi-Agent Systems, 1998, (1): 7-38
[44] 胡舜耕,张莉,钟义信.多 Agent 系统的理论、技术及其应用[J].计算机科学, 1999, 26(9): 20-24
[2] 马平,王英敏,张建等.基于遗传优化神经网络的故障诊断研究[J].微计算机信息,2007. 23(10): 142-143
[3] 赵文清,朱永利,张小奇等.粗糙集理论在电为变压器故障诊断中的应用[J].仪器仪表学报,2006. 27(6): 1722-1723
[4] 杨奎河,单甘霖,赵玲玲.最小二乘支持向量机在故障诊断中的应用[J].计算机科学, 2007. 34(1): 289-291
[5] 程涛.基于移动 Agent 的网络故障管理系统的研究与实现[D].硕士论文学位论文,合肥:合肥工业大学,2007 年
[6] 何永勇,褚福磊,陈真勇.基于多 Agent 的分布式故障智能诊断原型系统研究[J].计算机工程与科学,2002,24(1):88-92
[7] R.P16sch, R. Weinreich.An Agent-Based Environment for Remote Diagnosis, Supervision and Control[C]. In:Proceedings of the International Computer Science Conference, ICSC99, Hongkong, 1999,Dec.13-15,
[8] 黎洪生,刘俊刚,王为东.基于多 Agent 的远程故障诊断系统架构研究[J].计算机应用,2001,21(8):9-10
[9] 李祯,倪天倪.基于 Agent 的智能决策支持系统模型的研究及应用[J].计算机工程, 2002,28(5): 120-122
[10] 赵林度.多 Agent 诊断任务的执行与评价策略[J].管理工程学报,2003,17(2): 86-89
[11] 夏敬华,陆宝春,张卫,等.多 Agent 诊断系统的几个问题研究[J].系统工程理论与实践, 2000,2: 21-27
[12] 朱平,黄文虎,姜兴谓.基于 Agent 卫星故障诊断系统的开发研究[J].空间科学学报,1999,19(1): 76-81
[13] 李琦,王坚,张浩,等.Multi-agent 技术在远程诊断与维护系统中的应用[J].计算机工程, 2002,28(2): 137-139
[14] Looney C.G. Fuzzy Petri nets and application [C]. In: Tzafestas S.G. et al Fuzzy Reasoning in Information, Decision and Control Systems. Norwell, MA: Kluwer Academic Publishers, 1994,511-527.
[15] 林闯. 随机Petri模型的精化设计[J].软件学报,2000,11(1):104-109
[16] 乐晓波,庹清,何小飞,汪琳.时间Petri 网应用及其分析技术[J].吉首大学学报, 2001, 22(3): 65-68
[17] K.Jensen. An Introduction to the Theoretical Aspects of Coloured Petri nets [M]. Computer Science 1994,230-272.
[18] 袁崇义.Petri网原理与应用[M].北京:机械工业出版社,2005
[19] 蒋昌俊.Petri网的行为理论及其应用[M].北京:高等教育出版社,2003
[20] 鲍培明.基于BP网络的模糊Petri网的学习能力[J].计算机学报,2004, 27(5): 695-702
[21] 贾立新等.采用模糊Petri网的形式化推理算法及其应用[J].西安交大学报, 2003, 37(12): 1263-1266
[22] 李夏.基于 Petri 网的故障诊断技术研究及其在液压系统中的应用[D].博士学位论文,上海:同济大学,2006
[23] M. Gao, M. - C. Zhou. Fuzzy reasoning Petri nets for demanufacturing process decision. Electronics and the Environment[C]. In: Proceedings of the 2001 IEEE International Symposium, 2001,7-9:167-172
[24] 鲍培明.模糊 Petri 网模型的反向推理算法[J].南京师范大学学报,2003,3 (3):21-25
[25] Shyi-Ming Chen. Fuzzy backward reasoning using fuzzy Petri nets[C]. In: Systems, Man and Cybernetics, Part B, IEEE Transactions, 2000,30 (6): 846-856
[26] Shyi-Ming Chen, Jyh-Sheng Ke, Jin-Fu Chang. Knowledge representation using fuzzy Petri nets[C]. In: Knowledge and Data Engineering, IEEE Transactions, 1990,2(3): 311-319
[27] E.C.C.Tsang, D.S.Yeung, J.WT Lee. Learning capability in fuzzy Petri nets[C]. In: Systems, Man, and Cybernetics, 1999. IEEE SMC Conference Proceedings, 1999,3(12-15): 355-360
[28] R.P Brent. Fast training algorithms for multilayer neural nets. Neural Networks[C]. In: IEEE Transactions, May 1991,2(3): 346-354
[29] Wen Yu, F.Lara-Rosano. Dynamic knowledge inference and learning under adaptive fuzzy Petri net framework[C]. In: Systems, Man and Cybernetics, Part C, IEEE Transactions, 2000,30(4): 442-450
[30] C.G. Looney. Fuzzy Petri nets for rule-based decisionmaking[C]. In: Systems, Man and Cybernetics, IEEE Transactions,1988,18(1):178-183
[31] 江志斌.Petri 网及其在制造系统建模与控制中的应用[M].北京:机械工业出版社,2004
[32] 黄玉燕,詹素华.故障诊断的模糊 Petri 网模型[J].集美大学学报(自然科学版),2002,7(3):237-241
[33] 王蓓蓓等.基于模糊 Petri 网的知识表示方法在变压器故障诊断专家系统中的应用[J].电力系统及其自动化学报,2003,15(1):74-77
[34] 王楠等.基于粗糙集理论与模糊 Petri 网络的油浸电力变压器综合故障诊断[J].中国电机工程学报,2003,23(12):127-132
[35] 王建元,纪延超.模糊 Petri 网络知识表示方法及其在变压器故障诊断中的应用[J].中国电机工程学报,2003,23(1):121-125
[36] Shyi-Ming Chen. Weighted Fuzzy Reasoning Using Weighted Fuzzy Petri Nets[C]. In: IEEE Transactions on Knowledge and Data Engineering, 2002,14 (2): 386-397
[37] Meimei Gao, Zhiming Wu, MengChu Zhou. A Petri net-based formal reasoning algorithm for fuzzy production rule-based systems. Systems, Man, and Cybernetics, 2000 IEEE International Conference, 2000, 4 (8-11): 3093-3097
[38] 谭旭.模糊 Petri 网在网络故障诊断中的应用研究[硕士论文]长沙:长沙理工大学,2005 年
[39] Shyi-Ming Chen. Fuzzy backward reasoning using fuzzy Petri nets[C]. In: Systems, Man and Cybernetics, Part B, IEEE Transactions, 2000,30 (6): 846-856
[40] 赵龙文,候义斌.多 AGENT 系统及其组织结构[J].计算机应用研究,2000,(7): 12-14
[41] 周立柱,赵洪彪.Internet 环境中的软件 Agent[J].计算机科学, 1999,(3): 24-28
[42] 颜跃进,李舟君,陈跃新.多 Agent 系统体系结构[J].计算机科学, 1999, 28(5): 32-36
[43] Jennings N R, Sycara K, Wooldridge M. A roadmap of agent research and development. Autonomous Agents and Multi-Agent Systems, 1998, (1): 7-38
[44] 胡舜耕,张莉,钟义信.多 Agent 系统的理论、技术及其应用[J].计算机科学, 1999, 26(9): 20-24
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