基于案例推理的机车故障诊断专家系统研究
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摘要
专家系统是一种模拟专家决策能力的计算机系统。论文以机车故障诊断为应用背景，利用人工智能、故障诊断的理论和方法，研究并开发了一个机车故障诊断专家系统原型，以实现对机车故障的智能诊断。
论文在研究目前常用的故障诊断智能技术以及人工智能领域中新兴起的基于案例推理方法的基础上，给出了基于案例推理的机车故障诊断专家系统的设计方案和原型系统。分析和研究了机车故障诊断领域知识特点和大量的故障维修日志，探讨了基于案例推理方法构造专家系统的关键技术，主要包括基于案例推理的知识工程以及案例检索技术。
在运用知识工程技术进行案例的表示、组织以及案例库的构建中，论文根据机车故障诊断领域的特点以及故障诊断专家系统的应用需求，以基于特征的故障案例表示为基础，依据故障的特征属性和内容将机车故障案例按照故障种类分类，从而将整个案例库划分成了多个代表故障案例种类的案例集。在案例检索中，论文基于按故障分类构造机车故障案例库的思想，从故障案例种类中抽取出能与其它种类不同的关键特征，根据故障案例种类的层次结构，进而将整个案例库组织成多级分层索引结构。这种按故障分类，分层索引机制的策略思想不仅降低了案例表示、组织以及案例库的构建难度，而且极大地提高了案例检索的效率。
最后基于上述思想，设计和建立了系统的概念模型、物理模型，并构建了软件原型系统。通过对机车故障样本案例进行仿真测试，表明了设计思想是合理的，实现方法是有效的。
Expert system is a computer system which emulates the decision ability of experts in certain field. Aiming at developing a locomotive fault diagnosis system, the paper proposed a series of approaches to solve the problem encountered in intelligent locomotive fault diagnosis on the basis of artificial intelligence and fault diagnosis.
Based on the research on fault diagnosis technology in common use and burgeoning Case-based reasoning method in artificial intelligence, a scheme and a prototype of Case-based reasoning locomotive fault diagnosis is accomplished. Substantive log of maintenance and the characteristics of the knowledge in locomotive fault diagnosis is analyzed and the key technology of Case-based reasoning fault diagnosis system, such as case-based knowledge engineer and case index technology, is discussed in the paper. The strategy of layered index mechanism after the classification of fault is put forward originally.
In expression and management of case and the construction of knowledge base with case-based technology, the locomotive fault case is classified as case sets by characteristic and detail according to the demand of fault diagnosis expert system and the peculiarity of locomotive fault diagnosis on the foundation of characteristic-based case expression. The multi-layered structure of the knowledge base of the system is formed in accordance with the key characteristic abstracted from fault cases, which reduce the complexity of case expression and management and construction of knowledge base and enhance the index speed and efficiency dramatically.
Based on research above, the conceptual model and physical model is founded and the prototype of the system is finished. The emulation test to the software with locomotive fault cases in field proved the reasonability of the design and the validity of the implementation.
论文在研究目前常用的故障诊断智能技术以及人工智能领域中新兴起的基于案例推理方法的基础上，给出了基于案例推理的机车故障诊断专家系统的设计方案和原型系统。分析和研究了机车故障诊断领域知识特点和大量的故障维修日志，探讨了基于案例推理方法构造专家系统的关键技术，主要包括基于案例推理的知识工程以及案例检索技术。
在运用知识工程技术进行案例的表示、组织以及案例库的构建中，论文根据机车故障诊断领域的特点以及故障诊断专家系统的应用需求，以基于特征的故障案例表示为基础，依据故障的特征属性和内容将机车故障案例按照故障种类分类，从而将整个案例库划分成了多个代表故障案例种类的案例集。在案例检索中，论文基于按故障分类构造机车故障案例库的思想，从故障案例种类中抽取出能与其它种类不同的关键特征，根据故障案例种类的层次结构，进而将整个案例库组织成多级分层索引结构。这种按故障分类，分层索引机制的策略思想不仅降低了案例表示、组织以及案例库的构建难度，而且极大地提高了案例检索的效率。
最后基于上述思想，设计和建立了系统的概念模型、物理模型，并构建了软件原型系统。通过对机车故障样本案例进行仿真测试，表明了设计思想是合理的，实现方法是有效的。
Expert system is a computer system which emulates the decision ability of experts in certain field. Aiming at developing a locomotive fault diagnosis system, the paper proposed a series of approaches to solve the problem encountered in intelligent locomotive fault diagnosis on the basis of artificial intelligence and fault diagnosis.
Based on the research on fault diagnosis technology in common use and burgeoning Case-based reasoning method in artificial intelligence, a scheme and a prototype of Case-based reasoning locomotive fault diagnosis is accomplished. Substantive log of maintenance and the characteristics of the knowledge in locomotive fault diagnosis is analyzed and the key technology of Case-based reasoning fault diagnosis system, such as case-based knowledge engineer and case index technology, is discussed in the paper. The strategy of layered index mechanism after the classification of fault is put forward originally.
In expression and management of case and the construction of knowledge base with case-based technology, the locomotive fault case is classified as case sets by characteristic and detail according to the demand of fault diagnosis expert system and the peculiarity of locomotive fault diagnosis on the foundation of characteristic-based case expression. The multi-layered structure of the knowledge base of the system is formed in accordance with the key characteristic abstracted from fault cases, which reduce the complexity of case expression and management and construction of knowledge base and enhance the index speed and efficiency dramatically.
Based on research above, the conceptual model and physical model is founded and the prototype of the system is finished. The emulation test to the software with locomotive fault cases in field proved the reasonability of the design and the validity of the implementation.
引文
[1] A.I.Mechitov and H.M. Moshkovich. Knowledge Acquisition Tool for CaseBased Reasoning System. Expert System with Application, 1998, vol. 8: 201～212
[2] Aamodt, and Plaza. Case-based Reasoning: Foundational issues, methodological variations, and system approaches. AI Communications, 1997, vol. 7:39～52
[3] Aamodt. Explanation-driven case-based reasoning. In Wess; Althoff, Topics in Case-Based Reasoning, 1999. 274～288
[4] Martin T. Hagan, Howard B. Demuth, Mark H. Beale. Neural Network Design. Proceedings AAAI-91, Anaheim, CA, 2002. 212～275
[5] A. R. Golding, P. S. Rosenbloom. Improving Accuracy by Combining Rule- based and Case-based Reasoning. Artificial Intelligence, 1996, vol. 8: 215～254
[6] Isermann. On the applicability of model based fault detection for technical process. Control Engineering Practice 1999. 439～450
[7] Kyung shin, Ingoo Han. A Case-Based approach using inductive indexing for corporate bond rating. Decision Support Systems, 2001. 41～52
[8] Frank P M. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy:asurvey. Automatica, 1998. 459～474
[9] Michael Masuch, LaszloPolos. Knowledge representation and reasoning under uncertainty. New York: Springer-Verlag, 1999. 276～288
[10] Judea Pearl. Causality:models, reasoning, and inference. CoMBRidge, U.K., New York: CaMBRidge University Press, 2000. 237～252
[11] A. R. Montazei, K. M. Gupta. An Adaptive Agent for Case Description in Diagnostic CBR System. Computer in Industry, 1996, vol. 29: 209～224
[12] B. D. Pomeroy, R. R. Irving. A Blackboard Approach for Diagnosis in Pilot's Associate. IEEE Expert, 1998, vol. 5: 349～360
[13] B. D. Pomeroy, H. A. Spang, M. E. Dauch. Event-based Architecture for Diagnosis in Control Advisory System. Artificial Intelligence in Engineering, 1999, vol. 5: 174～181
[14] B. Falkenhainer, K. D. Forbus. Compositional Modeling: Finding the Right Model for the Job. Artificial Intelligence, 1999, vol. 51: 95～143
[15] B. J. kuippers. Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge. Automative, 1998, vol. 25: 571～585
[16] NilsJ. Nilsson. Artifical Intelligence:A new Synthesis. Int. J. ManMachine Studies, 2002. 223～247
[17] B. V. Dasarathy. Sensor Fusion Potential Exploitation-Innovative Architectures and Illustrative Application. Proceedings of IEEE, 1997, vol. 8: 24～38
[18] 蔡自兴等．人工智能及其应用．清华大学出版社，2000．187～267
[19] 王东，刘怀亮，徐国华．基于案例推理在故障诊断中的应用．计算机工程，2003，29(12)：10～12
[20] 徐明，胡守仁．基于案例属性特征的相似度计算模型研究．武汉理工大学学报，2003，25(1)：24～27
[21] 廖凯，张家栋．基于小波分析的机车转向架振动信号的降噪和故障诊断．铁道机车车辆，2003，16(4)：15～17
[22] 赵树洲，龚二旺．压缩压力检测在柴油机故障诊断中的应用．内燃机车，2003，19(8)．46～47
[23] 黄仁．机械设备的故障诊断与工况监测．东南大学出版社，1996．32～45
[24] 靳暮．神经网络学习样本的研究．98中国神经网络会议文集，1998．167～171
[25] 李昭原，罗晓沛．数据库技术新进展．清华大学出版社，1997．103～126
[26] 于江，王征等．基于案例推理的产品包装设计系统．计算机应用，2003，23(1)：39～40
[27] 刘振越．DF4内燃机车柴油机状态测试与故障诊断．铁道机车车辆，1998，15(3)：49～52
[28] 程瑞琪，杨文栋．基于事例与因果模型的故障诊断．机械科学与技术，1999，18(5)：783～785
[29] 路耀华．思维模拟与知识工程．清华大学出版社，1997．156～289
[30] 屈梁生，何正嘉．机械故障诊断学．上海科学技术出版社，1996．37～127
[31] 张荣梅，周义等．交通事故处理智能决策支持系统(YCIDSS)．计算机应用，2002，22(9)：60～61
[32] 李陶深．人工智能．重庆大学出版社，2002．97～112
[33] 王树德．技术诊断及其在国外内燃机车上的应用．内燃机车，1993，总230(4)：6～11
[34] 王铁峰．东风4型机车临修故障统计分析．内燃机车，1997，总279(4)：32～36
[35] 吴今培，肖健华．智能故障诊断与专家系统．科学技术出版社，1997．207～232
[36] 尹朝庆等．人工智能与专家系统．水利水电出版社，2002．78～179
[37] 钟秉林，颜廷虎．智能化故障诊断理论与方法的研究现状与展望．东南大学学报，1998，18(11)：1～11
[38] 张本生，于永利．基于案例的推理在维修性设计分析中的应用研究．计算机工程，2000，26(11)：69～70
[39] 林尧瑞，马少平．人工智能导论．清华大学出版社，1999．135～228
[40] 于跃海，郑瑞强等．基于案例推理的ICU应急诊断方案生成系统．东南大学学报，2001，31(2)：27～30
[41] 顾大可，俞勇．一个基于案例的动态工作流模型．上海交通大学学报，2001，35(9)：1290～1292
[42] 毛权．CBR中基于实例特征的相似实例检索模型研究．计算机研究与发展，1999，34(3)：27～31
[43] 程瑞琪，周美玉．柴油机诊断技术现状与专家系统策略研究．兰州铁道学院报，1999，18(2)：77～81
[44] 胡运权．基于事例推理的智能模型构建研究．哈尔滨工业大学，博士学位论文，2000
[45] 陈敏等．基于事例推理中事例组织与管理的研究．计算机工程，1994，20(5)：37～40
[46] 朱绍文，吕少鹏，马力等．一个基于实例推理的专家系统．计算机工程与应用，1999，18(1)：17～20
[47] 王国锋，张锡恩．基于安全推理的导弹故障诊断专家系统研究．系统工程与电子技术，1999，21(8)：26～29
[2] Aamodt, and Plaza. Case-based Reasoning: Foundational issues, methodological variations, and system approaches. AI Communications, 1997, vol. 7:39～52
[3] Aamodt. Explanation-driven case-based reasoning. In Wess; Althoff, Topics in Case-Based Reasoning, 1999. 274～288
[4] Martin T. Hagan, Howard B. Demuth, Mark H. Beale. Neural Network Design. Proceedings AAAI-91, Anaheim, CA, 2002. 212～275
[5] A. R. Golding, P. S. Rosenbloom. Improving Accuracy by Combining Rule- based and Case-based Reasoning. Artificial Intelligence, 1996, vol. 8: 215～254
[6] Isermann. On the applicability of model based fault detection for technical process. Control Engineering Practice 1999. 439～450
[7] Kyung shin, Ingoo Han. A Case-Based approach using inductive indexing for corporate bond rating. Decision Support Systems, 2001. 41～52
[8] Frank P M. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy:asurvey. Automatica, 1998. 459～474
[9] Michael Masuch, LaszloPolos. Knowledge representation and reasoning under uncertainty. New York: Springer-Verlag, 1999. 276～288
[10] Judea Pearl. Causality:models, reasoning, and inference. CoMBRidge, U.K., New York: CaMBRidge University Press, 2000. 237～252
[11] A. R. Montazei, K. M. Gupta. An Adaptive Agent for Case Description in Diagnostic CBR System. Computer in Industry, 1996, vol. 29: 209～224
[12] B. D. Pomeroy, R. R. Irving. A Blackboard Approach for Diagnosis in Pilot's Associate. IEEE Expert, 1998, vol. 5: 349～360
[13] B. D. Pomeroy, H. A. Spang, M. E. Dauch. Event-based Architecture for Diagnosis in Control Advisory System. Artificial Intelligence in Engineering, 1999, vol. 5: 174～181
[14] B. Falkenhainer, K. D. Forbus. Compositional Modeling: Finding the Right Model for the Job. Artificial Intelligence, 1999, vol. 51: 95～143
[15] B. J. kuippers. Qualitative Reasoning: Modeling and Simulation with Incomplete Knowledge. Automative, 1998, vol. 25: 571～585
[16] NilsJ. Nilsson. Artifical Intelligence:A new Synthesis. Int. J. ManMachine Studies, 2002. 223～247
[17] B. V. Dasarathy. Sensor Fusion Potential Exploitation-Innovative Architectures and Illustrative Application. Proceedings of IEEE, 1997, vol. 8: 24～38
[18] 蔡自兴等．人工智能及其应用．清华大学出版社，2000．187～267
[19] 王东，刘怀亮，徐国华．基于案例推理在故障诊断中的应用．计算机工程，2003，29(12)：10～12
[20] 徐明，胡守仁．基于案例属性特征的相似度计算模型研究．武汉理工大学学报，2003，25(1)：24～27
[21] 廖凯，张家栋．基于小波分析的机车转向架振动信号的降噪和故障诊断．铁道机车车辆，2003，16(4)：15～17
[22] 赵树洲，龚二旺．压缩压力检测在柴油机故障诊断中的应用．内燃机车，2003，19(8)．46～47
[23] 黄仁．机械设备的故障诊断与工况监测．东南大学出版社，1996．32～45
[24] 靳暮．神经网络学习样本的研究．98中国神经网络会议文集，1998．167～171
[25] 李昭原，罗晓沛．数据库技术新进展．清华大学出版社，1997．103～126
[26] 于江，王征等．基于案例推理的产品包装设计系统．计算机应用，2003，23(1)：39～40
[27] 刘振越．DF4内燃机车柴油机状态测试与故障诊断．铁道机车车辆，1998，15(3)：49～52
[28] 程瑞琪，杨文栋．基于事例与因果模型的故障诊断．机械科学与技术，1999，18(5)：783～785
[29] 路耀华．思维模拟与知识工程．清华大学出版社，1997．156～289
[30] 屈梁生，何正嘉．机械故障诊断学．上海科学技术出版社，1996．37～127
[31] 张荣梅，周义等．交通事故处理智能决策支持系统(YCIDSS)．计算机应用，2002，22(9)：60～61
[32] 李陶深．人工智能．重庆大学出版社，2002．97～112
[33] 王树德．技术诊断及其在国外内燃机车上的应用．内燃机车，1993，总230(4)：6～11
[34] 王铁峰．东风4型机车临修故障统计分析．内燃机车，1997，总279(4)：32～36
[35] 吴今培，肖健华．智能故障诊断与专家系统．科学技术出版社，1997．207～232
[36] 尹朝庆等．人工智能与专家系统．水利水电出版社，2002．78～179
[37] 钟秉林，颜廷虎．智能化故障诊断理论与方法的研究现状与展望．东南大学学报，1998，18(11)：1～11
[38] 张本生，于永利．基于案例的推理在维修性设计分析中的应用研究．计算机工程，2000，26(11)：69～70
[39] 林尧瑞，马少平．人工智能导论．清华大学出版社，1999．135～228
[40] 于跃海，郑瑞强等．基于案例推理的ICU应急诊断方案生成系统．东南大学学报，2001，31(2)：27～30
[41] 顾大可，俞勇．一个基于案例的动态工作流模型．上海交通大学学报，2001，35(9)：1290～1292
[42] 毛权．CBR中基于实例特征的相似实例检索模型研究．计算机研究与发展，1999，34(3)：27～31
[43] 程瑞琪，周美玉．柴油机诊断技术现状与专家系统策略研究．兰州铁道学院报，1999，18(2)：77～81
[44] 胡运权．基于事例推理的智能模型构建研究．哈尔滨工业大学，博士学位论文，2000
[45] 陈敏等．基于事例推理中事例组织与管理的研究．计算机工程，1994，20(5)：37～40
[46] 朱绍文，吕少鹏，马力等．一个基于实例推理的专家系统．计算机工程与应用，1999，18(1)：17～20
[47] 王国锋，张锡恩．基于安全推理的导弹故障诊断专家系统研究．系统工程与电子技术，1999，21(8)：26～29