某自动装填装置故障诊断专家系统研究
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摘要
随着人工智能技术的不断进步,诊断技术已开始进入一个新阶段,即智能化诊断阶段。将人工智能领域的各种方法加以综合利用并用于故障诊断,特别是针对大型复杂机械设备的诊断对象,将更有利于深入细致地刻画与描述故障的特征,使推理过程与客观实际更加相符,同时也克服了传统的故障诊断专家系统中所存在的知识“瓶颈”问题。将人工智能领域中的各种方法有机结合,可以大大提高故障诊断的水平和效率。
本文提供了一种用于自动装填智能故障诊断的通用方案,对于类似系统的设计开发具有借鉴意义。本系统的投入使用可以提高实时故障诊断的准确性和速度,使自动装填的可靠性大大提高,同时也使我国装甲车辆自动化水平提高到了一个新的层面。
在神经网络专家系统的设计中,对专家系统的知识库、推理机和解释机制分别进行全新的设计。专家系统知识库中,自动装填知识采用面向对象的表示方法存储在数据库中,而神经网络是把权值和阈值作为隐式知识库存储在数据库;专家系统和神经网络分别采用正反混合推理和正向推理;专家系统的解释机制采用预置文本与路径跟踪法,而神经网络的解释机制是把神经网络逆向推理的过程呈现在用户的面前。最后,利用VC++实现专家系统人机界面的设计。
With the development of artificial intelligence, there are the diagnosis techniques in a new phase ,which is intelligent diagnosis phase .Using the various methods in the fault diagnosis,especially,in connection with diagnosis subjects of large and complex machinery and equipment, diagnosis features will be described beneficially. The inference processes fit in with the objective reality better .At the same time ,the knowledge bottleneck problems of traditional fault diagnosis expert systems will be overcome .Some kinds of AI methods integrated can improve the levels and efficiency of fault diagnosis greatly.
This paper provides a universal solution which can be used to intelligently diagnose autoloader’s fault. It has the referential meaning for similar systems’designs. The system can be put into use to help improving the real-time fault diagnosis’s accuracy and speed and enhances the reliability of autoloader greatly. Meanwhile, it drives the armored vehicles’automation in our country into a new level.
In the neural network expert system's design, this paper carries out a brand-new design on the expert system's knowledge base, inference engine and explanation facility. In the expert system's knowledge base, autoloader knowledge is stored in the database with the object-oriented expression method. While neural network saves the weight and threshold as the implicit knowledge base in the database. The expert system and the neural network adopt backward and forward ratiocination and forward reasoning separately. The expert system’s explanation mechanism adopts preset text and path tracking method, while the neural network’s explanation mechanism presents the neural network’s reversion reasoning process to the front of the users. Finally, this paper uses VC++ to realize the expert system of man-machine interface’s design.
本文提供了一种用于自动装填智能故障诊断的通用方案,对于类似系统的设计开发具有借鉴意义。本系统的投入使用可以提高实时故障诊断的准确性和速度,使自动装填的可靠性大大提高,同时也使我国装甲车辆自动化水平提高到了一个新的层面。
在神经网络专家系统的设计中,对专家系统的知识库、推理机和解释机制分别进行全新的设计。专家系统知识库中,自动装填知识采用面向对象的表示方法存储在数据库中,而神经网络是把权值和阈值作为隐式知识库存储在数据库;专家系统和神经网络分别采用正反混合推理和正向推理;专家系统的解释机制采用预置文本与路径跟踪法,而神经网络的解释机制是把神经网络逆向推理的过程呈现在用户的面前。最后,利用VC++实现专家系统人机界面的设计。
With the development of artificial intelligence, there are the diagnosis techniques in a new phase ,which is intelligent diagnosis phase .Using the various methods in the fault diagnosis,especially,in connection with diagnosis subjects of large and complex machinery and equipment, diagnosis features will be described beneficially. The inference processes fit in with the objective reality better .At the same time ,the knowledge bottleneck problems of traditional fault diagnosis expert systems will be overcome .Some kinds of AI methods integrated can improve the levels and efficiency of fault diagnosis greatly.
This paper provides a universal solution which can be used to intelligently diagnose autoloader’s fault. It has the referential meaning for similar systems’designs. The system can be put into use to help improving the real-time fault diagnosis’s accuracy and speed and enhances the reliability of autoloader greatly. Meanwhile, it drives the armored vehicles’automation in our country into a new level.
In the neural network expert system's design, this paper carries out a brand-new design on the expert system's knowledge base, inference engine and explanation facility. In the expert system's knowledge base, autoloader knowledge is stored in the database with the object-oriented expression method. While neural network saves the weight and threshold as the implicit knowledge base in the database. The expert system and the neural network adopt backward and forward ratiocination and forward reasoning separately. The expert system’s explanation mechanism adopts preset text and path tracking method, while the neural network’s explanation mechanism presents the neural network’s reversion reasoning process to the front of the users. Finally, this paper uses VC++ to realize the expert system of man-machine interface’s design.
引文
[1]虞和济等.故障诊断的基本原理[M].北京:冶金工业出版社.1989.
[2]吴今培,肖建华.智能故障诊断与专家系统[M]北京:科学出版社,1997.1:1-163.
[3]王致杰,王耀才等.现代大型设备故障智能诊断技术的现状与展望[J].煤矿机械,2003(07):103.
[4] FEIGENBAUM E A.Panel history of AI research,1956-1961:proc.of the 6th IJCAI [C]. Tokio: [s. n. ],1979:1103-1105.
[5] Kun Chang Lee,Hyung Rae Cho,Jin Sung Kim.An expert system using an extended AND-OR graph.Knowledge-Based Systems.2008:38-51.
[6] Kuo-Wei Su,Sheue-Ling Hwang,Yu-Fa Chou.Applying knowledge structure to the usable fault diagnosis assistance system:A case study of motorcycle maintenance in Taiwan.Expert Systems with Applications.2006:370-382.
[7]杨兴,朱大奇,桑庆兵.专家系统研究现状与展望,计算机应用研究第24卷第5期,2007.5.
[8]曲明,郝红卫.CBR与RBR相结合的实时专家系统设计与实现[J].计算机工程, 2004,30(18):144-146.
[9]杨奕飞,瞿元新.基于CBR和RBR的航天测控设备故障诊断专家系统[J].飞行器测控学报, 2005,24(3):27-31.
[10]吴明强,史慧,朱晓华等.故障诊断专家系统研究的现状与展望[J].计算机测量与控制, 2005,13(12):1301-1304.
[11]张代胜,王悦,陈朝阳.融合实例与规则推理的车辆故障诊断专家系统[J] .机械工程学报, 2002,38(7):91-95.
[12]黄德浩,杨宗源,黄海涛.基于框架表示的组件库模型[J].计算机工程, 2002,28(7):111-123.
[13]付炜.基于框架网络结构的专家知识表示方法研究[J].计算机应用, 2002,22(1):3-6.
[14]孙增国.神经网络和模糊专家系统在故障诊断中的应用[D].大连:大连理工大学, 2004:31-32.
[15]许丽佳.D-S证据理论在信息融合中的改进[J].系统工程与电子技术, 2004,26(6):717-720.
[16]李冲祥.神经网络和证据理论集成的数据融合故障诊断方法研究[D].秦皇岛:燕山大学,2003:37-42.
[17] S.C.Tan,C.P.Lim,M.V.C.Rao.A hybrid neural network model for rule generation and its application to process fault detection and diagnosis. Engineering Applications of Artificial Intelligence.2007:203-213.
[18] Jian-Da Wu,Yu-Hsuan Wang,Peng-Hsin Chiang,Mingsian R.Bai.A study of fault diagnosis in a scooter using adaptive order tracking technique and neural network.Expert Systems with Applications.2007.
[19] Athakorn Kengpol,Worrapon Wangananon.The expert system for assessing customer satisfactionon fragrance notes:Using artificial neural networks. Computers & Industrial Engineering.2006: 567-584.
[20] Jian-Da Wu,Peng-Hsin Chiang,Yo-Wei Chang,Yao-jung Shiao.An expert system for fault diagnosis in internal combustion engines using probability neural network.Expert Systems with Applications.2007.
[21]梁戈超.基于遗传算法和神经网络的模拟电路故障诊断理论与方法[D].长沙:湖南大学,2004:30-33.
[22]朱明.数据挖掘[M].合肥:中国科技大学出版社,2002:1-5.
[23]何月顺.基于数据挖掘思想的故障模式分析.计算机应用研究.2005年11期
[24] ESTER M,PETAL K H.Knowledge discovery in large spatial datamining: focusing techniques for efficient class indertification: proc.of the 4th Symp. SSD’95,Advances in Spatial Data base[C].Berlin:Springer-Verlag,1995: 67-82.
[25] CHAATTRATICHAT J,DARLINGTON J,GHANEM M.Large scale datamining: the challenges and solution:KDD[C]. [S. .l ]: [s. n. ],1997.
[26] MICHAELW.Agent-based software engineering[J].IEE Proc.On Software Engineering, 1997,144(1): 26-27.
[27] KADAR B,MONNSTORI L,SZELKE E.An object-oriented frame-work for developing distributed manufacturing architecture[J].Journal of Intelligent Manufacturing,1998,9(2):173-179.
[28] JENNINGSN R, SYCARA K,WOOLDRIGEM. A roadmap of agent research and development in autonomous agents and multi-agent systems [M]. Boston:Kluwer Academic Publishers,1998.
[29] FAN Ycuping,CHEN Yunping,SUN Wansheng.System description and petri nets model for reconfiguration of fault diagnosis multi-immune agent:the 5thWorld Congress on Intelligent Control and Automation[C]. [S. .l ]: [s. n. ], 2004.
[30]李曙歌.基于面向对象知识表示的专家系统的实现.硕士学位论文.济南:山东大学.2006.4.
[31] (美)吉奥克(Giarratano,J.)等著,专家系统:原理与编程[M]北京:机械工业出版社2006.8:2-12.
[32] Martin T.Hagan Howard B.Demuth Mark H.Beale著.神经网络设计[M]北京:机械工业出版社2002.9:8-20.
[33]王晓垠.基于神经网络和专家系统的智能故障诊断系统的研究.硕士学位论文.南京:东南大学.2005.
[34]陈洛资,陈昭平,陈劼怀.数据库系统及应用基础:基于SQL Server 2000.北京:清华大学出版社2007.3.
[35]候俊杰.深入浅出(第2版).武汉:华中科技大学出版社.2001.
[36]李闽溟,吴继刚,周学明.VC++6.0数据库系统开发实例导航.北京:人民邮电出版社,2002.10.
[37]沈学军.自动装填模拟负载系统的研究与开发.硕士学位论文.长沙:湖南大学.2004.11:33-40.
[38]刘广璞,潘宏侠,姚竹亭.某火炮自动装填机构动作性能试验.太原师范学院学报.2004.6.
[39]丁宏民,翟少波,杨晨晖.某大口径火炮装填过程弹带磕碰问题研究.火炮发射与控制学报.2007.3.
[40]闫清东,张连第,赵毓芹等编.坦克构造与设计(上册).北京:北京理工大学出版社,2006.5:62-72.
[41]张相炎.火炮设计理论.北京:北京理工大学出版社,2005.2 170-239
[42]黄锡泉.齿轮箱状态监测与故障诊断专家系统研究.硕士学位论文.太原:中北大学,2006.
[43] J.W.Freestone.etal.The Diagnosis of Cylinder Power Faults in Diesel Engines By Flywheel Speed Measurement Proc of IMECHE International Conference on Vehicle Condition Monitoring And Fault Diagnosis.1985:15-24.
[44] Glenn White.Diagnosing a Low-Speed Gearbox Problem.DLI Engineering Corporation 2002.
[45]张振山,赵俊严,赵富全.坦克自动装弹机故障诊断技术.火炮发射与控制学报.2006.
[46]唐湘燕,陈效华.基于神经网络的火炮自动供输弹装置故障预测.火炮发射与控制学报.2007.3.
[47]孟浩东.基于神经网络和灰色理论的传动箱故障诊断研究.硕士学位论文.太原:中北大学.2005.
[48]侯宏花.车辆变速箱故障诊断方法研究.太原:华北工学院硕士学位论文.2002.
[49]潘宏侠等.车辆动力传力传动系统监测与故障诊断技术.华北工学院学报.2002:109-113.
[50]张秀春.基于神经网络的凝汽设备故障诊断专家系统研究.硕士学位论文.哈尔滨:哈尔滨工程大学.2007.1:41-45
[51]许东.地空导弹混合智能故障诊断专家系统的设计与实现.硕士学位论文.西安:西北工业大学.2002.3:34-37.
[52] Kim Hua Tan,Chee Peng Lim,Ken Platts,Hooi Shen Koay.An intelligent decision support system for manufacturing technology investments. Int. J. Production Economics.2006:179-190.
[53] Stephan Ebersbach,Zhongxiao Peng.Expert system development for vibration analysis in machine condition monitoring.Expert Systems with Applications. 2008:291-299.
[2]吴今培,肖建华.智能故障诊断与专家系统[M]北京:科学出版社,1997.1:1-163.
[3]王致杰,王耀才等.现代大型设备故障智能诊断技术的现状与展望[J].煤矿机械,2003(07):103.
[4] FEIGENBAUM E A.Panel history of AI research,1956-1961:proc.of the 6th IJCAI [C]. Tokio: [s. n. ],1979:1103-1105.
[5] Kun Chang Lee,Hyung Rae Cho,Jin Sung Kim.An expert system using an extended AND-OR graph.Knowledge-Based Systems.2008:38-51.
[6] Kuo-Wei Su,Sheue-Ling Hwang,Yu-Fa Chou.Applying knowledge structure to the usable fault diagnosis assistance system:A case study of motorcycle maintenance in Taiwan.Expert Systems with Applications.2006:370-382.
[7]杨兴,朱大奇,桑庆兵.专家系统研究现状与展望,计算机应用研究第24卷第5期,2007.5.
[8]曲明,郝红卫.CBR与RBR相结合的实时专家系统设计与实现[J].计算机工程, 2004,30(18):144-146.
[9]杨奕飞,瞿元新.基于CBR和RBR的航天测控设备故障诊断专家系统[J].飞行器测控学报, 2005,24(3):27-31.
[10]吴明强,史慧,朱晓华等.故障诊断专家系统研究的现状与展望[J].计算机测量与控制, 2005,13(12):1301-1304.
[11]张代胜,王悦,陈朝阳.融合实例与规则推理的车辆故障诊断专家系统[J] .机械工程学报, 2002,38(7):91-95.
[12]黄德浩,杨宗源,黄海涛.基于框架表示的组件库模型[J].计算机工程, 2002,28(7):111-123.
[13]付炜.基于框架网络结构的专家知识表示方法研究[J].计算机应用, 2002,22(1):3-6.
[14]孙增国.神经网络和模糊专家系统在故障诊断中的应用[D].大连:大连理工大学, 2004:31-32.
[15]许丽佳.D-S证据理论在信息融合中的改进[J].系统工程与电子技术, 2004,26(6):717-720.
[16]李冲祥.神经网络和证据理论集成的数据融合故障诊断方法研究[D].秦皇岛:燕山大学,2003:37-42.
[17] S.C.Tan,C.P.Lim,M.V.C.Rao.A hybrid neural network model for rule generation and its application to process fault detection and diagnosis. Engineering Applications of Artificial Intelligence.2007:203-213.
[18] Jian-Da Wu,Yu-Hsuan Wang,Peng-Hsin Chiang,Mingsian R.Bai.A study of fault diagnosis in a scooter using adaptive order tracking technique and neural network.Expert Systems with Applications.2007.
[19] Athakorn Kengpol,Worrapon Wangananon.The expert system for assessing customer satisfactionon fragrance notes:Using artificial neural networks. Computers & Industrial Engineering.2006: 567-584.
[20] Jian-Da Wu,Peng-Hsin Chiang,Yo-Wei Chang,Yao-jung Shiao.An expert system for fault diagnosis in internal combustion engines using probability neural network.Expert Systems with Applications.2007.
[21]梁戈超.基于遗传算法和神经网络的模拟电路故障诊断理论与方法[D].长沙:湖南大学,2004:30-33.
[22]朱明.数据挖掘[M].合肥:中国科技大学出版社,2002:1-5.
[23]何月顺.基于数据挖掘思想的故障模式分析.计算机应用研究.2005年11期
[24] ESTER M,PETAL K H.Knowledge discovery in large spatial datamining: focusing techniques for efficient class indertification: proc.of the 4th Symp. SSD’95,Advances in Spatial Data base[C].Berlin:Springer-Verlag,1995: 67-82.
[25] CHAATTRATICHAT J,DARLINGTON J,GHANEM M.Large scale datamining: the challenges and solution:KDD[C]. [S. .l ]: [s. n. ],1997.
[26] MICHAELW.Agent-based software engineering[J].IEE Proc.On Software Engineering, 1997,144(1): 26-27.
[27] KADAR B,MONNSTORI L,SZELKE E.An object-oriented frame-work for developing distributed manufacturing architecture[J].Journal of Intelligent Manufacturing,1998,9(2):173-179.
[28] JENNINGSN R, SYCARA K,WOOLDRIGEM. A roadmap of agent research and development in autonomous agents and multi-agent systems [M]. Boston:Kluwer Academic Publishers,1998.
[29] FAN Ycuping,CHEN Yunping,SUN Wansheng.System description and petri nets model for reconfiguration of fault diagnosis multi-immune agent:the 5thWorld Congress on Intelligent Control and Automation[C]. [S. .l ]: [s. n. ], 2004.
[30]李曙歌.基于面向对象知识表示的专家系统的实现.硕士学位论文.济南:山东大学.2006.4.
[31] (美)吉奥克(Giarratano,J.)等著,专家系统:原理与编程[M]北京:机械工业出版社2006.8:2-12.
[32] Martin T.Hagan Howard B.Demuth Mark H.Beale著.神经网络设计[M]北京:机械工业出版社2002.9:8-20.
[33]王晓垠.基于神经网络和专家系统的智能故障诊断系统的研究.硕士学位论文.南京:东南大学.2005.
[34]陈洛资,陈昭平,陈劼怀.数据库系统及应用基础:基于SQL Server 2000.北京:清华大学出版社2007.3.
[35]候俊杰.深入浅出(第2版).武汉:华中科技大学出版社.2001.
[36]李闽溟,吴继刚,周学明.VC++6.0数据库系统开发实例导航.北京:人民邮电出版社,2002.10.
[37]沈学军.自动装填模拟负载系统的研究与开发.硕士学位论文.长沙:湖南大学.2004.11:33-40.
[38]刘广璞,潘宏侠,姚竹亭.某火炮自动装填机构动作性能试验.太原师范学院学报.2004.6.
[39]丁宏民,翟少波,杨晨晖.某大口径火炮装填过程弹带磕碰问题研究.火炮发射与控制学报.2007.3.
[40]闫清东,张连第,赵毓芹等编.坦克构造与设计(上册).北京:北京理工大学出版社,2006.5:62-72.
[41]张相炎.火炮设计理论.北京:北京理工大学出版社,2005.2 170-239
[42]黄锡泉.齿轮箱状态监测与故障诊断专家系统研究.硕士学位论文.太原:中北大学,2006.
[43] J.W.Freestone.etal.The Diagnosis of Cylinder Power Faults in Diesel Engines By Flywheel Speed Measurement Proc of IMECHE International Conference on Vehicle Condition Monitoring And Fault Diagnosis.1985:15-24.
[44] Glenn White.Diagnosing a Low-Speed Gearbox Problem.DLI Engineering Corporation 2002.
[45]张振山,赵俊严,赵富全.坦克自动装弹机故障诊断技术.火炮发射与控制学报.2006.
[46]唐湘燕,陈效华.基于神经网络的火炮自动供输弹装置故障预测.火炮发射与控制学报.2007.3.
[47]孟浩东.基于神经网络和灰色理论的传动箱故障诊断研究.硕士学位论文.太原:中北大学.2005.
[48]侯宏花.车辆变速箱故障诊断方法研究.太原:华北工学院硕士学位论文.2002.
[49]潘宏侠等.车辆动力传力传动系统监测与故障诊断技术.华北工学院学报.2002:109-113.
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