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• 智能设计与数字化设计 • 上一篇    

基于故障知识库的机械零部件故障管理支持系统

  

  1. (1. 清华大学机械工程系，北京 100084； 
    2. 精密超精密制造装备及控制北京市重点实验室，北京 100084； 
    3. 陆军装备部装备技术合作中心，北京 100036； 
    4. 陆军航空兵研究所，北京 101121)
  • 出版日期:2019-06-30 发布日期:2019-08-02
  • 基金资助:
    北京市自然科学基金项目(3182012)

Failure Management and Support System of Mechanical Parts Based on Failure Knowledge-Base

  1. (1. Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;
    2. Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipment and Control, Beijing 100084, China;
    3. Army Equipment Department Equipment Technical Cooperation Centre, Beijing 100036, China;
    4. Institute of Army Aviation, Beijing 101121, China)
  • Online:2019-06-30 Published:2019-08-02

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摘要：  针对机械零部件故障知识表述困难，故障信息在不同设计人员间利用、分享和重 用效率低等问题，基于本体建模技术构建了故障知识库，设计开发了一个机械零部件故障管理 支持系统(FKMS)。通过机械零部件生命周期中不同角色对故障知识的需求分析，建立了系统的 功能结构模型，确定了故障知识的内容。利用本体建模技术构建了故障知识本体模型与实体关 系网络，保证了故障知识库结构的完备性。基于垂直模式建立了知识模型到数据库的映射，实 现了知识的高效存储与模型的可拓展。通过故障知识模型建立了故障原因关系网络，实现了故 障原因推理与置信度计算，解决了故障原因分析不全面的问题。基于 Django-Web 模块进行了 系统开发，并以直升机自由轮斜撑块涂层剥落故障为例验证了系统的知识管理和故障分析功能， 实现了对故障信息的分析与动态管理支持。

关键词: 故障知识, 本体模型, 知识库, 故障原因推理, 知识管理系统

Abstract:  In order to solve the difficulty in describing failure knowledge of mechanical parts and the low efficiency of sharing and reuse of failure knowledge among different designers, a failure knowledge base is constructed based on ontology modeling technology. A mechanical parts failure knowledge management & support system (FKMS) is designed and developed using Django-Web module. First, by analyzing knowledge requirement, the function structure of the system is established and the content of failure knowledge is determined. Next a failure knowledge ontology model and its entity relation network are constructed by ontology modeling technology, which ensures the integrity of the knowledge base structure. Then the mapping of knowledge model to database is established based on vertical model, enabling efficient storage and extensible structure. In addition, through failure reason networks based on the ontology mode, a fault reason analysis algorithm with belief propagation is put forward. Finally, the coating spallation of helicopter free-wheel sprag is used as a case in the process of knowledge management and failure analysis, which demonstrates the dynamic management support of the system.

Key words: failure knowledge, ontology model, knowledge-base, fault reasoning, knowledge management system