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Re-engineering legacy tech manual's troubleshooting procedures into smart model-based diagnostics

机译:将旧版技术手册的故障排除程序重新设计为基于智能模型的诊断程序

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Technical Manuals used for field maintenance of US Army systems rely heavily on troubleshooting procedures which are presented in "flow chart" format. These flow charts guide the technician through test procedures to isolate the cause of an equipment malfunction. These procedures are static, that is they are highly structured around a pre-determined sequence of tests, do not become "smarter" over time with historical maintenance data and they only take into account those symptoms and faults which the original developer considered. They are often incomplete, sometimes wrong, and are very difficult to update and maintain. As the Army moves to computer-assisted methods of maintenance, the opportunity exists to significantly enhance the basic logic and knowledge representation underlying troubleshooting procedures. The enhancements include knowledge based reasoning about faults related to symptoms, the ability to dynamically relate faults to symptoms, the ability to use historical maintenance data to continuously improve maintenance capability, and the ability to house "expert" diagnostics information in a form that becomes usable and available to novice technicians. However, can tree-based troubleshooting logic from legacy systems be efficiently re-engineered to a knowledge-based system with the same benefits? This paper addresses the aspects of transitioning from flow-chart intensive knowledge representation to a format which provides the benefits described above.
机译:用于美国陆军系统野外维护的技术手册在很大程度上依赖于以“流程图”格式显示的故障排除程序。这些流程图指导技术人员完成测试程序,以找出设备故障的原因。这些程序是静态的,也就是说,它们是围绕预定的测试序列高度结构化的,不会随着历史维护数据的使用而随着时间的推移变得“更智能”,并且它们仅考虑了原始开发人员考虑的那些症状和故障。它们通常是不完整的,有时是错误的,并且很难更新和维护。随着陆军转向计算机辅助维护方法,存在着显着增强故障排除程序基础的基本逻辑和知识表示的机会。增强功能包括与症状有关的故障的基于知识的推理,将故障与症状动态相关的能力,使用历史维护数据以不断提高维护能力的能力以及以可用形式容纳“专家”诊断信息的能力可供新手技术人员使用。但是,是否可以将旧系统中的基于树的故障排除逻辑有效地重新设计为具有相同优势的基于知识的系统?本文讨论了从流程图密集型知识表示到提供上述好处的格式的过渡。

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