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首页> 外文学位 >MODELING FAULT DIAGNOSIS PERFORMANCE ON A MARINE POWERPLANT SIMULATOR (HUMAN PROBLEM SOLVING, KNOWLEDGE REPRESENTATION).
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MODELING FAULT DIAGNOSIS PERFORMANCE ON A MARINE POWERPLANT SIMULATOR (HUMAN PROBLEM SOLVING, KNOWLEDGE REPRESENTATION).

机译：在海洋动力装置仿真器上建模故障诊断性能（人类问题解决，知识表示）。

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摘要

Human operators of large dynamic systems must possess good fault diagnosis skills. Factors affecting fault diagnosis skills are investigated in this thesis, and a model for fault diagnosis is developed.;A model for the fault diagnosis process which employs a conceptual entity called hypothesis frame to account for the observations from data and protocols has been proposed. Relevant information about a failure is "compiled" in the frames so that subjects could make quick and reliable inferences. Given symptoms of a failure, subjects would first try to match a frame. Once a frame is identified, subjects could use the information contained in the slots to make inferences. When no obvious frames could be processed, subjects could search in the system or symptom knowledge base for relevant information under the guidance of heuristics. This model could form the basis for implementing an on-line coach system for fault diagnosis.;A low fidelity simulator of a marine powerplant, was developed and used to study expert marine engineers' fault diagnosis performance. Based on the data collected, factors affecting the fault diagnosis performance were identified. They are: the initial feasible set (IFS) and the transition strategy. A subject's initial set of actions upon observing the symptoms forms the IFS which reflects the subjects' knowledge about a given failure. Transition strategy is concerned with the schemes subjects used to shift from the hypothesis formation stage to hypothesis evaluation stage. Two types of strategy were identified: breadth-depth strategy and balanced strategy. The data seem to indicate that subjects who had good IFS and used breadth-depth strategy performed better than subjects who had bad IFS and used balanced strategy. This finding seems to imply that both context-specific (IFS) and context-free (transition strategy) factors are important for fault diagnosis training.
机译：大型动态系统的人工操作员必须具有良好的故障诊断能力。本文研究了影响故障诊断技能的因素，并建立了故障诊断模型。提出了一种故障诊断过程模型，该模型采用了一种称为假设框架的概念性实体来解释来自数据和协议的观察结果。有关故障的相关信息被“汇总”在框架中，以便受试者可以快速而可靠地进行推断。给定失败的症状，受试者将首先尝试匹配框架。一旦确定了帧，受试者就可以使用插槽中包含的信息进行推断。如果无法处理明显的帧，则受试者可以在启发式方法的指导下在系统或症状知识库中搜索相关信息。该模型可为实现在线故障诊断教练系统的基础。开发了一种海洋动力装置的低保真模拟器，用于研究海洋工程专家的故障诊断性能。根据收集的数据，确定影响故障诊断性能的因素。它们是：初始可行集（IFS）和过渡策略。对象在观察到症状时的初始动作集形成了IFS，该IFS反映了对象对给定故障的了解。过渡策略与主题从假设形成阶段转移到假设评估阶段的计划有关。确定了两种策略：广度策略和平衡策略。数据似乎表明，IFS良好且使用广度策略的受试者的表现优于IFS较差且使用平衡策略的受试者。这一发现似乎暗示着上下文特定（IFS）和上下文无关（过渡策略）因素对于故障诊断培训都非常重要。

著录项

  • 作者

    SU, YUAN-LIANG DAVID.;

  • 作者单位

    Georgia Institute of Technology.;

  • 授予单位 Georgia Institute of Technology.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 1985
  • 页码 170 p.
  • 总页数 170
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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