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An architecture for the development of real-time fault diagnosis systems using model-based reasoning

机译:使用基于模型的推理开发实时故障诊断系统的体系结构

摘要

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.
机译:这里介绍的是一种使用基于模型的推理来实现基于实时遥测的诊断系统的体系结构。首先,我们介绍Paragon,这是一种用于物理系统模型的离线输入和验证的知识获取工具。 Paragon为领域专家提供了结构化的编辑功能,以捕获物理组件的结构,行为和因果关系。接下来,我们描述运行时诊断系统的体系结构。该诊断系统完全用Ada编写,使用Paragon离线开发的行为模型来模拟遥测流中反映的预期组件状态。诊断算法跟踪模型中包含的因果关系,以隔离系统故障。由于诊断过程仅依赖于行为模型,并且无需使用启发式规则即可实施,因此可用于隔离各种系统中的不可预测故障。最后,我们讨论了使用该技术构建的用于诊断科学仪器中故障的原型系统的实现。该原型演示了基于模型的推理的使用,以更低的成本开发具有更高诊断能力的可维护系统。

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