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Reinforcing fuzzy rule-based diagnosis of turbomachines with case-based reasoning

机译:基于事例推理的涡轮机模糊规则诊断增强

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摘要

This paper presents an integrated knowledge-based system, which combines fuzzy rule-based reasoning with case-based reasoning, for turbomachinery diagnosis. By incorporating a case-based reasoning sub-system in a fuzzy rule-based system, the integrated system allows past experience to be applied in a more direct way. This helps improve the diagnostic accuracy of the rule-based system. This approach has been implemented for the specific task of identifying possible causes of observed vibrations in rotating machines, based on the initial work presented in [18]. The ability that the case-based sub-system brings to the integrated system in improving the diagnostic efficacy of the original rule-based system is demonstrated with test results on real cases.
机译:本文提出了一个基于知识的集成系统,该系统将基于模糊规则的推理与基于案例的推理相结合,用于涡轮机械诊断。通过将基于案例的推理子系统合并到基于模糊规则的系统中,该集成系统允许以更直接的方式应用过去的经验。这有助于提高基于规则的系统的诊断准确性。根据[18]中介绍的初始工作,已针对特定任务实施了这种方法,以识别旋转机械中观察到的振动的可能原因。通过对实际案例的测试结果,证明了基于案例的子系统带给集成系统提高原始基于规则的系统的诊断效率的能力。

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