Based on the fuzzy Petri net modal, an efficient fault diagnostic reasoning algorithm is proposed. Its accuracy and feasibility in a gas turbine diagnosis system is verified.
并在这个模型的基础上，给出了有效的推理算法，并举例验证其正确性和在燃气轮机专家系统中应用的可行性。
A diagnostic method integrated covering theory and fuzzy reasoning is introduced in this paper. Based on it, a practical model applied for the fault diagnosis of power transformer is constructed.
介绍了一种在覆盖集理论框架上集成模糊推理的诊断方法，在此基础上建立了应用于电力变压器故障诊断的实用模型。
A diagnostic method integrating case based reasoning with fuzzy theory is presented in this paper, and a practical model for power transformer fault diagnosis is further built up.
提出一种在范例推理框架上集成模糊数学的故障诊断方法，并进一步建立起可应用于电力变压器故障诊断的实用模型。
Refer to hierarchical fault model, the integrated ANN diagnostic model can contract the scope of diagnostic reasoning, and find quickly the fault components.
集成神经网络模型以故障层次模型为参考，可以大大缩小诊断推理的求解空间，最终快速定位发生故障的根本部位。
The integrated ANN consists of fuzzy ART2 and BP network has ability of finding new fault type, accurate diagnostic reasoning and locating fault.
基于模糊ART神经网络及BP神经网络构建的集成神经网络更进一步具有发现新故障的能力，且能够对故障引发部位实现精确诊断和定位。
The integrated ANN consists of fuzzy ART2 and BP network has ability of finding new fault type, accurate diagnostic reasoning and locating fault.
基于模糊ART神经网络及BP神经网络构建的集成神经网络更进一步具有发现新故障的能力，且能够对故障引发部位实现精确诊断和定位。
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