基于融合理论的网络在线智能故障诊断模型

Intelligent Network Model Based on Information Fusion Theory for On-line Fault Diagnosis

针对复杂设备的在线故障诊断问题,依据认知科学和信息融合理论,基于网络环境,提出了一种新的网络在线智能故障诊断模型·它采用定性与定量、局部与综合诊断相结合的诊断策略,即首先进行快速定性诊断,一旦系统异常,立即启动集成神经网络组对来自设备多侧面的故障特征信息进行定量分析和分类,并由专家系统模块对神经网络组的推理过程进行定性解释,最后以D S证据推理模块在全局融合中心实现对各子网络的会诊,提高了诊断的精度和可靠性·作者所开发的丰满水电数字仿真系统的成功应用,验证了模型的有效性和实际应用价值·

In order to solve effectively the issues of on-line fault diagnosis for complex equipment, an intelligent network model is newly developed for on-line fault diagnosis based on the science of cognition and information fusion theories in Internet environment. It's such a diagnostic strategy that combines not only qualitative with quantitative diagnoses but local with integral diagnoses. In this way a qualitative diagnosis shall be made first. In case the equipment is abnormal, the integrated neural network group will start immediately the quantitative analysis and classification of multi-source characteristic information from sensors, and the ES module will explain qualitatively the reasoning process of ANNs. As a result, the D-S evidence reasoning module will diagnose synthetically the output of ANNs at integrated fusion center, thus improving evidently the precision and reliability of diagnosis conclusion. The model has been tested and run on Fengman Hydropower Station's digital simulation system we developed, and the result showed that the proposed model is not only effective, versatile and applicable in practical use but beneficial to the development of local fault diagnosis system.