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Research on fault diagnosis method of steam turbine generator unit based on multilayer information fusion

机译:基于多层信息融合的汽轮发电机组故障诊断方法研究

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摘要

Based on the idea of Multilayer information fusion technology, and from the reality of equipment fault diagnosis, We established neural network evidence fusion fault diagnosis system which is based on information fusion technology. Neural network has good nonlinear mapping ability, and d-s evidence theory has unique advantages in the expression of uncertainty. Both of the two methods have been widely used in the field of fault diagnosis. That is, through the effective combination of the fault feature information, use the seeds of neural network from different sides for equipment fault diagnosis of preliminary, then applying the preliminary diagnosis to Dempster - Shafer theory evidence for decision fusion. The diagnosis example indicates that, after fault feature information fusion, the credibility of the diagnostic increased significantly, and can effectively improve the diagnosis rate.
机译:基于多层信息融合技术的思想,结合设备故障诊断的实际,建立了基于信息融合技术的神经网络证据融合故障诊断系统。神经网络具有良好的非线性映射能力,并且d-s证据理论在不确定性的表达方面具有独特的优势。两种方法都已广泛用于故障诊断领域。也就是说,通过故障特征信息的有效结合,利用来自不同方面的神经网络的种子对设备进行故障的初步诊断,然后将初步诊断应用于Dempster-Shafer理论证据进行决策融合。诊断实例表明,融合故障特征信息后,诊断的可信度大大提高,可以有效提高诊断率。

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