The fault diagnosis system is classed into data fusion level module, feature level module and decision fusion level module according data fusion method.
将故障诊断系统按数据融合的方法分为数据级融合模块、特征级融合模块和决策级融合模块。
The feature level module adopts RBF neural network to extract feature of data and to make feature fusion.
特征级融合模块采用RBF神经网络，其功能是提取数据特征进而特征信息融合。
According to the fusion levels, there are data level, feature level, decision level included in data fusion.
从融合的层次结构出发，数据融合技术可分为数据级、特征级和决策级三个融合层次。
The data fusion level module mainly handles the metrical data of multi-sensors and extracts the feature of faults.
数据级融合模块主要对多传感器的测量信号进行处理，提取出故障诊断的特征信息。
We study the algorithms of feature-level fusion based on the viewpoint of dependence and independence multi-variant data analysis, respectively.
首先从多元数据分析的角度，研究了基于相关性的多元数据分析和基于独立性的多元数据分析的特征融合方法。
We study the algorithms of feature-level fusion based on the viewpoint of dependence and independence multi-variant data analysis, respectively.
首先从多元数据分析的角度，研究了基于相关性的多元数据分析和基于独立性的多元数据分析的特征融合方法。
应用推荐