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。
Then, a multi-level and multi-hierarchical blackboard model is brought forward, which can be applied to situation assessment of data fusion.
然后提出了一种用于数据融合中态势评估部分的分级多层黑板模型；
The data fusion level module mainly handles the metrical data of the multi-sensors, the soft metrical data and the working condition data of the system.
数据级融模块主要处理多传感器测量数据，软测量数据和系统的干扰数据。
In order to resolve the problem, the method of multi-sensor data fusion on decision level is submitted.
为了解决干扰情况下地震动信号发射源的定性问题，提出了在决策层上的多传感器数据融合的识别方法。
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。
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。
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