陈梵, 薛敏, 葛蓬, 李俊达. 基于云理论和多传感器加权平均的关键性能指标状态描述[J]. 微电子学与计算机, 2012, 29(1): 159-163.
引用本文: 陈梵, 薛敏, 葛蓬, 李俊达. 基于云理论和多传感器加权平均的关键性能指标状态描述[J]. 微电子学与计算机, 2012, 29(1): 159-163.
CHEN Fan, XUE Min, GE Peng, LI Jun-da. Key Index State Description Based on Cloud Theory and Multi-sensor Weighted Mean[J]. Microelectronics & Computer, 2012, 29(1): 159-163.
Citation: CHEN Fan, XUE Min, GE Peng, LI Jun-da. Key Index State Description Based on Cloud Theory and Multi-sensor Weighted Mean[J]. Microelectronics & Computer, 2012, 29(1): 159-163.

基于云理论和多传感器加权平均的关键性能指标状态描述

Key Index State Description Based on Cloud Theory and Multi-sensor Weighted Mean

  • 摘要: 利用了云理论以及多传感器加权平均的方法来对关键性能指标的状态进行定性描述.第一步用分布图法对状态正常情况下由数个传感器得到的数据进行一致性检验, 第二步采用多传感器加权平均方法并且融合出正常的状态下均方误差为最小的数据融合值, 第三步将任意时刻的关键性能指标数据和均方误差为最小的数据融合值相比较得出偏差值, 最后一步基于云理论构造出5个评语的评语集, 和结合偏差大小对当前的关键的性能指标进行了定性描述.实验结果表明该方法的有效性.

     

    Abstract: Key index analysis state was described qualitatively by using cloud theory and multi-sensor weighted mean method in this paper.Firstly, the data got from the sensors in natural state were tested conformably by using distributing graph method.Secondly, we can use the multi-sensor weighted mean method and get the smallest data confluent value of the average error in natural state.And then compared the key index data in any time with foregoing confluent value and the warp value was gained.At last we can construct five remark sets based on cloud theory, and combining the warp value we can describe the key index analysis state qualitatively.The experiment result indicates the validity of our method.

     

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