基于云模型的二次设备定性指标隶属度精准量化研究

Research on Accurate Quantification of Membership of Qualitative Index of Secondary Equipment Based on Cloud Model

为准确评估二次设备的健康状态,需要解决评价指标体系内定性指标隶属度结果主观性强、冗余度高等问题.提出了采用云模型对各定性指标隶属度进行精准量化的新思路。依据专家给出的经验评分值,以云模型雾化性质客观判定群体专家意见的共识程度;采用云发生器对定性指标实际状态以浮动云的形式进行刻画;根据等级界限区间生成用于评价浮动云隶属状态的标准空间,并将二者叠加,两种云图的重叠面积定义为浮动云隶属度。最后,以某220kV智能变电站某间隔智能终端为例,在指标层细化出16个单项指标,最终形成评价指标体系,对其中2个指标进行量化分析,该方法在精准量化定性指标隶属度的同时,又透过可视化云图反映了定性指标的实际情况。

In order to accurately assess the health status of secondary equipment,it is necessary to solve the problems of strong subjectivity and high redundancy of the qualitative index membership in the evaluation index system.Based on this,this paper proposes a new idea of using cloud model to accurately quantify the membership of qualitative index.Firstly,based on the experience score given by the experts,the cloud model atomization properties are used to objectively determine the degree of consensus among the group of expert opinions;then use the cloud generator to describe the actual state of each qualitative index in the form of a floating cloud;meanwhile,the standard state cloud space used to evaluate the membership state of floating cloud is generated according to the level boundary interval,and the overlapping area of the two kinds of cloud atlas is defined as the membership degree of floating cloud.Finally,taking a 220 kV intelligent substation intelligent terminal as an example,16 single indicators are refined in the index layer,and finally an evaluation index system is formed.Two of the indicators are analyzed quantitatively.This method not only accurately quantifies the membership degree of the qualitative index,but also reflects the actual situation of the qualitative index through the visual cloud image.