摘要
以高压开关柜为研究对象,提出了一种基于正态云模型和D-S证据理论的分层评估算法。通过对影响开关柜运行状态的指标进行聚类分层,运用正态云模型确定各指标与各评价等级的关联度,并利用改进的模糊算法进行第1层评估,在此基础上运用D-S证据理论对开关柜整体运行状态进行评估。采用KYN28A-12型号某开关柜的一次检测数据为例,通过实例验证证明了评估算法的有效性。该评估模型结构清晰,评价指标易于得到,为开关柜状态评估提供了一种新思路。
Taking the high-voltage switchgear cabinet as the studying object, method based on normal cloud model and D-S evidential theory is proposed. a hierarchical evaluation By hierarchical clustering indicators of the switchgear status, normal cloud model is used to determine the correlation degree of indicators and evaluation level. Also the improved fuzzy algorithm is used to evaluate the first layer. On the basis, D-S evidential theory is used to assess the overall state of the switchgear. As an example, test data of the KYN28A-12 model switchgear is analyzed. The simulation result demonstrates the effectiveness of the assessment algorithm. The assessment model is clear and doesn't need lots of historical data. It offers a new thinking to assess the operating state of the high-voltage switchgear.
出处
《高压电器》
CAS
CSCD
北大核心
2017年第9期247-252,共6页
High Voltage Apparatus
关键词
开关柜
状态评估
正态云模型
最优组合权重
D-S证据理论
high-voltage switchgear
state assessment
normal cloud model
optimized combination weighting D-S evidential theory