基于不完整数据的粗糙集电网故障诊断方法

针对电网发生故障时,可能产生的保护装置或断路器拒动、误动以及通信装置传输缺陷所造成的数据不完整情况,提出了一种基于粗糙集理论的新约简算法,并将约简结果综合为一个统一的专家库表·同时应用模糊集和概率论理论,为每条规则加入了相应规则置信度和设备置信度·对于符合的结论,根据支持某一决策的规则数目以及每条规则的置信度,提出了综合分析置信度的算法,并将其应用于电网故障诊断中·运用VB语言编程实现了对故障算例决策表的约简,并通过具体算例测试,证明了该约简算法的有效性和实用性·

A Knowledge Acquisition by Rough Set Based on Incomplete Data Sets and Its Application in Fault Diagnosis for Electricity Networks

A newly reduced algorithm based on rough set(RS) theory is proposed for fault diagnosis in case no complete data are available when the power network failed and then caused possibly the protections/breakers to malfunction and/or the transmission defects in communication. Furthermore, the reduced result can be synthesize into one as a tabulated expert decision library. With fuzzy sets and probability applied to the rules of rough sets, the confidence levels of each rule and relevant equipment are taken into consideration and computed. Another algorithm is also proposed to analyze synthetically the confidence level of a diagnostic conclusion in accordance to the number of rules for a certain decision-making process and the confidence level of each rule, which is also to be put into application to power network fault diagnosis. In the example given as fault diagnosis, the reduction of the tabulated decisions is implemented through the VB-based programming language, of which the results show the effectiveness and practicability of the method proposed here.