摘要
针对传统的线路切割法在电路故障诊断表现出的诸多问题,提出了一种基于D-S证据理论的多故障分类器的信息融合系统框架模型。在该模型中,基于SVM的故障分类器模型、基于贝叶斯的故障分类器模型和基于神经网络的故障分类器模型中的故障集合的并集共同构成识别框架,并利用Dempster合成法则对测试数据进行融合。实例研究表明,该模型增强了诊断系统的可分析性,有效提高了故障模式的识别能力。
Aiming at the problem of circuitry incision during the process of circuit fault diagnosis,an information fusing model is proposed based on D-S evidence theory.The frame discrimination is constructed by the combining sets of faults gained based on SVU,D-S evidence theory and neural net.Then the testing data is fused by Dempster fusing rule.Finally an example illustrates the increaser degree of analysis for diagnosis,and the results show that the model is effective and reasonable.
出处
《计算机与数字工程》
2012年第12期76-78,125,共4页
Computer & Digital Engineering
基金
国家自然科学基金资助项目(编号:71171198)资助