基于变参数区间直觉模糊集的故障诊断方法

Method for Fault Diagnosis Based on Interval Intuitionistic Fuzzy Sets with Varying Parameters

针对故障诊断效果经常受众多不确定模糊性因素影响的问题,利用直觉模糊集(IFS)能较好表达不确定性信息的优势,提出了基于区间直觉模糊集(IVIFS)的故障诊断新方法.介绍了IFS的概念,引出了IVIFS和带参IVIFS的定义及其内在联系;在IFS定义及隶属度、非隶属度、犹豫度关系的基础上,构建了激励惩罚型变参数IVIFS;对IVIFS在故障诊断中的应用进行了统计解释,并构建了基于变参数IVIFS的故障诊断模型;以风机的故障诊断实例为研究对象,对模型进行了验证,结果表明了该方法的有效性和可行性.

Aiming at the problem that the effectiveness about fault diagnosis was affected by some factors on uncertainties, a novel fault diagnosis method based on interval intuitionistic fuzzy sets（IVIFS） was proposed in accordance with the advantages that the intuitionistic could represent the probabilistic information about fault perfectly. The concepts for intuitionistic fuzzy sets（IFS） and IVIFS with varying parameters were introduced based on the theory of IFS, meanwhile their internal connection was analyzed in great detail. The incentive-penalty IVIFS with varying parameter was constructed with the respect to the degree of membership and the degree of non-membership; in addition, the application of IVIFS in the field of fault diagnosis was explained statistically, and the model for fault diagnosis based on IVIFS with varying parameter was established in accordance with the principle of nearest principle. The faults about fans were regarded as the study to validate the model, then the experimental results proved the effectiveness and feasibility for the proposed method to some extent.