基于改进布谷鸟算法与SVM的矿用变压器故障诊断

矿用变压器主要用于含有易燃气体和煤尘的矿井中，为采煤机、运输车及照明系统提供电源。针对目前矿用变压器故障诊断准确率不高的情况，提出了一种基于改进布谷鸟算法和支持向量机(SVM)的矿用变压器故障诊断方法。首先引入改进的布谷鸟算法对支持向量机参数进行寻优，获得具有最佳参数的支持向量机模型，然后利用支持向量机对变压器故障进行分类来实现变压器故障的诊断，最后，通过算例仿真对所提算法和检测方法进行了验证，Matlab仿真结果表明：利用改进布谷鸟算法和诊断模型得到的矿用变压器故障诊断准确率要高于传统的矿用变压器故障诊断方法。

Fault Diagnosis of Mining Transformer Based on ImprovedCuckoo Algorithm and SVM

Mine transformers are mainly used in mines containing flammable gases and coal so as to provide power for coal mining machines, transporter and lighting systems. At present, because the accuracy of mine transformer fault detection is not high, this paper presents a fault diagnosis method for mine transformers based on improved cuckoo algorithm and support vector machine (SVM). In this paper, the improved cuckoo algorithm is introduced to optimize the parameters of the SVM, and the SVM model with the best parameters can obtain, then the transformer faults are classified by using the support vector machine. Finally, the effectiveness of algorithm and detection method is verified in this paper. Matalab simulation results show that using algorithm and diagnosis model in this article provides better overall performance than other method.