VMD和SO优化SVM的光纤复合海缆故障诊断研究

Fault diagnosis of fiber-optic composite submarine cable based on VMD and SO optimized SVM

为了进一步提高光纤复合海底电缆的故障诊断准确率,提出了基于VMD及SO优化SVM的故障诊断方法。首先,使用VMD对故障数据进行分解,得到若干条IMF分量并利用皮尔逊相关系数做进一步筛选。其次,对筛选得到的IMF分量进行特征提取,分别提取各分量的峭度、近似熵及模糊熵。最后,将上述特征值构成的特征向量输入经SO优化的SVM中进行训练及分类,得到故障诊断结果。实验结果表明,采用本文提出的基于VMD和SO优化SVM的故障识别方法,光纤复合海底电缆的故障识别准确率达到了100%,分别比SVM、GA-SVM、GWO-SVM、CNN方法的识别准确度高7.5%、5%、5%、7.5%。

In order to further improve the fault diagnosis accuracy of fiber optic composite submarine cable,a fault diagnosis method based on VMD and SO optimization SVM is proposed.Firstly,VMD was used to decompose the fault data,several IMF components were obtained,and Pearson correlation coefficient was used for further screening.Secondly,feature extraction is carried out on the selected IMF components to extract the kurtosis,approximate entropy and fuzzy entropy of each component respectively.Finally,the eigenvectors composed of the above eigenvalues are input into the SVM optimized by SO for training and classification,and the fault diagnosis results are obtained.The experimental results show that the fault recognition accuracy of fiber-optic composite submarine cable can reach 100%by using the optimized SVM method based on VMD and SO,which is 7.5%,5%,5%and 7.5%higher than that of SVM,GA-SVM,GGO-SVM and CNN respectively.