Identification Algorithm of Electrical Equipment Type and Fault State Based on FastPCA and SVM

In order to improve the intelligence of electrical equipment type and fault state identification under infrared image, a comprehensive analysis method combining FastPCA and SVM algorithm is proposed in this paper. First, the K-mean operator is used to segment the infrared image in complex background.Then, the additional error cost coefficient C and the parameter y of radial basis function (RBF) are optimized by the parameter optimization tool. The speed and accuracy of different experimental samples are analyzed under different y values. Finally, the type and fault recognition of electrical equipment under infrared image are realized.The experimental results show that the algorithm can effectively improve the correctness of electrical equipment type and fault identification in infrared image, and the software identification system platform has the advantages of high precision, strong anti-interference and convenient practical application.