Damage Identification for Transmission Tower Based on Support Vector Machine and RBF

Transmission tower occupies an important position in the event of transmission of electricity. The failure of transmission tower would cause serious economic losses. As a damage identification parameter, variation ratio of curvature mode has a great ability to damage location. In the field of damage location identification on transmission tower, variation ratio of curvature mode achieved good results even in the condition of tiny damage such as 1%. Support vector machine, as new machine learning algorithm, has shown its superiority of the ability of regression in the fields of damage identification. In this paper, the method of least squares support vector machine is applied to study on the damage extent identification of transmission tower. It is found that this method can extremely approach the targets even under the condition of little sample and it has accurate ability of damage extent identification.