Mask R-CNN and multifeature clustering model for catenary insulator recognition and defect detection

Rod insulators are vital parts of the catenary of high speed railways(HSRs).There are many different catenary insulators,and the background of the insulator image is complicated.It is difficult to recognise insulators and detect defects automatically.In this paper,we propose a catenary intelligent defect detection algorithm based on Mask region-convolutional neural network(R-CNN)and an image processing model.Vertical projection technology is used to achieve single shed positioning and precise cutting of the insulator.Gradient,texture,and gray feature fusion(GTGFF)and a K-means clustering analysis model(KCAM)are proposed to detect broken insulators,dirt,foreign bodies,and flashover.Using this model,insulator recognition and defect detection can achieve a high recall rate and accuracy,and generalized defect detection.The algorithm is tested and verified on a dataset of realistic insulator images,and the accuracy and reliability of the algorithm satisfy current requirements for HSR catenary automatic inspection and intelligent maintenance.

Electric Field Distribution of Soluble Salt Deposition on the Surface of Insulators in Railway Overhead Lines

Different constituents of soluble salts have different effects on the insulation performance of insulators.To study the electric field distribution of soluble salt deposition on the surface of high-speed railway insulators,a two-dimensional model of the cantilever insulator electrostatic field and constant-current field with soluble salt deposition is constructed.The simulation results indicate that the relative dielectric constant of dry pollution is the main factor that affects the electric field distribution on the surface of the insulator.The electric field intensity is arranged in the following order:CaSO_(4)>KNO_(3)>NaNO_(3)>K_(2)SO_(4)>NaCl>MgSO_(4),and the conductivity of each dirty liquid in the wet state becomes a key factor affecting the electric field distribution,which is specifically shown as sodium chloride>nitrate>sulfate.The simulation results are compared with existing test results to verify that they were correct.It is also found that the electric field intensity of the insulator with good hydrophobicity is slightly greater than that of the insulator without hydrophobicity.The results provide a theoretical basis for the classification of regional pollution levels and the testing of insulator contamination in the laboratory.