In order to detect the fault condition of the electric insulation equipment on catenary

we studied the fault characteristics of the electric insulation equipment by using ultraviolet imaging technology and infrared thermal imaging technology. Through on-site detection of the faulty electric equipment

we identified three typical discharge and heating failures on catenary. With the help of partial discharge tests of insulators

apparent discharge capacities and ultraviolet images of the faulty equipment under various filthy states were obtained. By extracting the characteristics of the ultraviolet images

the facula areas were accurately calculated. By comparing the capacities of partial discharge with the areas of facula on ultraviolet images

the direct proportional linear correlation between the two features was obtained. Moreover

we analyzed the impacts of shooting distance

gains and angles on the areas of facula

and used normalization to the areas of the facula under different parameters to figure out the apparent discharge capacities. By conducting tests

the regular pattern of temperature rise through a longtime under different fault conditions was generalized: the maximum temperature rise after discharging increased with the increment of fault degrees

providing a basis for detecting faults by using thermal imaging technology. The fuzzy logical inference should be conducted based on the discharge capacities detected by the ultraviolet images and the maximum temperature rise detected by the thermal images

and then an assessment system of the condition of catenary insulation based on ultraviolet and infrared imaging technologies has been established

and the accuracy rate is 92.5% in the test. Therefore

it can be confirmed that the catenary insulation health condition assessment system is effective.