A monitoring method for the operating state characteristics of bushing in UHV converter valve hall was proposed from the perspective of intelligent image processing and three-dimensional modeling technology. This method mainly included using intelligent image processing technology to identify and classify the databases of infrared thermal imager and ultraviolet imager, using Kalman filtering technology to realize on-line measurement in real time for the insulation distance of typical metal fittings, and using three-dimensional modeling technology based on finite element method to build the electric field simulation model of typical main equipment bushing in valve hall, and the electric field distribution on the surface of key metal fittings was obtained. Combined with the image database information, insulation distance information, and electric field distribution information of typical main equipment bushing, its operation state parameters were obtained effectively, and its operation state was evaluated by the intelligent algorithm automatically. The results show that when the Kalman filtering technology is not used, the prediction deviation of the distance at key positions changes severely in 0‒160 s. After using the Kalman filtering technology, the jump amplitude of prediction deviation decreases and is basically controlled at the same error level. The neural network has good learning effect, the fitness function tends to be stable after 100 iterations, and the local weight of fuzzy neural network shows typical nonlinear characteristics. The research conclusion can explore potential hidden dangers and locate positive faults effectively, which provide effective data support and protection strategies for the operation and maintenance of main equipment bushing.