Research on Internal Temperature Prediction of Slow Wave Structure Based on Experimental Data

Abstract

At present, there are many researches on the thermal characteristics of traveling wave tube, but few researches and discussions on the measurement of its internal temperature field are involved. Moreover, it is difficult to monitor the internal temperature of traveling wave tube. In related research, an RBF neural network model based on ANSYS slow wave structure simulation data has been proposed. Data outside the slow wave structure is input into the model to calculate its internal thermal characteristics. On this basis, a simplified model of slow wave structure was designed in this study. The real data outside the model tube measured by the infrared temperature measurement system was input into the inversion model to get the internal temperature, and the error is small compared with the real internal temperature.