Internal Temperature Prediction And Measurement Of High Power Vacuum Electronic Devices

Traveling wave tube is an important microwave power electronic device,which has a wide range of applications,such as radar,satellite communications,electronic confrontation and so on.With the increase of the requirements of the performance of the traveling wave tube,the thermal characteristics of the traveling wave tube and the thermal optimization design are of great significance.At present,though there are many researches on the thermal characteristics of the traveling wave tube,the research on the internal temperature field measurement is rarely involved.The measurement of the internal temperature field is also difficult,and the research on the internal temperature field measurement is very important for the optimal design and the inside temperature field monitoring of the traveling wave tube the.The slow wave structure and the collector are the two parts with the highest temperature when the traveling wave tube works.Therefore,in this paper,ANSYS finite element thermal analysis is carried out on the slow wave structure and collector,the TWT's body temperature measurement system is developed and a method based on the thermal simulation model of slow wave structure and collector and the BP neural network model optimized by genetic algorithm is proposed to estimate the inner temperature distribution of them.Firstly,the finite element simulation model of slow wave structure is established by using ANSYS finite element software.The heat power generated by electron impact on the helix is calculated and its high frequency heat loss is calculated.Then,it is loaded into the helix as a thermal load.Through ANSYS simulation calculation,the temperature distribution cloud pictures and heat flux vector pictures and temperature propagation path diagram are obtained.And the finite element simulation model of the collector is established.The heat flux distribution of the collector in the collector is obtained by electron injection.Therefore,the thermal load is calculated by the nonuniform loading method and the ANSYS simulation is used to obtain the temperature distribution cloud pictures and heat flux vector pictures of collector.The establishment of the thermal simulation model of the slow wave structure and the collector is laid a foundation for the study of the internal temperature field prediction method.Secondly,the TWT body temperature measurement system is designed and developed,and the system is used to measure the body temperature of the traveling wave tube under different conditions.The two-dimensional interpolation algorithm and the MATLAB tool are used to draw three-dimensional temperature cloud picture according to the measured results.So that the body temperature is more intuitive and convenient to observe.Finally,based on the ANSYS thermal simulation model of slow wave structure and collector,combined with the BP neural network optimized by genetic algorithm,this paper proposed the internal temperature prediction method of slow wave structure and collector.Firstly,the BP neural network optimized by genetic algorithm is established,and then the ANSYSY simulation model is used to collect the data samples.Finally,the internal heat flux distribution is obtained through the trained neural network by inputing the body temperature.Take the internal heat flux distribution into Simulation model to get the internal and external temperature values of the entire model.The method is easy to implement and the cost is low.From the results,it can be seen that the method has high accuracy and good feasibility.What's more,this method has a certain reference value for the study of the inside temperature field of the traveling wave tube.