| At present,the integration degree of all kinds of electronic equipment is getting higher and higher,and the performance has been greatly improved,at the same time,it brings the problem of increasing the heat production of the equipment.Too high temperature will affect the normal operation of equipment,reduce the reliability of equipment operation,and even damage electronic equipment.At present,there are many internal temperature measurement methods for non vacuum sealed electronic equipment,but in the field of vacuum electronic devices,it is very difficult to measure the internal temperature of high-power vacuum devices such as X-ray bulb tube,traveling wave tube,gyrotron,etc.,and the research on internal temperature inversion is relatively small.Based on the application requirements of satellite communication and medical devices,this project focuses on the research of TWT internal temperature inversion technology,which has high application value.The main research contents are as follows:1.Establish the ANSYS finite element simulation model of TWT slow wave structure and collector,analyze the thermal stability of slow wave structure and collector,and get their temperature nephogram and heat flow vector diagram.In the post-processing,the load value,internal temperature and external temperature data are derived to lay the foundation for the subsequent internal temperature inversion.The test physical model is designed,and the corresponding ANSYS modeling and thermal stability analysis are carried out.The internal and external temperature data are derived to prepare for the verification of the reliability of the inversion model.2.Two kinds of TWT body temperature measurement systems,thermocouple and infrared thermal imager,are designed.Thermocouple temperature measurement system can measure the temperature of TWT body at many points,display the temperature data and temperature curve on the upper computer in real time,and save the data in My SQL database for later query.Temperature nephogram is obtained by two-dimensional interpolation of temperature data measured by thermocouple.The infrared temperature measurement system can continuously measure the temperature image on the surface of the tube body and solve the error problem caused by interpolation.The relevant factors that affect the accuracy of infrared temperature measurement are explored,and the influence of these factors on the results is reduced in the design of experiments.The temperature of the heating process of the experimental model was measured by using the infrared temperature measurement system,and the filter processing was carried out.3.Establish the internal temperature inversion model.According to the characteristics of multi-point measurement data of thermocouple temperature measurement system,shallow BP neural network and DNN neural network model are designed.The multi-point temperature outside the tube and the load inside the tube are used as the input and output of the network to train the network.In the inversion,input the temperature outside the pipe into the trained network to calculate the internal load value,apply the load on the ANSYS simulation model,and carry out the thermal stability analysis to get the temperature distribution of the whole model.According to the characteristics of the temperature image data measured by the infrared temperature measurement system,a CNN neural network model is designed.The input and output are the temperature matrix obtained from the ANSYS simulation of the outer surface and the inner surface of the tube.The infrared temperature measurement system is used to measure the temperature matrix inside and outside the detection model.The external temperature matrix is input into the CNN model established by the simulation data of the detection model ANSYS to calculate the internal temperature matrix,and compared with the measured value,to test the accuracy of the inversion of the model to the real data.The accuracy of the final result is high. |
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