Optimization method of traveling-wave tube beam wave interaction distribution structure
A technology of injection wave interaction and optimization method, which is applied in the field of traveling wave tubes to achieve the effect of improving efficiency
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2014-07-23
Smart Images
Figure 1 Figure 2 Figure 3
Abstract
Description
technical field
[0001] The invention belongs to the technical field of traveling wave tubes, and in particular relates to a method for optimizing the injection wave interaction distribution structure of a traveling wave tube. Background technique
[0002] Traveling wave tube is one of the most widely used vacuum electronic devices, widely used in satellite communication, radar, electronic countermeasures and other fields. At present, the use of computer-aided design (Computer Aided Design, CAD) technology is one of the main means to save costs, improve design and improve the overall performance of traveling wave tubes. In the CAD technology of traveling wave tubes, it is of great significance to analyze the interaction between electron beam and high-frequency electromagnetic field in traveling wave tube (namely beam interaction). The injection wave interaction in the traveling wave tube is a process in which the energy of the signal is amplified from left to right: the sign...
Examples
Embodiment Construction
[0021] Below to figure 1 The optimization of the interaction distribution structure is taken as an example, and the present invention will be further described in conjunction with the accompanying drawings and specific implementation examples.
[0022] Specifically, it contains 6 variables (that is, the four distribution length variables z 1 ,z 2 ,z 3 ,z 4 and two pitch variables p 1 ,p 2 , where p 1 is the distribution length z 2 Partial pitch size, p 2 is the distribution length z 4 part of the pitch size), p 0 (distribution length z 1 Part of the pitch size) variables can be determined empirically or by appropriate scans, which can save optimization time. Divide the variables of these 6 interactive distribution structures into two parts, area 1 and area 2, for optimization, where area 2 nests and calls the optimization algorithm of the variables in area 1, and returns the best result of its optimization to the optimization in area 1 algorithm.
[0023] 1. Calcu...