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相控阵天线补偿控制的热变形建模

Thermal Deformation Modeling for Phased Array Antenna Compensation Control.

作者信息

Liu Hui, Wang Wei, Tang Dafeng, Zhang Liyin, Wang Youming, Miao Enming

机构信息

School of Automation, Xi'an University of Posts & Telecommunications, Xi'an 710121, China.

School of Mechano-Electronic Engineering, Xidian University, Xi'an 710071, China.

出版信息

Sensors (Basel). 2022 Mar 17;22(6):2325. doi: 10.3390/s22062325.

DOI:10.3390/s22062325
PMID:35336496
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8950197/
Abstract

Thermal compensation control can correct errors caused by the thermal deformation of phased array antenna (PAA) panels. Thermal deformation of the panel is needed to calculate the compensation value. While the PAA is working, thermal deformation is unconditional to measure, but predicting it by temperature is feasible. However, thermal deformation is also affected by other factors, such as the structural shape, assembly method, and material parameters, and it is difficult to measure these parameters of PAA because of the complex structure. In contrast, the measurement method of the temperature and thermal deformation of the PAA in the laboratory is much easier. Therefore, a comprehensive influence parameters (CIPs)-finite element method (FEM) method was proposed in this study, it can extract the influence of above parameters on thermal deformation from temperature and thermal deformation measurement data and build a thermal deformation prediction model. Experiments have verified that the CIPs-FEM can greatly reduce the difficulty of thermal deformation modeling and have a high prediction accuracy.

摘要

热补偿控制可以校正相控阵天线(PAA)面板热变形引起的误差。需要面板的热变形来计算补偿值。在PAA工作时,热变形无条件可测量,但通过温度预测它是可行的。然而,热变形也受其他因素影响,如结构形状、组装方法和材料参数,并且由于结构复杂,难以测量PAA的这些参数。相比之下,在实验室中测量PAA温度和热变形的方法要容易得多。因此,本研究提出了一种综合影响参数(CIPs)-有限元法(FEM),它可以从温度和热变形测量数据中提取上述参数对热变形的影响,并建立热变形预测模型。实验已验证CIPs-FEM可以大大降低热变形建模的难度并具有较高的预测精度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/b2ec42eb1d25/sensors-22-02325-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/5b44da21beb1/sensors-22-02325-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/2b56f194b824/sensors-22-02325-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/d52e044bbc53/sensors-22-02325-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/46b76ca1fce9/sensors-22-02325-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/1b3e797bcc21/sensors-22-02325-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/499fa68ea6c3/sensors-22-02325-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/94706ad8ebfe/sensors-22-02325-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/8021282914d2/sensors-22-02325-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/b2ec42eb1d25/sensors-22-02325-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/5b44da21beb1/sensors-22-02325-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/2b56f194b824/sensors-22-02325-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/d52e044bbc53/sensors-22-02325-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/46b76ca1fce9/sensors-22-02325-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/1b3e797bcc21/sensors-22-02325-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/499fa68ea6c3/sensors-22-02325-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/94706ad8ebfe/sensors-22-02325-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/8021282914d2/sensors-22-02325-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86c2/8950197/b2ec42eb1d25/sensors-22-02325-g009.jpg

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