Rapid Deformation Calculation for Large Reflector Antennas:A Surrogate Model Method

The surface accuracy of the large-aperture reflector antenna has a significant influence on the observation efficiency.Recent researchers have focused on using the finite element(FE)simulation to study the effect of gravity and heat on the deformation distribution of the main reflector.However,the temperature distribution of the antenna is challenging to obtain,and it takes a long time for the FE simulation to carry out FE modeling and postprocessing.To address these limitations,this study presents a surrogate model based on Extreme Gradient Boosting(XGBoost)and deep Convolutional Neural Network(CNN)to get the deformation distribution of the main reflector quickly.In the design of the surrogate model,using the XGBoost algorithm and sparse sampling to solve the difficulty of obtaining the entire temperature distribution is first proposed,and then a deep CNN is developed for estimating deformation.Based on the effect of dynamic loads on the antenna structure,a diverse data set is generated to train and test the surrogate model.The results show that the surrogate model reduces the calculating time dramatically and can obtain the indistinguishable deformation compared to the FE simulation.This technique provides a valuable tool for temperature and deformation calculation of large-aperture antennas.

施主掺杂对BaTiO3钙钛矿半导体纳米晶光催化性能的影响

以沉淀法制备的Cu2O为牺牲模板剂,采用水热法制备La施主掺杂的BaTiO3钙钛矿半导体纳米晶,借助X射线衍射(XRD)、透射电子显微镜(TEM)、高分辨透射电镜(HRTEM)、X射线光电子能谱((XPS)、扫描电子显微镜(SEM)、紫外-可见漫反射光谱(UV-Vis DRS)表征La掺杂的BaTiO3晶的物相、微观形貌及光催化性能。结果表明,La掺杂BaTiO3构建了晶体缺陷,有效提高了BaTiO3的光催化性能。当掺杂量为4%(w/w)时,样品的光催化性能最好,在可见光照射360 min后,对4-硝基苯酚溶液的降解率可达到93.2%。该催化剂5次循环后的活性仍然大于86.7%,表明La施主掺杂的BaTiO3是一种有效的可见光催化剂。

基于Triplet loss的电磁阀故障识别方法

针对电磁阀故障识别对专家知识依赖过高,现有智能诊断系统多需要人为提取信号特征等问题,以某型号电磁阀作为研究对象,人为设置故障工况,采集各种工况下的多通道运行数据,利用TensorFlow平台搭建了对该电磁阀的端对端故障识别模型。此外,在此基础上又提出了基于Triplet loss函数的改进模型,并进行了验证测试。结果表明,基于Triplet loss的故障识别模型除具有更高的识别准确率之外,对于在不同动作频率下工作的电磁阀信号有更好的泛化能力。