新型免抬式电动刀架的研究

本文介绍了一种ＣＮＣ机床新型免抬式电动刀架的机械结构及控制电路。该电动刀架采用梯形螺柱螺套副升降机构，可使刀架转位分度时无需抬起上刀体。刀架转位分度采用机－ 电结合的方法，即先在控制电路中使用霍尔元件进行粗定位，再在机械上采用三齿盘实现精定位。     

Remote-controlled flexible pose measurement system and method for a moving target in wind tunnel

The measurement of position and attitude parameters for the isolated target from a high-speed aircraft is a great challenge in the field of wind tunnel simulation technology. This paper proposes a remote-controlled flexible pose measurement system in wind tunnel conditions for the separation of a target from an aircraft. The position and attitude parameters of a moving object are obtained by utilizing a single camera with a focal length and camera orientation that can be changed based on different measurement conditions. Using this proposed system and method, both the flexibility and efficiency of the pose measurement system can be enhanced in wind tunnel conditions to meet the measurement requirements of different objects and experiments, which is also useful for the development of an intelligent position and attitude measurement system. The position and the focal length of the camera also can be controlled remotely during measurements to enlarge both the vertical and horizontal measurement range of this system. Experiments are conducted in the laboratory to measure the position and attitude of moving objects with high flexibility and efficiency, and the measurement precision of the measurement system is also verified through experiments.     

基于Mecanum轮配送车的视觉与磁带双重导引技术研究

针对卫星总装过程中提出的物料配送需求,设计并实现了以Mecanum轮全方位移动平台为基础,可在狭窄配送通道内快速、灵活移动的智能物料配送车。结合总装现场实际环境条件,配送车采用了视觉导引与磁带导引相结合的智能导引策略,有效消除了光照强度变化、地面裂纹、电磁信号干扰等环境因素对车道线采集的影响,最终实现总装物料从库房至多工位的自动配送。     

Visual inspection of aircraft skin: Automated pixel-level defect detection by instance segmentation

Skin defect inspection is one of the most significant tasks in the conventional process of aircraft inspection. This paper proposes a vision-based method of pixel-level defect detection, which is based on the Mask Scoring R-CNN. First, an attention mechanism and a feature fusion module are introduced, to improve feature representation. Second, a new classifier head—consisting of four convolutional layers and a fully connected layer—is proposed, to reduce the influence of information around the area of the defect. Third, to evaluate the proposed method, a dataset of aircraft skin defects was constructed, containing 276 images with a resolution of 960 × 720 pixels. Experimental results show that the proposed classifier head improves the detection and segmentation accuracy, for aircraft skin defect inspection, more effectively than the attention mechanism and feature fusion module. Compared with the Mask R-CNN and Mask Scoring R-CNN, the proposed method increased the segmentation precision by approximately 21% and 19.59%, respectively. These results demonstrate that the proposed method performs favorably against the other two methods of pixel-level aircraft skin defect detection.     

基于机器学习的单孔绝热气膜冷却效率分布预测研究

为了研究利用机器学习技术对绝热冷却效率进行直接预测的方法及特点,搭建了基于上采样卷积神经网络的机器学习模型,生成了用于训练以及验证的数值模拟数据集,使用了监督式学习的方法对模型进行了训练.训练使用反向传播算法和基于随机梯度下降的Adam优化算法,输入模型的参数包括吹风比、主流湍流强度、喷射角、孔形状、孔尺寸,模型输出为...     

基于SVM算法的虚假航迹识别

针对云雨杂波和主被动干扰导致多雷达传感器产生虚假目标航迹的问题,利用支持向量机(SVM)算法的自主学习能力,通过构建基于数据驱动的判别模型进行虚假航迹识别。针对航迹起始得到的目标潜在航迹,利用人工智能数据驱动、自学习的特点,设计了SVM算法。通过对已标记真假的目标航迹样本进行离线学习,形成虚假航迹识别的SVM分类器,实现了基于数据驱动的判别模型代替先验知识规则约束的固定模型,并在工程应用中,利用SVM分类器在线识别虚假航迹,完成实时剔除。通过实测雷达数据实验验证,该算法的目标虚假航迹准确率高达95%以上,完全满足实际的工程应用需求。相比基于阈值或规则进行硬性判断的传统虚假航迹识别方法,所提出的算法不仅提高了准确率,还具有较高的实时性,能够适应复杂多变的杂波环境,在实际应用中具有更强的适应性和实用性。因此,提出的基于SVM算法的虚假航迹识别方法对于密集杂波场景下的虚假航迹剔除问题具有显著的实际应用价值。     

A spanwise loss model for axial compressor stator based on machine learning

In the early stage of aircraft engine design, the through-flow method is an important tool for designers. The accuracy of the through-flow method depends heavily on the accuracy of the loss model. However, most existing models cannot(or cannot well) provide the spanwise loss distribution. To construct an effective spanwise loss model, both turbomachinery knowledge and machine learning skills were used in this paper. A large number of numerical simulations were carried out to build a database con...     

Advanced ensemble modeling method for space object state prediction accounting for uncertainty in atmospheric density

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space traffic management activities such as the satellite conjunction analysis. This paper investigates the evolution of orbit error distribution in the presence of atmospheric density uncertainties, which are modeled using probabilistic machine learning techniques. The recently proposed “HASDM-ML,” “CHAMP-ML,” and “MSIS-UQ” machine learning models for density estimation (Licata and Mehta, 2022b; Licata et al., 2022b) are used in this work. The investigation is convoluted because of the spatial and temporal correlation of the atmospheric density values. We develop several Monte Carlo methods, each capturing a different spatiotemporal density correlation, to study the effects of density uncertainty on orbit uncertainty propagation. However, Monte Carlo analysis is computationally expensive, so a faster method based on the Kalman filtering technique for orbit uncertainty propagation is also explored. It is difficult to translate the uncertainty in atmospheric density to the uncertainty in orbital states under a standard extended Kalman filter or unscented Kalman filter framework. This work uses the so-called “consider covariance sigma point (CCSP)” filter that can account for the density uncertainties during orbit propagation. As a test-bed for validation purposes, a comparison between CCSP and Monte Carlo methods of orbit uncertainty propagation is carried out. Finally, using the HASDM-ML, CHAMP-ML, and MSIS-UQ density models, we propose an ensemble approach for orbit uncertainty quantification for four different space weather conditions.     

PC机与数控机床的通讯方法

随着CAD/CAM技术的兴起,传统手工数控程序编制已经被图形交互式的CAM系统所代替.程序编制成功后可以利用WINDOWS通信终端将程序传输至数控机床.     

一种适用于航天器某些故障诊断的知识获取方法

尽可能快地找出航天器在工作过程中出现的故障，采取补救措施，可减少或避免重大损失。故障诊断专家系统可帮助人们作出快速诊断，但它的诊断准确率主要取决于其知识的正确性。以往这些知识是靠领域专家给出的。本文根据航天器某些故障的特点，提出了一种处理连续变元示例的知识自动获取方法，用这种方法获取的诊断故障的规则，在实践中检验是正确的