Shenyang Institute of Automation,Chinese Academy Of Sciences
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一种精准温控式生物3D打印系统
No full text本发明涉及一种精准温控式生物3D打印系统，包括温控装置、温控打印头、料仓和温控送料管，其中温控打印头可移动地设于温控装置上侧，料仓置于一个水浴温控箱中并通过温控送料管与所述温控打印头连接，所述温控装置包括由上至下依次设置的盖体、箱体和底座，且所述盖体内设有第一制冷组件，所述底座内设有第二制冷组件，所述箱体侧壁上设有红外观测窗口，且所述箱体内部设有测温组件对应所述红外观测窗口，所述箱体包括多个嵌合叠加的连接壳体，所述测温组件包括测温底座和多个测温模块，且各个测温模块依次嵌合叠加。本发明温控装置内部温度均匀，并保证精确控温，并且高度可根据需要调整，另外打印喷头和输料管外侧均设置保温结构
Double-module unfoldable stretch-draw integral structure with self-unfolding folding hinge
No full text本发明涉及一种张力结构，特别涉及一种具有自展开折叠铰链的双模块可展开张拉整体结构。包括下模块单元和上模块单元；下模块单元包括三根下折叠杆；上模块单元包括三根上折叠杆，三根下折叠杆沿周向分布，且下端通过旋转铰链与底座连接，三根上折叠杆与三根下折叠杆通过张力绳连接，形成可展开张拉整体结构。三根下折叠杆通过一组竖索依次首尾连接；三根上折叠杆通过另一组竖索依次首尾连接；三根上折叠杆的上端通过水平索依次连接。本发明占用空间小，适用于航天器运载，节约质量和体积；可在空间上建造大型、轻型结构
一种变形舱段数字孪生体建模方法
No full text本发明涉及一种变形舱段数字孪生体建模方法，涉及逆向建模领域。该方法针对三维激光扫描设备扫描得到的变形舱段的点云数据，对其进行数据处理、特征提取和模型构建。通过使用NX软件提供的二次开发接口，采用C语言作为优选的开发语言进行程序化建模。构建得到的舱段数体孪生体可以为变形舱段虚拟装配对接模型的构建提供虚拟模型基础，为装配过程的部件选配和路径寻优提供数据模型。通过使用NX二次开发程序完成变形舱段数字孪生体的构建，可以将建模过程流程化、规范化，帮助减少重复性操作，提高建模效率，便于用户掌握整个建模流程
辅助多旋翼无人机飞行系统
No full text本实用新型涉及多旋翼无人机技术领域，特别涉及一种辅助多旋翼无人机飞行系统。包括机身及设置于机身两侧的四个主旋翼，还包括两个收放式副旋翼；两个收放式副旋翼分别位于机身的两侧，可进行收放；当两个收放式副旋翼展开时，在机身的两侧形成辅助旋翼。机身的两侧设有收容舱；两个收放式副旋翼可分别收纳于两个收容舱内。本实用新型提高了无人机的飞行速度及转向能力，实现无人机在短时间内飞行更远的距离和能够快速原地水平旋转，达到提高无人机应用作业能力的目标
Research on Industrial Software for Equipment Management in Industrial Production Process
No full text当前,自主工业软件已成为中国工业发展的"卡脖子"问题,设备管理软件作为工业软件中不可缺少的典型应用代表,成为国内研究机构及高新技术公司研究创新的重点方向。基于上述背景,本文介绍了一种前后端分离架构的设备智能管理软件,实现对设备基础信息与运行状态的管理,助力企业数字化转型,提高企业设备管理效率,为我国工业软件自主开发的研究与应用工作提供参考案例。</p
Study of multi-electrode excitation mode for 3D electrical resistance tomography
No full textMulti-electrode excitation is an effective way to improve the performance of 3D electrical tomography (ET) system compared with single electrode excitation. This paper systematically discusses various sensing strategies for multi-electrode excitation with different combinations in radial and axial directions. A typical 3 × 8 3D ERT sensor is adopted to analyze the influence of different excitation modes on performance indexes, such as number of independent measurements, dynamic range of measurements, sensitivity distribution and correlation coefficient of image reconstruction. On the basis of radial rotation angle between the excitation electrodes mapped to the same plane and whether the excitation electrodes are located in the same axial layer, five typical electrode combination modes are designed under dual-electrode excitation and single-electrode measurement protocol. The results show that the variation trend of different indexes influenced by excitation mode is inconsistent. The entropy-based method is applied to comprehensively evaluate the different excitation modes with the selected multiple performance indexes. Among all above modes, the mode in which excitation electrodes are vertically aligned is better universal one. The experimental results show that the position characteristics of the preferable mode can obtain better image reconstruction quality in different distribution models. Furthermore, the better excitation mode will provide guidance for design of other multi-electrode excitation in 3D ET systems with different structures.</p
Binocular Feature Fusion and Spatial Attention Mechanism Based Gaze Tracking
No full textGaze tracking is widely used in driver safety driving, visual impairment detection, virtual reality, human robot interaction, and reading process tracking. However, varying illumination, various head poses, different distances between human and cameras, occlusion of hair or glasses, and low-quality images pose huge challenges to accurate gaze tracking. In this article, based on binocular feature fusion and convolution neural network, a novel method of gaze tracking is proposed, in which local binocular spatial attention mechanism (LBSAM) and global binocular spatial attention mechanism (GBSAM) are integrated into the network model to improve the accuracy. Furthermore, the proposed method is validated on the GazeCapture database. In addition, four groups of comparative experiments have been conducted: between binocular feature fusion model and binocular data fusion model; among the local binocular spatial attention model, the local binocular channel attention model, and the model without local binocular attention mechanism; between the model with GBSAM and that without GBSAM; and between the proposed method and other state-of-the-art approaches. The experimental results verify the advantages of binocular feature fusion, LBSAM and GBSAM, and the effectiveness of the proposed method.</p
High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System
No full textInspired by box jellyfish that has distributed and complementary perceptive system, we seek to equip manipulator with a camera and an Inertial Measurement Unit (IMU) to perceive ego motion and surrounding unstructured environment. Before robot perception, a reliable and high-precision calibration between camera, IMU and manipulator is a critical prerequisite. This paper introduces a novel calibration system. First, we seek to correlate the spatial relationship between the sensing units and manipulator in a joint framework. Second, the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent manner. The calibration has been evaluated on our collected visual inertial-manipulator dataset. The systematic comparisons and analysis indicate the consistency, precision and effectiveness of our proposed calibration method
Research on vertical takeoff strategy on water surface of tiltrotor cross-domain unmanned vehicle
No full text针对跨介质飞行器研究领域目前存在的任务负载小以及近水面介质属性强非线性变化导致的推力损失问题，设计了一种倾转四旋翼跨介质飞行器构型，具有较大的起飞负载，并建立了倾转四旋翼跨介质飞行器近水面静力学模型；在控制策略上，设计了水面垂直起飞流程以及切换控制策略，等效提高了跨介质飞行器近水面推重比，并进一步增强了倾转四旋翼跨介质飞行器起飞过程的稳定性，最后进行实验验证。结果表明，设计的水面垂直起飞流程及切换控制策略，可以实现大负载下倾转四旋翼跨介质飞行器的水面垂直起飞过程。</p
一种基于支持向量机回归的磨削去除量预测方法
No full text本发明公开了一种基于支持向量机回归的磨削去除量预测方法，属于机器学习技术领域。该方法是使用支持向量机回归算法对实验数据进行训练和测试，得到支持向量机预测模型，从而实现对磨削去除量的预测；步骤：(1)数据处理：将实验数据分为训练集数据和测试集数据，并进行归一化处理；(2)构建SVR模型：设定预测模型参数，并对训练集数据进行训练得到预测模型；(3)测试SVR模型：利用预测模型对测试集数据进行测试；(4)判断SVR模型：判断测试结果是否满足要求；(5)预测去除量：如果测试结果满足要求，则保存预测模型并输出预测结果；否则重新选择预测模型参数并进行训练，直至测试结果满足要求