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BODY STRUCTURE OF AUTONOMOUS UNDERWATER ROBOT WITH HIGH MOBILITY AND GREAT SUBMERGING DEPTH
No full textDisclosed is an autonomous underwater robot with high mobility and a great submerging depth, the robot comprising a submarine body (1), a channel propeller (3) and rudder-propeller coupling mechanisms. The submarine body (1) is of a vertically flat structure, the channel propeller (3) is horizontally arranged at the bow of the submarine body (1), and the rudder-propeller coupling mechanisms are arranged on two sides of the submarine body (1); and the channel propeller (3) and the rudder-propeller coupling mechanisms cooperatively control the six degrees of freedom of the submarine body. Each rudder-propeller coupling mechanism comprises a front horizontal rudder plate (5), an auxiliary propeller (6), a rear horizontal rudder plate (11) and a main propeller(12). Each of the two front horizontal rudder plates (5) is provided with one auxiliary propeller (6), and each of the two rear horizontal rudder plates (11) is provided with one main propeller (12). The underwater robot can be used i...(前1000字
LARGE-RANGE CRUISE AUTONOMOUS UNDERWATER ROBOT STRUCTURE
No full textA large-range cruise autonomous underwater robot structure, comprising a robot body (1), a horizontal channel thruster (6), a vertical channel thruster (18), a main thruster system, and a stabilizing wing system. The robot body (1) is of a revolving body structure; and the horizontal channel thruster (6) and the vertical channel thruster (18) are disposed on the bow of the robot body (1) and are perpendicular to one another; and the main thruster system and the stabilizing wing system are disposed at the stern of the robot body (1). The underwater robot structure is suitable for large-range and long-distance detection sampling
一种多目视觉下的导管中心线点云处理方法
No full text本发明涉及一种多目视觉下的导管中心线点云处理方法。其步骤为:将多目相机两两配对，对两两配对的相机进行双目视觉标定，利用统一的标定板将相机坐标系转换到基坐标系下，完成全局标定，进而利用图像处理技术和三维重建原理得到两两配对相机下的三维空间点云，借助于点云的法向量进行点云去重，在点云K邻域进行点云降采样，无序点云有序化等点云处理方法得到导管的中心线曲线。本发明方法可以实现任意异形导管的中心线三维重建，精度高，效率高，应用范围广泛
一种硅化物颗粒增强钛铝基复合涂层及其激光熔覆制备方法
No full text本发明涉及了一种硅化物颗粒增强钛铝基复合涂层及其激光熔覆制备方法。该发明采用半导体激光器通过对激光熔覆工艺参数优化和控制TiAl‑Si系涂层各成分及显微组织等途径制备出具有原位自生Ti5Si3颗粒(含量高达10～14％)增强钛铝基复合涂层，基底相主要为耐高温γ相，获得良好的综合表面性能。本发明通过有效的成分及组织调控和激光工艺参数优化有效降低了钛铝涂层表面开裂敏感性，制备的TiAl‑5Si复合涂层具有低密度、优良的耐磨性及高温抗氧化性，适合作为钛合金表面高温防护涂层
一种火炬对接无人机
No full text本发明涉及无人机技术领域，特别涉及一种火炬对接无人机。包括旋翼无人机、机械臂、视觉引导系统及视觉定位系统，其中机械臂设置于旋翼无人机机身的下方，机械臂用于与目标火炬对接；视觉引导系统设置于旋翼无人机机身的正前方，视觉引导系统用于远距离检测目标火炬的位置；视觉定位系统设置于旋翼无人机的旋翼下方，视觉定位系统用于近距离检测目标火炬的位置。本发明可实现无人机在视觉引导系统引导下的大范围全自主火炬对接，机械臂在视觉定位系统驱动下的小范围精准火炬对接以及机械臂和火炬姿态不影响桨叶安全运行等功能
A Unified Framework for Large-Scale Occupancy Mapping and Terrain Modeling Using RMM
No full textBuilding suitable representations for diversified environments to enable robot autonomous navigation is a complicated task, especially for large-scale environments, where the captured vast amount of data will give rise to computation and storage bottlenecks. In this letter, we first propose the random mapping method (RMM), which can efficiently project the irregular points in the low-dimensional data set into the high-dimensional one, where the points are approximately linearly separable or distributed. In the mapped space, we then propose a unified environment modeling framework in the form of linear parametric model, which can represent the occupancy maps and terrain models consistently. Adopting the idea of parallel computing, we then apply our method to the large-scale environment modeling to reduce the wall-clock time of calculation without losing much accuracy. Experiments were fully conducted to evaluate the proposed random mapping method and the proposed environmental modeling method, show ing their better comprehensive performance compared to the typical methods and state-of-the-art methods
Research on Dynamic Uniform Loading Method of Grain Box of Transport Vehicle Based on Three-dimensional Point Cloud
No full text为了解决联合收获机-运输车协同作业时，运输车粮箱装载不均匀，导致粮箱装载利用率低的问题，提出了一种基于三维点云的动态均匀装载方法。该方法利用相机获取运输车粮箱内装载物的三维点云作为状态反馈信息，建立装载均匀性评估方式，以最均匀装载状态为目标，通过实时调整卸料装载点位置，使粮箱保持在均匀的装载状态。针对装载物相互遮挡对相机形成视觉盲区的问题，通过建立装载物的堆体模型和相机的遮挡模型，以最小期望误差对盲区内装载物高度进行估计，并据此进行点云填充，从而得到能完整反映粮箱装载状态的三维点云。在搭建平台进行的实验中，对粮箱装载过程中可能出现的轻载、中载和重载3种装载状态进行测量，并对盲区点云位置进行估计，其盲区估计的平均误差低于5cm。仿真结果表明，动态均匀装载方法能在有限装载周期内，将粮箱从任意的初始装载状态装载为均匀状态。单次装载量的平均高度增量为2cm，粮箱的初始装载状态为空载时，装载物的最大高度方差为1cm2。单因素仿真结果表明，稳定状态下的装载物高度方差与单次装载量正相关。</p
Service Encapsulation Method Based on Industrial Internet
No full textBased on the analysis of software and hardware integration and highly heterogeneous infrastructure in the traditional industrial field, this paper puts forward the concept of service packaging engine, puts forward a unified service packaging model for Industry by using the Internet thinking design mode, and can complete the control of complex industrial field equipment by editing only simple logic in the programming interface. This article focuses on basic service encapsulation
Intelligent Fault Diagnosis for Bearings of Industrial Robot Joints Under Varying Working Conditions Based on Deep Adversarial Domain Adaptation
No full textIndustrial robots are one of the most typical machines in smart manufacturing systems. Their joint bearing faults account for a significant portion of failures. Data-driven bearing fault diagnosis methods, especially deep learning methods, have become a research hotspot due to the development of the industrial Internet of Things and big data. However, the varying working conditions of industrial robots, such as the continuous changing of load and speed, challenge the existing data-driven methods. Although adversarial-based domain adaptive methods are promising for solving this problem, they still face an equilibrium issue in the model training process. Therefore, a novel deep perceptual adversarial domain adaptive (DPADA) method is proposed for fault diagnosis of industrial robot bearings under varying conditions in this article. Here, a novel perceptual loss is proposed to force the target domain and the source domain to have the same distribution, which helps to improve the stability of adversarial training. Correspondingly, a timestamp mapping-based vibration signal screening method is proposed to improve data preprocessing efficiency for fault diagnosis of industrial robots. Extensive experimental results show that the accuracy of DPADA is superior to convolutional neural network (CNN) and conditional domain-adversarial network (CDAN)-based methods. A comparison is further performed on transfer tasks in three classical transfer scenes of industrial robots
Obstructive Sleep Apnea Detection Scheme Based on Manually Generated Features andParallel Heterogeneous Deep Learning Model under IoMT
No full textObstructive sleep apnea (OSA) syndrome is a common sleep disorder and a key cause of cardiovascular and cerebrovascular diseases that seriously affect the lives and health of people. The development of Internet of Medical Things (IoMT) has enabled the remote diagnosis of OSA. The physiological signals of human sleep are sent to the cloud or medical facilities through Internet of Things, after which diagnostic models are employed for OSA detection. In order to improve the detection accuracy of OSA, in this study, a novel OSA detection system based on manually generated features and utilizing aparallel heterogeneous deep learning model in the context of IoMT is proposed, and the accuracy of the proposed diagnostic model is investigated. The OSA recognition scheme used in our model is based on short-term heart rate variability (HRV) signals extracted from ECG signals. First, the HRV signals and the linear and nonlinear features of HRV are combined into a one-dimensional (1-D) sequence. Simultaneously, a two-dimensional (2-D) HRV time-frequency spectrum image is obtained. The 1-D data sequences and 2-D images are coded in different branches of the proposed deep learning network for OSA diagnosis. To validate the performance of the proposed scheme, the Physionet ApneaECG public database is used. The proposed scheme outperforms the existing methods in terms of accuracy and provides a novel direction for OSA recognition.</p