Shenyang Institute of Automation,Chinese Academy Of Sciences
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Effect of Stress Wave Propagation on Surface Stress Relaxation in 7050 Aluminum Panel Shocked by a Nanosecond Laser
No full textIntegral panel is an important structure to reduce aircraft weight. Nanosecond laser beams can be used for the forming and surface modification in panels. To explore the propagation of laser-induced stress waves and their influence on surface stress relaxation, a simulation model is used to capture the propagation process of stress waves. The results show that the stress wave first decays rapidly, and then the attenuation rate decreases gradually. In the initial propagation stage, the attenuation of the stress wave can be fitted by σx=Ee-kx; then, after propagating a certain distance, the stress wave amplitude is more suitable to σx= Ex-k. During the propagation processing, the stress wave is reflected on the shocked and back surface. A tensile stress wave is formed by the reflection of the incident compressive stress wave, and the value of the stress wave is improved. The stress wave has a great influence on the residual stress distribution in 1mm thin panels. When the stress wave is reflected on the back surface, a stress is induced into the surface. When the stress wave is reflected by the shocked surface, the stress on the surface is relaxed because the incident wave is a tensile wave. Therefore, when a nanosecond laser is used in thin panels, the shock wave has an important influence on the stress distribution, which needs to be considered in engineering applications.</p
Shape Sensing for Continuum Robots by Capturing Passive Tendon Displacements With Image Sensors
No full textContinuum robots and soft robots have shown great potential in industrial and medical applications. Sensing the shapes of continuum robots is a challenging but significant problem for enhancing their performance during various tasks. In this letter, we present a novel method to estimate the shapes of continuum robots by capturing passive tendon displacements with image sensors. This method is reliable but low-cost. To reconstruct the shape of the continuum robot, an intuitive way based on screw theory and the material frame is also presented. The displacements of passive tendons are related to the integral of the geometric parameters of the continuum robot. By using passive tendon displacements, not only bending but also twisting of the robot can be calculated. The experiments show that our method can estimate the shapes of the robot deformed in different conditions. The mean distal position error is 3.01% of the length and the mean shape error is 1.86% of the length. The mean distal direction error is 4.1 degrees. Besides, sensing the shapes of continuum robots in real-time is also achieved
一种基于低压智能开关的配网台区自动化保护方法
No full text本发明公开了一种基于低压智能开关的配网台区自动化保护方法，包括如下步骤：步骤1：在台区内各级开关位置设置断路器，并且每个断路器均配置保护装置，构成低压智能开关装置；步骤2：以每一台低压智能开关装置为最小单元，以每个配变台区为自治区域，分层分级划分保护区域；步骤3：根据划分的区域信息结合本地信息制定分布式保护策略，并且根据分布式保护策略建立分布式智能保护算法模型，实现故障的检测、定位与隔离；步骤4：对制定的分布式智能保护算法模型进行训练。本发明分区域独立管控，实现快速、有选择的隔离故障，停电范围更小、恢复供电更快
Soft Exoskeleton With Fully Actuated Thumb Movements for Grasping Assistance
No full textIt has been clinically proven that exoskeletons are effective self-training rehabilitation or daily living assistance devices for patients with hand dysfunctions. However, exoskeleton-assisted hand exercises with high degrees-of-freedom are considered as challenging tasks because the digit space, especially the thumb, cannot accommodate enough actuators. In this article, we report a tendon-driven soft hand exoskeleton with a hybrid configuration for thumb actuation. The soft hand exoskeleton system uses the least number of actuators to realize full degrees-of-freedom actuation for all digits. It is tested on a stroke patient with hemiplegia and a healthy subject. The experimental results show that the hand exoskeleton could assist the stroke patient to accomplish various training tasks, such as thumb encircling, grasping, pinching, releasing, and writing. It was found that digit trajectories and joint angle changes of the stroke patient were close to those of the healthy subject. Especially, the range of motion of the stroke patient shows significant improvement with the hand exoskeleton assistance compared to that without the hand exoskeleton assistance. The research in this article paves the way to develop fully actuated soft hand exoskeleton that can be eventually integrated with an electroencephalogram or electromyography for self-training rehabilitation or daily living assistance
Underwater visual-inertial odometry based on monocular direct method
No full text为将视觉惯性里程计（VIO）有效地应用到水下场景中，提出一种适用于自主水下机器人（AUV）执行近距离作业任务时的水下VIO。针对水下环境中缺乏角点以及存在大量重复特征的特点，该系统在视觉部分使用了基于直接法的数据关联方式，在特征点提取过程中将像素点的梯度模作为特征提取的标准；为保证提取出足够多且有效的特征点，采用动态调整特征点提取数量和提取阈值的方法。此外，通过最小化光度误差对视觉状态量进行估计。在AQUALOC数据集上的实验表明，本系统采用的直接法在比较恶劣的水下环境中获得了比ORBSLAM3更高的定位精度，并可构造出相对稠密的地图。</p
SIASAIL-I solar sail: From system design to on-orbit demonstration missions
No full textSolar sails, characterized by passive propulsion, have attracted an increasing attention of researchers, which has important value in the field of deep space exploration. SIASAIL-I is an on-orbit verification mission for solar sails based on a 6U cubesat, designed and produced by Shenyang Institute of Automation, Chinese Academy of Sciences (SIA, CAS). SIASAIL-I deployment mechanism is composed by two-stage deployment system, which can achieve direction transformation, stretching and membrane deploying in the narrow space of the cubesat. SIASAIL-I only takes up within 0.5U (48 mm x 90 mm x 95 mm) space and the total mass is within 1kg. SIASAIL-I was successfully launched from the Xiaoxiang-1 07 satellite on August 31, 2019, and successfully deployed a 0.78 m x 0.78 m sail in low earth orbit in December. This paper introduces the design process of SIASAIL-I system, including deployment mechanism, a series of ground experiments, and an de-orbit mission analysis, which aims to provide some engineering experience for the development of solar sails
CF-DAML: Distributed automated machine learning based on collaborative filtering
No full textThe search for a good machine learning (ML) model takes a long time and requires the considerations of many alternatives, including data preprocessing, algorithm selection, and hyperparameter tuning methods. Thus, tedious searches face a combinatorial explosion problem. In this work, we build a new automated machine learning (AutoML) system called CF-DAML, a distributed automated system based on collaborative filtering (CF), to address these challenges by recommending and training suitable models for supervised learning tasks. CF-DAML first computes some informative meta-features for a new dataset, then uses a weighted l(1)-norm (W1-norm) to accurately calculate the k nearest neighbors (kNN) of the new dataset, and finally recommends the top N models with good performances on each of its neighbors to the new dataset. We also design a distributed system (DSTM) for training the models to reduce the time complexity substantially. In addition, we develop a multilayer selective stacked ensemble system (MSSE), whose base models are selected from among suitable candidate models based on their runtimes, classification accuracies, and diversities, to enhance the stability of CF-DAML. To our knowledge, this is the first work to combine memory-based CF and the selective stacked ensemble to solve the AutoML problem. Extensive experiments are conducted on many UCI datasets and the comparative results demonstrate that our approach outperforms the current state-of-the-art methods
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
一种空间站舱内实验平台通风管路结构
No full text本发明属于载人航天空间站应用系统技术领域，特别涉及一种空间站舱内实验平台通风管路结构。包括科学实验平台、管路固定支架系统、通风管路系统及管路系统下部支撑结构，其中管路固定支架系统设置于科学实验平台上，通风管路系统设置于管路固定支架系统上，管路系统下部支撑结构设置于科学实验平台的下部，管路系统下部支撑结构用于固定通风管路系统。本发明结构紧凑，占用体积较小，不影响科学载荷安装空间，结构空间利用率高，满足操作空间要求，便于拆装
面向固定翼无人机海上回收的拦阻机构及控制方法
No full text本发明涉及一种面向固定翼无人机海上回收的拦阻机构及控制方法，其中回收绳高度调节组件设有滑块，且所述滑块上设有回收绳转向组件，回收绳两端分别绕过对应侧的回收绳转向组件后绕置于对应侧的回收绳收放组件中；回收绳高度调节组件包括皮带、调节驱动电机和减摇控制模块，皮带通过调节驱动电机驱动移动，且调节驱动电机通过减摇控制模块控制转速，滑块与皮带一侧固连；回收绳收放组件包括绕线轮、收放驱动电机和柔性变阻尼控制模块，回收绳缠绕于绕线轮上，且绕线轮通过收放驱动电机驱动转动，收放驱动电机通过柔性变阻尼控制模块控制转速。本发明可以降低甲板摇摆对无人机回收的影响，确保无人机水上回收过程中的控制精度