Shenyang Institute of Automation,Chinese Academy Of Sciences
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Spatial curing growth mechanism and defect control of alumina green bodies manufactured by stereo-lithography
No full textUnderstanding the spatial curing growth mechanism and defect formation of green bodies is of great significance for the manufacture of precision and high-performance ceramic products. In this work, the effects of different powder volume fractions and average particle sizes on the spatial curing growth mechanism and defect regulation of alumina green bodies in stereo-lithography were discussed by combining novel mathematical theories and experiments. We found the spatial curing growth characteristics and defect shapes of green bodies in the mathematical model, and obtained the distribution patterns of the beam zone, scattering zone, inadequate curing area and overlap area, as well as their relationship with defect evolution. Furthermore, we verified these characteristics of green bodies through experiments and found that these characteristics could be improved by the most optimal experimental parameters based on mathematical theories. In particular, the print layer thickness could selectively modify the curing shape and improve the printing condition.</p
A supervised independent component analysis algorithm for motion imagery-based brain computer interface
No full textRecognizing the corresponding neural activities of independent components(ICs) obtained by independent component analysis(ICA) is of prime importance to take use of ICA in EEG analysis. There are many methods trying to solve this problem. But most of them combining ICA, a unsupervised method, and recognition of ICs in a separate way. In this paper, we propose a supervised method to extract the independent components corresponding to different motion imagery(MI) activities in the brain. By designing a new optimization objective and solving it, we combine the idea of ICA with principle of MI in an individual algorithm. From the perspective of event-related desynchronization and synchronization (ERD/ERS), specific frequency band power of the motion-related component should be enhanced or suppressed when executing or imaging movement of body. Therefore, the new optimization function extract the components that satisfy both independence and band power maximization for specific motions. Then, we solve this optimization problem based on the fixed-point iteration scheme. In the experimental stages, we show that our methods can extract motion-related independent components without losing independence. Experimental results show that, although basing on the principle of ERD/ERS, our methods’ effectiveness can be verified in the perspective of movement-related potential (MRP). Additionally, by identifying features in the extracted motion-related independent components, we can achieve better motion recognition accuracy. When using the proposed algorithms with different schema, the results yielded significant accuracy imporvements of 6.9%(p</p
Amplitude of undulating fin in the vicinity of a wall: Influence of unsteady wall effect on marine propulsion
No full textTo investigate the role of the amplitude of an object under the unsteady wall effect in fluid dynamics, we modelled an undulating fin near a wall in a two-dimensional Cartesian coordinate system. The fin was tethered in a uniform flow and controlled by a user-defined function program. The unsteady wall effect improved the propulsion force and propulsion efficiency at different amplitudes, but the lift force behaved differently. We determined the critical amplitude for the model, below which the lift force is positive within an appropriate off-wall distance range. At amplitudes larger than the critical amplitude and as the off-wall distance decreases, the average lift force is, however, always negative, causing the undulating fin to overturn towards the wall and lose stability. The essence of propulsion and lift variation lies in the change in the shape of the space between the wall and the fin, which affects the fluid flow structure and pressure distribution. In addition, some interesting phenomena related to the vortex core arrangement and pressure distribution were introduced at different amplitudes caused by the unsteady wall effect. The present results may provide new insights into the behaviours of benthic fish, reducing their undulating amplitudes and pitch angles near walls.</p
AuNU dimers on ITO substrate with the highest refractive index sensitivity as chemical sensor
No full textWe synthesized gold (Au) nano-urchins (AuNUs) and deposited these AuNUs on indium tin oxide (ITO) glass. We compared the influence of the resistance of ITO glass and the deposition density of NUs on refractive index sensitivity (RIS) of these ITO substrates, and found that ITO glass with resistance of 8-12 /sq and substrates with many AuNU dimers gave the highest RIS which was as high as 455 nm/RIU (refractive index unit), which is the highest on substrate as we known. Compared with AuNUs deposited on quartz glass, the extinction peak intensity and RIS were enhanced on ITO glass. The RIS enhancement is mainly attributed to the considerably enhanced electric field at the tips of AuNUs, electrical hot spots generated by AuNU aggregates (such as dimers), and the repulsive forces decrease in each AuNU by the ITO layer. It is thought that further shape, distribution, and size change of AuNUs and dimers on ITO glass will greatly affect the RIS and spectral characteristics. AuNU substrate is then proposed for heparin detection through Au etching. The results showed that heparin detection was realized in a linear range of 0.05 to 5 g/mL with a detection limit of 8 ng/mL, which has potential to be applied in the practical environment.</p
Acoustics-Based Autonomous Docking for A Deep-Sea Resident ROV
No full textThis paper presents autonomous docking of an inhouse built resident Remotely Operated Vehicle (ROV), called Rover ROV, through acoustic guided techniques. A novel cage-type docking station has been developed. The docking station can be placed on a deep-sea lander, taking the Rover ROV to the seafloor. Instead of using vision-based pose estimation techniques and expensive navigation sensors, the Rover ROV docking adopts an ultra-short baseline (USBL) and low-cost inertial sensors to build an adaptive fault-tolerant integrated navigation system. To solve the problem of sonar-based failure positioning, the measurement residuals are exploited to detect measurement faults. Then, an adaptation scheme for estimating the statistical characteristics of noise in real-time is proposed, which can provide robust and smooth positioning results. It is more suitable for a compact and low-cost deep-sea resident ROV. Field experiments have been conducted successfully in the Qiandao Lake and the South China Sea area with a depth of 3000 m, respectively. The experimental results show that the functionality of autonomous docking has been achieved. Under the guidance of the navigation system, the Rover ROV can autonomously and efficiently return to the docking station within a range of 100 m even when the amounts of outliers exist in the acoustic positioning data. These achievements can be applied to current ROVs by an easy retrofit.</p
一种深海用水下复合散热系统及方法
No full text本发明属于水下装备技术领域，具体说是一种深海用水下复合散热系统及方法。包括：控制器、耐压舱外壳、耐压换热组件、散热系统以及隔热层；控制器与散热系统连接，且控制器和散热系统均设于耐压舱外壳内；隔热层设于耐压舱外壳内，耐压舱外壳内焊接有封闭的耐压舱夹层，所述隔热层贴附安装在耐压舱夹层的舱内壁上，以将其与舱内设备隔开；耐压换热组件插设入耐压舱外壳内的耐压舱夹层，耐压换热组件外露且固设于耐压舱外壳外；散热系统与耐压舱夹层连接；散热系统通过通海口连入耐压舱外壳外；所述耐压舱夹层内设有相变液。本发明充分利用舱内空间，采用液冷与相变换热相结合的方式，适用于耐压舱壳较厚且材料导热系数低的水下密闭环境中使用
基于增强现实的复杂易变形舱段对接可视化装配辅助方法
No full text本发明公开了一种基于增强现实的复杂易变形舱段对接可视化装配辅助方法，涉及智能装配领域。该方法利用实测的舱段三维模型构建虚拟装配仿真环境，进行配合间隙及干涉状态检测；采用装配路径智能优化算法，通过标准通讯接口协议与虚拟装配仿真环境进行信息交互，完成最优装配路径规划；将装配引导路径和视觉检测得到的实际装配路径以3D图像、路径偏差数值等形式叠加到虚实配准后的增强现实环境中，实现可视化智能装配辅助功能。本发明可解决复杂易变形舱段对接过程中频繁出现的卡死错位等装配难题，降低对操作人员经验技能的依赖，大幅提高装配效率及一次装配成功率
Incremental Learning Framework for Autonomous Robots Based on Q-Learning and the Adaptive Kernel Linear Model
No full textThe performance of autonomous robots in varying environments needs to be improved. For such incremental improvement, here we propose an incremental learning framework based on Q-learning and the adaptive kernel linear (AKL) model. The AKL model is used for storing behavioral policies that are learned by Q-learning. Both the structure and parameters of the AKL model can be trained using a novel L2-norm kernel recursive least squares (L2-KRLS) algorithm. The AKL model initially without nodes and gradually accumulates content. The proposed framework allows to learn new behaviors without forgetting the previous ones. A novel local epsilon-greedy policy is proposed to speed the convergence rate of Q-learning. It calculates the exploration probability of each state for generating and selecting more important training samples. The performance of our incremental learning framework was validated in two experiments. A curve-fitting example shows that the L2-KRLS-based AKL model is suitable for incremental learning. The second experiment is based on robot learning tasks. The results show that our framework can incrementally learn behaviors in varying environments. Local epsilon-greedy policy-based Q-learning is faster than the existing Q-learning algorithms
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 sigma(x)=Ee(-kx); then, after propagating a certain distance, the stress wave amplitude is more suitable to sigma(x)= 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
Optimization method of Data interaction in power IoT based on particle swarm algorithm
No full textThe ubiquitous power Internet of things (IoT) constructs an intelligent service system with comprehensive perception, efficient response and flexible processing around all departments of the power system and with the support of communication technologies such as mobile Internet and artificial intelligence. With the rapid development of smart IoT perceptual devices and edge computing, it has become possible for perceptual devices and edge IoT agents to cooperate in processing tasks. The task completion time can be greatly reduced through the cooperative processing among multiple entities in the IoT. However, as the scale of the Internet of things and number of to-be-processed tasks expanding year by year, the simple task data interaction between devices can not meet the needs of the completion time. Therefore, it is an urgent problem to optimize data transmission and data interaction in the process of collaborative task processing among IoT devices. Motivated by this point, we propose an optimization method of data interaction in power IoT based on particle swarm algorithm. Evaluation on example IoT networks shows the effectiveness of our method to reduce overall task completion time