Shenyang Institute of Automation,Chinese Academy Of Sciences
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一种微型仿生跳跃机器人用电机驱动电路
No full text本发明公开了一种微型仿生机器人的驱动电路，能够驱动直流无刷电机，其中电机驱动电路包括反极性保护电路，能驱动直流无刷电机的电机驱动电路，用于改变输入电压给电机霍尔传感器供电的线性稳压器电路，用于降低信号噪声的PI滤波电路，用于显示电源和故障状态的指示灯电路，用于将芯片内部输出电压进行5v和3.3v配置的BUCK电路，用于接受PWM信号以及抱闸和换向信号的控制模块，以及与电机相连接的接口模块组成。由上述电路组成的驱动电路，具有能够接受较大范围电压，使用方便，集成化程度高，电路结构简单，结构紧凑，抗干扰能力强，易于推广的优点
Triggering grabbing type multi-cavity sampling mechanism
No full text本发明涉及航天工程中样品采集技术领域，特别涉及一种触发抓取式多腔采样机构。该机构包括转位组件、采样腔、转盘组件及开腔组件，其中转位组件的输出端与转盘组件连接，并且驱动转盘组件转动；转盘组件上沿周向设有多个采样腔；开腔组件设置于转位组件的下方，用于开启与开腔组件相对应的一个采样腔。本发明通过触发抓取式多腔采样机构的运动，在采样腔与星体表面接触后触发，从而在扭转弹簧的驱动下采样腔门关闭，达到抓取星表样品的目的，对于星体表面一些凹陷的地形有一定的适应能力
一种铺粉式激光增减材加工方法
No full text本发明公开了一种铺粉式激光增减材加工方法，属于激光加工技术领域。由于现有增材制造技术仅能获得近净零件，尚无法制备可直接应用的高尺寸精度和表面质量的零件。为了实现直接获得高尺寸精度和表面质量的零件，本发明采用了铺粉式增材技术、高精度铣削加工的减材技术和合理的工艺参数衔接等方式实现了高表面质量的零件的快速成型，使零件可以直接达到使用要求，提高生产效益
一种面向铝合金激光增材修复的成形质量控制方法
No full text本发明公开了一种面向铝合金激光增材修复的成形质量控制方法，属于铝合金修复的成形控制技术领域。在激光修复过程中，通过循环水冷却系统控制成形，冷却系统由不锈钢循环水冷却板、K型热电偶、零件夹具、温度监控仪和水冷机等关键部件构成。该冷却系统可以通过对基板温度的实时监控，使基板温度均匀降低。通过设置正确的循环水冷却温度与冷却时间，使修复过程中的热积累有效减少，从而细化组织，减少孔隙率，提高合金性能，改善成形质量。该冷却方法及冷却装置在铝合金基材冷却方面有具有很大的应用前景
一种烟热模拟训练路径自动切换装置
No full text本实用新型涉及一种烟热模拟训练路径自动切换装置。装置包括旋转门本体、转门器及电插锁；旋转门本体包括金属网栅通道外框、旋转门框、金属网；转门器包括驱动电机、摆臂及防护外壳；电插锁包括电磁锁舌、磁力传感器及锁片、光栅编码器，驱动控制电路。本实用新型能够在烟热模拟训练中实现路径的自动切换，有效降低了训练设备被暴力破坏的风险，可以有效的提高消防烟热模拟训练的训练效率，路径自动切换装置包含位置反馈可以实时检测到路径的变换状态，提高烟热训练系统的使用寿命和便利性
An optimal visual servo trajectory planning method for manipulators based on system nondeterministic model
No full textWhen a manipulator captures its target by a visual servo system, uncertainties can arise because of mechanical system and visual sensors exist error. This paper proposes an intelligent method to predict the successful rate for a manipulator to capture its target with motion and sensor errors. Because the mapping between the joint space of the manipulator and the Cartesian space at the end of the manipulator is nonlinear, when there is a bounded error of the manipulator's joint, the error range of the end motion is constantly changing with the different joint positions. And at the same time, the visual servo camera will also measure the target from different positions and postures, so as to produce measurement results with different error ranges. The unknown time-varying error property not only greatly affects the stability of the closed-loop control but also causes the capture failure. The purpose of this paper is to estimate the success probability of different capture trajectories by establishing the nondeterministic model of manipulator control system. First, a system model including motion subsystem and feedback subsystem was established with system error described by Gaussian probability. And then Bayesian estimation was introduced into the system model to estimate the executing state of the predefined trajectory. Linear least quadratic regulators (LQR) control is used to simulate the input correction in the closed-loop control between motion subsystem and feedback subsystem. At last, the successful probability of capturing the target is established by the Gaussian distribution at the end point of the trajectory with geometric relationship calculation between tolerance range and error distribution. The effectiveness and practicability of the proposed method are proved by simulation and experiment
A novel transfer learning model for traditional herbal medicine prescription generation from unstructured resources and knowledge
No full textTraditional Chinese medicine (TCM) is an essential part of the world's traditional medicine. However, there are still many issues in the promotion and development of TCM, such as a lot of unique TCM treatments are taught only between the master and an apprentice in practice, it takes dozens of years for a TCM practitioner to master them and the complicated TCM treatment principles. Intelligent TCM models, as a promising method, can overcome these issues. The performance of previously proposed AI models for intelligent TCM is restricted since they rely on clinical medical records, which are limited, hard to collect, and unavailable for intelligent TCM researchers. In this work, we propose a two-stage transfer learning model to generate TCM prescriptions from a few medical records and TCM documentary resources, called TCMBERT for short. First, the TCMBERT is trained on TCM books. Then, it is fine-tuned on a limited number of medical records to generate TCM prescriptions. The experimental results show that the proposed model outperforms the state-of-the-art methods in all comparison baselines on the TCM prescription generation task. The TCMBERT and the training process can be used in TCM tasks and other medical tasks for dealing with textual resources
Adaptive Sliding Mode Robust Control of Multi-joint Lasso Driven Manipulator
No full text套索驱动的机械臂在运动过程中,末端执行器的姿态变化会导致关节伺服系统的负载转动惯量发生改变。负载转动惯量的摄动会造成系统的建模失配,产生建模不确定性,系统鲁棒性下降。首先,根据D-H坐标法建立了基于套索传动机械臂的动力学模型;其次,提出自适应滑模鲁棒控制的基本策略,对机械臂进行控制;再次,引入HJI理论,通过对Lyapunov函数的设计,建立滑模控制律,选取机械臂整体动力学模型为研究对象,引入不确定性参数,加以仿真分析;最后,通过样机实验,对常规滑模控制、基于HJI理论的自适应滑模鲁棒控制的控制策略进行比较,验证本文所提方法的有效性。</p
Toward accurate polyp segmentation with cascade boundary-guided attention
No full textIn clinical practice, accurate polyp segmentation provides important information for the early detection of colorectal cancer. Benefiting from the advancement of deep learning techniques, various neural networks have been developed for polyp segmentation. However, most state-of-the-art methods have suffered from the challenge of precisely segmenting polyps with clear boundaries. To tackle this challenge, in this paper, we propose a novel and effective cascade boundary-guided attention network based on an encoder–decoder framework. Specifically, instead of just using the addition of shallow and deep features, the fine-grained boundary information is explicitly introduced into the skip connection of encoder and decoder layers to achieve accurate polyp segmentation. Moreover, the cascade refinement strategy is utilized into the multi-stage enhancement of boundary features to progressively produce better predictions. Extensive evaluations on five public benchmark datasets show that our method outperforms state-of-the-arts on various polyp segmentation tasks. Further experiments conducted on the cross-dataset (training on one dataset and testing on another dataset) validate the generalization ability of the proposed method.</p
An efficient approach of centroid alignment for spaceflight vehicles considering parameter uncertainties
No full textThis paper deals with centroid alignment for the spaceflight vehicles that work on orbit under microgravity environment, due to the unavailability of centroid measurement on ground, which is based on the principle of mass–radius products in different configurations of static equilibrium. A physical prototype of articulated mechanism for centroid alignment, consisting of three sets of linear modules with moving mass mounted, was developed and experimentally validated. The variational method was adopted to derive the error model for accuracy and sensitivity analysis of the developed articulated mechanism with the consideration of parameter uncertainties, from which it is found that the centroid position of the whole system is much more sensitive to the angular parameter variations than the linear ones. With the developed error model, an iterative approach of centroid alignment to ensure the centroid offset to meet the requirement is proposed, regardless of whether the parameter variations can be ignored, and numerous simulations verify the efficiency of the proposed approach.</p