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检索条件"机构=Key Laboratory of Networked Control Systems State Key Laboratory of Robotics"

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A Safety Joint with Passive Compliant and Manual Override Mechanisms for Medical robotics

A Safety Joint with Passive Compliant and Manual Override Me...

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IEEE International Conference on Intelligence and Safety for robotics (ISR)

作者： Jia Zheng Shuangyi Wang James Housden Zeng-Guang Hou Davinder Singh Kawal Rhode School of General Engineering Beihang University Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Biomedical Engineering and Imaging Sciences King's College London London UK Xtronics Ltd. Gravesend UK

Force and collision control is a primary concern to guarantee the safe use of medical robots as such systems normally need to interact with clinicians and patients, while at the same time cooperate with other devices. Among different strategies, passive features working with intrinsically safety components are treated as one of the most effective approaches and therefore deserve in-depth study. In this study, we focus on the design of a novel back-drivable safety joint that incorporates a torque limiter with passive compliance and a manual override mechanism to disconnect the robotic joint from its drive train. The design and working principle of the proposed joint are explained, followed by the mathematical analysis of its performance and the impacts of parameters. An example of the design was manufactured and tested experimentally to validate the working concepts. It is concluded that the proposed multi-functional safety joint provides more versatility and customization to the design of bespoke medical robots and would limit the maximum torque that can be exserted onto the patient, allow the clinician to push the joint back, and enable the operator to switch back to manual override.

关键词： Torque Medical robotics Mathematical analysis Manuals Switches Drives Back

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Position tracking for continuum robots with joint limit constraints

Position tracking for continuum robots with joint limit cons...

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2019 IEEE International Conference on Unmanned systems and Artificial Intelligence, ICUSAI 2019

作者： Lin, Dengliang Dong, Xin Yang, Chenguang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Nottingham University Department of Mechanical Materials and Manufacturing Engineering NottinghamNG7 2RD United Kingdom Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

ISBN: (纸本)9781728158594

This paper presents a novel tip-following approach for real-time position tracking and avoiding obstacle of continuum robots with joint limit constraints. This type of hyper-redundant robot, which is more flexible and compliant to explore in complex and constrained environments, such as in pipeline or narrow entrance. However, tradictional method based on inverse kinematic model is difficult to control the end-effector of continuum robot to avoid abstcales in the constrained circumstance. Therefore a new tip-following method based on forward kinematic model is proposed to control the robot and make it inspect the environment. For the method, we use nonliner progamming approach to solve the optimization problem, which is used to find minimum of constrained nonlinear objective function to ensure that the end-effector of the robot follow the desired position with minimal error. In this paper, we employ a 24 DoF continuum robot with continuous backbone and compliant joint to the simulation, and it is testified that the proposed approch can ensure joint limit avoidance, track the end postion in real time and minimize the tracking errors. © 2019 IEEE.

关键词： End effectors

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Design and Implementation of a Lightweight Lower Extremity Exoskeleton

Design and Implementation of a Lightweight Lower Extremity E...

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3rd International Conference on Mechanical, System and control Engineering, ICMSC 2019

作者： Mu, Jiamin Jiang, Hongzhou Hua, Yuxiang Zhao, Jie Zhu, Yanhe State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China Department of Fluid Control and Automation Harbin Institute of Technology Harbin150001 China

This paper summarizes the biomechanics simulation and design of a lightweight lower extremity exoskeleton. The biomechanics simulation was carried out using LifeMOD to obtain joint torques of human body in the condition of its applications including walking on flat ground, ascending stairs, sitting down and standing up which provided the design criteria of actuating torques. The anthropomorphically based exoskeleton has 7 degrees of freedom per leg, two of which are powered by brushless DC motors, and the total mass is less than 12 kg due to the use of carbon fiber material and the compact structural design and optimization. controlling and sensing system based on CANopen communication protocol is proposed which can provide high communication efficiency and reliability for the control of the exoskeleton. © The Authors, published by EDP Sciences, 2019.

关键词： Biomechanics

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Influence of the pyrolysis of benzotriazole passivator on the characteristics of dissolved gas in the insulating oil

Influence of the pyrolysis of benzotriazole passivator on th...

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International Conference on High Voltage Engineering and Application, ICHVE

作者： Sihang Gao Jiajun Li Tingjing Ke Yang Liu Dong Ding Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing China State Grid Chongqing Electric Power Company Chongqing Chongqing China Baoding Electric Power Corporation Baoding China State Key Laboratory of Transmission & Distribution Equipment and Power System Safety and New technology Chongqing University Chongqing China

ISBN: (数字)9781728155111

ISBN: (纸本)9781728155128

Insulation failures of oil-immersed power transformer induced by sulfur corrosion can be controlled by adding the metal passivator into insulating oil. However, it has been reported that the addition of benzotriazole and its derivative passivators into insulating oil would cause abnormal generation of dissolved gases in the oil during the operation of oil-immersed transformer. Therefore, this paper investigated on the effect of passivator on the characteristics of dissolved gas in the oil under the action of thermal field. Benzotriazole (BTA) that widely used in the oil-immersed transformer was selected as the research object, the thermogravimetric analysis of BTA was conducted, and a series of accelerate thermal ageing experiments of oil-paper insulation with and without BTA were also conducted, the composition and content of dissolved gases in oil were measured and analyzed. The results show that BTA was pyrolyzed continuously as the temperature increase. The addition of BTA in oil accelerated the contents of H2, CO and CO2 and decelerated the content of hydrocarbon gases, which lead to abnormal generation of dissolved gases in oil. All of these may interfere the operation condition evaluation of oil-immersed transformer based on DGA technology.

关键词： Oils Gases Aging Power transformer insulation Oil insulation Thermal conductivity Partial discharges

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Authentication Technology in Industrial control System Based on Identity Password

Authentication Technology in Industrial Control System Based...

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第三十九届中国控制会议

作者： Luyao Yang Wenli Shang Chunyu Chen Tianyu Wang Zhoubin Liu Shenyang Institute of Automation Chinese Academy of Sciences School of Information Science and Engineering Northeastern University University of Chinese Academy of Sciences Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Electric Power Research Institute State Grid Zhejiang Electric Power Co.Ltd.

Aiming at the current lack of certification capability in domestic industrial control systems, an industrial control system authentication scheme based on identity cryptography algorithm is proposed. When authenticating between control system devices, the scheme integrates the identity-based digital signature algorithm into the SSL/TLS handshake protocol to complete identity authentication between the engineering station and the trusted PLC. At the same time, when the connection is established for the first time between devices, the connection authentication is selected by the challenge/response based method. The authentication technology based on the identity cryptographic algorithm no longer requires the existence of a public key certificate. This eliminates the need to revoke, store, and issue certificates, simplifies the certification process and reduces the amount of computation required by the authentication process. At the same time, the improved handshake protocol is universal in industrial control systems. The authentication technology based on the identity and password algorithm no longer requires the existence of a public key certificate, eliminating the need for certificate revocation, storage, and issuance, simplifying authentication steps, and reducing system maintenance. Finally, by establishing a test environment, the improved handshake protocol is implemented, and the feasibility of the authentication scheme is verified and analyzed.

关键词： Industrial control security digital signature identity authentication SSL/TLS handshake protocol

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Multivariate Time Series Forecast in Industrial Process Based on XGBoost and GRU

Multivariate Time Series Forecast in Industrial Process Base...

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IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

作者： Naiju Zhai Peifu Yao Xiaofeng Zhou Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China China Copper Co.LTD Kunming China

ISBN: (数字)9781728152448

ISBN: (纸本)9781728152455

In this paper, a time series prediction model that merges eXtreme Gradient Boosting (XGBoost) and Gate Recurrent Unit (GRU), XGB-GRU model, is proposed for multivariate time series prediction in industry. The XGB-GRU model uses XGBoost's strong feature extraction capabilities to extract the hidden information of multiple control variables in industrial data. Next, the model uses GRU's unique gating unit to extract the timing information in the industrial data. Finally, the importance of XGBoost output variables to guide actual production and solve the problem of inexplicability of neural networks. Predicting the temperature of the heating furnace verifies that the proposed XGB-GRU is better than a single XGBoost and GRU model. And the model has a good fit to the predicted value.

关键词： Heating systems Furnaces Time series analysis Predictive models Feature extraction Timing Data mining

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Group Feature Learning and Domain Adversarial Neural Network for aMCI Diagnosis System Based on EEG

Group Feature Learning and Domain Adversarial Neural Network...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Chen-Chen Fan Haiqun Xie Liang Peng Hongjun Yang Zhen-Liang Ni Guan’an Wang Yan-Jie Zhou Sheng Chen Zhijie Fang Shuyun Huang Zeng-Guang Hou State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China First People's Hospital of Foshan Foshan China CAS Center for Excellence in Brain Science and Intelligence Technology Beijing China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology China

Medical diagnostic robot systems have been paid more and more attention due to its objectivity and accuracy. The diagnosis of mild cognitive impairment (MCI) is considered an effective means to prevent Alzheimer's disease (AD). Doctors diagnose MCI based on various clinical examinations, which are expensive and the diagnosis results rely on the knowledge of doctors. Therefore, it is necessary to develop a robot diagnostic system to eliminate the influence of human factors and obtain a higher accuracy rate. In this paper, we propose a novel Group Feature Domain Adversarial Neural Network (GF- DANN) for amnestic MCI (aMCI) diagnosis, which involves two important modules. A Group Feature Extraction (GFE) module is proposed to reduce individual differences by learning group- level features through adversarial learning. A Dual Branch Domain Adaptation (DBDA) module is carefully designed to reduce the distribution difference between the source and target domain in a domain adaption way. On three types of data set, GF-DANN achieves the best accuracy compared with classic machine learning and deep learning methods. On the DMS data set, GF-DANN has obtained an accuracy rate of 89.47%, and the sensitivity and specificity are 90% and 89%. In addition, by comparing three EEG data collection paradigms, our results demonstrate that the DMS paradigm has the potential to build an aMCI diagnose robot system.

关键词： Deep learning Neural networks Medical services Human factors Sensitivity and specificity Feature extraction Robot sensing systems

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A study on rotate vector reducer performance degradation based on acoustic emission techniques

A study on rotate vector reducer performance degradation bas...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： An, Haibo Liang, Wei Ding, Xiaojian Zhang, Yinlong Tan, Jindong State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Guangzhou Chinese Academy of Sciences Guangzhou511548 China Fifth Electronic Institute of MIIT Guangzhou510610 China Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee KonxvilleTN37996 United States

ISBN: (纸本)9781728163215

This paper presents a performance degradation analysis for rotate vector (RV) reducer using acoustic emission (AE) techniques. Unlike the AE signals from fixed gear reducer that are steady and have unchanged route, the AE signals from RV reducer have variant propagation paths and strengths. This work investigates the kinematics model using AE techniques to solve the inherent issues of RV reducer performance degradation analysis, such as signal variabilities and inappropriate thresholds. Firstly, the propagation path of AE signals within the crankshaft is developed. Secondly, the attenuation trend of AE signals is exponentially formulated based on the corresponding propagation curve. The proposed method has been evaluated on the developed RV reducer platform. AE signals were collected under various working conditions, i.e., four abrasion states with eight types of loads and five rotation speeds. The experimental analysis on typical parameters (e.g., signal energies) proves the effectiveness and accuracy of the developed method based on AE techniques. © 2019 IEEE.

关键词： Crankshafts

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Identification of muscle morphology with noncontact capacitive sensing: Preliminary study

Identification of muscle morphology with noncontact capaciti...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Enhao Zheng Jiacheng Wan Dongfang Xu Qining Wang Hong Qiao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Information Engineering China university of geosciences (Beijing) Beijing China The Robotics Research Group College of Engineering Peking University Beijing China

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Human-machine interface with muscle signals serves as an important role in the field of wearable robotics. To compensate for the limitations of the existing surface Electromyography (sEMG) based technologies, we previously proposed a noncontact capacitive sensing approach that could record the limb shape changes. The sensing approach frees the human skin from contacting to the metal electrodes, thus enabling the measurement of muscle signals by dressing the sensing front-ends outside of the clothes. We validated the capacitive sensing in human motion intent recognition tasks with the wearable robots and produced comparable results to existing studies. However, the biological significance of the capacitance signals is still unrevealed, which is an indispensable issue for robot intuitive control. In this study, we address the problems of identifying the relationships between the muscle morphological parameters and the capacitance signals. We constructed a measurement system that recorded the noncontact capacitive sensing signals and the muscle ultrasound (US) images simultaneously. With the designed device, five subjects were employed and the US images from the gastrocnemius muscle (GM) and the tibialis anterior (TA) muscle during level walking were sampled. We fitted the calculated muscle morphological parameters (the pinnation angles and the muscle fascicle length) and the capacitance signals of the same gait phases. The results demonstrated that at least one-channel capacitance signal strongly correlated to the muscle morphological parameters (R 2 > 0.5, quadratic regression). The average R 2 s of the most correlated channels were up to 0.86 for pinnation angles and 0.83 for the muscle fascicle length changes. The interesting findings in this preliminary study suggest the biological physical significance of the capacitance signals during human locomotion. Future efforts are worth being paid in this new research direction for more promising results.

关键词： Muscles Robot sensing systems Capacitance Legged locomotion Electrodes Ultrasonic variables measurement

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An Abnormal state Forecasting Method for Substation Equipment based on Improved LSTM

An Abnormal State Forecasting Method for Substation Equipmen...

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2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019

作者： Li, Tong Yu, Shimao Song, Chunhe Yu, Tongwei Zeng, Peng Shen, Li State Grid Liaoning Electric Power Co. Ltd. Liaoning Electric Power Research Institute Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China State Grid Liaoning Electric Power Co. Ltd. Shenyang China

ISBN: (纸本)9781728149301

Abnormal state accumulation over a long period will cause an electrical equipment fault. Therefore, Substation equipment state forecasting plays a vital role in smart grids. Fault forecasting method based on deep learning have been put forward in recent years, but they have deficiencies dealing with temporal features. This paper proposes an abnormal forecasting method for substation equipment based on improved LSTM, and temporal features of power equipment fault can be extracted effectively for a long-time span. The method reads secondary equipment information through SCADA system, then extracts feature to carry out deep learning training. In this paper, RNN and LSTM are firstly compared, and then the structure and algorithm of improved LSTM are given. This method increases coupling between forget gate and cell state compared with the standard LSTM structure, so as to make better use of information at previous moment. Meanwhile problems of network training and overfitting are discussed. Experiments are conducted to demonstrate that improved LSTM is capable of forecasting accurately the complex electric equipment state with a long forecasting horizon. The accuracy of abnormal state forecasting can reach more than 93% which has a better performance compared with many other methods. © 2019 IEEE.

关键词： SCADA systems

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