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arXiv 2022年

作者： Mao, Bing Wu, Xiaoqun Liu, Hui Xu, Yuhua Lü, Jinhu The School of Mathematics and Statistics Wuhan University Hubei430072 China Hubei Key Laboratory of Computational Science Wuhan University Hubei430072 China Research Center of Complex Network Wuhan University Hubei430072 China The School of Automation Huazhong University of Science and Technology Hubei430074 China The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Hubei430074 China The School of Statistics and Data Science Nanjing Audit University Jiangsu211815 China The School of Automation Science and Electrical Engineering Beihang University Beijing100191 China

Adaptive fuzzy control strategies are established to achieve global prescribed performance with prescribed-time convergence for strict-feedback systems with mismatched uncertainties and unknown nonlinearities. Firstly, to quantify the transient and steady performance constraints of the tracking error, a class of prescribed-time prescribed performance functions are designed, and a novel error transformation function is introduced to remove the initial value constraints and solve the singularity problem in existing works. Secondly, based on dynamic surface control methods, controllers with or without approximating structures are established to guarantee that the tracking error achieves prescribed transient performance and converges into a prescribed bounded set within prescribed time. In particular, the settling time and initial value of the prescribed performance function are completely independent of initial conditions of the tracking error and system parameters, which improves existing results. Moreover, with a novel Lyapunov-like energy function, not only the differential explosion problem frequently occurring in backstepping techniques is solved, but the drawback of the semi-global boundedness of tracking error induced by dynamic surface control can be overcome. The validity and effectiveness of the main results are verified by numerical simulations on practical examples. Copyright © 2022, The Authors. All rights reserved.

关键词： Fuzzy control

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complex Fusion Structure Slow Dissociation Simulation Prediction Method

Complex Fusion Structure Slow Dissociation Simulation Predic...

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Chinese automation Congress (CAC)

作者： Dongsheng Zhang Yigeng Wang Wanyi Huang Naval Architecture & Ocean Engineering Institute China Shipbuilding NDRI Engineering Co. Ltd Shanghai China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School and Hospital of Stomatology China Medical University Shenyang China Liaoning Provincial Key Laboratory of Oral Diseases China Medical University Shenyang China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Human skeletal implants, as a category of critically important medical consumables, are designed to remain inside the body for long periods. Titanium or titanium alloys are commonly chosen as the primary construction materials. Recently, the academic community has explored an innovative approach to implant construction that uses titanium as the base framework and zinc as the filling material to create an interconnected composite structure. In this structure, zinc gradually dissolves over the lifetime of the implant, promoting bone growth into the pores formed after its dissolution. Given the continuous dissociation of zinc, the physical and chemical properties of the implant exhibit a slow and continuous change over its lifecycle. However, there is currently no effective method to precisely predict and assess the state changes of such complex structures over long periods of time. This study focuses on the typical application scenarios of human skeletal implants, and verifies the accuracy of short-term steady-state numerical calculation models through rigorous experimental methods. Based on this, we propose a complex fusion structure slow dissociation reverse simulation prediction method based on short-term steady-state calculation results. This method aims to simulate the steady-state performance of implants in the short term, and reverse deduce the structural changes and performance evolution caused by zinc dissociation during long-term use, thereby providing a more scientific basis and support for the design and evaluation of medical implants.

关键词： Titanium alloys Implants Prediction methods Market research Filling Steady-state Numerical models Forecasting Zinc Periodic structures

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A Novel Two-Stage Framework for 2D/3D Registration in Neurological Interventions

A Novel Two-Stage Framework for 2D/3D Registration in Neurol...

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IEEE International Conference on Robotics and Biomimetics

作者： De-Xing Huang Xiao-Hu Zhou Xiao-Liang Xie Shi-Qi Liu Zhen-Qiu Feng Jian-Long Hao Zeng-Guang Hou Ning Ma Long Yan The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The School of Information Shanxi University of Finance and Economics Taiyuan China The CAS Center for Excellence in Brain Science and Intelligence Technology Beijing China The Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology Taipa Macau The Department of Interventional Neuroradiology Beijing Tiantan Hospital Capital Medical University Beijing China

ISBN: (纸本)9781665481106

2D/3D medical image registration of pre-operative volumes and intra-operative images plays an important role in neurological interventions. However, vast space of transformation parameters makes this task incredibly challenging. In this paper, a novel two-stage framework for 2D/3D registration is proposed. It consists of two basic modules: CNN regression for preliminarily estimating transformation parameters, and centroid alignment for further reducing estimation errors to get refined images. Experimental results on two patients show the proposed framework can achieve superior performances to baseline methods with an inference rate of 22 FPS, satisfying real-time requirements (6~12 FPS) in clinical practice. Extensive ablation studies prove the effectiveness of centroid alignment in significantly improving registration accuracies. These promising results indicate the framework has the potential to be integrated into navigation frameworks for neurological interventions, facilitating treatments of physicians.

关键词： Image registration Estimation error Three-dimensional displays Navigation Biomimetics Medical services Real-time systems

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Lidar-Inertial and Downward Vision Based Mobile Robot SLAM in Digital Workshops

Lidar-Inertial and Downward Vision Based Mobile Robot SLAM i...

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Data Driven control and Learning systems (DDCLS)

作者： Yanchao Zhang Hao Geng Bin Liu Yinlong Zhang Xudong Yuan Sichao Zhang School of Information Science and Engineering Shenyang University of Technology Shenyang China Guangzhou Institute of Industrial Intelligence Guangzhou China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In order to solve the problems of long-term cumulative error and the absence of absolute pose in the existing Lidar-Inertial measurement Unit (IMU) fusion methods for Automated Guided Vehicle (AGV) Simultaneous Localization and Mapping (SLAM), we propose a new SLAM method for mobile robot, integrating Lidar, IMU, and a downward vision camera. Firstly, we tightly couple Lidar-IMU and downward vision camera using a multimodal fusion framework. Downward visual measurements are integrated as QR factors into the factor graph, providing absolute pose information to correct cumulative error in the Lidar-IMU system and enable the joint pose estimation of the AGV. Secondly, an enhanced Iterative Closest Point (ICP) point cloud matching algorithm has been developed to correct the incorrect pose. This approach achieves Scan-to-Map alignment by employing a coarse-to-fine matching strategy, thereby enhancing the accuracy of point cloud alignment. Finally, the extended Kalman filter is used to optimize the Lidar pose drift, as well as the Lidar mapping effectively by using the Lidar-IMU as the measurements and the downward visual measurements as the updates. The algorithm has been extensively evaluated on the developed AGV experimental platform. The experimental results show that the position error is less than 0.02 meters and the orientation error is less than 1°, which solves the problems of long-term error accumulation and the lack of absolute pose information for AGV navigation.

关键词： Point cloud compression Visualization Laser radar Simultaneous localization and mapping Conferences Robot vision systems measurement uncertainty

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A numerical boundary integral method for cross-sectional distribution of gas/water two phase flows

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Journal of Physics: Conference Series 2009年第1期147卷

作者： Y Y Xu F Dong C Tan Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 CHINA

A clearer understanding of two-phase flows requires getting the distribution of gas/water two-phase flows non-invasively. A numerical method to get the cross-sectional distribution of gas/water two-phase flows, via acquiring the common boundary of the two domains, is presented. This approach is based on the boundary integral equations reduced from Green's formula and their derivatives, considering that the gas phase is isolating and the conductivity of water phase is known. The forward problem is solved by boundary element method, which shows considerable accuracy but much smaller matrix size compared with finite element method. The boundary integral equations with non-smooth boundaries are discreted, and their Frechet derivatives are linearized. An iterative method is adopted, and the initial guess is estimated with the aid of the Linear Back Projection Algorithm for electrical resistance tomography. Numerical results show that the method can locate the gas bubbles and determine their shape effectively. Residual error is defined to investigate the convergence processes. In the anterior steps, the processes converge more quickly for fewer elements; while in the posterior steps more mesh elements are needed to get better results. Element increment contributes to decrease the final residual errors, but it tends to be faint when the number of elements is considerably large.

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Online Non-Contact Weighing Duck Carcasses Using 2d Images and Deep Learning

SSRN

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SSRN 2022年

作者： Zhao, Yuliang Tian, Kaixuan Chen, Ruoyu Yang, Yongliang School of Control Engineering Northeastern University Hebei Qinhuangdao066001 China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China

In the poultry meat processing industry, non-contact weighing methods based on computer vision have become increasingly popular due to their low costs and high efficiency. However, the accuracy of the traditional 2D image weighing techniques is reduced by the overlap and sway of carcasses. In this paper, we propose a more accurate regression model, Vggx, to weigh duck carcasses through image processing and deep learning. We adopt an image segmentation technique to obtain 2D images of a single duck section under a complex background. The images of the same duck are fused together to estimate its 3D information. Then, we use a convolutional neural network regression model to estimate the weight of duck carcass with the acquired 3D information. The Mean Absolute Percentage Error of our model is 1.46% and the average weight error of our model is 23.1 gram. Experimental results demonstrate that our method is high performance. © 2022, The Authors. All rights reserved.

关键词： Image segmentation

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Comparison of differential pressure model based on flow regime for gas/liquid two-phase flow

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Journal of Physics: Conference Series 2009年第1期147卷

作者： F Dong F S Zhang W Li C Tan Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 CHINA

Gas/liquid two-phase flow in horizontal pipe is very common in many industry processes, because of the complexity and variability, the real-time parameter measurement of two-phase flow, such as the measurement of flow regime and flow rate, becomes a difficult issue in the field of engineering and science. The flow regime recognition plays a fundamental role in gas/liquid two-phase flow measurement, other parameters of two-phase flow can be measured more easily and correctly based on the correct flow regime recognition result. A multi-sensor system is introduced to make the flow regime recognition and the mass flow rate measurement. The fusion system is consisted of temperature sensor, pressure sensor, cross-section information system and v-cone flow meter. After the flow regime recognition by cross-section information system, comparison of four typical differential pressure (DP) models is discussed based on the DP signal of v-cone flow meter. Eventually, an optimum DP model has been chosen for each flow regime. The experiment result of mass flow rate measurement shows it is efficient to classify the DP models by flow regime.

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Oil-water two-phase flow velocity measurement with Continuous wave ultrasonic Doppler

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Journal of Physics: Conference Series 2018年第9期1065卷

作者： Weiling Liu Chao Tan Feng Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China

Oil-water two-phase flow exists widely in many industries. Accurate measurement of flow velocity is of significance for quantify the volume or mass flow rate as well as monitor the operation safety. A non-intrusive one-side Continuous Wave Ultrasonic Doppler (CWUD) sensor is presented for measuring the overall superficial velocity of oil-water two-phase flow. The one-side CWUD sensor consists of two-chip transducer with resonant frequency of 1MHz, both of which are installed at the bottom of test pipe, and the sample volume cover the whole radial direction of pipe cross-section. The Doppler shift signal collected by ultrasonic sensor is directly related to the average velocity of dispersed phase within the sample volume of CWUD. The overall superficial flow velocity is derived by a linear correction of measured average velocity, based on the analysis of average Doppler shift properties in different flow conditions, i.e. water continuous flow and oil continuous flow. Dynamic experiments were conducted at a horizontal oil-water two-phase flow loop. It can be found that the average Doppler shift within the sample volume increases with overall superficial flow velocity, however, varies with different continuous phases at the same overall superficial flow velocity. The results show that the mean relative error of overall superficial flow velocity is 3.45%.

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Flow rate measurement of oil-water two-phase flow based on V-cone flow meter

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Journal of Physics: Conference Series 2009年第1期147卷

作者： F Dong C Tan W Li F S Zhang Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 CHINA

In petroleum industry, oil-water two-phase flow widely exists in production wells, and the measurement of oil-water flow is significant in oil well logging. One method in common use is to build a theoretic model to connect differential pressures generated by a throttling set with flow-rate. Several measuring models were adopted and compared for model selection and modification. A V-cone with 0.65 diameter ratio was selected as the throttling set because of its special structure and intrinsic advantages. In the experiments, the differential pressures measured under different flow range were processed with a homogeneous flow model. And the results show that the error is small in the condition where the oil and water are well mixed, while the error is big when they are not well mixed. A polynomial of the error and the water percentage was fitted to improve the model accuracy and widen the measurement range.

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Flow Rate measurement of Oil/Gas/Water Three‐Phase Flow with V‐Cone Flow Meter

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AIP Conference Proceedings 2010年第1期1207卷

作者： F. S. Zhang F. Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China

Mass flow rate is an important parameter of oil/gas/water three‐phase flow, most multi‐phase flow meters are based on the measurement of total mass flow rate and phase fraction. As the Reynolds number of three‐phase flow grows to a certain number, the oil and water phase are considered as a homogenous mixture with a mixed density. In this case, oil/gas/water three‐phase flow could be measured as gas/liquid two‐phase flow. A V‐cone flow meter with beta ratio of 0.65 is used to make the mass flow rate measurement, the calibration experiment is carried out with oil/water flow, the effect of oil proportion and the mixture Reynolds number on the discharge coefficient of V‐cone flow meter is discussed. Comparison of four typical differential pressure correlations is put forward under experiment condition. Lin correlation best behaved in the experiment and error analysis is done based on it. The experiment result shows the mass flow rate of oil/gas/water flow could be measured by V‐cone flow meter efficiently and the experiment error is acceptable.

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