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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2022

作者： He, Tianfang Xu, Aidong Wang, Kai Zeng, Peng Laboratory of Industrial Control Network and System State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China University of Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Industrial Control Network and System State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9781839538360

Blockages of pressure transmitter sensing line are a recurring problem in nuclear plants. The traditional solution is to purge them with nitrogen periodically, which is time consuming and radiation intensive. It is thus desirable to monitor the status of sensing lines on-site. The noise analysis method is a promising method for sensing line health monitoring. However, the existing noise analysis methods, which evaluate the sensing line status by analyzing time domain or frequency domain features of process noise signal, are susceptible to working conditions of pressure transmitters. Further, blockage degree of the sensing line can not be determined by existing methods. Therefore, this paper proposes a machine learning based noise analysis method for health monitoring of pressure transmitter sensing line, in which 1-D Convolutional Neural Network (CNN) is used to extract features from process noise signals. Experimental results show that the proposed method achieved satisfactory results in diagnosis accuracy, false alarm rate and robustness of the model under different working conditions. Further, blockage degree of sensing line can also be evaluated. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Frequency domain analysis

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Design and manufacturing of micro/nanorobots

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International Journal of Extreme Manufacturing 2024年第6期6卷 169-202页

作者： Junmin Liu Rencheng Zhuang Dekai Zhou Xiaocong Chang Longqiu Li State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbinPeople's Republic of China Key Laboratory of Micro-systems and Micro-structures Manufacturing HarbinPeople's Republic of China Zhengzhou Research Institute of Harbin Institute of Technology ZhengzhouPeople's Republic of China

Micro/nanorobots(MNRs)capable of performing tasks at the micro-and nanoscale hold great promise for applications in cutting-edge fields such as biomedical engineering,environmental engineering,and *** cope with the intricate and dynamic environments encountered in practical applications,the development of high performance MNRs is *** have evolved from single-material,single-function,and simple structure to multi-material,multi-function,and complex ***,the design and manufacturing of high performance MNRs with complex multi-material three-dimensional structures at the micro-and nanoscale pose significant challenges that cannot be addressed by conventional serial design strategies and single-process manufacturing *** material-interface-structure-function/performance coupled design methods and the additive/formative/subtractive composite manufacturing methods offer the opportunity to design and manufacture MNRs with multimaterials and complex structures under multi-factor coupling,thus paving the way for the development of high performance *** this paper,we take the three core capabilities of MNRs—mobility,controllability,and load capability—as the focal point,emphasizing the coupled design methods oriented towards their function/performance and the composite manufacturing methods for their functional *** limitations of current investigation are also discussed,and our envisioned future directions for design and manufacture of MNRs are *** hope that this review will provide a framework template for the design and manufacture of high performance MNRs,serving as a roadmap for researchers interested in this area.

关键词： micro/nanorobots functional structure design manufacturing

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A WLS-Based Step-by-Step Identification Method for Industrial Robot Dynamics Parameters

A WLS-Based Step-by-Step Identification Method for Industria...

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International Conference on Control, Automation and robotics (ICCAR)

作者： Qianjiang Wang Mingxiu Kong Chuancheng Bian Hao Hong State Key Laboratory of Robotics and System School of Mechatronics Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350373172

ISBN: (纸本)9798350373189

In order to improve the accuracy of robot dynamics parameter identification, this paper designs a step-by-step identification method based on weighted least squares. The robot dynamics model is first linearized to obtain the minimum parameter set. Subsequently, the friction model is built separately and experiments are designed to recognize the joint friction parameters first. Based on this, the excitation trajectory of finite term Fourier series is designed and optimized and data are collected. The joint moments obtained from the difference between the overall experimentally collected moments and the calculated friction moments are used to obtain the complete robot dynamics parameters based on weighted least squares identification. Comparison of the designed overall identification experiments shows that the total moment residuals of this method are reduced by 35.52% compared with the one-time identification method, which proves the effectiveness of this method.

关键词： Parameter estimation Accuracy Automation Service robots Friction Industrial robots Kinetic theory

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A Time-Optimal Trajectory Planning Algorithm for Six-Degree-of-Freedom Robots Based on NURBS Curves

A Time-Optimal Trajectory Planning Algorithm for Six-Degree-...

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International Conference on Control, Automation and robotics (ICCAR)

作者： Hao Hong Minxiu Kong Jiawang Wang Qianjiang Wang School of Mechatronics Engineering Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (数字)9798350373172

ISBN: (纸本)9798350373189

In this paper, we research and analyse the practical needs of robotic arm to complete the complex path planning of robotic arm and smooth transition of multi-attitude in the shortest time under the premise of satisfying the dynamics constraints, and put forward the time-optimal trajectory planning based on NURBS curves and multi-attitude interpolation algorithm based on quaternion with NURBS curves. Using the complex nature of quaternions, the quaternions are converted into three-dimensional space points for curve interpolation, and finally converted back to quaternions to achieve the second-order continuity of multi-gesture interpolation; a time-optimal trajectory planning algorithm based on NURBS curves is designed, which discretises the curves, and fits the NURBS curves using the discrete points. At the same time, the optimal rate solution under all the constraints is calculated point by point according to the discrete points on the motion path, and the optimal velocity curve satisfying the dynamics constraints is obtained, so as to achieve the time-optimal trajectory planning. Finally, the feasibility of the designed trajectory planning algorithm is verified in the simulation software and experimental platform, and it is proved that the algorithm can effectively improve the running speed by at least 30%.

关键词： Surface reconstruction Interpolation Trajectory planning Service robots Quaternions Heuristic algorithms Software algorithms

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RETRACTED ARTICLE: Automatic spraying motion planning of a shotcrete manipulator

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Intelligent Service robotics 2023年第5期16卷 643-643页

作者： Liu, Gangfeng Sun, Xianchao Liu, Yubin Liu, Tao Li, Changle Zhang, Xuehe State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

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Research on Surface Defect Detection Technology of Long-Distance and Long-Span FAST Cable

Research on Surface Defect Detection Technology of Long-Dist...

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Mechatronics and robotics Engineering (ICMRE), International Conference on

作者： Xin Tong Xuehe Zhang Gangfeng Liu Changle Li Jie Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Aiming at the problems of large cable span, small number of defect samples and complex background environment in the FAST cable defect detection task, a set of real-time defect detection algorithms based on convolutional neural network is proposed to realize the accurate location and classification of defects. It can achieve a good detection effect for defects with multiple angles and sizes, especially suitable for medium and long distances. The algorithm is verified on the dataset, and its recognition accuracy can reach 91.7%. Equipped on the hardware inference platform, it fully meets the efficiency and accuracy requirements of FAST cable inspection site, can be used in actual cable quality inspection tasks, and can be widely promoted to real-time defect detection of various high-altitude hanging cables.

关键词： Mechatronics Simulation Inspection Real-time systems Inference algorithms Hardware Convolutional neural networks

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Data Augmentation for Improving CNNs in Medical Image Classification

Data Augmentation for Improving CNNs in Medical Image Classi...

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6th International Conference on Intelligent Computing and Signal Processing (ICSP)

作者： Yi Ren Zengmin He Yang Deng Bo Huang State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

Medical image is essential for physicians to diagnose diseases. And convolutional neural networks (CNNs) have gained momentum for computer-aided diagnosis (CAD) medical image. However, there are still challenges in CNNs related to a lack of data and class-imbalanced datasets. Data augmentation is utilized to address the issues mentioned above. In this study, the Pseudo-color enhancement algorithm (OCEAN and TWILIGHT), common linear transform, CLAHE enhancement, and K-means clustering algorithm were applied to pneumonia X-ray images for data augmentation. Thus, five processed datasets were finally obtained. The results indicated that five data-augmentation methods effectively improved the performance of CNNs for the pneumonia X-ray images binary classification detection, in which the CLAHE enhancement and OCEAN enhancement methods had the accuracy and F1 Score with 97.42%, 97.19%, and 97.42%, 98.36%, respectively. DenseNet121 showed the best classification performance of four CNNs utilized in this study, as evidenced by the area under the receiver operating characteristic (ROC) curves (AUC). To verify the generalizability of the two enhancement methods, CLAHE and OCEAN enhancement methods were applied to the Magnetic Resonance Imaging (MRI) dataset of Alzheimer's disease, which had the accuracy and F1 Score with 98.15% , 98.15%, and 97.22%, 97.68%, respectively. Therefore, these simple and efficient data-augmentation methods effectively improve the performance of CNNs for diagnosing medical image, which can provide theoretical reference for physicians to diagnose the above two diseases, and advance the application of clinical medicine.

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A Contactless Magnetic Frequency-Boosting Mechanism for Wind Energy Harvesting

A Contactless Magnetic Frequency-Boosting Mechanism for Wind...

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Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)

作者： Yunfei Li Manjuan Huang Tianyi Tang Heng Zhao Lining Sun Huicong Liu State Key Laboratory of Robotics and System Harbin Institute of Technology (HIT) CHINA School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University CHINA

ISBN: (数字)9798350380200

ISBN: (纸本)9798350380217

This paper presents a non-contact magnetic frequency-boosting wind energy harvester suitable for low wind speed environments, designed to power various IoT sensors. The device comprises a driving component, a driven component, and a stator component. These components work together to convert low-speed rotational motion caused by wind into high-speed rotational motion, thereby achieving high-power electromagnetic energy output. Performance tests have shown that the output voltage increases with wind speed, reaching a peak voltage of 27V and a peak power of 1.6W at a wind speed of 10 m/s. The device has successfully powered LED bulbs and Bluetooth sensors, demonstrating its practicality for real-time environmental monitoring applications.

关键词： Temperature sensors Wind energy Wind speed Magnetic sensors Voltage Stators Sensor systems Environmental monitoring Electromagnetics Power generation

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Aerodynamic Analysis and Deployment Mechanism of A Foldable Mars Quadrotor

Aerodynamic Analysis and Deployment Mechanism of A Foldable ...

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IEEE International Conference on Mechatronics and Automation

作者： Kaijie Zhu Dewei Tang Qiquan Quan Kaiyi Wang Yachao Dong Zongquan Deng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

The Mars quadrotor is a vertical take-off and landing aerial platform developed to enhance the efficiency of Mars exploration. The four-blade rotor has a high thrust coefficient due to its high solidity, which enables the quadrotor to navigate the Martian atmospheric environment efficiently. This paper proposes a payload-carrying Mars quadrotor featuring four four-bladed rotors that can fold along the rotor arms. The computational fluid dynamics (CFD) method is employed to perform numerical hovering simulations, exploring the propulsion capability and aerodynamic efficiency of rotors with different diameters. The mass distribution and hovering time are estimated when the quadrotor consists of the rotors with the highest figure of merit. The results demonstrate that a larger rotor diameter of the quadrotor yields greater payload capacity and shorter hovering time. During the launch, the quadrotor is folded and constrained within an envelope to protect it from vibrations and shocks. A lifting mechanism with shape-constraint slides is utilized for quadrotor deployment.

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A Kinematic Decoupling Whole-body Control Method for a Mobile Humanoid Upper Body Robot

A Kinematic Decoupling Whole-body Control Method for a Mobil...

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Frontiers of robotics and Software Engineering (FRSE), International Conference on

作者： Fengjia Ju Hongzhe Jin Jie Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

The mobile humanoid upper body robot combines the humanoid upper body robot with the mobile platform. It has high redundancy and can complete complex tasks. However, coupling joints, including the waist joints and the mobile platform, exist in the configuration of the robot. During the task execution, the motion of the end-effectors on the dual arms are not independent, but interfere with each other through the motion of the waist and the mobile platform. Therefore, we need to decouple the waist and mobile platform from the dual arms. Based on the pseudo-inverse method of the redundant manipulators, we consider the motion of the coupling joints as a disturbance term and propose a kinematic decoupling whole-body control method. The method realizes the decoupling and cooperation of dual arms, avoids the interference of the inverse kinematics model of the dual arms, and fully releases the application potential of the high redundancy. The decoupling method allows the waist joints and the mobile platform to move randomly without affecting the task operation at the end-effectors, and to further plan their movements separately in order to smooth the whole body motion. The simulations on the mobile humanoid upper body robot verifies our method.

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