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Chinese automation Congress (CAC)

作者： Shenggang Li Wenli Shang Chunyu Chen Yan Lu Zhiwei Dong Ye Xu School of Automation and Electrical Engineering Shenyang Insitute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Shenyang Ligong University China Shenyang Insitute of Automation Institutes for Robtics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Power Grid Technology Center State Grid Liaoning Electric Power Company Limited Electric Power Research Institute Shenyang China School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In today's information age, in order to meet the requirement of high efficiency outlier detection in the production process of industrial control system, the intrusion characteristics are analyzed and warned in time to prevent from happening. An intrusion detection scheme (IGR-MEM) based on information gain ratio feature selection and maximum entropy model is proposed. The collected industrial control data are normalized and a new information gain ratio feature selection method considering feature correlation and redundancy is proposed to choose the best feature subset from the network connection data. According to the extracted training sample feature subset, the maximum entropy model is devoted to construct the classifier, and finally the trained classifier is applied for intrusion detection. The test results express that the IGR-MEM scheme is able to select the best feature collection, improve the detection efficiency, and improve the accuracy of ICS security monitoring and reduce the false alarm rate compared with other algorithms.

关键词： Feature extraction Entropy Intrusion detection Security Process control Redundancy Standards

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A Filtering Approach Based on MMAE for a SINS/CNS Integrated Navigation System

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IEEE/CAA Journal of Automatica Sinica 2018年第6期5卷 1113-1120页

作者： Fangfang Zhao Cuiqiao Chen Wei He Shuzhi Sam Ge School of Computer Science and Engineering and Center for RoboticsUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Automation and Electrical Engineering University of Science and Technology of BeijingBeijing 100083China Social Robotics Laboratory Interactive Digital Media Instituteand Department of Electrical and Computer EngineeringNational University of SingaporeSingapore 117576Singapore Singapore 117576 Singapore

This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.

关键词： Celestial navigation integrated navigation multiple model adaptive estimation unscented Kalman filter （MMAEUKF） strap-down inertial navigation

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Plasmonic microbubble dynamics in Binary liquids

arXiv

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arXiv 2021年

作者： Li, Xiaolai Wang, Yuliang Zeng, Binglin Detert, Marvin Prosperetti, Andrea Zandvliet, Harold J.W. Lohse, Detlef Robotics Institute School of Mechanical Engineering and Automation Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Beijing100191 China Physics of Interfaces and Nanomaterials MESA+ Institute University of Twente Enschede7500 AE Netherlands Physics of Fluids Max Planck Center Twente for Complex Fluid Dynamics and J. M. Burgers Centre for Fluid Mechanics MESA+ Institute University of Twente Enschede7500 AE Netherlands Max Planck Institute for Dynamics and Self-Organization Göttingen37077 Germany Robotics Institute School of Mechanical Engineering and Automation Beihang University Beijing100191 China Physics of Fluids Max Planck Center Twente for Complex Fluid Dynamics and J. M. Burgers Centre for Fluid Mechanics MESA+ Institute and Physics of Interfaces and Nanomaterials MESA+ Institute University of Twente Enschede7500 AE Netherlands Physics of Fluids Max Planck Center Twente for Complex Fluid Dynamics and J. M. Burgers Centre for Fluid Mechanics MESA+ Institute University of Twente Enschede7500 AE Netherlands

The growth of surface plasmonic microbubbles in binary water/ethanol solutions is experimentally studied. The microbubbles are generated by illuminating a gold nanoparticle array with a continuous wave laser. Plasmonic bubbles exhibit ethanol concentration-dependent behaviors. For low ethanol concentrations (fe) of 67.5%, bubbles do not exist at the solid−liquid interface. For high fe values of 80%, the bubbles behave as in pure ethanol. Only in an intermediate window of 67.5% fe 80% do we find sessile plasmonic bubbles with a highly nontrivial temporal evolution, in which as a function of time three phases can be discerned. (1) In the first phase the microbubbles grow, while wiggling. (2) As soon as the wiggling stops, the microbubbles enter the second phase in which they suddenly shrink, followed by (3) a steady reentrant growth phase. Our experiments reveal that the sudden shrinkage of the microbubbles in the second regime is caused by a depinning event of the three-phase contact line. We systematically vary the ethanol concentration, laser power, and laser spot size to unravel water recondensation as the underlying mechanism of the sudden bubble shrinkage in phase 2. Copyright © 2021, The Authors. All rights reserved.

关键词： Plasmonics

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Magnetic Continuum Robot for Intelligent Manipulation in Medical Applications

SmartBot

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SmartBot 2025年

作者： Yuanbiao Ma Xuanyu An Qijun Yang Mingxue Cai Zhiqiang Tang Jinke Chang Veronica Iacovacci Tiantian Xu Li Zhang Qianqian Wang Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments School of Mechanical Engineering Southeast University Nanjing China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Mechanical Engineering National University of Singapore Queenstown Singapore Department of Engineering Science University of Oxford Oxford UK Department of Surgical Biotechnology Division of Surgery & Interventional Science Centre for Biomaterials in Surgical Reconstruction and Regeneration University College London London UK BioRobotics Institute Scuola Superiore Sant’Anna Pisa Italy Department of Excellence in Robotics & AI Scuola Superiore Sant’Anna Pisa Italy Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China Chow Yuk Ho Technology Center for Innovative Medicine The Chinese University of Hong Kong Hong Kong China Multi-Scale Medical Robotics Center Hong Kong Science Park Hong Kong China

Magnetic continuum robots (MCRs) have garnered substantial attention as a new class of flexible robotic systems capable of navigating complex and confined spaces with remarkable dexterity. By combining continuous, deformable structures with remotely applied magnetic fields, MCRs achieve contactless, remote manipulation, making them well-suited for medical applications. This review introduces recent advances in MCR research, focusing on design principles, structural configurations, and control strategies. Various MCR designs and structures, including those integrated with permanent magnets, magnetic matter, ferromagnetic sphere, and micro coil, are discussed. Furthermore, different magnetic actuation platforms are introduced, and the level of MCR automation is classified based on control strategies. Key intelligent manipulation capabilities of MCRs, including navigation, delivery, printing, grasping, imaging, and sensing are explored. Finally, future development priorities and directions are identified to provide insights for advancing intelligent robotic systems.

关键词： intelligent manipulation magnetic actuation magnetic continuum robot medical application

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Depth selection for deep ReLU nets in feature extraction and generalization

arXiv

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arXiv 2020年

作者： Han, Zhi Yu, Siquan Lin, Shao-Bo Zhou, Ding-Xuan State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Information Science and Engineering Northeastern University Shenyang China Center of Intelligent Decision-Making and Machine Learning School of Management Xi'an Jiaotong University Xi'an China School of Data Science Department of Mathematics City University of Hong Kong Hong Kong

Deep learning is recognized to be capable of discovering deep features for representation learning and pattern recognition without requiring elegant feature engineering techniques by taking advantage of human ingenuity and prior knowledge. Thus it has triggered enormous research activities in machine learning and pattern recognition. One of the most important challenge of deep learning is to figure out relations between a feature and the depth of deep neural networks (deep nets for short) to reflect the necessity of depth. Our purpose is to quantify this feature-depth correspondence in feature extraction and generalization. We present the adaptivity of features to depths and vice-verse via showing a depth-parameter trade-off in extracting both single feature and composite features. Based on these results, we prove that implementing the classical empirical risk minimization on deep nets can achieve the optimal generalization performance for numerous learning tasks. Our theoretical results are verified by a series of numerical experiments including toy simulations and a real application of earthquake seismic intensity prediction. Copyright © 2020, The Authors. All rights reserved.

关键词： Feature extraction

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Development of a Smart Instrumentation for Analyzing Railway Track Health Monitoring Using Forced Vibration

Development of a Smart Instrumentation for Analyzing Railway...

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International Conference on Application of Information and Communication Technologies (AICT)

作者： BS Chowdhry Ali Akbar Shah Nick Harris Tanweer Hussain Kashif Nisar National Center of Robotics and Automation -Condition Monitoring Systems Lab Mehran University of Engineering & Technology Jamshoro Pakistan School of ECS University of Southampton UK DHA Suffa University Karachi Pakistan Faculty of Computing and Informatics University Malaysia Sabah Kota Kinabalu Sabah Malaysia

ISBN: (数字)9781728173863

ISBN: (纸本)9781728173870

Harmonic responses play a prominent role in determining metallic faults in railways. Therefore, it is useful to develop some instrumentation governed by the principles of forced vibration to evaluate the health condition of a railway track. The conventional systems developed to identify track damage have large deviations in measurements and are not reliable for examining track faults such as track drainage faults and surface damaged faults. This study focuses on the development of an instrument that analyzes track damage wirelessly in real time. Based on forced vibration, the relation between the harmonic response with the amplitude is demonstrated. The developed instrument was validated on an actual railway track. The result shows that, the developed instrument can be used to determine the serviceability of the railway track, thus avoiding any potential catastrophic events.

关键词： Vibrations Instruments Fault location Harmonic analysis Rail transportation Real-time systems Monitoring

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Hollow ZnO nanorod in PVDF matrix for high-performance sensing, vibration energy harvesting and wearable application

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Scientific reports 2025年第1期15卷 19885页

作者： Pawan Arunkumar Upadhye Shambo Roy Chowdhury Vanish Kumar Rahul Ranjan Sanjeev Kumar Sudip Mondal Junghwan Oh Mrinmoy Misra Mechatronics Engineering Department School of Engineering Manipal University Jaipur Jaipur India. Department of Robotics and Automation Engineering The Neotia University Kolkata West Bengal India. National Agri-Food Biotechnology Institute (NABI) S.A.S. Nagar 140306 Punjab India. Department of Chemical Engineering Indian Institute of Technology Kharagpur India. Department of Physics Chandigarh University Gharuan Mohali 140413 India. kumarsanju25@***. Digital Healthcare Research Center Pukyong National University Busan 48513 the Republic of Korea. Smart Gym-Based Translational Research Center for Active Senior's Healthcare Pukyong National University Busan 48513 Republic of Korea. jungoh@pknu.ac.kr. Mechatronics Engineering Department School of Engineering Manipal University Jaipur Jaipur India. mrinmoy.mishra@jaipur.manipal.edu.

The hollow ZnO nanorods embedded in PVDF matrix were synthesized using a precise solvent casting technique, demonstrating superior performance and significantly enhancing the piezoelectric response, enabling the efficient detection of subtle mechanical stimuli such as gentle touch, bending, and vibration. The incorporation of ZnO nanorods facilitated the formation of the β-phase in PVDF, improved the material's crystallinity, and enhanced visible emission properties, contributing to its energy-harvesting efficiency. The ZnO/PVDF composite outperformed the PVDF film by approximately 6.5 times under repeated tapping energy harvesting conditions. Similarly, the ZnO/PVDF composite outperformed pure PVDF by charging the 10 µF capacitor to 5 V in just 12 s at a vibration frequency of 26.7 ± 0.38 Hz. The harvested energy was successfully deployed to power a standalone Bluetooth Low Energy (BLE) module, which acted as a transmission node for remotely monitoring vibration data from the ZnO/PVDF composite-based sensor. This innovative approach aligns with the advancements in Internet of Things (IoT) technology, highlighting its potential for energy-efficient wearable devices and remote sensing applications in vibration monitoring and other smart systems.

关键词： Flexible Internet of things Nanorods Self-powered ZnO

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Probabilistic learning vector quantization on manifold of symmetric positive definite matrices

arXiv

引用

arXiv 2021年

作者： Sonna, Fengzhen Tang Feng, Haifeng Tino, Peter Si, Bailu Ji, Daxiong 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 Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China School of computer Science University of Birmingham BirminghamB15 2TT United Kingdom School of Systems Science Beijing Normal University Beijing100875 China Institute of Marine Electronics and Intelligent Systems Ocean College Zhejiang University Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of Education Zhoushan316021 China

In this paper, we develop a new classification method for manifold-valued data in the framework of probabilistic learning vector quantization. In many classification scenarios, the data can be naturally represented by symmetric positive definite matrices, which are inherently points that live on a curved Riemannian manifold. Due to the non-Euclidean geometry of Riemannian manifolds, traditional Euclidean machine learning algorithms yield poor results on such data. In this paper, we generalize the probabilistic learning vector quantization algorithm for data points living on the manifold of symmetric positive definite matrices equipped with Riemannian natural metric (affine-invariant metric). By exploiting the induced Riemannian distance, we derive the probabilistic learning Riemannian space quantization algorithm, obtaining the learning rule through Riemannian gradient descent. Empirical investigations on synthetic data, image data, and motor imagery EEG data demonstrate the superior performance of the proposed method. © 2021, CC BY-NC-SA.

关键词： Learning algorithms

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A generalized model for predicting the optimal overlap rate and height of successive single-layer involved in laser metal deposition process based on the aspect ratio

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Optics & Laser Technology 2025年 191卷

作者： Enjie Dong Tingyu Chang Gan Li Ze Liu Liming Xia Linjie Zhao Junwen Lu Jiaxuan Chen Mingjun Chen Jian Cheng State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang 150001 China Department of Mechanical Engineering City University of Hong Kong Hong Kong China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Guangdong 518055 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou 310027 China Aircraft Repair & Overhaul Plant/Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance Civil Aviation Flight University of China Guanghan 618307 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou 450000 China

The surface flatness of single-layer islands deposition is essential for high-quality multi-layer component deposition and the stability of the Laser metal deposition (LMD) manufacturing process. The aspect ratio of single-track deposition and the overlap rate are critical factors influencing the flatness of single-layer island deposition. Existing methods for determining the optimal overlap rate, whether through experimental approaches or simplified recursive overlap models, still suffer from long development cycles and limited accuracy. In this study, a generalized, efficient and reliable model for predicting the optimal overlap rate only using the aspect ratio of the single-track deposition as the input parameter was developed after fully understanding the influence of the aspect ratio and overlap rate on the morphology, stacking effect and flatness of single-layer islands. Besides, a prediction model for the height of the single-layer island, based on the input parameters of the aspect ratio and the overlap rate has also been developed. Further, verification datasets from different experimental batches and materials were used to validate the accuracy and generalizability of the island height prediction model. The validation results indicated that the relative error between the predicted and actual values was less than 10%. The single-track aspect ratio can be directly used to guide the LMD multi-layer component deposition, regardless of the combination of powder and substrate materials, using these reliable and generalized prediction models for the optimal overlap rate and the island height developed in current study. The single-layer island deposition stage was completely eliminated, thereby significantly shorten the development cycle and reduce the cost of LMD process parameter development.

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Introduction of a Flexible Adaptive AUV-Capture Device Based on bio-inspired hydraulic Soft Robot

Introduction of a Flexible Adaptive AUV-Capture Device Based...

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IEEE International Conference on robotics and Biomimetics

作者： Hao Deng Hang Su Tao Mei Wenjun Xu Zhengkun Cheng Xiang Dong Robotics Research Center Peng Cheng Laboratory Shenzhen China School of Electrical Engineering and Automation Anhui University Hefei Anhui China

To capture the non-cooperative and cross-scale underwater objects, an underwater soft bionic robot is proposed according to task function analysis and bionics inspiration. The device was mainly composed of a soft bionic arm and a soft body. It has the abilities of long-distance reachability, end pose adjustment, cross-scale capture, target measurement and recognition. The soft bionic arm is driven by water filling, which has the characteristics of light weight and large shrinkage ratio. It consists of several serially arranged modular soft actuators with diverse functions which can be designed for deep-sea object retrieving. The soft modules are connected by quick-shift joints, which make it possible to adjust the arm configuration specific to the task requirement in situ. The method to test the performance of each functional module is also introduced.

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