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Adaptive Remaining Useful Life Prediction Based on a System-Level Variable Structure Degradation Model

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Wang, Xiangyu Si, Xiaosheng Xi, Xiaopeng Zhou, Donghua Shandong University of Science and Technology College of Electrical Engineering and Automation Qingdao 266590 China Xi’an Research Institute of High-Tech Department of Automation Xi’an 710025 China Xi’an Jiaotong University Key Laboratory of Education Ministry for Modern Design and RotorBearing System Xi’an 710049 China Universidad Técnica Federico Santa María Advanced Center for Electrical and Electronic Engineering Valparaíso Chile Southeast University School of Automation Nanjing 211189 China

Accurate prediction of remaining useful life (RUL) for complex systems is often challenged by dynamic and non-stationary degradation behaviors, as well as model mismatches arising from fixed-structure assumptions. To address these challenges, this study proposes an adaptive RUL prediction method based on a system-level variable structure degradation model (SVSDM). In terms of model construction, the initial SVSDM is developed using historical data from multiple sensors, with calibration moments determined by the proposed triggering mechanism. When the calibration is triggered, the model structure is updated accordingly;otherwise, only the parameters of the SVSDM are updated. For RUL prediction, the probability density function (PDF) based on the SVSDM is analytically derived under the first hitting time (FHT) concept. To implement the proposed method, parameter estimation for the SVSDM is performed using maximum likelihood estimation (MLE) algorithm, with dynamic parameter updates facilitated by the Kalman filter (KF). Finally, a case study on furnace wall degradation demonstrates the effectiveness and practical applicability of the proposed method. © 1963-2012 IEEE.

关键词： Kalman filter maximum likelihood estimation model calibration Remaining useful life system-level variable structure degradation model triggering mechanism

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Advancing Embodied Intelligence in Robotic-Assisted Endovascular Procedures: A Systematic Review of AI Solutions

arXiv

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arXiv 2025年

作者： Yao, Tianliang Lu, Bo Kowarschik, Markus Yuan, Yixuan Zhao, Hubin Ourselin, Sebastien Althoefer, Kaspar Ge, Junbo Qi, Peng Department of Control Science and Engineering College of Electronic and Information Engineering Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China Department of Electronic Engineering Faculty of Engineering The Chinese University of Hong Kong 999077 Hong Kong Robotics and Microsystems Center School of Mechanical and Electrical Engineering Soochow University Suzhou215131 China Bavaria Forchheim91301 Germany CREATe Division of Surgery & Interventional Science UCL LondonHA7 4LP United Kingdom School of Biomedical Engineering & Imaging Sciences King’s College London LondonSE1 7EH United Kingdom Centre for Advanced Robotics @ Queen Mary School of Engineering and Materials Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Cardiology Zhongshan Hospital Fudan University Shanghai Institute of Cardiovascular Diseases Shanghai200032 China State Key Laboratory of Cardiovascular Diseases Medical Innovation Center Shanghai East Hospital School of Medicine Tongji University Shanghai200092 China

Endovascular procedures have revolutionized the treatment of vascular diseases thanks to minimally invasive solutions that significantly reduce patient recovery time and enhance clinical outcomes. However, the precision and dexterity required during these procedures poses considerable challenges for interventionists. Robotic systems have emerged offering transformative solutions, addressing issues such as operator fatigue, radiation exposure, and the inherent limitations of human precision. The integration of Embodied Intelligence (EI) into these systems signifies a paradigm shift, enabling robots to navigate complex vascular networks and adapt to dynamic physiological conditions. Data-driven approaches, advanced computer vision, medical image analysis, and machine learning techniques, are at the forefront of this evolution. These methods augment procedural intelligence by facilitating real-time vessel segmentation, device tracking, and anatomical landmark detection. Reinforcement learning and imitation learning further refine navigation strategies and replicate experts’ techniques. This review systematically examines the integration of EI principles into robotic technologies, in relation to endovascular procedures. We discuss recent advancements in intelligent perception and data-driven control, and their practical applications in robot-assisted endovascular procedures. By critically evaluating current limitations and emerging opportunities, this review establishes a framework for future developments, emphasizing the potential for greater autonomy and improved clinical outcomes. Emerging trends and specific areas of research, such as federated learning for medical data sharing, explainable AI for clinical decision support, and advanced human-robot collaboration paradigms, are also explored, offering insights into the future direction of this rapidly evolving field. © 2025, CC BY.

关键词： Medical robotics

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Intuitive tasks planning using visuo-tactile perception for human robot cooperation

arXiv

引用

arXiv 2021年

作者： Katyara, Sunny Ficuciello, Fanny Teng, Tao Chen, Fei Siciliano, Bruno Caldwell, Darwin G. Department of Advanced Robotics Istituto Italiano di Tecnologia Via Morego 30 Genova16163 Italy Department of Information Technology and Electrical Engineering PRISMA Lab University of Naples Federico II Naples80125 Italy Universita Cattolica del Sacro Cuore Via E.Parmense 84 Piacenza29122 Italy Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

Designing robotic tasks for co-manipulation necessitates to exploit not only proprioceptive but also exteroceptive information for improved safety and autonomy. Following such instinct, this research proposes to formulate intuitive robotic tasks following human viewpoint by incorporating visuo-tactile perception. The visual data using depth cameras surveils and determines the object dimensions and human intentions while the tactile sensing ensures to maintain the desired contact to avoid slippage. Experiment performed on robot platform with human assistance under industrial settings validates the performance and applicability of proposed intuitive task formulation. © 2021, CC BY.

关键词： Robot programming

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FreeDriveRF: Monocular RGB Dynamic NeRF without Poses for Autonomous Driving via Point-Level Dynamic-Static Decoupling

arXiv

引用

arXiv 2025年

作者： Wen, Yue Song, Liang Liu, Yijia Zhu, Siting Miao, Yanzi Han, Lijun Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China Dimanshen Technology Co. Ltd. China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China

Dynamic scene reconstruction for autonomous driving enables vehicles to perceive and interpret complex scene changes more precisely. Dynamic Neural Radiance Fields (NeRFs) have recently shown promising capability in scene modeling. However, many existing methods rely heavily on accurate poses inputs and multi-sensor data, leading to increased system complexity. To address this, we propose FreeDriveRF, which reconstructs dynamic driving scenes using only sequential RGB images without requiring poses inputs. We innovatively decouple dynamic and static parts at the early sampling level using semantic supervision, mitigating image blurring and artifacts. To overcome the challenges posed by object motion and occlusion in monocular camera, we introduce a warped ray-guided dynamic object rendering consistency loss, utilizing optical flow to better constrain the dynamic modeling process. Additionally, we incorporate estimated dynamic flow to constrain the pose optimization process, improving the stability and accuracy of unbounded scene reconstruction. Extensive experiments conducted on the KITTI and Waymo datasets demonstrate the superior performance of our method in dynamic scene modeling for autonomous driving. Our implementation will be available at https://***/IRMVLab/FreeDriveRF. Copyright © 2025, The Authors. All rights reserved.

关键词： Optical flows

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An Experimental Testing of Optimized Fuzzy Logic-Based MPPT for a Standalone PV System Using Genetic Algorithms

引用

Mathematical Problems in Engineering 2023年第1期2023卷

作者： Yahiaoui, Fatah Chabour, Ferhat Guenounou, Ouahib Bajaj, Mohit Hussain Bukhari, Syed Sabir Shahzad Nazir, Muhammad Pushkarna, Mukesh Mbadjoun Wapet, Daniel Eutyche Faculté de Technologie Université de Béjaïa Béjaïa06000 Algeria GREAH Laboratory University of le Havre 25 Rue Philippe Lebon Le Havre76600 France Dehradun248002 India Graphic Era Hill University Dehradun248002 India Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Electrical and Electronics Engineering Chung-Ang University Dongjak-gu Seoul06974 Korea Republic of Faculty of Automation Huaiyin Institute of Technology Huai'an223003 China Department of Electrical Engineering GLA University Mathura281406 India National Advanced School of Engineering Université de Yaoundé I Yaoundé Cameroon

The choice and the dimensioning of the controller for the maximum power point tracking (MPPT) are determined for the ideal energy efficiency of the photovoltaic (PV) systems. Many works have been developed in the field of MPPT methods, especially fuzzy logic controllers. However, these are robust if the parameters of the membership functions have been well designed. In this paper, the performances of an intelligent fuzzy logic controller (FLC)-based MPPT method have been optimized by an evolutionary genetic algorithm (GA). The works presented in the literature have shown the efficiency of the proposed method compared to classical methods. In our paper, the validation of the experimental results obtained is given with respect to a reference signal. The control of the simulated PV source and the proposed method are built using the Simulink/Matlab environment and implemented on the dSPACE DS1104 controller to validate the practical execution of the suggested method. The standalone PV system has been tested in an emulated test bench experimentation. Experimental results confirm the efficiency of the proposed method and its high accuracy in handling fast varying load conditions. © 2023 Fatah Yahiaoui et al.

关键词： Genetic algorithms

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Dynamics of opinions with bounded confidence in social cliques: Emergence of fluctuations

arXiv

引用

arXiv 2021年

作者： Zhang, Jiangbo Yuan, Deming Wang, Lei Altafini, Claudio Shi, Guodong School of Sciences Southwest Petroleum University Chengdu China Research School of Engineering The Australian National University CanberraACT Australia School of Automation Nanjing University of Science and Technology Nanjing China Australian Center for Field Robotics The University of Sydney SydneyNSW2008 Australia Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney SydneyNSW2008 Australia

In this paper, we study the evolution of opinions over social networks with bounded confidence in social cliques. Node initial opinions are independently and identically distributed;at each time step, nodes review the average opinions of a randomly selected local clique. The clique averages may represent local group pressures on peers. Then nodes update their opinions under bounded confidence: only when the difference between an agent individual opinion and the corresponding local clique pressure is below a threshold, this agent opinion is updated according to the DeGroot rule as a weighted average of the two values. As a result, this opinion dynamics is a generalization of the classical Deffuant-Weisbuch model in which only pairwise interactions take place. First of all, we prove conditions under which all node opinions converge to finite limits. We show that in the limits the event that all nodes achieve a consensus, and the event that all nodes achieve pairwise distinct limits, i.e., social disagreements, are both nontrivial events. Next, we show that opinion fluctuations may take place in the sense that at least one agent in the network fails to hold a converging opinion trajectory. In fact, we prove that this fluctuation event happens with a strictly positive probability, and also constructively present an initial value event under which the fluctuation event arises with probability one. These results add to the understanding of the role of bounded confidence in social opinion dynamics, and the possibility of fluctuation reveals that bringing in cliques in Deffuant-Weisbuch models have fundamentally changed the behavior of such opinion dynamical processes. © 2021, CC BY-NC-ND.

关键词： Dynamics

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Aleatoric-Uncertainty-Aware Maximum Intensity Projection-Based GAN for 7T-Like Generation from 3T TOF-MRA

引用

IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Tang, Wei Dai, Yuxiang Zhang, Boyu Shi, Zhang Chu, Ying-Hua Zhuang, Peixian Shen, Dinggang Wang, Chengyan Wang, He Fudan University Institute of Science and Technology for Brain-Inspired Intelligence Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Shanghai 200433 China Fudan University Department of Radiology Zhongshan Hospital Shanghai200031 China Siemens Healthineers Ltd. MR Research Collaboration Team Shanghai310000 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education the School of Automation and Electrical Engineering Beijing100083 China ShanghaiTech University School of Biomedical Engineering State Key Laboratory of Advanced Medical Materials and Devices Shanghai201210 China Shanghai United Imaging Intelligence Co. Ltd. Shanghai200232 China Shanghai Clinical Research and Trial Center Shanghai201210 China Fudan University Human Phenome Institute Shanghai200437 China Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine Department of Radiology Shanghai200434 China

Time-of-flight magnetic resonance angiography (TOF-MRA) is a prevalent vascular imaging technique for assessing cerebrovascular diseases. Compared to routine 3T TOF-MRA, 7T TOF-MRA provides vascular structures with a higher signal-to-noise ratio (SNR) and better vessel contrast, revealing greater vascular details. However, the inaccessibility of 7T scanners and specific physiological and technical concerns limit its clinical application. Therefore, we aimed to generate high-quality 7T-like TOF-MRA from 3T TOF-MRA. Considering the spatial sparsity of vessel signals, the visibility discrepancy of distal and small vessels between 3T and 7T images, and the subtle spatial misalignment between paired data, we proposed a novel aleatoric-uncertainty-aware maximum intensity projection-based generative adversarial network (AU-MIPGAN). In our method, we employed a knowledge distillation (KD) framework to incorporate multi-directional MIP information into the 3T-to-7T learning process to strengthen the learning of vessels and provide three-dimensional (3D) vascular morphological knowledge for the student model, facilitating accurate generation of vascular structures. Furthermore, we exploited AU modeling to compensate for the spatial misalignment between paired 3T and 7T images during the training procedure, which helped the model concentrate more on learning the intrinsic gap between 3T and 7T images. Qualitative and quantitative results demonstrated that the proposed AU-MIPGAN can achieve promising performance for 7T-like TOF-MRA generation. © 2013 IEEE.

关键词： Blood vessels

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A novel data glove design with parallelogram structure based on linkage mechanism of human hand

A novel data glove design with parallelogram structure based...

引用

CSAA/IET International Conference on Aircraft Utility Systems 2020, AUS 2020

作者： Chen, Zhuoyuan Zhou, Jianfeng Wang, Shaoping Zhang, Pengyu Zhang, Chao Huang, Shouqing School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big-Data Based Precision Medicine Beihang University Beijing China The Department of Mechanical and Aerospace Engineering Case Western Reseerve University Cleveland United States Beijing Institute of Spacecraft Environment Engineering China Academy of Space Technology Beijing China

ISBN: (纸本)9781839535635

In this paper, a noval type of data glove is designed based on the principle of parallelogram, which aims to detect gestures in real time. In addition to the flexion and extension angles, this glove can detect the adduction and abduction angles of each finger. Because the overall structure of this data glove is optimized according to the linkage mechanism among joints of human hand. The data glove has the advantages of simple structure, convenient wearing, light weight and good comfort. The glove is composed of four parts: framework, bearings, connecting rods and potentiometers. The framework and connecting rods are respectively made of photosensitive resin and laser cut carbon fiber board. Potentiometers are installed on the bearings to detect the angle of rotation. In this paper, kinematic modeling of human hand is carried out. When knowing the rotation angles of each joint of human hand, the posture of the hand can be calculated by the model. Finally, the data glove is tested on the wearer's hand. Angles of each joint measured by the data glove is compared with the actual angles to verify the accuracy and feasibility of this design. © 2020 Institution of Engineering and technology. All rights reserved.

关键词： Structural design

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H2 model reduction for diffusively coupled second-order networks by convex-optimization

arXiv

引用

arXiv 2021年

作者： Yu, Lanlin Cheng, Xiaodong Scherpen, Jacquelien M.A. Xiong, Junlin School of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China Westlake Institute for Advanced Study Westlake University Hangzhou310024 China Department of Engineering University of Cambridge Trumpington Street CambridgeCB2 1PZ United Kingdom Jan C. Willems Center for Systems and Control Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands Department of Automation University of Science and Technology of China Hefei230026 China

This paper provides an H2 optimal scheme for reducing diffusively coupled second-order systems evolving over undirected networks. The aim is to find a reduced-order model that not only approximates the input-output mapping of the original system but also preserves crucial structures, such as the second-order form, asymptotically stability, and diffusive couplings. To this end, an H2 optimal approach based on a convex relaxation is used to reduce the dimension, yielding a lower order asymptotically stable approximation of the original second-order network system. Then, a novel graph reconstruction approach is employed to convert the obtained model to a reduced system that is interpretable as an undirected diffusively coupled network. Finally, the effectiveness of the proposed method is illustrated via a large-scale networked mass-spring-damper system. Copyright © 2021, The Authors. All rights reserved.

关键词： Convex optimization

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Review on polishing of atomic-level surfaces for potassium dihydrogen phosphate

引用

Tribology International 2024年 198卷

作者： Meng, Fanning Zhang, Zhenyu Zeng, Zinuo Fan, Cheng Gu, Yang Gao, Fei Luo, Hao Wang, Jianmei Li, Guo School of Mechanical Engineering Hangzhou Dianzi University Hangzhou 310018 China State Key Laboratory of High-performance Precision Manufacturing Dalian University of Technology Dalian 116024 China College of Management Science Chengdu University of Technology Chengdu 610059 China Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electrical Engineering Soochow University Suzhou 215021 China Institute of Development for Science and Technology Hainan University Haikou 570228 China Department of Mechanical Engineering Tsinghua University Beijing 100084 China Luoyang Bearing Research Institute Co. Ltd Luoyang 471039 China Baoshan Longi Silicon Material Co. Ltd Baoshan 678315 China School of Mechanical Engineering Taiyuan University of Science and Technology Taiyuan 030024 China Research Center of Laser Fusion China Academy of Engineering Physics Mianyang 621900 China

Potassium dihydrogen phosphate (KDP) is a key material for inertial confinement fusion and nonlinear optic devices. However, KDP is soft-brittle, deliquescent and temperature-sensitive, making it become a difficult-to-process crystal. Even that, high-performance devices of KDP strictly require atomic-level surfaces, rising a challenge for ultra-precision machining. Due to the nature of deliquescence of KDP, traditional polishing methods are disabled to machine it. As a result, it is significant to summarize advanced polishing methods to achieving atomic-level surfaces of KDP. This review presents the fluid jet polishing, deliquescent polishing and chemical mechanical polishing (CMP) for KDP. It indicates that CMP with rare earth could obtain atomic-level surfaces and the lowest subsurface damages. Finally, future polishing directions on KDP are proposed and discussed. © 2024 Elsevier Ltd

关键词： Atomic surface Atomic-level polishing Chemical mechanical polishing KDP

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