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Stochastic process-based degradation modeling and RUL prediction: from Brownian motion to fractional Brownian motion

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science China(Information sciences) 2021年第7期64卷 5-24页

作者： Hanwen ZHANG Maoyin CHEN Jun SHANG Chunjie YANG Youxian SUN School of Automation and Electrical Engineering University of Science and Technology Beijing State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University Department of Automation Tsinghua University School of Automation and Electrical Engineering Linyi University Department of Electrical and Computer Engineering University of Alberta

Brownian motion(BM) has been widely used for degradation modeling and remaining useful life(RUL) prediction, but it is essentially Markovian. This implies that the future state in a BM-based degradation process relies only on its current state, independent of the past states. However, some practical industrial devices such as Li-ion batteries, ball bearings, turbofans, and blast furnace walls show degradations with long-range dependence(LRD), where the future degradation states depend on both the current and past degradation states. This type of degradation naturally brings two interesting problems, that is, how to model the degradations and how to predict their RULs. Recently, in contrast to the work that uses only BM, fractional Brownian motion(FBM) is introduced to model practical degradations. The most important feature of the FBM-based degradation models is the ability to characterize the non-Markovian degradations with LRD. Although FBM is an extension of BM, it is neither a Markovian process nor a semimartingale. Therefore, how to obtain the first passage time of an FBM-based degradation process has become a challenging task. In this paper, a review of the transition of RUL prediction from BM to FBM is provided. The peculiarities of FBM when addressing the LRD inherent in some practical degradations are discussed. We first review the BM-based degradation models of the past few decades and then give details regarding the evolution of FBM-based research. Interestingly, the existing BM-based models scarcely consider the effect of LRD on the prediction of RULs. Two practical cases illustrate that the newly developed FBMbased models are more generalized and suitable for predicting RULs than the BM-based models, especially for degradations with LRD. Along with the direction of FBM-based RUL prediction, we also introduce some important and interesting problems that require further study.

关键词： remaining useful life degradation model Brownian motion fractional Brownian motion long-range dependence

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Grid-Metaverse: The Path From Digital Twins and Prototype Tests on DC Microgrids

Grid-Metaverse: The Path From Digital Twins and Prototype Te...

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2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Ma, Wenxuan Liu, Mengxiang Hong, Guangrun Yang, Shuo Deng, Ruilong Zhejiang University State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Hangzhou310027 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom

ISBN: (纸本)9798350333336

With the development of cutting-edge technologies and the efforts of business giants, Metaverse is becoming increasingly reachable. In addition to the fields of healthcare, education and cultural tourism, Metaverse will also have a profound impact on the power grid. The digital twin (DT) is regarded as the foundation of Metaverse, but its high cost hinders the broad application of DTs in power grids. In this paper, we propose a path to build the DTs in the direct current (DC) microgrid, which is a representative block in the future power grid with the penetration of renewable energy sources, forming Grid-Metaverse that can significantly reduce the cost and improve the interactivity. A model-based DT, which is originated from the physical model, and a data-driven DT, using the graph neural network with the data from the model-based one, are built together to illustrate this path and to show their roles in the Grid-Metaverse. Moreover, in the prototype tests, the threats of denial-of-service (DoS) and false data injection (FDI) attacks are validated through the developed DTs. © 2023 IEEE.

关键词： Renewable energy resources

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Distributed data-driven consensus control of multi-agent systems under switched uncertainties

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control Theory and technology 2023年第3期21卷 478-487页

作者： Wenjie Liu Yifei Li Gang Wang Jian Sun Jie Chen National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

Cooperative control of multi-agent systems(MASs),particularly consensus control,has gained significant attention in the last two decades,thanks to the rapid and sustained development of distributed and networked *** this paper,we present some new results focused on consensus control of a set of unknown linear MASs(whose system matrices are unknown)under unknown switched uncertainties,with an emphasis on distributed data-driven *** proposed controller is end-to-end,designed by solving two data-based semi-definite programs(SDPs),which adjust to the changes of the uncertainty *** approach achieves asymptotic consensus of the MAS provided that the switching is slow enough and the uncertainty is *** illustrate the effectiveness of our proposed method through a numerical example.

关键词： Data-driven control Multi-agent systems Consensus-Switched uncertainties

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Accurate and straightforward symplectic approach for fracture analysis of fractional viscoelastic media

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Applied Mathematics and Mechanics(English Edition) 2022年第3期43卷 403-416页

作者： Chenghui XU Sen LENG Zhenhuan ZHOU Xinsheng XU Zichen DENG MIIT Key Laboratory of Dynamics and Control of Complex Systems Department of Engineering MechanicsNorthwestern Polytechnical UniversityXi'an 710072China State Key Laboratory of Structure Analysis of Industrial Equipment Department of Engineering MechanicsDalian University of TechnologyDalian 116024Liaoning ProvinceChina

An accurate and straightforward symplectic method is presented for the fracture analysis of fractional two-dimensional(2D)viscoelastic *** fractional Kelvin-Zener constitutive model is used to describe the time-dependent behavior of viscoelastic *** the framework of symplectic elasticity,the governing equations in the Hamiltonian form for the frequency domain(s-domain)can be directly and rigorously *** the s-domain,the analytical solutions of the displacement and stress fields are constructed by superposing the symplectic eigensolutions without any trial function,and the explicit expressions of the intensity factors and J-integral are derived *** studies are provided to validate the accuracy and effectiveness of the present solutions.A detailed analysis is made to reveal the effects of viscoelastic parameters and applied loads on the intensity factors and J-integral.

关键词： symplectic approach viscoelastic material fractional Kelvin-Zener model crack fracture parameter

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Progress and challenge of functional single-atom catalysts for the catalytic oxidation of volatile organic compounds

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Chinese Chemical Letters 2024年第9期35卷 83-91页

作者： Zeyu Jiang Yadi Wang Changwei Chen Chi He Department of Environmental Science and Engineering Xi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of Multiphase Flow in Power Engineering School of Energy and Power EngineeringXi’an Jiaotong UniversityXi’an 710049China National Engineering Laboratory for VOCs Pollution Control Material&Technology University of Chinese Academy of SciencesBeijing 101408China

The catalytic oxidation of volatile organic compounds(VOCs)is of considerable significance for the sustainable development of the chemical industry;thus,considerable efforts have been devoted to the exploration of efficient catalysts for use in this *** this regard,the development and utilization of single-atom catalysts(SACs)in VOCs decomposition is a rapidly expanding research *** can be employed as potential catalysts for oxidizing VOC molecules due to their optimal utilization efficiency,unique atomic bonding structures,and unsaturated *** has been achieved,while the challenges surrounding precise regulation of the microstructures of SACs for improving their low-temperature efficiency,stability,and product selectivity under practical conditions are ***,elucidating structure-performance relationships and establishing intrinsic modulating mechanisms are urgently required for guiding researchers on how to synthesize effective and stable functional SACs ***,recent advances in the design and synthesis of functional SACs for application in the catalytic oxidation of VOCs are *** experimental and theoretical studies revealing higher efficiency,stability,and selectivity of as-prepared functional SACs are being ***,the future perspectives in terms of promising catalysts with multi-sized composite active sites and the illustration of intrinsic mechanism are *** rapid intelligent screening of applicable SACs and their industrial applications are also discussed.

关键词： Single-atom catalysts VOCs catalytic oxidation Hydrocarbon activation Oxygen species transformation Surface chemistry Intrinsic mechanism

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Proximity Estimation with Position Adjustment for Autonomous industrial Inspection

Proximity Estimation with Position Adjustment for Autonomous...

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2024 International Conference on Artificial Intelligence of Things and Systems, AIoTSys 2024

作者： Zhou, Ziyi Huang, Ping Zheng, Song Xu, Zhezhuang Zhuang, Zixiong College of Electrical Engineering and Automation Fuzhou Univ. and Key Lab. of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9798331507886

Due to the similarity in appearance and dense deployment of devices in industrial environments, relying solely on machine vision makes it challenging for inspection robots to accurately identify similar devices. Although wireless signals from industrial internet of things (IoT) can serve as identification features, signal fluctuations impact the accuracy and efficiency of recognition. To address this issue, this paper proposes a proximity estimation algorithm with position adjustment for autonomous industrial inspection. The algorithm considers the spatial relationships between nodes and the topological relationship between the signal strength and variations among the nodes. By analyzing the topological relationship between the signal strength and variations among the nodes, the robot autonomously adjusts its position and selects the proximal node based on the spatial topology relationship between them. We have built an inspection platform using quadruped robots to evaluate the effectiveness of the experiments. The experimental results demonstrate that the algorithm further improves the efficiency of identifying proximal devices while ensuring the estimation accuracy of the algorithm. © 2024 IEEE.

关键词： Topology

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Improved material descriptors for bulk modulus in intermetallic compounds via machine learning

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Rare Metals 2023年第7期42卷 2396-2405页

作者： De-Xin Zhu Kun-Ming Pan Yuan Wu Xiao-Ye Zhou Xiang-Yue Li Yong-Peng Ren Sai-Ru Shi Hua Yu Shi-Zhong Wei Hong-Hui Wu Xu-Sheng Yang National Joint Engineering Research Center for Abrasion Control and Molding of Metal Materials Henan Key Laboratory of High-Temperature Structural and Functional MaterialsHenan University of Science and TechnologyLuoyang471003China Longmen Laboratory Luoyang471003China State Key Laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing100083China Guangdong Province Key Laboratory of Durability for Marine Civil Engineering School of Civil EngineeringShenzhen UniversityShenzhen518060China Department of Industrial and Systems Engineering The Hong Kong Polytechnic UniversityHong Kong999077China

Bulk modulus is an important mechanical property in the optimal design and selection of intermetallic *** this study,bulk modulus datasets of intermetallic compounds were collected,and the features affecting the bulk modulus of intermetallics were screened via feature *** features B_(cal),dB_(avg),and TIE(corresponding to calculated bulk modulus,mean bulk modulus,and third ionization energy,respectively)were found to be the dominant factors influencing bulk modulus and can be extended to other multi-component ***,we predicted the bulk modulus with an accuracy of 95%using surrogate machine learning models with the selected features,and these features were also demonstrated to be effective for high-entropy ***,symbolic regression provided an expression for the relationship between bulk modulus and the screened *** machine learning models provide a new approach for optimizing and predicting the bulk moduli of intermetallic compounds.

关键词： Bulk modulus Intermetallic compounds Machine learning Symbolic regression

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Effect of trigger system on experimental dispersion characteristics of active surface wave testing

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Earthquake engineering and engineering Vibration 2024年第2期23卷 311-318页

作者： Lin Shibin Jeramy C.Ashlock Zhu Liming Qin Zexiang Li Bo Zhu Xingji Zhai Changhai State Key Laboratory of Precision Blasting Jianghan UniversityWuhan 430056China Hubei Key Laboratory of Blasting Engineering Jianghan UniversityWuhan 430056China Department of Civil Construction&Environmental EngineeringIowa State UniversityAmesIA 50010USA Wuhan Airport Road Development Co. Ltd.Wuhan 430065China School of Civil and Environmental Engineering Harbin Institute of TechnologyShenzhen 518055China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of TechnologyHarbin 150090China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disaster of the Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbin 150090China

A trigger system is typically employed in active seismic testing to trigger and synchronize multichannel surface wave data *** effect of the trigger system on the dispersion image of surface waves is empirically known to be negligible,however,theoretical explanation regarding the effect of the trigger system is *** study systematically examines the theory for surface wave dispersion analysis and proves that the effect of the trigger system on a dispersion image is negligible via a solid theoretical ***,based on the new theoretical explanation,an alternative method that uses only the relative phase difference between sensors to extract dispersion characteristics with better conceptual clarity is *** active surface wave testing cases are considered to validate the theory and *** results indicate that(1)an accurate trigger system is not necessary for surface wave data acquisition,and(2)it is unnecessary to assume that the impact point is the generation point of the surface waves for the experimental dispersion analysis.

关键词： site investigation surface waves data acquisition dispersion

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A Hybrid Deep Neural Network for Nonlinear Causality Analysis in Complex industrial control System 48

A Hybrid Deep Neural Network for Nonlinear Causality Analysi...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Feng, Tian Chen, Qiming Shi, Yao Lang, Xun Xie, Lei Su, Hongye Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China Yunnan University Information School Department of Electronic Engineering Kunmin China

ISBN: (纸本)9781728163277

It is important to efficiently and accurately locate the fault root cause to maintain the control performance, when the industrial control system fails. However, this task is very challenging because the industrial control system is large in scale and complex in connection. This paper proposes a novel neural causality analysis network with directed acyclic graph to locate the root cause for complex industrial systems. This network fits the temporal nonlinearity and intervariable non-linearity to mine the causal graph. The proposed method is data-driven, which acts without process knowledge. Compared with the state-of-the-art, this method can effectively output accurate root cause from nonlinear and highly coupled data. The effectiveness and advantages are demonstrated by industrial cases. © 2023 IEEE.

关键词： industrial control system neural network root cause analysis

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Interval Weight state Update Approach with Deep Reinforcement Learning for Dynamic Load Change Tasks in Air Separation Processes

Interval Weight State Update Approach with Deep Reinforcemen...

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Data Driven control and Learning Systems (DDCLS)

作者： Ruiyu Qiu Guanghui Yang Zuhua Xu Zhijiang Shao State Key Lab of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou P. R. China HuZhou Research Institute of Industrial Control Technology

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

The air separation unit (ASU) is important for producing high-purity oxygen, nitrogen, and argon, and dynamic load change operation helps meet the needs of downstream industries. The ASU has an extremely long delay, and the requirements for this operation are strict, and model predictive control (MPC) is usually used for this task. However, the burden of online MPC computation is a key issue in improving production and economic efficiency. In this paper, a framework based on Reinforcement Learning (RL) is proposed to solve the long-delayed task in ASU. The state and reward function are specially designed for this task. First, training increases the sampling time of the original model to create a low resolution environment, which makes training more efficient. As a sacrifice, the control precision is reduced in the original high resolution environment. Then, an algorithm called Interval Weighted state Update (IWSU) is proposed to restore the agent and keeps the action accuracy in the original environment. The dynamic load change task works as the case in this paper. The performance of RL is compared with that of MPC, and results show that RL is almost exactly the same as MPC in key flow indicators, and can well meet the remaining content and purity range requirements. IWSU shows good performance compared with directly applying the agent to the original high resolution environment.

关键词： Training Target tracking Switches Production control systems Separation processes Nitrogen

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