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An Early Two-Stage Fault Detection and Location Strategy Based on Collaboration Principal Component Analysis Method for Thermoelectric Generator System Monitoring

SSRN

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SSRN 2024年

作者： Meng, Jing-Hui Liu, Yan Zhang, Kai Bi, Jing-Liang Lu, Gui Beijing Key Laboratory of Emission Surveillance and Control for Thermal Power Generation North China Electric Power University Beijing102206 China School of Energy Power and Mechanical Engineering North China Electric Power University Beijing102206 China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China CNNC Key Laboratory on Nuclear Reactor Thermal Hydraulics Technology Nuclear Power Institute of China Chengdu610213 China

Most existing research primarily focuses on enhancing the performance of thermoelectric generators (TEGs), while the significance of process monitoring, an equally vital aspect of device performance, has been neglected. This study introduces a novel two-stage monitoring approach, consisting of fault detection and fault location, based on collaboration principal component analysis (CPCA) method, to monitor the TEGs system effectively. Initially, a comprehensive mathematical model for the multi-physics TEGs system is established, and its accuracy is validated using experimental data. Subsequently, in the early stage of fault detection, a CPCA method is developed for fault monitoring and diagnosis, which can completely and effectively preserve and extract more internal information compared to conventional PCA-based methods. Finally, in the fault location stage, the CPCA method accurately identifies the faulty unit’s location by calculating its fault contribution among the TE units. By simulating the TEGss system under three different operating conditions, the results demonstrate that: 1) Abnormal operations can be detected 4-20 minutes prior to the occurrence of an actual fault;2) CPCA method shows a quite competitive effect among PCA-based methods;3) Faulty thermoelectric units can be precisely located under various working conditions. Introducing this advanced two-stage monitoring method effectively ensures safe operation and prolongs the device's lifespan. © 2024, The Authors. All rights reserved.

关键词： Principal component analysis

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Longitudinal Transition Analysis and control of a Tilt-Body VTOL Aircraft

Longitudinal Transition Analysis and Control of a Tilt-Bo...

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International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Lou, Jinhao Zhao, Longfei Li, Ke Zhong, Xiancheng Shang, Yaoxing Jiao, Zongxia School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Key Laboratory of Advanced Aircraft Systems Beijing100083 China Science and Technology on Aircraft Control Laboratory Beijing100083 China Ningbo Institute of Technology Beihang University Ningbo315800 China Tianmushan Laboratory Hangzhou310023 China State Grid Qinghai Electric Power Co. Ltd. Qinghai Xining810001 China

ISBN: (纸本)9789819622351

Vertical takeoff and landing (VTOL) aircrafts are characterized by large flight envelopes and significant variations in flight operational conditions, making the analysis of flight envelopes and the design of controllers inherent challenges. This study focused on a tilt-body VTOL aircraft, analyzing its longitudinal flight envelope, namely transition corridors. It demonstrated that the tilt-body have a broad flight envelope and designed a longitudinal flight controller based on transition corridor trimming and total energy control theory. The theoretical approach was validated through simulation, achieving full-speed range level flight control and effective longitudinal flight control for the tilt-body. Simulation results show that this method can compensate for nonlinearities in the model and exhibits robustness, allowing the tilt-body aircraft to demonstrate excellent flight performance during transition flight. This research provides valuable insights and guidance for the analysis and control of a class of VTOL aircraft, particularly significant for the design of new VTOL configurations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： VTOL/STOL aircraft

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Exploring the Economic Feasibility of Advanced Air Mobility in the Early Stages

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 4826-4830页

作者： Jingqiu Guo Long Chen Lingxi Li Xiaoxiang Na Ljubo Vlacic Fei-Yue Wang Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University–Purdue University Indianapolis (IUPUI) Indianapolis IN USA Department of Engineering University of Cambridge Cambridge U.K. Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith University Nathan QLD Australia State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.

关键词： Active appearance model Costs Economics Transportation Helicopters Aircraft propulsion Public transportation

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Oxidation of emerging organic contaminants by in-situ H_(2)O_(2) fenton system

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Green Energy & Environment 2024年第3期9卷 417-434页

作者： Yuqin Ni Chuxiang Zhou Mingyang Xing Yi Zhou State Environmental Protection Key Lab of Environmental Risk Assessment and Control on Chemical Processes School of Resources&Environmental EngineeringEast China University of Science and TechnologyShanghai200237China Key Laboratory for Advanced Materials and Institute of Fine Chemicals National Engineering Laboratory for Industrial Wastewater TreatmentSchool of Chemistry and Molecular EngineeringEast China University of Science and Technology130 Meilong RoadShanghai200237China Department of Applied Natural Sciences Technische Hochschule LubeckMonkhofer Weg 23923562 LubeckGermany

The existence and risk of emerging organic contaminants(EOCs)have been under consideration and paid much effort to degrade these *** system is one of the most widely used technologies to solve this *** original Fenton system relies on the hydroxyl radicals produced by Fe(Ⅱ)/H_(2)O_(2) to oxidize the organic ***,the application of the Fenton system is limited by its low iron cycling efficiency and the high risks of hydrogen peroxide transportation and *** introduction of external energy(including light and electricity etc.)can effectively promote the Fe(Ⅲ)/Fe(Ⅱ)cycle and the reduction of oxygen to produce hydrogen peroxide in *** review introduces three in-situ Fenton systems,which are electro-Fenton,Photo-Fenton,and chemical *** mechanism,influencing factors,and catalysts of these three in-situ Fenton systems in degrading EOCs are discussed *** review strengthens the understanding of Fenton and in-situ Fenton systems in degradation,offering further insight into the real application of the in-situ Fenton system in the removal of EOCs.

关键词： In-situ H_(2)O_(2)production Fenton Emerging organic contaminants Photocatalysis Electrocatalysis

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Phase-Amplitude Reduction and Optimal Phase Locking of Collectively Oscillating Networks

arXiv

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arXiv 2023年

作者： Mircheski, Petar Zhu, Jinjie Nakao, Hiroya Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China

We present a phase-amplitude reduction framework for analyzing collective oscillations in networked dynamical systems. The framework, which builds on the phase reduction method, takes into account not only the collective dynamics on the limit cycle but also deviations from it by introducing amplitude variables and using them with the phase variable. The framework allows us to study how networks react to applied inputs or coupling, including their synchronization and phase-locking, while capturing the deviations of the network states from the unperturbed dynamics. Numerical simulations are used to demonstrate the effectiveness of the framework for networks composed of FitzHugh-Nagumo elements. The resulting phase-amplitude equation can be used in deriving optimal periodic waveforms or introducing feedback control for achieving fast phase locking while stabilizing the collective oscillations. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamical systems

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Deterministic Message Flow Scheduling in industrial Internet: Message Middleware Use Case

Deterministic Message Flow Scheduling in Industrial Internet...

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International Conference on Communication technology (ICCT)

作者： Xin Wang Chonghan Zhou Jing Jiang Key Laboratory of Information and Communication Systems Ministry of Information Industry and Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University (BISTU) Beijing China State Grid Economic and Technological Research Institute co. LTD Beijing China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

This article mainly focuses on message flow scheduling for industrial message middleware in the integration of deterministic network with industrial internet, which is to find the optimal matching between telecom operator and message requests from industrial users. However, current deterministic network is limited to two or three layers, and the whole transmission reliability and latency involving industrial networking and service layers cannot be guaranteed, resulting in uncontrollable message scheduling reliability, deterministic latency, low channel resource utilization etc. To this end, an integer linear programming (ILP) model is formulated for message flow scheduling issue, with multi-objectives optimization of resource utilization and profit under customized message sending latencies, and deterministic reliability. A heuristic algorithm is also proposed. Furthermore, we present a Deep Reinforcement Learning based Message Flow Scheduling algorithm (DRL-MFS), which not only solves complex message flow scheduling problems, but also achieves the self-optimization automatically. Proposed message flow scheduling approaches are simulated based on data from real cloud messaging service platforms. Simulations results prove that proposed DRL-MFS is superior to heuristic, and is close to ILP model in multi-objective optimization under three urgency levels of message sending. The reliability of three methods is proven to be deterministic.

关键词： Job shop scheduling Scheduling algorithms Simulation Heuristic algorithms Deep reinforcement learning Telecommunications Telecommunication network reliability Resource management Middleware Optimization

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引用

Chinese Automation Congress (CAC)

作者： Yumin Lang Jiande Wu Xun Lang Wanke Yu Chuanyan Yang Hongye Su Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Oscillation is a significant indication of the deterioration of control system performance and needs to be carefully monitored to ensure safe and stable process operations. However, industrial processes are often prone to noisy artifacts and nonstationary trends, resulting in low signal-to-noise ratios. In order to tackle this problem, this study introduces a novel framework for enhanced trend removal and noise reduction, which is featured by the following steps:(i) The circulant singular spectrum analysis (CiSSA) is used to decompose oscillation data into several reconstructed components (RCs). (ii) The estimated power spectral density (PSD) of these RCs is then smoothed using the Savitzky-Golay filter (SGF) to eliminate noise and identify the RCs corresponding to oscillatory components. (iii) These identified RCs are subsequently reconstructed to produce purified oscillatory data. The effectiveness of the suggested approach is validated using simulations and real-world industrial case studies. The findings indicate that the method notably enhances the quality of oscillatory data.

关键词： Power filters Noise reduction Process control Market research Information filters Noise measurement Oscillators Spectral analysis Monitoring Signal to noise ratio

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Quantification of Valve Stiction in control Loops Using Adaptive Differential Evolution Algorithm

Quantification of Valve Stiction in Control Loops Using Adap...

引用

Chinese Automation Congress (CAC)

作者： Dong Yang Xun Lang Jiande Wu Wanke Yu Songhua Liu Lei Xie Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurately and promptly quantifying stiction is crucial for valve maintenance in industrial settings and ensuring the stability of control loop performance. However, current Hammerstein-based stiction quantification methods overlook valve dynamics, potentially leading to inaccurate quantification. Therefore, this paper proposes a novel stiction quantification method based on an adaptive differential evolution algorithm. In addition to considering the impact of valve dynamics on stiction, the proposed method demonstrates a certain level of robustness against the interference of unknown noise. Finally, the effectiveness of the proposed method is demonstrated through a series of simulations and industrial case studies.

关键词： Adaptation models Heuristic algorithms Noise Interference Valves Stability analysis Robustness Data models Maintenance Classification algorithms

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Differentially Private Distributed Nonconvex Stochastic Optimization with Quantized Communication

arXiv

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arXiv 2024年

作者： Chen, Jialong Wang, Jimin Zhang, Ji-Feng Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China School of Automation and Electrical Engineering Zhongyuan University of Technology Zheng Zhou450007 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

This paper proposes a new distributed nonconvex stochastic optimization algorithm that can achieve privacy protection, communication efficiency and convergence simultaneously. Specifically, each node adds general privacy noises to its local state to avoid information leakage, and then quantizes its noise-perturbed state before transmitting to improve communication efficiency. By using a subsampling method controlled through the sample-size parameter, the proposed algorithm reduces cumulative differential privacy parameters ϵ, δ, and thus enhances the differential privacy level, which is significantly different from the existing works. By using a two-time-scale step-sizes method, the mean square convergence for nonconvex cost functions is given. Furthermore, when the global cost function satisfies the Polyak-Lojasiewicz condition, the convergence rate and the oracle complexity of the proposed algorithm are given. In addition, the proposed algorithm achieves both the mean square convergence and finite cumulative differential privacy parameters ϵ, δ over infinite iterations as the sample-size goes to infinity. A numerical example of the distributed training on the "MNIST" dataset is given to show the effectiveness of the algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

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Forget less,count better:a domain-incremental self-distillation learning benchmark for lifelong crowd counting

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Frontiers of Information technology & Electronic Engineering 2023年第2期24卷 187-202页

作者： Jiaqi GAO Jingqi LI Hongming SHAN Yanyun QU James ZWANG Fei-Yue WANG Junping ZHANG Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China Institute of Science and Technology for Brain-inspired Intelligence Fudan UniversityShanghai 200433China Shanghai Center for Brain Science and Brain-inspired Technology Shanghai 201210China School of Information Science and Technology Xiamen UniversityXiamen 361005China College of Information Sciences and Technology the Pennsylvania State UniversityUniversity ParkPA 16802USA State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Crowd counting has important applications in public safety and pandemic control.A robust and practical crowd counting system has to be capable of continuously learning with the newly incoming domain data in real-world scenarios instead of fitting one domain ***-the-shelf methods have some drawbacks when handling multiple domains:(1)the models will achieve limited performance(even drop dramatically)among old domains after training images from new domains due to the discrepancies in intrinsic data distributions from various domains,which is called catastrophic forgetting;(2)the well-trained model in a specific domain achieves imperfect performance among other unseen domains because of domain shift;(3)it leads to linearly increasing storage overhead,either mixing all the data for training or simply training dozens of separate models for different domains when new ones are *** overcome these issues,we investigate a new crowd counting task in incremental domain training setting called lifelong crowd *** goal is to alleviate catastrophic forgetting and improve the generalization ability using a single model updated by the incremental ***,we propose a self-distillation learning framework as a benchmark(forget less,count better,or FLCB)for lifelong crowd counting,which helps the model leverage previous meaningful knowledge in a sustainable manner for better crowd counting to mitigate the forgetting when new data arrive.A new quantitative metric,normalized Backward Transfer(nBwT),is developed to evaluate the forgetting degree of the model in the lifelong learning *** experimental results demonstrate the superiority of our proposed benchmark in achieving a low catastrophic forgetting degree and strong generalization ability.

关键词： Crowd counting Knowledge distillation Lifelong learning

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