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A multi-perspective functionality loss assessment of coupled railway and airline systems under extreme events

RELIABILITY ENGINEERING & SYSTEM SAFETY 2024年 243卷

作者： Zhang, Hui Xu, Min Ouyang, Min Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China Hong Kong Polytech Univ Dept Civil & Environm Engn Hong Kong Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Wuhan Peoples R China

The coupled national-scale railway and airline systems (CRASs) have drastically improved inter-city connectivity and national economics, but they remain susceptible to various extreme events. These events, including flooding and typhoon, often manifest as localized events because all direct interrupted components lie in a small region relative to the large-scale distribution of CRASs. Instead of the hazard-specific modeling of each localized event, this paper introduces four types of localized disruption models to simulate localized events with various locations, impact coverages, and time spans. A multi-perspective framework is then proposed for travel time-based functionality loss assessment of CRASs under localized events. Taking CRASs in China as an application, results demonstrate that (1) the functionality loss is highly sensitive to the event location, and events in areas with more population, higher GDP, and larger transport systems tend to cause higher functionality loss;(2) the impact coverage of events has a limited influence on functionality loss, as critical areas identified under circle-shaped impact coverage keep consistent with those under administrative district-based coverage;(3) the functionality loss and critical areas vary largely with the time span of localized events. The findings provide valuable insights in devising mitigation strategies for CRASs against various extreme events.

关键词： Coupled railway and airline systems Localized events Functionality loss assessment Multi-perspective

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An impulsive and switched system based maintenance plan optimization in building energy retrofitting project

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APPLIED MATHEMATICAL MODELLING 2023年第1期117卷 479-493页

作者： Wang, Bo Xia, Xiaohua Cheng, Zhongtao Liu, Lei Fan, Huijin Huazhong Univ Sci & Technol Key Lab Minist Educ Image Proc & Intelligent Control Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Univ Pretoria Dept Elect Elect & Comp Engn ZA-0028 Pretoria South Africa

The maintenance time schedule optimization into the investment budget decision for building energy retrofitting and maintenance planning is incorporated. The aggregate performance and population dynamics of the totality of retrofitted items is described by an impulsive switched system model. The items are switched to different working states by maintenance actions with impulsive effects. Considering the retrofitting project with deterioration. The objective of optimal maintenance control is to maximize the overall energy savings and financial payback. The optimal maintenance control problem is showed to be feasible and bounded. The maintenance time schedule and intensities are simultaneously optimized by an improved differential evolution (DE) algorithm. Compared with the fixed maintenance time schedule, the proposed approach is validated by simulation results, specifically, 3.36% of energy saving and 23.09% of internal rate of return (IRR) can be improved.

关键词： Building energy retrofitting Maintenance plan optimization Time schedule optimization Impulsive and switched system modelling Improved differential evolution

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Conditional Sliding Mode control-Based Fixed-Time Stabilization of Fuzzy Uncertain Complex System

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第3期32卷 921-933页

作者： Ren, Fangmin Wang, Xiaoping Li, Yangmin Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Key Lab Brain Inspired Intelligent Syst Wuhan 430074 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Kowloon Hong Kong Peoples R China

This work explores the fixed-time stabilization of fuzzy uncertain systems based on conditional integral sliding mode control. The difficulties in solving such problems include the integral windup problem and the severe chattering problem when the system converges. Moreover, the design of the traditional fixed-time controller algorithm in the integral sliding mode control becomes complicated. In order to overcome these difficulties: 1) a piecewise function which can bring distant states closer to the sliding surface is considered in the integral function to prevent the integral windup problem, 2) a class of state variable controllers with odd power is designed to solve the chattering problem due to there is no sign function, 3) a fixed-time control algorithm is introduced into the integral function and the controller to guarantee that both the reachability and sliding motion phases are fixed-time stable. Furthermore, based on 1) and 3), an appropriate fixed-time conditional integral sliding mode controller is constructed to ensure the fixed-time reachability of the designed sliding mode surface. Besides, combining 1), 2) and 3), a class of chattering-free fixed-time integral sliding-mode controllers is established to obtain the fixed-time reachability of the sliding mode surface and the fixed-time stability of sliding mode dynamics. This method dramatically reduces the chattering problem and can adjust integral windup. Finally, two numerical simulations are presented to verify the theoretical results, showing the robustness of the designed overshoot factor and the chattering-free scheme for sliding mode control.

关键词： Sliding mode control Uncertain systems Windup Robustness Uncertainty Heuristic algorithms Stability criteria Chatter-free conditional integral sliding mode control fixed-time stable T-S fuzzy uncertain system

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Remaining Useful Life Prediction for a Multi-stack Solid Oxide Fuel Cell System with Degradation Interactions

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1207-1214页

作者： Xiaojuan Wu Liangfei Xu Yang Huang Danan Yang Junhao Wang Houjun Wang Xi Li School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 610054China State Key Lab of Automotive Safety and Energy School of Vehicle and MobilityTsinghua UniversityBeijing 100084China School of Artificial Intelligencei and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and TechnologyWuhan 430074China

Due to the constraints of manufacturing and materials,high-power plants cannot rely on only one solid oxide fuel cell stack.A multi-stack system is a solution for a highpower system,which consists of multiple fuel cell stacks.A short lifetime is one of the main challenges for the fuel cell before largescale commercial applications,and prognostic is an important method to improve the reliability of fuel *** from the traditional prognostic approaches applied to single-stack fuel cell systems,the key problem in multi-stack prediction is how to solve the correlation of multi-stack degradation,which can directly affect the accuracy of *** response to this difficulty,a standard Brownian motion is added to the traditional Wiener process to model the degradation of each stack,and then the probability density function of the remaining useful life(RUL)of each stack is ***,a Copula function is adopted to reflect the dependence between life distributions,so as to obtain the remaining useful life for the whole multi-stack system.1 The simulation results show that compared with the traditional prediction model,the proposed approach has a higher prediction accuracy for multi-stack fuel cell systems.

关键词： Degradation interaction multi-stack remaining useful life(RUL) solid oxide fuel cell(SOFC)

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Extraction method of dispensing track for components based on transfer learning and Mask-RCNN

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MULTIMEDIA TOOLS AND APPLICATIONS 2023年第1期83卷 2959-2978页

作者： Peng, Gang Xiong, Chao Zhou, Yicheng Yang, Jin Li, Xinde Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China Minist Educ Key Lab Image Proc & Intelligent Control Wuhan Peoples R China South East Univ Sch Automat Nanjing Peoples R China

In the process of dispensing, the traditional dispensing robot generally obtains the component pad profile according to the Mark point assisted positioning, and directly uses the profile as the dispensing profile. However, due to the influence of welding and other factors, the posture of the components often changes after welding, which easily causes the actual dispensing contour to be difficult to completely match the pad, so there is a certain deviation in the dispensing. Moreover, component recognition based on convolutional neural network requires a large number of samples for training, which is not conducive to the expansion of dispensing components. This paper focuses on the high-precision dispensing task. Based on the indirect positioning components, this paper uses Mask RCNN to extract complex component dispensing track in different environments. Compared with traditional methods, this method has higher robustness and dispensing accuracy. At the same time, the transfer learning method is used to train the neural network, so that the algorithm has better scalability and flexibility when facing the detection and segmentation tasks of new components. The experimental results show that the component dispensing track extraction method proposed in this paper has higher precision and flexibility than the traditional method.

关键词： Component dispensing Mark point Mask-RCNN Track extraction Transfer learning

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Improved Kalman Filtering Algorithm Based Multi-Sensor Integration for Silicon Single Crystal Growth Process 7

Improved Kalman Filtering Algorithm Based Multi-Sensor Integ...

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7th International Symposium on Autonomous Systems, ISAS 2024

作者： Xie, Ruidong Zhu, Pei Ma, Wenle Zhang, Zheqi Yi, Yingmin Guo, Zheng Xi'an University of Technology Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an710048 China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China

ISBN: (纸本)9798350363173

The study primarily delves into addressing the data filtering challenge inherent in the silicon single crystal growth process by proposing a multi-sensor integrated detection approach. This approach is designed to alleviate the diminished filtering accuracy resulting from the reliance on a single sensor and the conventional Kalman filtering algorithm. By utilizing an enhanced adaptive Kalman filtering algorithm and the maximum likelihood estimation criterion to incorporate the innovation variance directly into the gain calculation of the Kalman filter, dynamic adjustment of the estimation model is achieved while interference from system noise and measurement noise is reduced. Finally, simulation-based comparative experiments between the adaptive and conventional Kalman filtering algorithms are performed. The results show that the performance of the adaptive Kalman filtering algorithm is superior to that of the conventional Kalman filtering algorithm in terms of accuracy and stability when detecting signals from multiple sensors. The research findings furnish dependable data support for refining the decision-making process in crystal growth technology, augmenting the precision and scientific integrity of crystal safety production scheduling and decision-making endeavors. © 2024 IEEE.

关键词： Kalman filters

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Improved Fixed-Time Stabilization of Fuzzy Neural Networks With Distributed Delay via Adaptive Sliding Mode control

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2023年第6期31卷 2029-2043页

作者： Ren, Fangmin Wang, Xiaoping Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Educ Minist China Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan Peoples R China

This article investigates fixed-time stabilization of fuzzy neural networks with distributed delay by designing an adaptive sliding mode controller. First, according to stability theory and related inequalities, a new fixed-time stability theorem is put forward, and the settling time is given. In order to stabilize the system, a new integral sliding mode surface is designed, and the corresponding sliding mode control strategy and adaptive sliding mode control strategy are established. Some criteria that can be obtained, and it is shown that the neuronal states of neural networks will arrive at the sliding surface in a fixed time, and then approach zero along the sliding surface. Compared with existing sliding mode control techniques, this work extends the previous related results by choosing different parameters of the controller and the sliding mode manifold to gain various protocols. Finally, two examples are provided to verify the validity of the theorems in this work.

关键词： Stability criteria Sliding mode control Fuzzy neural networks Fuzzy control Asymptotic stability Convergence Neural networks Adaptive control fixed-time stable fuzzy neural network sliding mode control

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Dual-active Li‖Te-Bi liquid metal batteries with enhanced coulombic efficiency and cycling stability

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CHEMICAL COMMUNICATIONS 2025年第31期61卷 5750-5753页

作者： Guo, Yewei Li, Zehang Cu, Qiao Feng, Shaoming Zhang, Weixin Wang, Kangli Li, Haomiao Jiang, Kai Huazhong Univ Sci & Technol Sch Mat Sci & Engn Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Elect & Elect Engn State Key Lab Adv Electromagnet Technol Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan Peoples R China

Tellurium (Te), a chalcogenide with higher electrical conductivity than sulfur (S) and selenium (Se), can be made into liquid metal batteries with high energy density. The Te-Bi alloy positive electrode inhibits Te dissolution and enhances lithium diffusion, which further improves the coulombic efficiency and cycling stability of lithium batteries. Due to the dual-activity mechanism, Li & Vert;Te5Bi5 achieves similar to 100% capacity utilization. Our results highlight a viable strategy for advancing high-voltage LMBs, providing an option for achieving long-life stationary energy storage solutions.

关键词： Bismuth alloys

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Source-Free Domain Adaptation (SFDA) for Privacy-Preserving Seizure Subtype Classification

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IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 2023年 31卷 2315-2325页

作者： Zhao, Changming Peng, Ruimin Wu, Dongrui Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Res Inst Shenzhen Shenzhen 518000 Peoples R China

Electroencephalogram (EEG) based seizure subtype classification is very important in clinical diagnostics. Source-free domain adaptation (SFDA) uses a pre-trained source model, instead of the source data, for privacy-preserving transfer learning. SFDA is useful in seizure subtype classification, which can protect the privacy of the source patients, while reducing the amount of labeled calibration data for a new patient. This paper introduces semi-supervised transfer boosting (SS-TrBoosting), a boosting-based SFDA approach for seizure subtype classification. We further extend it to unsupervised transfer boosting (U-TrBoosting) for unsupervised SFDA, i.e., the new patient does not need any labeled EEG data. Experiments on three public seizure datasets demonstrated that SS-TrBoosting and U-TrBoosting outperformed multiple classical and state-of-the-art machine learning approaches in cross-dataset/cross-patient seizure subtype classification.

关键词： Boosting ensemble learning EEG seizure subtype classification source-free domain adaptation transfer learning

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Unsupervised domain adaptation for cross-patient seizure classification

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JOURNAL OF NEURAL ENGINEERING 2023年第6期20卷 066002-066002页

作者： Wang, Ziwei Zhang, Wen Li, Siyang Chen, Xinru Wu, Dongrui Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Minist Educ Image Proc & Intelligent Contr Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Belt & Rd Joint Lab Measurement & Control Technol Wuhan 430074 Peoples R China

Objective. Epileptic seizure is a chronic neurological disease affecting millions of patients. Electroencephalogram (EEG) is the gold standard in epileptic seizure classification. However, its low signal-to-noise ratio, strong non-stationarity, and large individual difference nature make it difficult to directly extend the seizure classification model from one patient to another. This paper considers multi-source unsupervised domain adaptation for cross-patient EEG-based seizure classification, i.e. there are multiple source patients with labeled EEG data, which are used to label the EEG trials of a new patient. Approach. We propose an source domain selection (SDS)-global domain adaptation (GDA)-target agent subdomain adaptation (TASA) approach, which includes SDS to filter out dissimilar source domains, GDA to align the overall distributions of the selected source domains and the target domain, and TASA to identify the most similar source domain to the target domain so that its labels can be utilized. Main results. Experiments on two public seizure datasets demonstrated that SDS-GDA-TASA outperformed 13 existing approaches in unsupervised cross-patient seizure classification. Significance. Our approach could save clinicians plenty of time in labeling EEG data for epilepsy patients, greatly increasing the efficiency of seizure diagnostics.

关键词： EEG seizure classification transfer learning domain adaptation source domain selection

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