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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Wang, Ying Cao, Yunpeng Li, Shuying Zhu, Linhai Yao, Kun College of Power and Energy Engineering Harbin Engineering University Harbin150001 China School of Energy Science and Engineering Harbin Institute of Technology Harbin150001 China Shenzhen518055 China

ISBN: (纸本)9783031734069

In order to solve the problems caused by the inherent complex nonlinearity and the limitation of traditional linear modeling technology in engine fault diagnosis, the Equilibrium manifold model is introduced in this paper, The equilibrium manifold model can describe the actual operating state of the engine more accurately, and capture the higher-order nonlinear characteristics that are ignored by the traditional linear ***, a dual-channel sensor fault diagnosis and isolation approach is proposed, which integrates the nonlinear engine model with the Cubature Kalman filter. Simulations conducted that, compared to traditional Kalman filter-based methods, this approach not only reduces the demands on data storage and computational resources but also achieves accurate sensor fault diagnosis. Crucially, it effectively separates engine gas path faults from sensor faults, thus eliminating the potential interference of gas path faults on sensor fault diagnosis and isolation outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Kalman filters

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A trajectory-level robot skill learning method based on fuzzy systems

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science China(Information sciences) 2025年第5期68卷 38-52页

作者： Chao ZENG Zhen DENG Boyang TI Yongsheng GAO Department of Computer Science University of Liverpool School of Mechanical Engineering and Automation Fuzhou University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics and System Harbin Institute of Technology

Learning from demonstration(LfD) allows for the effective transfer of human manipulation skills to a robot by building a model that represents these skills based on a limited number of demonstrated ***,a skilllearning model that can comprehensively satisfy multiple requirements,such as computational complexity,modeling accuracy,trajectory smoothness,and robustness,is still ***,this work aims to provide such a model by employing fuzzy ***,we introduce an LfD model named Takagi-Sugeno-Kang fuzzy system-based movement primitives(TSKFMPs),which exploits the advantages of the fuzzy theory for effective robotic imitation learning of human *** work formulates the TSK fuzzy system and gradient descent(GD) as imitation learning models,leveraging recent advancements in GD-based optimization for fuzzy *** study takes a two-step strategy.(ⅰ) The input-output relationships of the model are established using TSK fuzzy systems based on demonstration *** this way,the skill is encoded by the model parameter in the latent space.(ⅱ) GD is used to optimize the model parameter to increase the modeling accuracy and trajectory *** further explain how learned trajectories are adapted to new task scenarios through local *** conduct multiple tests using an open dataset to validate our method,and the results demonstrate performance comparable with those of other ***,we implement it in a real-world case study.

关键词： robot skill learning movement primitives TSK fuzzy systems gradient descent robotics

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A Riccati Matrix Equation Solver Design Based Neurodynamics Method and Its Application

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IEEE Transactions on Automation science and engineering 2025年 22卷 15163-15176页

作者： Xiao, Pingdan Fang, Junjie Wei, Zhengmiao Dong, Yu Du, Sichun Wen, Shiping Hong, Qinghui Hunan University College of Computer Science and Electronic Engineering Changsha418002 China University of Technology Sydney Australian AI Institute Faculty of Engineering and Information Technology UltimoNSW2007 Australia

Riccati matrix equation (RME), a critical nonlinear matrix equation in autonomous driving and deep learning. However, memory-compute separation in traditional solving systems leads to latency and inefficiency when solving nonlinear equations, particularly under real-time requirements. Existing hardware lacks dedicated accelerators for RME, no specialized solvers quick addressing its nonlinear complexity. To address this issue, we propose a novel RME solver based on a memristive array, which leverages the parallel and fast computing advantages of analog circuits to quickly solve any order RME. Inspired by Neurodynamics for non-linear matrix equations, we first introduce an innovative Neurodynamics-based RME solving algorithm specifically designed from an analog circuit perspective. Based on this algorithm, we constructed a pioneering closed-loop analog circuit solver, overcoming bottlenecks in using circuits for such nonlinear matrix equations. Our evaluation demonstrates that the proposed solver achieves over 90% accuracy for a 128th-order parameter Riccati matrix equation. Compared to traditional digital processors, the solver offers significant energy efficiency advantages and is three orders of magnitude faster than CPU. Additionally, the solver successfully accelerates our proposed dung beetle optimizer-linear quadratic control algorithm for vehicle suspension control, achieving high precision while significantly reducing time and energy consumption compared to CPU and GPU. © 2004-2012 IEEE.

关键词： Riccati equations

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A Magnetic Signal Based Device Fingerprinting Scheme in Wireless Charging

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IEEE Transactions on Dependable and Secure Computing 2025年第3期22卷 2943-2958页

作者： Li, Jiachun Meng, Yan Zhang, Le Chen, Guoxing Tian, Yuan Zhu, Haojin Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China Electrical and Computer Engineering Department Institute for Technology Los AngelesCA90095 United States

Wireless charging is widely used to charge smart devices with limited battery capacity. However, it is susceptible to the identity spoofing attack, where adversaries can impersonate malicious devices as legitimate ones to gain unauthorized access and potentially disrupt the wireless charging system (e.g., resulting in incorrect billing, overheating, or even explosions). Device fingerprinting is a classical method for defending against identity spoofing attacks. However, applying existing schemes in wireless charging scenarios has drawbacks such as inconvenience (e.g., requiring specialized devices or user participation) and ineffectiveness (e.g., vulnerability to spoofing). Thus, we design a novel passive, effective, and robust device fingerprinting scheme called MagID for wireless charging systems. The insight of MagID lies in the fact that during wireless charging, the magnetic signal around a device can reflect inherent hardware differences. These differences can be extracted as unique fingerprints for authentication purposes. MagID leverages a novel scheme, SUPER-ARRAY, to precisely measure magnetic data and generate effective fingerprints for authenticating a device's identity before starting charging progress. Experimental results demonstrate that MagID achieves an accuracy rate of 98.14% across various charging devices. We have also tested its performance under different impact factors and verified its compatibility with various wireless charging pads. © 2004-2012 IEEE.

关键词： Charging stations

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Heterologous Image Matching Based on Salience Region

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2025年第4期52卷 894-900页

作者： Zhai, Jinlong Xu, Yang Yan, Xiaohu Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen Polytechnic University Shenzhen518055 China

To address the matching problem caused by the significant differences in spatial features, spectrum and contrast between heterologous images, a heterologous image matching method based on salience region is proposed in this paper. Firstly, texture features and corner features are detected. Secondly, the epanechnikov kernel function is used to calculate the point with the maximum kernel function value among all feature points, which is then defined as E-point. Thirdly, the salience region is defined and extracted according to the position of the E-point. Finally, six groups of heterologous images are used as data sources, and compared with HAPCG, HOWP, SIFT, and PSO_SIFT algorithms respectively. The results show that the comprehensive matching performance of the proposed method is better than the original algorithm without salience region processing. The root mean square error and the matching time are less than the original method while ensuring a similar number of matching points, which greatly improves the accuracy and speed of heterologous image matching. © (2025.0), (International Association of Engineers). All Rights Reserved.

关键词： Image matching

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A New Approach to Determine Feasible Operating Region of Unbalanced Distribution Networks with Distributed Photovoltaics

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IEEE Transactions on Power Delivery 2025年第3期40卷 1493-1504页

作者： Prasad, Manorath Rather, Zakir Hussain Razzaghi, Reza Doolla, Suryanarayana Indian Institute of Technology Bombay Department of Energy Science and Engineering Mumbai India Monash University Department of Electrical and Computer Systems Engineering Melbourne Australia

Amidst rising distributed generation and its potential role in grid management, this article presents a new realistic approach to determine the operational space and flexibility potential of an unbalanced active distribution network. The feasible operating region of an active distribution network is constituted by its range of active-reactive power exchanges with the bulk power system without breaching network constraints. This study explores the potential of highly penetrated single- and three-phase distributed photovoltaics and voltage-sensitive loads to determine the feasible operating region at different operating points. The cumulative response of Volt-Var controlled distributed photovoltaics and voltage-sensitive loads determines the power flow at the bulk power system-active distribution network interconnection, ensuring feasibility with respect to voltage magnitude and unbalance constraints. Further, the correspondence of feasible operating region with the tap-settings of substation transformer enables a novel feature to traverse throughout the available operating region and facilitate bulk power system-active distribution network power coordination. Additionally, a nodal sensitivity-based adjustable Volt-Var control scheme is proposed for distributed photovoltaics, improving the feasible operating region. The proposed strategy is validated on bulk power systemactive distribution network integrated test system. Bulk power system: IEEE-9 bus system-Active distribution network: (highly unbalanced IEEE-13 bus distribution system (medium voltage) + modified CIGRE low voltage system). © 1986-2012 IEEE.

关键词： Power distribution networks

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Exploiting Multi-Level Data Uncertainty for Japanese-Chinese Neural Machine Translation

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IEICE Transactions on Information and Systems 2025年第5期E108.D卷 440-443页

作者： Li, Zezhong Ma, Jianjun Ren, Fuji Faculty of Computer Science Zhejiang University of Water Resources and Electric Power China Faculty of Foreign Languages Dalian University of Technology China College of Computer Science and Engineering The Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China China

The performance of Neural Machine Translation (NMT) heavily depends on the severity of data uncertainty existing in the training examples. In terms of its causes, data uncertainty can be categorized into intrinsic and extrinsic uncertainty, both of which can increase the learning difficulty in NMT, and lead to degradation in translation performance. To cope with this challenge, we propose a simple yet effective method to estimate the data uncertainty and incorporate it into the adaptive training of NMT, which can mitigate the hurt brought by the uncertain data. Our method consists of two modules: 1) we propose a mBERT based model for estimating token-level and sentence-level data uncertainties jointly, which is trained with multi-task learning;2) we propose heterogeneous ways of incorporating the derived multi-level uncertainties into the NMT training by using soft-masked embedding and weighted loss. Extensive experiments on Japanese↔Chinese translation show that our proposed methods substantially outperform the strong baselines in terms of BLEU scores, and verify the effectiveness of modeling data uncertainty in NMT. Copyright © 2025 The institute of Electronics, Information and Communication Engineers.

关键词： Neural machine translation

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Effects of nanosized Au on the interface of zinc phthalocyanine/TiO_(2)for CO_(2)photoreduction

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Chinese Chemical Letters 2025年第2期36卷 418-422页

作者： Linlu Bai Wensen Li Xiaoyu Chu Haochun Yin Yang Qu Ekaterina Kozlova Zhao-Di Yang Liqiang Jing Department Key Laboratory of Functional Inorganic Materials Chemistry(Heilongjiang University) Ministry of EducationSchool of Chemistry and Materials ScienceInternational Joint Research Center and Lab for Catalytic TechnologyHarbin 150080China School of Materials Science and Chemical Engineering Harbin University of Science and TechnologyHarbin 150080China Federal Research Center Boreskov Institute of Catalysis 630090 NovosibirskRussian Federation

The interface modulation significantly affects the photocatalytic performances of supported metal phthalocyanines(MPc)-based ***,ZnPc was loaded on nanosized Au-modified TiO_(2)nanosheets(Au-T)to obtain wide-spectrum ZnPc/Au-T *** with large Au NP(8 nm)-mediated ZnPc/Au-T photocatalyst,ultrasmall Au NP(3 nm)-mediated one shows advantageous photoactivity,achieving 3-and 10-fold CO_(2)conversion rates compared with reference ZnPc/T and pristine TiO_(2)nanosheets,*** monochromatic beam-assisted surface photovoltage and photocurrent action,etc.,the introduction of ultrasmall Au NPs more effectively facilitates intrinsic interfacial charge ***,ZnP c molecules are found more dispersed with the existence of small Au NPs hence exposing abundant Zn^(2+)sites as the catalytic center for CO_(2)*** work provides a feasible design strategy and renewed recognition for supported MPc-based photocatalyst systems.

关键词： Supported MPc photocatalyst Au nanoparticle Interface modulation Charge separation CO_(2)photoreduction

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DIEONet:Domain-Invariant Information Extraction and Optimization Network for Visual Place Recognition

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computers, Materials & Continua 2025年第3期82卷 5019-5033页

作者： Shaoqi Hou Zebang Qin Chenyu Wu Guangqiang Yin Xinzhong Wang Zhiguo Wang School of Computer Science and Technology Xinjiang UniversityUrumqi830046China School of Information and Software Engineering University of Electronic Science and Technology ofChinaChengdu611731China Institute of Public Security Kash Institute of Electronics and Information IndustryKashi844000China

Visual Place Recognition(VPR)technology aims to use visual information to judge the location of agents,which plays an irreplaceable role in tasks such as loop closure detection and *** is well known that previous VPR algorithms emphasize the extraction and integration of general image features,while ignoring the mining of salient features that play a key role in the discrimination of VPR *** this end,this paper proposes a Domain-invariant Information Extraction and Optimization Network(DIEONet)for *** core of the algorithm is a newly designed Domain-invariant Information Mining Module(DIMM)and a Multi-sample Joint Triplet Loss(MJT Loss).Specifically,DIMM incorporates the interdependence between different spatial regions of the feature map in the cascaded convolutional unit group,which enhances the model’s attention to the domain-invariant static object *** Loss introduces the“joint processing of multiple samples”mechanism into the original triplet loss,and adds a new distance constraint term for“positive and negative”samples,so that the model can avoid falling into local optimum during *** demonstrate the effectiveness of our algorithm by conducting extensive experiments on several authoritative *** particular,the proposed method achieves the best performance on the TokyoTM dataset with a Recall@1 metric of 92.89%.

关键词： Visual place recognition domain-invariant information mining module multi-sample joint triplet loss

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DELTa: Dynamic Energy-and-Latency-aware Task scheduling for Fog-Cloud Paradigm

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IEEE Access 2025年 13卷 74617-74633页

作者： Mahapatra, Abhijeet Pradhan, Rosy Majhi, Santosh K. Mishra, Kaushik Department of Computer Science & Engineering Odisha Burla768018 India Sikkim Manipal University Sikkim Manipal Institute of Technology Department of Artificial Intelligence and Data Science Sikkim India Department of Electrical Engineering Odisha Burla768018 India Department of Computer Science and Information Technology Chhattisgarh Bilaspur495009 India Manipal Academy of Higher Education Manipal Institute of Technology Bengaluru Department of Computer Science and Engineering Manipal India

The rapid proliferation of IoT devices like smartphones, smartwatches, etc. has significantly elevated the quantity of data requiring execution. It poses challenges for centralized Cloud computing servers, such as latency overhead and increased consumption of energy. To address this, Fog computing has been incorporated in this research as a complementary paradigm to the Cloud-based computing model. It thereby reduces the huge distance between end-user IoT gadgets and the Cloud computing servers. In order to improve the latency and waiting time this research employs a Multi-Level Queue (MLQ) for classifying tasks based on their priority. For parallel processing, a Self-adaptive Fuzzy C-means++ (SaFCm++) approach has been applied to cluster the Fog computing nodes depending on the heterogeneity of the computational nodes. For efficient scheduling, a Dynamic Energy-and-Latency-aware Task scheduling (DELTa) approach has been proposed to optimize latency, makespan, and utilization of resources. Extensive simulations are carried out for different test cases considering task and machine heterogeneity, followed by a statistical analysis. The overall improvements of the proposed method over other baselines are 9.75% for makespan, 64.59% for service latency, 13.90% for resource utilization, and 12.75% for energy consumption. The proposed energy-efficient scheduling method effectively manages diverse tasks and resources, enhancing task processing efficiency while minimizing energy consumption and maximizing resource utilization. Furthermore, the value of the Friedman statistics FF for the proposed model is estimated at 5.44, which shows superiority over the crucial value for four methodologies and four evaluation matrices. © 2013 IEEE.

关键词： Fog computing

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