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Recent Advances in Drilling Tool Temperature:A State‑of‑the‑Art Review

Chinese Journal of Mechanical engineering 2022年第6期35卷 23-62页

作者： Zhaoju Zhu Xinhui Sun Kai Guo Jie Sun Jianfeng Li School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350116China School of Mechanical Engineering Shandong UniversityJinan 250061China

Drilling is regarded as the most complex manufacturing process compared with other conventional machining *** the drilling process,most of the energy consumed in metal cutting is converted to heat and increases temperature *** resulting thermal phenomena are important since they influence the mode of deformation,the final metallurgical state of the machined surface,and the rate of tool ***,understanding the temperature characteristics in the drilling process is crucial for enhancing the drill performance and process *** efforts have been conducted to measure and control the drilling tool temperature ***,very few studies have been conducted from a comprehensive perspective to review all the *** address this gap in the literature,a rigorous review concerning the state-of-the-art results and advances in drilling tool temperature is presented in this paper by referring to the wide comparisons among literature *** multiple aspects of drilling tool temperature are precisely detailed and discussed in terms of theoretical analysis and thermal modeling,methods for temperature measuring,the effect of cutting parameters,tool geometries and hole-making methods on temperature and temperature controlling by different cooling *** conclusion,several possible future research directions are discussed to offer potential insights for the drilling community and future researchers.

关键词： Drilling Tool temperature Advance materials Cutting characteristics

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Luminescence: a new perspective for investigating perovskite precursors

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Science China Materials 2025年第1期68卷 312-313页

作者： Haofeng Zheng Shaocong Hou School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China Wuhan University Shenzhen Research Institute Shenzhen 518057China

In the past two decades, perovskite materials have made significant progress in optoelectronic semiconductors, emerging as formidable candidates for the next generation of commercial solar cells, light-emitting diodes (LEDs), and *** the fundamental solution chemistry and photophysics in solution-processed perovskite devices is crucial for comprehending to achieve highly efficient optoelectronic devices.

关键词： optoelectronic diodes perovskite

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Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049ShaanxiChina Department of Electrical Engineering and Automation Luoyang Institute of Science and TechnologyLuoyang 471023HenanChina School of Mechanical Engineering Hangzhou Dianzi UniversityHangzhou 310018ZhejiangChina

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation Data-driven Machine learning Ensemble learning Ensemble diversity

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Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 723-733页

作者： Xiongbo Wan Chaoling Zhang Fan Wei Chuan-Ke Zhang Min Wu IEEE the School of Automation China University of Geosciencesthe Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systemsand the Engineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationWuhan 430074China

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic *** addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI *** the designed controller,the involved fuzzy system is ensured to be asymptotically *** examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

关键词： Dynamic event-triggered mechanism(DETM) hybrid dynamic variables model predictive control(MPC) robust positive invariant(RPI)set T-S fuzzy systems

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Optimal Scheduling of Integrated Electricity and Gas System with Numerical Stability Condition-Free Method

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CSEE Journal of Power and Energy Systems 2025年第2期11卷 607-611页

作者： Suhan Zhang Chi Yung Chung Wei Gu Ruizhi Yu Shuai Lu Pengfei Zhao Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong KongChina School of Electrical and Electronic Engineering Southeast UniversityNanjing 210000China Institute of Automation Chinese Academy of SciencesBeijing 100000China

Though an accurate discretization approach for gas flow dynamics, the method of characteristics (MOC) is liable to instability for inappropriate step sizes. This letter addresses the numerical stability limitation of MOC, in the context of lEGS's optimal scheduling. Specifically, the proposed method enables flexible temporal step sizes without sacrificing accuracy, significantly reducing non-convergence due to numerical oscillations. The effectiveness of the proposed method is validated through case studies in different simulation settings.

关键词： Integrated electricity and gas system method of characteristics numerical stability optimal scheduling partial differential equation

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Life Prediction of IGBT Across Working Condition via a CNN-Transformer Network

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IEEE Transactions on Device and Materials Reliability 2025年第2期25卷 195-202页

作者： Zhu, Shuai Jian, Maoliang Yanga, Xiaoni Deng, Li Ya, Lianqiao Shanghai University School of Mechatronic Engineering and Automation Shanghai200072 China Shanghai University School of Microelectronics Shanghai201800 China

Insulated Gate Bipolar Transistors (IGBTs) are extensively utilized in a multitude of fields owing to their proficiency in power conversion and their dependable operation. Anticipating the service life of IGBTs to preemptively mitigate the repercussions of device failure, this research advances a novel lifespan forecasting methodology underpinned by a Convolutional Neural Network (CNN) and Transformer hybrid model. The methodology commences with accelerated aging power cycling tests within a range of temperature thresholds, utilizing the Siemens Power Tester to gather aging parameters at disparate junction temperatures. A pivotal observation is the alteration of the saturated voltage drop, VCE(ON), throughout the aging process, which is then harnessed as a critical aging indicator for model training. Following this, the accrued datasets from three distinct groups undergo a rigorous preprocessing phase. Subsequently, the proposed forecasting technique is deployed to predict lifespan across varying operating conditions. The empirical findings underscore that the model introduced in this paper, when predicated on the variations in saturated voltage drop, achieves markedly enhanced predictive fidelity in both single-step and multi-step forecasting scenarios, outperforming alternative comparative methodologies. Especially in single step prediction, the mean values of the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) are 0.996, 0.0016 and 0.0026, respectively. © 2001-2011 IEEE.

关键词： Insulated gate bipolar transistors (IGBT)

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Intelligent Optimization of Particle-Jamming-Based Variable Stiffness Module Design Using a Grey-box Model Based on Virtual Work Principle

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Journal of Bionic engineering 2024年第5期21卷 2324-2339页

作者： Hao Huang Zhenyun Shi Ziyu Liu Tianmiao Wang Chaozong Liu School of Mechanical Engineering and Automation Beihang UniversityBeijing100191China Beijing Advanced Innovation Centre for Biomedical Engineering School of Engineering MedicineBeihang UniversityBeijing100191China Division of Surgery&Interventional Science Royal National Orthopaedic HospitalUniversity College LondonStanmoreHA74LPUK

Soft grippers are favored for handling delicate objects due to their compliance but often have lower load capacities compared to rigid *** Stiffness Module(VSM)offer a solution,balancing flexibility and load capacity,for which particle jamming is an effective technology for stiffness-tunable robots requiring safe interaction and load *** applica-tions,such as rescue scenarios,require quantitative analysis to optimize VSM design parameters,which previous analytical models cannot effectively *** address this,a Grey-box model is proposed to analyze the mechanical response of the particle-jamming-based VSM by combining a White-box approach based on the virtual work principle with a Black-box approach that uses a shallow neural network *** Grey-box model demonstrates a high level of accuracy in predict-ing the VSM force-height mechanical response curves,with errors below 15%in almost 90%of the cases and a maximum error of less than 25%.The model is used to optimize VSM design parameters,particularly those unexplored *** results from the load capacity and force distribution comparison tests indicate that the VSM,optimized through our methods,quantitatively meets the practical engineering requirements.

关键词： Grey-box model Neural network Variable stiffness module Particle jamming Virtual work principle

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Model-free Speed Control of Single-phase Flux Switching Motor with an Asymmetrical Rotor

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CES Transactions on Electrical Machines and Systems 2024年第3期8卷 255-263页

作者： Zongsheng Zhang Congcong Guo School of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Qingdao Technical College Qingdao 266555China

This paper proposes and implements a model-free open-loop iterative learning control(ILC)strategy to realize the speed control of the single-phase flux switching motor(FSM)with an asymmetrical *** on the proposed winding control method,the asymmetrical rotor enables the motor to generate continuous positive torque for positive rotation,and relatively small resistance torque for negative *** initial iteration coefficient and variable iteration coefficient optimized scheme was proposed based on the characteristics of the hardware circuit,thereby forming the model-free strategy.A series of prototype experiments was carried *** results verify the effectiveness and practicability of the proposed ILC strategy.

关键词： Asymmetrical rotor Model-free iterative control Prototype experiments Single-phase flux switching motor

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Designing Proportional-Integral Consensus Protocols for Second-Order Multi-Agent Systems Using Delayed and Memorized State Information

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 878-892页

作者： Honghai Wang Qing-Long Han the College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern UniversityShenyang 110819China the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

This paper is concerned with consensus of a secondorder linear time-invariant multi-agent system in the situation that there exists a communication delay among the agents in the network.A proportional-integral consensus protocol is designed by using delayed and memorized state *** the proportional-integral consensus protocol,the consensus problem of the multi-agent system is transformed into the problem of asymptotic stability of the corresponding linear time-invariant time-delay *** that the location of the eigenvalues of the corresponding characteristic function of the linear time-invariant time-delay system not only determines the stability of the system,but also plays a critical role in the dynamic performance of the *** this paper,based on recent results on the distribution of roots of quasi-polynomials,several necessary conditions for Hurwitz stability for a class of quasi-polynomials are first *** allowable regions of consensus protocol parameters are *** necessary and sufficient conditions for determining effective protocol parameters are *** designed protocol can achieve consensus and improve the dynamic performance of the second-order multi-agent ***,the effects of delays on consensus of systems of harmonic oscillators/double integrators under proportional-integral consensus protocols are ***,some results on proportional-integral consensus are derived for a class of high-order linear time-invariant multi-agent systems.

关键词： Consensus protocol Hurwitz stability multi-agent systems quasi-polynomials time delay

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Optical nanoprobes in biomedical diagnosis assays: Recent progress

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Smart Materials in Medicine 2024年第1期5卷 75-91页

作者： Chen, Fuli Guo, Jiuchuan Guo, Jinhong Chen, Wenjun Ma, Xing Shenzhen518055 China School of Sensing Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China

Biomedical assays based on optical nanoprobes play an important role in human health. Optical nanoprobes, the nanomaterials with special optical properties, are widely utilized in biomedical assays. Compared with traditional materials, the well-performed optical nanoprobes have certain properties, such as negligible interferences from the background fluorescence and scattering, simple operations and instruments, high sensitivity, and excellent specificity. This paper reviews the mechanisms, materials, and applications of optical nanoprobes. The mechanisms of optical nanoprobes involve fluorescence, phosphorescence, Förster resonance energy transfer (FRET), upconversion luminescence and chemiluminescence. Time-resolved luminescent nanoprobes are usually prepared from rare earth compounds and quantum dots (QDs). Ultralong inorganic phosphorescent nanoprobes are prepared from transition metal compounds, while ultralong organic phosphorescent nanoprobes are usually prepared from π-conjugated compound nanocrystals that exhibit a rigid confinement to suppress the non-radiative transitions and contain heavy atoms to enhance ISC. Time-resolved luminescent nanoprobes and ultralong phosphorescent nanoprobes minimize background interferences by longer luminescence lifetime. Chemiluminescent nanoprobes are usually prepared from compounds that can react with reactive oxygen species (ROS) to form peroxide bonds. Upconversion luminescent nanoprobes are usually prepared from inorganic rare earth fluoride nanocrystals. Chemiluminescent nanoprobes and upconversion luminescent nanoprobes can avoid background interferences because excitation light of shorter wavelength is not needed. FRET nanoprobes and luminescence quenching nanoprobes are prepared from a donor and an acceptor that can be linked or delinked by the analyte. Optical nanoprobes are applied in both in vitro diagnoses and in vivo imaging. The in vitro applications of optical nanoprobes include the determination of varietie

关键词： Rare earths

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