Due to the calculation problem of classical methods (such as Lyapunovexponent) for chaotic behavior, a new method of identifying nonlinear dynamics with higher-ordertime-frequency entropy (HOTFE) based on time-frequen...Due to the calculation problem of classical methods (such as Lyapunovexponent) for chaotic behavior, a new method of identifying nonlinear dynamics with higher-ordertime-frequency entropy (HOTFE) based on time-frequency analysis and information theorem is proposed.Firstly, the meaning of HOTFE is defined, and then its validity is testified by numericalsimulation. In the end vibration data from rotors are analyzed by HOTFE. The results demonstratethat it can indeed identify the early rub-impact chaotic behavior in rotors and also is simpler tocalculate than previous methods.展开更多
The use of time-frequency entropy to quantitatively assess the stability of submerged arc welding process considering the distribution features of arc energy is reported in this paper. Time-frequency entropy is employ...The use of time-frequency entropy to quantitatively assess the stability of submerged arc welding process considering the distribution features of arc energy is reported in this paper. Time-frequency entropy is employed to calculate and analyze the stationary current signals, non-stationary current and voltage signals in the submerged arc welding process. It is obtained that time-frequency entropy of arc signal can be used as arc stability judgment criteria of submerged arc welding. Experimental results are provided to confirm the effectiveness of this approach.展开更多
Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conductin...Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conducting ECG-based studies.From a review of existing studies,two main factors appear to contribute to this problem:the uneven distribution of arrhythmia classes and the limited expressiveness of features learned by current models.To overcome these limitations,this study proposes a dual-path multimodal framework,termed DM-EHC(Dual-Path Multimodal ECG Heartbeat Classifier),for ECG-based heartbeat classification.The proposed framework links 1D ECG temporal features with 2D time–frequency features.By setting up the dual paths described above,the model can process more dimensions of feature information.The MIT-BIH arrhythmia database was selected as the baseline dataset for the experiments.Experimental results show that the proposed method outperforms single modalities and performs better for certain specific types of arrhythmias.The model achieved mean precision,recall,and F1 score of 95.14%,92.26%,and 93.65%,respectively.These results indicate that the framework is robust and has potential value in automated arrhythmia classification.展开更多
Fault features in mechanical systems often manifest as transient impulses,which can be effectively analyzed using time-frequency analysis(TFA)methods.Recently,a new TFA technique known as the time-reassigned multi-syn...Fault features in mechanical systems often manifest as transient impulses,which can be effectively analyzed using time-frequency analysis(TFA)methods.Recently,a new TFA technique known as the time-reassigned multi-synchrosqueezing transform(TMssT)was proposed to capture these transient impulses for fault diagnosis.However,the TMSST,which is based on the short-time Fourier transform(STFT),suffers from unclear high-frequency re-presentations owing to the fixed sliding window used in the STFT.To address this limitation,the current study combined TMSST with the S-transform and a local maximum method to enhance the time-frequency representation for improved signal analysis.Furthermore,an extractive reconstruction algorithm that binds the maximum value of the spectral envelope is proposed for spectral decomposition.To validate the proposed technique,a simulated noise-added signal and four experimental bearing defect datasets were used.The results demonstrate that the proposed technique can effectively and accurately extract fault features from bearing signals regardless of whether the bearings operate under constant or varying speed conditions.This study offers a novel and efficient approach for fault diagnosis in mechanical systems with complex dynamic behaviors.展开更多
The state-of-the-art optical atomic clocks and the time-frequency signal transmission open a fresh field for gravity potential(geopotential)determination.Various methods,including optical fiber frequency transfer,sate...The state-of-the-art optical atomic clocks and the time-frequency signal transmission open a fresh field for gravity potential(geopotential)determination.Various methods,including optical fiber frequency transfer,satellite two-way,satellite common-view,satellite carrier phase,VLBI,tri-frequency combination,and dual-frequency combination,were developed to determine the geopotential differences using optical atomic clocks and then determine the geopotential at station B based on the geopotential at station A.This review elaborates the principles,methods,scientific objectives,applications,and relevant research trends of geopotential determination based on time-frequency signals.展开更多
With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communicat...With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communication system.In particular,the abnormal signals may emulate the normal signals,which makes it very challenging for abnormal signal recognition.In this paper,we propose a new abnormal signal recognition scheme,which combines time-frequency analysis with deep learning to effectively identify synthetic abnormal communication signals.Firstly,we emulate synthetic abnormal communication signals including seven jamming patterns.Then,we model an abnormal communication signals recognition system based on the communication protocol between the transmitter and the receiver.To improve the performance,we convert the original signal into the time-frequency spectrogram to develop an image classification algorithm.Simulation results demonstrate that the proposed method can effectively recognize the abnormal signals under various parameter configurations,even under low signal-to-noise ratio(SNR)and low jamming-to-signal ratio(JSR)conditions.展开更多
High-entropy materials(HEMs)have attracted considerable research attention in battery applications due to exceptional properties such as remarkable structural stability,enhanced ionic conductivity,superior mechanical ...High-entropy materials(HEMs)have attracted considerable research attention in battery applications due to exceptional properties such as remarkable structural stability,enhanced ionic conductivity,superior mechanical strength,and outstanding catalytic activity.These distinctive characteristics render HEMs highly suitable for various battery components,such as electrodes,electrolytes,and catalysts.This review systematically examines recent advances in the application of HEMs for energy storage,beginning with fundamental concepts,historical development,and key definitions.Three principal categories of HEMs,namely high-entropy alloys,high-entropy oxides,and highentropy MXenes,are analyzed with a focus on electrochemical performance metrics such as specific capacity,energy density,cycling stability,and rate capability.The underlying mechanisms by which these materials enhance battery performance are elucidated in the discussion.Furthermore,the pivotal role of machine learning in accelerating the discovery and optimization of novel high-entropy battery materials is highlighted.The review concludes by outlining future research directions and potential breakthroughs in HEM-based battery technologies.展开更多
One-dimensional ensemble dispersion entropy(EDE1D)is an effective nonlinear dynamic analysis method for complexity measurement of time series.However,it is only restricted to assessing the complexity of one-di-mension...One-dimensional ensemble dispersion entropy(EDE1D)is an effective nonlinear dynamic analysis method for complexity measurement of time series.However,it is only restricted to assessing the complexity of one-di-mensional time series(TS1d)with the extracted complexity features only at a single scale.Aiming at these problems,a new nonlinear dynamic analysis method termed two-dimensional composite multi-scale ensemble Gramian dispersion entropy(CMEGDE_(2D))is proposed in this paper.First,the TS_(1D) is transformed into a two-dimensional image(I_(2D))by using Gramian angular fields(GAF)with more internal data structures and geometri features,which preserve the global characteristics and time dependence of vibration signals.Second,the I2D is analyzed at multiple scales through the composite coarse-graining method,which overcomes the limitation of a single scale and provides greater stability compared to traditional coarse-graining methods.Subsequently,a new fault diagnosis method of rolling bearing is proposed based on the proposed CMEGDE_(2D) for fault feature ex-traction and the chicken swarm algorithm optimized support vector machine(CsO-SvM)for fault pattern identification.The simulation signals and two data sets of rolling bearings are utilized to verify the effectiveness of the proposed fault diagnosis method.The results demonstrate that the proposed method has stronger dis-crimination ability,higher fault diagnosis accuracy and better stability than the other compared methods.展开更多
High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic f...High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic features enable forming-free resistive switching,multilevel conductance modulation,and synaptic plasticity,making HEOs attractive for neuromorphic computing.This review outlines recent progress in HEO-based memristors across materials engineering,switching mechanisms,and synaptic emulation.Particular attention is given to vacancy migration,phase transitions,and valence-state dynamics—mechanisms that underlie the switching behaviors observed in both amorphous and crystalline systems.Their relevance to neuromorphic functions such as short-term plasticity and spike-timing-dependent learning is also examined.While encouraging results have been achieved at the device level,challenges remain in conductance precision,variability control,and scalable integration.Addressing these demands a concerted effort across materials design,interface optimization,and task-aware modeling.With such integration,HEO memristors offer a compelling pathway toward energy-efficient and adaptable brain-inspired electronics.展开更多
(NbZrHfTi)C high-entropy ceramics,as an emerging class of ultra-high-temperature materials,have garnered significant interest due to their unique multi-principal-element crystal structure and exceptional hightemperatu...(NbZrHfTi)C high-entropy ceramics,as an emerging class of ultra-high-temperature materials,have garnered significant interest due to their unique multi-principal-element crystal structure and exceptional hightemperature properties.This study systematically investigates the mechanical properties of(NbZrHfTi)C high-entropy ceramics by employing first-principles density functional theory,combined with the Debye-Grüneisen model,to explore the variations in their thermophysical properties with temperature(0–2000 K)and pressure(0–30 GPa).Thermodynamically,the calculated mixing enthalpy and Gibbs free energy confirm the feasibility of forming a stable single-phase solid solution in(NbZrHfTi)C.The calculated results of the elastic stiffness constant indicate that the material meets the mechanical stability criteria of the cubic crystal system,further confirming the structural stability.Through evaluation of key mechanical parameters—bulk modulus,shear modulus,Young’s modulus,and Poisson’s ratio—we provide comprehensive insight into the macro-mechanical behaviour of the material and its correlation with the underlying microstructure.Notably,compared to traditional binary carbides and their average properties,(NbZrHfTi)C exhibits higher Vickers hardness(Approximately 28.5 GPa)and fracture toughness(Approximately 3.4 MPa⋅m^(1/2)),which can be primarily attributed to the lattice distortion and solid-solution strengthening mechanism.The study also utilizes the quasi-harmonic approximation method to predict the material’s thermophysical properties,including Debye temperature(initial value around 563 K),thermal expansion coefficient(approximately 8.9×10^(−6) K−1 at 2000 K),and other key parameters such as heat capacity at constant volume.The results show that within the studied pressure and temperature ranges,(NbZrHfTi)C consistently maintains a stable phase structure and good thermomechanical properties.The thermal expansion coefficient increasing with temperature,while heat capacity approaches the Dulong-Petit limit at elevated temperatures.These findings underscore the potential of(NbZrHfTi)C applications in ultra-high temperature thermal protection systems,cutting tool coatings,and nuclear structural materials.展开更多
High entropy alloy attracts widespread attention due to its excellent mechanical properties.It becomes a new type of alloy material with high application potential,but the grinding performance of High entropy alloy re...High entropy alloy attracts widespread attention due to its excellent mechanical properties.It becomes a new type of alloy material with high application potential,but the grinding performance of High entropy alloy receives little attention.This paper conducts grinding simulation and surface grinding experiments on FeCoCrNi high entropy and alloys to analyze the grinding removal mechanism of the FeCoCrNi-based High entropy alloy.We also discuss the influence of grinding parameters,element types,element content and forming methods on grinding force and sub-surface plastic deformation after grinding.The simulation and experimental results show that as the increase of grinding depth,both tangential grinding force and normal grinding force increase,and the thickness of sub-surface plastic deformation layer decreases.With the increase of grinding speed,both tangential grinding force and normal grinding force decrease,and the thickness of sub-surface plastic deformation layer caused by grinding process shows a trend of gradual decrease.Under the same processing parameters,the normal grinding force is greater than the tangential grinding force.In FeCoCrNi series high entropy alloys,the grinding force and subsurface plastic deformation layer thickness of high entropy alloys increased with the addition in Ti content.The grinding force and plastic deformation formed by adding Ti element are greater than those formed by adding Al element,and High entropy alloys prepared using laser cladding method exhibit greater grinding force and plastic deformation than those prepared using selective laser melting method.The research results provide theoretical reference and experimental basis for high-quality grinding of high entropy alloys,which may be helpful for the design and manufacturing of high entropy alloy parts.展开更多
High-entropy oxides(HEOs)derive their exceptional properties from the atomic-level homogenization of multiple constituent elements within the crystal lattice,which induces a sophisticated local environment that fundam...High-entropy oxides(HEOs)derive their exceptional properties from the atomic-level homogenization of multiple constituent elements within the crystal lattice,which induces a sophisticated local environment that fundamentally reconfigures electron density distributions and coordination environment at active sites.However,the mechanisms by which multi-component systems in HEOs precisely regulate high-activity catalytic sites remain poorly understood.This work addresses this gap by designing medium-entropy perovskite oxides through the strategic incorporation of transition metals with distinct electronegativities and ionic radii,aiming to unravel how local environmental modifications impact the energy band location,coordination states,and adsorption behavior of the Co site.A family of A_(4)BO_(4)-type medium-entropy oxides PrSr(Fe_(0.2)Co_(0.2)Ni_(0.2)Cu_(0.2)M_(0.2))O_(4)(M=Sc,Cr,Mn)was successfully synthesized.Divergent atomic properties among Sc,Cr,and Mn(electronegativity,ionic size,and metal-oxygen bond strength)triggered pronounced electron redistribution,effectively tuning the d-band center of Co.Remarkably,Cr substitution significantly enhanced O_(4) adsorption at Co-active sites,as indicated by an elongated O-O bond length(1.234Å→1.279Å).Concurrently,Cr doping destabilized the M'-O-Cr bonds(M'=Fe,Co,Ni,Cu)and lowered the thermodynamic barrier for oxygen vacancy formation.Electrochemical tests revealed that PrSr(Fe_(0.2)Co_(0.2)Ni_(0.2)Cu_(0.2)Cr_(0.2))O_(4)(PSMO-Cr)exhibited the highest electrical conductivity and fastest oxygen surface exchange kinetics.At 700℃,the area-specific resistance(ASR)of the PSMO-Cr cathode was 0.07Ωcm^(2).Corresponding fuel cells achieved a maximum power density of 0.76 W cm^(-2).In electrolysis mode,the maximum current density reached 0.56 A cm^(-2) under 1.3 V at 700℃using PSMO-Cr as the anode.These results demonstrate that PSMO-Cr is a promising bifunctional catalyst for energy conversion applications.展开更多
High entropy alloys(HEAs)have recently attracted significant attention due to their exceptional mechanical properties and potential applications across various fields.Friction stir welding and processing(FSW/P),as not...High entropy alloys(HEAs)have recently attracted significant attention due to their exceptional mechanical properties and potential applications across various fields.Friction stir welding and processing(FSW/P),as notable solid-state welding and processing techniques,have been proved effectiveness in enhancing microstructures and mechanical properties of HEAs.This review article summarizes the current status of FSW/P of HEAs.The welding materials and conditions used for FSW/P in HEAs are reviewed and discussed.The effects of FSW/P on the evolutions of grain structure,texture,dislocation,and secondary phase for different HEAs are highlighted.Furthermore,the influences of FSW/P on the mechanical properties of various HEAs are analyzed.Finally,potential applications,challenges,and future directions of FSW/P in HEAs are forecasted.Overall,FSW/P enable to refine grains of HEAs through dynamic recrystallization and to activate diverse deformation mechanisms of HEAs through tailoring phase structures,thereby significantly improving the strength,hardness,and ductility of both single-and dual-phase HEAs.Future progress in this field will rely on comprehensive optimization of processing parameters and alloy composition,integration of multi-scale modeling with advanced characterization for in-depth exploration of microstructural mechanisms,systematic evaluation of functional properties,and effective bridging of the gap between laboratory research and industrial application.The review aims to provide an overview of recent advancements in the FSW/P of HEAs and encourage further research in this area.展开更多
Selective laser melting(SLM),as an additive manufacturing technology,has garnered widespread attention for its capability to fabricate components with complex geometries and to tailor the microstructure and mechanical...Selective laser melting(SLM),as an additive manufacturing technology,has garnered widespread attention for its capability to fabricate components with complex geometries and to tailor the microstructure and mechanical properties under specific conditions.However,the intrinsic influence mechanism of microstructure formation under non-equilibrium solidification conditions in SLM processes has not been clearly revealed.In the present work,the influence of Al concentration and process parameters on the microstructure forming mechanism of Al_(x)CoCrFeNi HEAs prepared by SLM is investigated by molecular dynamics simulation method.The simulation results show that the difference in Al content significantly affects the microstructure formation of HEAs,including the growth rate and morphology of columnar crystals,stress distribution at grain boundaries,and defect structure.In addition,the results show that increasing the substrate temperature improves the solidification formability,reduces microstructural defects,and helps reduce residual stress in Al_(x)CoCrFeNi HEAs.By analyzing the influence of heat and solute flow in the molten pool on the growth of columnar crystals,it is found that spatial fluctuations in Al concentration during the non-equilibrium solidification process inhibit the high cooling rates induced by steep temperature gradients.These findings promote the understanding of the forming mechanism of microstructure in HEAs prepared by SLM and provide theoretical guidance for designing high-performance SLM-fabricated HEAs.展开更多
High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environm...High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environments,tunable electronic structures,abundant unsaturated active sites,and dynamic structural reassembly—collectively enhance electrochemical activity and durability under operating conditions.This review summarizes recent advances in HEACs for hydrogen evolution,oxygen evolution,and overall water splitting,highlighting their disorder-driven advantages over crystalline counterparts.Catalytic performance benchmarks are presented,and mechanistic insights are discussed,focusing on how multimetallic synergy,amorphization effect,and in‐situ reconstruction cooperatively regulate reaction pathways.These insights provide guidance for the rational design of next‐generation amorphous high‐entropy electrocatalysts with improved efficiency and durability.展开更多
Seismic resilience(SR)has emerged as a critical focus in earthquake engineering to evaluate the ability of structures to endure,recover from,and adapt to seismic events.This study presents an entropy-based multicriter...Seismic resilience(SR)has emerged as a critical focus in earthquake engineering to evaluate the ability of structures to endure,recover from,and adapt to seismic events.This study presents an entropy-based multicriteria approach for selecting optimal intensity measures(IMs)to assess SR of structures.Eight representative IMs,derived from time histories and response spectrum are evaluated.Incremental dynamic analysis is con-ducted on a reinforced concrete structure,using engineering demand parameters such as the maximum interstory drift and floor acceleration to generate fragility curves via a probabilistic seismic demand model.The optimal IMs are identified through a multi-criteria decision-making process,with scores calculated using the entropy weight method to incorporate factors such as efficiency,proficiency,and uncertainty based on infor-mation entropy.An effective SR framework is derived from fragility results.The findings indicate that peak ground velocity and spectral IMs are the most effective,while energy-related IMs underestimate SR.The study highlights the importance of optimizing IMs for more accurate seismic resilience assessments.The proposed entropy-based multi-criteria approach is shown to be both reliable and effective for selecting optimal IMs in this context.展开更多
Conversion of ammonia into hydrogen,a crucial pathway for the hydrogen economy,is severely constrained by the intricacy of the required equipment and the low efficiency.Herein,Pd@Pt Ni Co Ru Ir coreshell mesoporous bi...Conversion of ammonia into hydrogen,a crucial pathway for the hydrogen economy,is severely constrained by the intricacy of the required equipment and the low efficiency.Herein,Pd@Pt Ni Co Ru Ir coreshell mesoporous bifunctional electrocatalysts were fabricated via a one-step wet-chemical reduction approach.By utilizing the limiting effect of triblock copolymers,gradient distribution control of six metal elements(Pd core and Pt/Ni/Co/Ru/Ir high-entropy alloys shell) was achieved,where the high-entropy alloy shell forms high-density active sites through lattice distortion effect.With the help of lattice distortion and mesoporous-confinement-enabled interfacial coupling effects,Pd@Pt Ni Co Ru Ir catalyst exhibited exceptional bifunctional performance in alkaline media:A low hydrogen evolution reaction(HER) overpotential of 30.5 m V at 10 m A/cm^(2) and a high ammonia oxidation reaction(AOR) peak current density of 19.6 m A/cm^(2) at 0.7 V vs.RHE,representing a 3.83-fold enhancement over commercial Pt/C.Moreover,a rechargeable Zn-NH_(3) battery system was constructed and achieved 92.3 % Faradaic efficiency(FE) for NH_(3)-to-H_(2) conversion with outstanding stability at 16 m A/cm^(2),thereby providing an innovative solution for efficient ammonia decomposition-based hydrogen production.展开更多
The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time...The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time and frequency domains. To improve the resolution of the time-frequency decomposition results, we use the instantaneous frequency distribution function（IFDF） to express the seismic signal. When the instantaneous frequencies of the nonstationary signal satisfy the requirements of the uncertainty principle, the support of IFDF is just the support of the amplitude ridges in the signal obtained using the short-time Fourier transform. Based on this feature, we propose a new iteration algorithm to achieve the sparse time-frequency decomposition of the signal. The iteration algorithm uses the support of the amplitude ridges of the residual signal obtained with the short-time Fourier transform to update the time-frequency components of the signal. The summation of the updated time-frequency components in each iteration is the result of the sparse timefrequency decomposition. Numerical examples show that the proposed method improves the resolution of the time-frequency decomposition results and the accuracy of the analysis of the nonstationary signal. We also use the proposed method to attenuate the ground roll of field seismic data with good results.展开更多
Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional...Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.展开更多
Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyze...Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyzed. Experimental results show that for a spectrum of some density, the joint time-frequency gain-modification based speech enhancement algorithm achieves significant improvement in intelligibility. Additionally, the spectrum region where the estimated spectrum is smaller than the clean spectrum, is the most important region contributing to intelligibility improvement for the enhanced whisper. The spectrum region where the estimated spectrum is larger than twice the size of the clean spectrum is detrimental to speech intelligibility perception within the whisper context.展开更多
文摘Due to the calculation problem of classical methods (such as Lyapunovexponent) for chaotic behavior, a new method of identifying nonlinear dynamics with higher-ordertime-frequency entropy (HOTFE) based on time-frequency analysis and information theorem is proposed.Firstly, the meaning of HOTFE is defined, and then its validity is testified by numericalsimulation. In the end vibration data from rotors are analyzed by HOTFE. The results demonstratethat it can indeed identify the early rub-impact chaotic behavior in rotors and also is simpler tocalculate than previous methods.
文摘The use of time-frequency entropy to quantitatively assess the stability of submerged arc welding process considering the distribution features of arc energy is reported in this paper. Time-frequency entropy is employed to calculate and analyze the stationary current signals, non-stationary current and voltage signals in the submerged arc welding process. It is obtained that time-frequency entropy of arc signal can be used as arc stability judgment criteria of submerged arc welding. Experimental results are provided to confirm the effectiveness of this approach.
基金supported by the Innovative Human Resource Development for Local Intel-lectualization program through the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.IITP-2026-2020-0-01741)the research fund of Hanyang University(HY-2025-1110).
文摘Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conducting ECG-based studies.From a review of existing studies,two main factors appear to contribute to this problem:the uneven distribution of arrhythmia classes and the limited expressiveness of features learned by current models.To overcome these limitations,this study proposes a dual-path multimodal framework,termed DM-EHC(Dual-Path Multimodal ECG Heartbeat Classifier),for ECG-based heartbeat classification.The proposed framework links 1D ECG temporal features with 2D time–frequency features.By setting up the dual paths described above,the model can process more dimensions of feature information.The MIT-BIH arrhythmia database was selected as the baseline dataset for the experiments.Experimental results show that the proposed method outperforms single modalities and performs better for certain specific types of arrhythmias.The model achieved mean precision,recall,and F1 score of 95.14%,92.26%,and 93.65%,respectively.These results indicate that the framework is robust and has potential value in automated arrhythmia classification.
基金Supported by National Natural Science Foundation of China(Grant No.62271230)Shandong Provincial Central Guidance on Local Science and Technology Development Fund(Grant No.YDZX2022178).
文摘Fault features in mechanical systems often manifest as transient impulses,which can be effectively analyzed using time-frequency analysis(TFA)methods.Recently,a new TFA technique known as the time-reassigned multi-synchrosqueezing transform(TMssT)was proposed to capture these transient impulses for fault diagnosis.However,the TMSST,which is based on the short-time Fourier transform(STFT),suffers from unclear high-frequency re-presentations owing to the fixed sliding window used in the STFT.To address this limitation,the current study combined TMSST with the S-transform and a local maximum method to enhance the time-frequency representation for improved signal analysis.Furthermore,an extractive reconstruction algorithm that binds the maximum value of the spectral envelope is proposed for spectral decomposition.To validate the proposed technique,a simulated noise-added signal and four experimental bearing defect datasets were used.The results demonstrate that the proposed technique can effectively and accurately extract fault features from bearing signals regardless of whether the bearings operate under constant or varying speed conditions.This study offers a novel and efficient approach for fault diagnosis in mechanical systems with complex dynamic behaviors.
基金National Natural Science Foundation of China(Grant Nos.42388102,42030105,42192535)the Open Fund of State Key Laboratory of Precision Geodesy,Innovation Academy for Precision Measurement Science and Technology,Chinese Academy of Sciences(Grant No.SKLPG2025-1-5)。
文摘The state-of-the-art optical atomic clocks and the time-frequency signal transmission open a fresh field for gravity potential(geopotential)determination.Various methods,including optical fiber frequency transfer,satellite two-way,satellite common-view,satellite carrier phase,VLBI,tri-frequency combination,and dual-frequency combination,were developed to determine the geopotential differences using optical atomic clocks and then determine the geopotential at station B based on the geopotential at station A.This review elaborates the principles,methods,scientific objectives,applications,and relevant research trends of geopotential determination based on time-frequency signals.
基金supported by Natural Science Foundation of China(No.62371231)Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu under Grant BK20222001Jiangsu Provincial Key Research and Development Program(No.BE2023027).
文摘With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communication system.In particular,the abnormal signals may emulate the normal signals,which makes it very challenging for abnormal signal recognition.In this paper,we propose a new abnormal signal recognition scheme,which combines time-frequency analysis with deep learning to effectively identify synthetic abnormal communication signals.Firstly,we emulate synthetic abnormal communication signals including seven jamming patterns.Then,we model an abnormal communication signals recognition system based on the communication protocol between the transmitter and the receiver.To improve the performance,we convert the original signal into the time-frequency spectrogram to develop an image classification algorithm.Simulation results demonstrate that the proposed method can effectively recognize the abnormal signals under various parameter configurations,even under low signal-to-noise ratio(SNR)and low jamming-to-signal ratio(JSR)conditions.
基金supported by the Fujian Provincial Science and Technology Planning Project(No.2022HZ027006,No.2024HZ021023)National Natural Science Foundation of China(No.U22A20118).
文摘High-entropy materials(HEMs)have attracted considerable research attention in battery applications due to exceptional properties such as remarkable structural stability,enhanced ionic conductivity,superior mechanical strength,and outstanding catalytic activity.These distinctive characteristics render HEMs highly suitable for various battery components,such as electrodes,electrolytes,and catalysts.This review systematically examines recent advances in the application of HEMs for energy storage,beginning with fundamental concepts,historical development,and key definitions.Three principal categories of HEMs,namely high-entropy alloys,high-entropy oxides,and highentropy MXenes,are analyzed with a focus on electrochemical performance metrics such as specific capacity,energy density,cycling stability,and rate capability.The underlying mechanisms by which these materials enhance battery performance are elucidated in the discussion.Furthermore,the pivotal role of machine learning in accelerating the discovery and optimization of novel high-entropy battery materials is highlighted.The review concludes by outlining future research directions and potential breakthroughs in HEM-based battery technologies.
基金Supported by the National Natural Science Foundation of China(Grant No.51975004)the Outstanding Youth Fund of Universities in Anhui Province of China(Grant No.2022AH020032).
文摘One-dimensional ensemble dispersion entropy(EDE1D)is an effective nonlinear dynamic analysis method for complexity measurement of time series.However,it is only restricted to assessing the complexity of one-di-mensional time series(TS1d)with the extracted complexity features only at a single scale.Aiming at these problems,a new nonlinear dynamic analysis method termed two-dimensional composite multi-scale ensemble Gramian dispersion entropy(CMEGDE_(2D))is proposed in this paper.First,the TS_(1D) is transformed into a two-dimensional image(I_(2D))by using Gramian angular fields(GAF)with more internal data structures and geometri features,which preserve the global characteristics and time dependence of vibration signals.Second,the I2D is analyzed at multiple scales through the composite coarse-graining method,which overcomes the limitation of a single scale and provides greater stability compared to traditional coarse-graining methods.Subsequently,a new fault diagnosis method of rolling bearing is proposed based on the proposed CMEGDE_(2D) for fault feature ex-traction and the chicken swarm algorithm optimized support vector machine(CsO-SvM)for fault pattern identification.The simulation signals and two data sets of rolling bearings are utilized to verify the effectiveness of the proposed fault diagnosis method.The results demonstrate that the proposed method has stronger dis-crimination ability,higher fault diagnosis accuracy and better stability than the other compared methods.
基金financially supported by the National Natural Science Foundation of China(Grant No.12172093)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2021A1515012607)。
文摘High-entropy oxides(HEOs)have emerged as a promising class of memristive materials,characterized by entropy-stabilized crystal structures,multivalent cation coordination,and tunable defect landscapes.These intrinsic features enable forming-free resistive switching,multilevel conductance modulation,and synaptic plasticity,making HEOs attractive for neuromorphic computing.This review outlines recent progress in HEO-based memristors across materials engineering,switching mechanisms,and synaptic emulation.Particular attention is given to vacancy migration,phase transitions,and valence-state dynamics—mechanisms that underlie the switching behaviors observed in both amorphous and crystalline systems.Their relevance to neuromorphic functions such as short-term plasticity and spike-timing-dependent learning is also examined.While encouraging results have been achieved at the device level,challenges remain in conductance precision,variability control,and scalable integration.Addressing these demands a concerted effort across materials design,interface optimization,and task-aware modeling.With such integration,HEO memristors offer a compelling pathway toward energy-efficient and adaptable brain-inspired electronics.
基金supported by the National Natural Science Foundation of China(Nos.92166105 and 52005053)High-Tech Industry Science and Technology Innovation Leading Program of Hunan Province(No.2020GK2085)the Science and Technology Innovation Program of Hunan Province(No.2021RC3096).
文摘(NbZrHfTi)C high-entropy ceramics,as an emerging class of ultra-high-temperature materials,have garnered significant interest due to their unique multi-principal-element crystal structure and exceptional hightemperature properties.This study systematically investigates the mechanical properties of(NbZrHfTi)C high-entropy ceramics by employing first-principles density functional theory,combined with the Debye-Grüneisen model,to explore the variations in their thermophysical properties with temperature(0–2000 K)and pressure(0–30 GPa).Thermodynamically,the calculated mixing enthalpy and Gibbs free energy confirm the feasibility of forming a stable single-phase solid solution in(NbZrHfTi)C.The calculated results of the elastic stiffness constant indicate that the material meets the mechanical stability criteria of the cubic crystal system,further confirming the structural stability.Through evaluation of key mechanical parameters—bulk modulus,shear modulus,Young’s modulus,and Poisson’s ratio—we provide comprehensive insight into the macro-mechanical behaviour of the material and its correlation with the underlying microstructure.Notably,compared to traditional binary carbides and their average properties,(NbZrHfTi)C exhibits higher Vickers hardness(Approximately 28.5 GPa)and fracture toughness(Approximately 3.4 MPa⋅m^(1/2)),which can be primarily attributed to the lattice distortion and solid-solution strengthening mechanism.The study also utilizes the quasi-harmonic approximation method to predict the material’s thermophysical properties,including Debye temperature(initial value around 563 K),thermal expansion coefficient(approximately 8.9×10^(−6) K−1 at 2000 K),and other key parameters such as heat capacity at constant volume.The results show that within the studied pressure and temperature ranges,(NbZrHfTi)C consistently maintains a stable phase structure and good thermomechanical properties.The thermal expansion coefficient increasing with temperature,while heat capacity approaches the Dulong-Petit limit at elevated temperatures.These findings underscore the potential of(NbZrHfTi)C applications in ultra-high temperature thermal protection systems,cutting tool coatings,and nuclear structural materials.
基金Supported by National Natural Science Foundation of China(Grant No.52275412)Fundamental Research Funds for the Central Universities of China(Grant No.N2403015).
文摘High entropy alloy attracts widespread attention due to its excellent mechanical properties.It becomes a new type of alloy material with high application potential,but the grinding performance of High entropy alloy receives little attention.This paper conducts grinding simulation and surface grinding experiments on FeCoCrNi high entropy and alloys to analyze the grinding removal mechanism of the FeCoCrNi-based High entropy alloy.We also discuss the influence of grinding parameters,element types,element content and forming methods on grinding force and sub-surface plastic deformation after grinding.The simulation and experimental results show that as the increase of grinding depth,both tangential grinding force and normal grinding force increase,and the thickness of sub-surface plastic deformation layer decreases.With the increase of grinding speed,both tangential grinding force and normal grinding force decrease,and the thickness of sub-surface plastic deformation layer caused by grinding process shows a trend of gradual decrease.Under the same processing parameters,the normal grinding force is greater than the tangential grinding force.In FeCoCrNi series high entropy alloys,the grinding force and subsurface plastic deformation layer thickness of high entropy alloys increased with the addition in Ti content.The grinding force and plastic deformation formed by adding Ti element are greater than those formed by adding Al element,and High entropy alloys prepared using laser cladding method exhibit greater grinding force and plastic deformation than those prepared using selective laser melting method.The research results provide theoretical reference and experimental basis for high-quality grinding of high entropy alloys,which may be helpful for the design and manufacturing of high entropy alloy parts.
基金supported by the National Natural Science Foundation of China(51872078,52272197,52572219)Heilongjiang Provincial Natural Science Foundation of China(LH2024E106)。
文摘High-entropy oxides(HEOs)derive their exceptional properties from the atomic-level homogenization of multiple constituent elements within the crystal lattice,which induces a sophisticated local environment that fundamentally reconfigures electron density distributions and coordination environment at active sites.However,the mechanisms by which multi-component systems in HEOs precisely regulate high-activity catalytic sites remain poorly understood.This work addresses this gap by designing medium-entropy perovskite oxides through the strategic incorporation of transition metals with distinct electronegativities and ionic radii,aiming to unravel how local environmental modifications impact the energy band location,coordination states,and adsorption behavior of the Co site.A family of A_(4)BO_(4)-type medium-entropy oxides PrSr(Fe_(0.2)Co_(0.2)Ni_(0.2)Cu_(0.2)M_(0.2))O_(4)(M=Sc,Cr,Mn)was successfully synthesized.Divergent atomic properties among Sc,Cr,and Mn(electronegativity,ionic size,and metal-oxygen bond strength)triggered pronounced electron redistribution,effectively tuning the d-band center of Co.Remarkably,Cr substitution significantly enhanced O_(4) adsorption at Co-active sites,as indicated by an elongated O-O bond length(1.234Å→1.279Å).Concurrently,Cr doping destabilized the M'-O-Cr bonds(M'=Fe,Co,Ni,Cu)and lowered the thermodynamic barrier for oxygen vacancy formation.Electrochemical tests revealed that PrSr(Fe_(0.2)Co_(0.2)Ni_(0.2)Cu_(0.2)Cr_(0.2))O_(4)(PSMO-Cr)exhibited the highest electrical conductivity and fastest oxygen surface exchange kinetics.At 700℃,the area-specific resistance(ASR)of the PSMO-Cr cathode was 0.07Ωcm^(2).Corresponding fuel cells achieved a maximum power density of 0.76 W cm^(-2).In electrolysis mode,the maximum current density reached 0.56 A cm^(-2) under 1.3 V at 700℃using PSMO-Cr as the anode.These results demonstrate that PSMO-Cr is a promising bifunctional catalyst for energy conversion applications.
基金supported by National Natural Science Foundation of China(Grant No.52171032)Hebei Natural Science Foundation(Grant No.E2023501002)Fundamental Research Funds for the Central Universities(Grant No.2024GFYD003)。
文摘High entropy alloys(HEAs)have recently attracted significant attention due to their exceptional mechanical properties and potential applications across various fields.Friction stir welding and processing(FSW/P),as notable solid-state welding and processing techniques,have been proved effectiveness in enhancing microstructures and mechanical properties of HEAs.This review article summarizes the current status of FSW/P of HEAs.The welding materials and conditions used for FSW/P in HEAs are reviewed and discussed.The effects of FSW/P on the evolutions of grain structure,texture,dislocation,and secondary phase for different HEAs are highlighted.Furthermore,the influences of FSW/P on the mechanical properties of various HEAs are analyzed.Finally,potential applications,challenges,and future directions of FSW/P in HEAs are forecasted.Overall,FSW/P enable to refine grains of HEAs through dynamic recrystallization and to activate diverse deformation mechanisms of HEAs through tailoring phase structures,thereby significantly improving the strength,hardness,and ductility of both single-and dual-phase HEAs.Future progress in this field will rely on comprehensive optimization of processing parameters and alloy composition,integration of multi-scale modeling with advanced characterization for in-depth exploration of microstructural mechanisms,systematic evaluation of functional properties,and effective bridging of the gap between laboratory research and industrial application.The review aims to provide an overview of recent advancements in the FSW/P of HEAs and encourage further research in this area.
基金supported by the National Natural Science Foundation of China(Grant No.12102133).
文摘Selective laser melting(SLM),as an additive manufacturing technology,has garnered widespread attention for its capability to fabricate components with complex geometries and to tailor the microstructure and mechanical properties under specific conditions.However,the intrinsic influence mechanism of microstructure formation under non-equilibrium solidification conditions in SLM processes has not been clearly revealed.In the present work,the influence of Al concentration and process parameters on the microstructure forming mechanism of Al_(x)CoCrFeNi HEAs prepared by SLM is investigated by molecular dynamics simulation method.The simulation results show that the difference in Al content significantly affects the microstructure formation of HEAs,including the growth rate and morphology of columnar crystals,stress distribution at grain boundaries,and defect structure.In addition,the results show that increasing the substrate temperature improves the solidification formability,reduces microstructural defects,and helps reduce residual stress in Al_(x)CoCrFeNi HEAs.By analyzing the influence of heat and solute flow in the molten pool on the growth of columnar crystals,it is found that spatial fluctuations in Al concentration during the non-equilibrium solidification process inhibit the high cooling rates induced by steep temperature gradients.These findings promote the understanding of the forming mechanism of microstructure in HEAs prepared by SLM and provide theoretical guidance for designing high-performance SLM-fabricated HEAs.
基金supported by the Australian Research Council(ARC)Projects(DP220101139,DP220101142,and LP240100542).
文摘High‐entropy amorphous catalysts(HEACs)integrate multielement synergy with structural disorder,making them promising candidates for water splitting.Their distinctive features—including flexible coordination environments,tunable electronic structures,abundant unsaturated active sites,and dynamic structural reassembly—collectively enhance electrochemical activity and durability under operating conditions.This review summarizes recent advances in HEACs for hydrogen evolution,oxygen evolution,and overall water splitting,highlighting their disorder-driven advantages over crystalline counterparts.Catalytic performance benchmarks are presented,and mechanistic insights are discussed,focusing on how multimetallic synergy,amorphization effect,and in‐situ reconstruction cooperatively regulate reaction pathways.These insights provide guidance for the rational design of next‐generation amorphous high‐entropy electrocatalysts with improved efficiency and durability.
基金partly supported by Engineering Partners Inter-national,LLC,Richfield,MN 55423(PC13803,482842-58309).
文摘Seismic resilience(SR)has emerged as a critical focus in earthquake engineering to evaluate the ability of structures to endure,recover from,and adapt to seismic events.This study presents an entropy-based multicriteria approach for selecting optimal intensity measures(IMs)to assess SR of structures.Eight representative IMs,derived from time histories and response spectrum are evaluated.Incremental dynamic analysis is con-ducted on a reinforced concrete structure,using engineering demand parameters such as the maximum interstory drift and floor acceleration to generate fragility curves via a probabilistic seismic demand model.The optimal IMs are identified through a multi-criteria decision-making process,with scores calculated using the entropy weight method to incorporate factors such as efficiency,proficiency,and uncertainty based on infor-mation entropy.An effective SR framework is derived from fragility results.The findings indicate that peak ground velocity and spectral IMs are the most effective,while energy-related IMs underestimate SR.The study highlights the importance of optimizing IMs for more accurate seismic resilience assessments.The proposed entropy-based multi-criteria approach is shown to be both reliable and effective for selecting optimal IMs in this context.
基金provided by the National Natural Science Foundation of China (No.52573275)Taishan Scholars Program of Shandong Province (No.tsqn202507205)+4 种基金Youth Innovation Team of Higher Education Institutions in Shandong Province (No.2023KJ105)Collaborative Innovation Center of Yellow River Basin Pharmaceutical Green Manufacturing and Engineering Equipment,University of Jinan,Jinan 250022,ChinaJinan City University Integration Development Strategy Project (No.JNSX2023021)supported by Talents’ plan Foundation of Guangdong Second Provincial General Hospital (No.2024D003)Science and Technology Projects in Guangzhou (No.2025A04J4629)。
文摘Conversion of ammonia into hydrogen,a crucial pathway for the hydrogen economy,is severely constrained by the intricacy of the required equipment and the low efficiency.Herein,Pd@Pt Ni Co Ru Ir coreshell mesoporous bifunctional electrocatalysts were fabricated via a one-step wet-chemical reduction approach.By utilizing the limiting effect of triblock copolymers,gradient distribution control of six metal elements(Pd core and Pt/Ni/Co/Ru/Ir high-entropy alloys shell) was achieved,where the high-entropy alloy shell forms high-density active sites through lattice distortion effect.With the help of lattice distortion and mesoporous-confinement-enabled interfacial coupling effects,Pd@Pt Ni Co Ru Ir catalyst exhibited exceptional bifunctional performance in alkaline media:A low hydrogen evolution reaction(HER) overpotential of 30.5 m V at 10 m A/cm^(2) and a high ammonia oxidation reaction(AOR) peak current density of 19.6 m A/cm^(2) at 0.7 V vs.RHE,representing a 3.83-fold enhancement over commercial Pt/C.Moreover,a rechargeable Zn-NH_(3) battery system was constructed and achieved 92.3 % Faradaic efficiency(FE) for NH_(3)-to-H_(2) conversion with outstanding stability at 16 m A/cm^(2),thereby providing an innovative solution for efficient ammonia decomposition-based hydrogen production.
基金funded by the National Basic Research Program of China(973 Program)(No.2011 CB201002)the National Natural Science Foundation of China(No.41374117)the great and special projects(2011ZX05005–005-008HZ and 2011ZX05006-002)
文摘The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time and frequency domains. To improve the resolution of the time-frequency decomposition results, we use the instantaneous frequency distribution function（IFDF） to express the seismic signal. When the instantaneous frequencies of the nonstationary signal satisfy the requirements of the uncertainty principle, the support of IFDF is just the support of the amplitude ridges in the signal obtained using the short-time Fourier transform. Based on this feature, we propose a new iteration algorithm to achieve the sparse time-frequency decomposition of the signal. The iteration algorithm uses the support of the amplitude ridges of the residual signal obtained with the short-time Fourier transform to update the time-frequency components of the signal. The summation of the updated time-frequency components in each iteration is the result of the sparse timefrequency decomposition. Numerical examples show that the proposed method improves the resolution of the time-frequency decomposition results and the accuracy of the analysis of the nonstationary signal. We also use the proposed method to attenuate the ground roll of field seismic data with good results.
基金Aeronautical Science Foundation of China (20071551016)
文摘Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.
基金The National Natural Science Foundation of China(No.61301295,61273266,61301219,61201326,61003131)the Natural Science Foundation of Anhui Province(No.1308085QF100,1408085MF113)+2 种基金the Natural Science Foundation of Jiangsu Province(No.BK20130241)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province(No.12KJB510021)the Doctoral Fund of Anhui University
文摘Some factors influencing the intelligibility of the enhanced whisper in the joint time-frequency domain are evaluated. Specifically, both the spectrum density and different regions of the enhanced spectrum are analyzed. Experimental results show that for a spectrum of some density, the joint time-frequency gain-modification based speech enhancement algorithm achieves significant improvement in intelligibility. Additionally, the spectrum region where the estimated spectrum is smaller than the clean spectrum, is the most important region contributing to intelligibility improvement for the enhanced whisper. The spectrum region where the estimated spectrum is larger than twice the size of the clean spectrum is detrimental to speech intelligibility perception within the whisper context.
