With the increasing penetration of renewable energy,the coordination of energy storage with thermal power for frequency regulation has become an effective means to enhance grid frequency security.Addressing the challe...With the increasing penetration of renewable energy,the coordination of energy storage with thermal power for frequency regulation has become an effective means to enhance grid frequency security.Addressing the challenge of improving the frequency regulation performance of a thermal-storage primary frequency regulation system while reducing its associated losses,this paper proposes a multi-dimensional cooperative optimization strategy for the control parameters of a combined thermal-storage system,considering regulation losses.First,the frequency regulation losses of various components within the thermal power unit are quantified,and a calculation method for energy storage regulation loss is proposed,based on Depth of Discharge(DOD)and C-rate.Second,a thermal-storage cooperative control method based on series compensation is developed to improve the system’s frequency regulation performance.Third,targeting system regulation loss cost and regulation output,and considering constraints on output overshoot and system parameters,an improved Particle Swarm Optimization(PSO)algorithm is employed to tune the parameters of the low-pass filter and the series compensator,thereby reducing regulation losses while enhancing performance.Finally,simulation results demonstrate that the total loss cost of the proposed control strategy is comparable to that of a system with only thermal power participation.However,the thermal power loss cost is reduced by 42.16%compared to the thermal-only case,while simultaneously improving system frequency stability.Thus,the proposed strategy effectively balances system frequency stability and economic efficiency.展开更多
Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To addre...Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To address frequency stability issues caused by low inertia and weak damping,this paper proposes a multi-timescale frequency regulation coordinated control strategy for PV-storage integrated systems.First,a self-synchronizing control strategy for grid-connected inverters is designed based on DC voltage dynamics,enabling active inertia support while transmitting frequency variation information.Next,an energy storage inertia support control strategy is developed to enhance the frequency nadir,and an active frequency support control strategy for PV system considering a frequency regulation deadband is proposed,where the deadband value is determined based on the power regulation margin of synchronous generators,allowing the PV-storage system to adaptively switch between inertia support and primary frequency regulation under different disturbance conditions.This approach ensures system frequency stability while fully leveraging the regulation capabilities of heterogeneous resources.Finally,the real-time digital simulation results of the PV-storage integrated system demonstrate that,compared to existing control methods,the proposed strategy effectively reduces the rate of change of frequency and improves the frequency nadir under various disturbance scenarios,verifying its effectiveness.展开更多
A diverse range of light and waves,spanning from near-infrared to ultraviolet,alongside ultrasound,have proven effective in propelling nanomotors.This review encapsulates the advancements in nanomotor research propell...A diverse range of light and waves,spanning from near-infrared to ultraviolet,alongside ultrasound,have proven effective in propelling nanomotors.This review encapsulates the advancements in nanomotor research propelled by waves of varying frequencies.It delves into the driving mechanisms and control methodologies of different nanomotor types,emphasizing the role of frequency.Nanomotors can be classified based on the frequency of the driving wave,encompassing ultraviolet light-driven,visible light-driven,near-infrared-driven,and ultrasounddriven variants.Each category corresponds to distinct propulsion mechanisms,including momentum transfer,photothermal effects,self-electrophoresis,and acoustic radiation force.Notably,visible light and near-infrared radiation predominantly propel momentum transfer nanomotors,while photothermal nanomotors are chiefly active within the infrared spectrum.Ultraviolet light drives most self-electrophoretic nanomotors,while ultrasound-driven nanomotors respond to acoustic radiation force.Furthermore,precise control over nanomotor speed and direction is achievable by adjusting the frequency of incident waves within a narrow range,modulating wave absorption rates.Lastly,this paper explores microwave nanomotors,an area yet to be reported,shedding light on potential driving mechanisms.展开更多
This paper studies the structural response of high-speed train wipers under the combined action of complex flow fields and scraping actions.The stress concentration areas are determined through simulation analysis,and...This paper studies the structural response of high-speed train wipers under the combined action of complex flow fields and scraping actions.The stress concentration areas are determined through simulation analysis,and the stress and aerodynamic load measurement points are reasonably arranged accordingly.The actual measurement is carried out in combination with the operating conditions of the existing lines.The stress variations and spectral characteristics of the train under different speed levels(80,160,180,200 km/h),tunnel entry and exit,and scraper action conditions were compared and analyzed.The stress amplification factors under tunnel intersection and scraper action were obtained,providing boundary conditions for the design of wipers for highspeed s.The research results show that the maximum stress of the wiper structure obtained through simulation calculation is concentrated at the connection of the wiper arm.Structural stress increases with the rise of speed grade.The stress increases by 1.11 times when the tunnel meets.When the scraper operates,the stress on the scraper arm increases by 4.1–7.6 times.Due to the broadband excitation effect of the aerodynamic load,the spectral energy of the structure is relatively high at the natural frequency,which excites the natural mode of the wiper.展开更多
Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capabili...Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capability of FH communication,the parameters such as fixed frequency interval,hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics.In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming,a heuristically accelerated Q-learning(HAQL)method is proposed in this paper.Firstly,a theoretical model for the parameter decision-making of FH system is made,and the key parameters affecting the energy efficiency of the system are analyzed.Secondly,a Q-learning model in complex electromagnetic environment is proposed,which includes setting states,actions and rewards,as well as a HAQL-based decisionmaking algorithm is put forward.Lastly,simulations are carried out under different jamming environments,and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm,the e-greedy QL algorithm and the HQL-OSGM algorithm,respectively.展开更多
When the converter bus voltage of a voltage source converter-based high voltage direct current(VSC-HVDC)system drops below a certain predetermined threshold,the system enters low-voltage ride-through(LVRT)mode to avoi...When the converter bus voltage of a voltage source converter-based high voltage direct current(VSC-HVDC)system drops below a certain predetermined threshold,the system enters low-voltage ride-through(LVRT)mode to avoid overcurrent and potential equipment failure,during which it operates as a controlled current source.The influence mechanism of LVRT control strategies on short-circuit current and overall system stability remains not yet fully and systematically investigated.First,this paper provides an overview of several LVRT strategies for VSC-HVDC systems and examines their effects on short-circuit current contribution.Next,it analyzes in detail the mechanisms through which active and reactive currents injected during LVRT impact system frequency stability,voltage stability,and synchronization stability.To address these interrelated issues,an optimized and comprehensive LVRT strategy incorporating short-circuit current constraints is proposed.The approach determines the active current ratio based on system frequency stability requirements and dynamically adjusts the active current recovery rate via phase control of the VSC-HVDC bus.The remaining capacity is allocated to reactive current support,thereby enhancing voltage and synchronization stability while maintaining sufficient short-circuit current margin and system frequency stability.Finally,simulations conducted on the PSS/E platform,using actual grid data from a selected cross-section system,validate convincingly the effectiveness of the proposed parameter optimization strategy for VSC-HVDC low-voltage ride-through.展开更多
Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blas...Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blasting,blasting,tunnel boring machine(TBM)vibration,rockburst wave,earthquakes.Specifically,these dynamic sources are characterized by a wide range of wave frequencies f,resulting in differences in failure modes.A series of true-triaxial compression tests were conducted on granite to simulate the excavation-induced stress path in three-dimensional(3D)stresses.Subsequently,a dynamic disturbance with various frequencies was applied to a cuboid specimen,to reveal the behavior associated with brittle failure.The dynamic disturbance with frequencies f of 5 Hz,10 Hz,and 40 Hz generates less disturbed energy components in the granite together with higher peak strength.However,dynamic disturbances with f of 20 Hz and 30 Hz resulted in a lower peak strength;the peak strength of the rock increases sp albeit it decreases at first,then increases.This U-shaped phenomenon relates to the natural frequency of the granite under such stress conditions.Different rock lithologies consisting of diverse mineral composition,respond differently to each sensitive resonance frequency.Interestingly,the weak disturbance stress with a high frequency f and low amplitude A increases the ratio of crack damage to peak strength(scd/sp)in the granite.This leads to the inhibition of the expansion of the granite during the dynamic disturbance process.Multiple penetrating tensileeshear cracks appear in the s3-direction as the disturbance frequency f increases.展开更多
This paper presents a programmable frequency scan algorithm based on harmonic balance.The core idea involves treating systems under perturbation as nonlinear time-periodic(NTP)systems.Steady-state harmonics are first ...This paper presents a programmable frequency scan algorithm based on harmonic balance.The core idea involves treating systems under perturbation as nonlinear time-periodic(NTP)systems.Steady-state harmonics are first solved via Newton-Raphson iteration through a set of nonlinear equations,and then input-output variables are selected to estimate the linear transfer function of the original NTP system without perturbations.The applications and insights of the proposed algorithm are discussed,particularly in guiding existing frequency scan algorithms,which are restricted by time-domain signal generation or measurement.This improvement is achieved through linear stability analysis of NTP systems with perturbations.展开更多
The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,t...The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,the carrier frequency offset(CFO)stands out as a primary RF fingerprint(RFF)of the transmitter,offering the potential to distinguish among different transmitters.However,accurately estimating CFO in time-varying channels poses significant challenges due to multipath effects and Doppler shifts.In this paper,we focus on estimating CFO for wireless device identification in the orthogonal frequency division multiplexing(OFDM)communication system.To achieve precise CFO estimation under time-varying channels,we propose a frequency domain correlation and spline interpolation(FCSI)algorithm.This approach utilizes pilots distributed across different subcarriers to correlate with prior local sequences,facilitating accurate CFO estimation.Classification is then performed based on the Euclidean distance between the prior RFF and the tested RFF dataset.Simulation results demonstrate that the proposed Mconsecutive average method effectively reduces the classification error rate in the challenging high-frequency(HF)skywave channel environment.展开更多
In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,eff...In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).展开更多
This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loo...This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.展开更多
Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learni...Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.展开更多
Ground penetrating radar(GPR)offers a rapid and non-destructive approach to evaluating asphalt mixtures by capturing variations in their dielectric constant.As a critical electromagnetic parameter,the dielectric const...Ground penetrating radar(GPR)offers a rapid and non-destructive approach to evaluating asphalt mixtures by capturing variations in their dielectric constant.As a critical electromagnetic parameter,the dielectric constant demonstrates significant potential for assessing the material composition and mechanical properties of asphalt mixtures.However,the relationship between the dielectric constant and mechanical properties remains unclear.To investigate the factors affecting the dielectric constant and its correlation with the mechanical properties of asphalt mixtures,a systematic analysis of the influencing parameters was conducted.Fitting equations were established to quantify the relationships between the dielectric constant and mechanical properties.Firstly,the effects of compaction state,testing frequency,and testing temperature on the dielectric constant were evaluated.Subsequently,forward simulations of GPR were executed on asphalt pavements with diverse air voids and detection frequencies.Finally,a fitting analysis was performed to determine the correlation between the dielectric constant and the dynamic modulus,compressive strength,and splitting tensile strength.The results indicated that the dielectric constant increased with the compaction state,decreased with increasing testing frequency until stabilized,and was insignificantly affected by changes in testing temperature.The change of air void in asphalt pavement has significantly affected the amplitude and timing of electromagnetic wave reflection.A linear positive correlation was identified between the dielectric constant and dynamic modulus as well as compressive strength,while a quadratic positive correlation existed with splitting tensile strength.This study provided theoretical and practical foundations for enhancing the reliability and accuracy of non-destructive testing in asphalt pavement.展开更多
Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater imag...Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater image enhancement methods,although they can improve the image quality to some extent,often lead to problems such as detail loss and edge blurring.To address these problems,we propose FENet,an efficient underwater image enhancement method.FENet first obtains three different scales of images by image downsampling and then transforms them into the frequency domain to extract the low-frequency and high-frequency spectra,respectively.Then,a distance mask and a mean mask are constructed based on the distance and magnitude mean for enhancing the high-frequency part,thus improving the image details and enhancing the effect by suppressing the noise in the low-frequency part.Affected by the light scattering of underwater images and the fact that some details are lost if they are directly reduced to the spatial domain after the frequency domain operation.For this reason,we propose a multi-stage residual feature aggregation module,which focuses on detail extraction and effectively avoids information loss caused by global enhancement.Finally,we combine the edge guidance strategy to further enhance the edge details of the image.Experimental results indicate that FENet outperforms current state-of-the-art underwater image enhancement methods in quantitative and qualitative evaluations on multiple publicly available datasets.展开更多
This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher ope...This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.展开更多
Understanding how rock slopes respond to blasting loads is crucial for maintaining excavation safety and slope stability.Nevertheless,the spatiotemporal evolution,nonlinear dependence on blasting parameters,and predic...Understanding how rock slopes respond to blasting loads is crucial for maintaining excavation safety and slope stability.Nevertheless,the spatiotemporal evolution,nonlinear dependence on blasting parameters,and predictive behavior of dominant frequency responses in slope vibrations remain insufficiently understood and quantified.This study combines time-frequency analysis with machine learning to explore how the dominant frequency(f_(d))evolves in slopes under blasting.Continuous Wavelet Transform(CWT)was employed to characterize the temporal-frequency evolution of vibration signals,revealing that the dominant frequency exhibits strong spatial dependence and nonlinear variability influenced by blasting parameters and rock mass structures.Three machine learning models,namely Back Propagation Neural Network(BP),Support Vector Machine(SVM),and Random Forest(RF),were developed to predict f_(d) based on 1,000 monitoring samples obtained from numerical and field simulations.Among them,the RF model achieved the highest prediction accuracy,with mean absolute percentage errors(MAPE)below 15%,demonstrating strong robustness and generalization capability.Our analysis shows that external excitation factors,especially the loading frequency(f_(d)),mainly control the frequency response,while internal controlling factors,such as spatial position,lithological variation,and mechanical heterogeneity,modulate localized frequency amplification and energy redistribution.The results reveal that f_(d) tends to decrease with elevation and distance from the blasting source,whereas structural planes and weathered zones induce high-frequency amplification due to scattering and modal coupling effects.This study offers a new framework combining time-frequency analysis and machine learning to measure the nonlinear interaction between blasting and rock mass response,offering new insights for dynamic stability evaluation and hazard mitigation in complex rock slope systems.展开更多
Take care of your hair to help it stay clean,strong and healthy.Wash your hair when it gets dirty,but not too often.For most people,that means every two to three days.People with oily hair wash it every one to two day...Take care of your hair to help it stay clean,strong and healthy.Wash your hair when it gets dirty,but not too often.For most people,that means every two to three days.People with oily hair wash it every one to two days.Use a brush or comb to keep your hair neat and smooth.It's also important to be gentle so you don't pull or break your hair.Never go to bed with wet hair.It can break easily when you sleep.Dry it before bed!展开更多
Objective: To develop an evidence-based plan for cleaning operating room and evaluate the impact on high-frequency contact surfaces. Method: The evidence application model of the JBI Evidence-Based Nursing Center was ...Objective: To develop an evidence-based plan for cleaning operating room and evaluate the impact on high-frequency contact surfaces. Method: The evidence application model of the JBI Evidence-Based Nursing Center was utilized to create a strategy, which was implemented in a tertiary-level hospital in Yunnan Province. The adenosine triphosphate (ATP) biological biofluorescence detection method was used to assess the quality of cleaning before and after the intervention. Results: A total of 17 quality review indicators were established in this study. Following the application of evidence, the implementation rate for 16 quality review indicators increased significantly, from a range of 0-65.8% to 81.5-100%. Moreover, the pass rate of ATP bioluminescence detection on high-frequency contact surfaces increased from 14.07% to 47.19%, with significant difference (p < 0.05). Conclusion: The evidence-based environmental cleaning program proved to enhance the overall cleanliness of operating room and reduce the risk of surgical infections. This strategy holds promise for effective cleaning of operating room.展开更多
The large-scale integration of power electronic interface-based renewable energy with intermittency and uncertainty poses severe challenges for power system secure operation,especially frequency security.Determining t...The large-scale integration of power electronic interface-based renewable energy with intermittency and uncertainty poses severe challenges for power system secure operation,especially frequency security.Determining the system frequency regulation ability under contingency is an open problem.To bridge this gap,a unit commitment(UC)to concentrate solar power considering operational risk and frequency dynamic constraints(RFUC-CSP)is proposed in this paper.A concentrating solar power(CSP)plant with renewable energy characteristics and synchronous units is employed to improve renewable energy utilization and provide frequency support.Firstly,an analytical operational risk model is established to quantify the operational risk under renewable energy integration.Then,the frequency dynamic response characteristic of the system is considered to construct frequency security constraints.A novel RFUC-CSP framework is formulated by incorporating operational risk and frequency security constraints into the UC model,which can allocate operational flexibility of power systems by optimizing the admissible uncertainty level to reduce operational risk.The effectiveness of the proposed RFUC-CSP model is demonstrated by case studies on the modified IEEE 30-bus and IEEE RTS-79 system,and the cost-effectiveness of the CSP plant is quantified.展开更多
基金supported by the Science and Technology Development Project of Jilin Province(Project No.YDZJ202301ZYTS284).
文摘With the increasing penetration of renewable energy,the coordination of energy storage with thermal power for frequency regulation has become an effective means to enhance grid frequency security.Addressing the challenge of improving the frequency regulation performance of a thermal-storage primary frequency regulation system while reducing its associated losses,this paper proposes a multi-dimensional cooperative optimization strategy for the control parameters of a combined thermal-storage system,considering regulation losses.First,the frequency regulation losses of various components within the thermal power unit are quantified,and a calculation method for energy storage regulation loss is proposed,based on Depth of Discharge(DOD)and C-rate.Second,a thermal-storage cooperative control method based on series compensation is developed to improve the system’s frequency regulation performance.Third,targeting system regulation loss cost and regulation output,and considering constraints on output overshoot and system parameters,an improved Particle Swarm Optimization(PSO)algorithm is employed to tune the parameters of the low-pass filter and the series compensator,thereby reducing regulation losses while enhancing performance.Finally,simulation results demonstrate that the total loss cost of the proposed control strategy is comparable to that of a system with only thermal power participation.However,the thermal power loss cost is reduced by 42.16%compared to the thermal-only case,while simultaneously improving system frequency stability.Thus,the proposed strategy effectively balances system frequency stability and economic efficiency.
基金supported by the State Grid Corporation of China under Grant for Science and Technology Projects(No.SGNXJYOOZWJS2500029).
文摘Energy storage-equipped photovoltaic(PV-storage)systems can meet frequency regulation requirements under various operating conditions,and their coordinated support for grid frequency has become a future trend.To address frequency stability issues caused by low inertia and weak damping,this paper proposes a multi-timescale frequency regulation coordinated control strategy for PV-storage integrated systems.First,a self-synchronizing control strategy for grid-connected inverters is designed based on DC voltage dynamics,enabling active inertia support while transmitting frequency variation information.Next,an energy storage inertia support control strategy is developed to enhance the frequency nadir,and an active frequency support control strategy for PV system considering a frequency regulation deadband is proposed,where the deadband value is determined based on the power regulation margin of synchronous generators,allowing the PV-storage system to adaptively switch between inertia support and primary frequency regulation under different disturbance conditions.This approach ensures system frequency stability while fully leveraging the regulation capabilities of heterogeneous resources.Finally,the real-time digital simulation results of the PV-storage integrated system demonstrate that,compared to existing control methods,the proposed strategy effectively reduces the rate of change of frequency and improves the frequency nadir under various disturbance scenarios,verifying its effectiveness.
基金supported by the National Key Research and Development Program of China(2021YFA1401103)the National Natural Science Foundation of China(52473109,52073071)+3 种基金China Scholarship Council(CSC)(202306790056)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX22_2301)111 Project(B23008)the Innovative Leading Talent Team supported by 2022Wuxi Taihu Talent Program(1096010241230120)。
文摘A diverse range of light and waves,spanning from near-infrared to ultraviolet,alongside ultrasound,have proven effective in propelling nanomotors.This review encapsulates the advancements in nanomotor research propelled by waves of varying frequencies.It delves into the driving mechanisms and control methodologies of different nanomotor types,emphasizing the role of frequency.Nanomotors can be classified based on the frequency of the driving wave,encompassing ultraviolet light-driven,visible light-driven,near-infrared-driven,and ultrasounddriven variants.Each category corresponds to distinct propulsion mechanisms,including momentum transfer,photothermal effects,self-electrophoresis,and acoustic radiation force.Notably,visible light and near-infrared radiation predominantly propel momentum transfer nanomotors,while photothermal nanomotors are chiefly active within the infrared spectrum.Ultraviolet light drives most self-electrophoretic nanomotors,while ultrasound-driven nanomotors respond to acoustic radiation force.Furthermore,precise control over nanomotor speed and direction is achievable by adjusting the frequency of incident waves within a narrow range,modulating wave absorption rates.Lastly,this paper explores microwave nanomotors,an area yet to be reported,shedding light on potential driving mechanisms.
文摘This paper studies the structural response of high-speed train wipers under the combined action of complex flow fields and scraping actions.The stress concentration areas are determined through simulation analysis,and the stress and aerodynamic load measurement points are reasonably arranged accordingly.The actual measurement is carried out in combination with the operating conditions of the existing lines.The stress variations and spectral characteristics of the train under different speed levels(80,160,180,200 km/h),tunnel entry and exit,and scraper action conditions were compared and analyzed.The stress amplification factors under tunnel intersection and scraper action were obtained,providing boundary conditions for the design of wipers for highspeed s.The research results show that the maximum stress of the wiper structure obtained through simulation calculation is concentrated at the connection of the wiper arm.Structural stress increases with the rise of speed grade.The stress increases by 1.11 times when the tunnel meets.When the scraper operates,the stress on the scraper arm increases by 4.1–7.6 times.Due to the broadband excitation effect of the aerodynamic load,the spectral energy of the structure is relatively high at the natural frequency,which excites the natural mode of the wiper.
基金State Key Program of National Natural Science of China under grant nos.U19B2016。
文摘Frequency hopping(FH)communication has good anti-fading,anti-jamming and anti-eavesdropping capabilities,so it is one of the main ways to combat electronic jamming.In order to further improve the anti-jamming capability of FH communication,the parameters such as fixed frequency interval,hopping rate and hopping frequency in conventional FH can be assigned with time-varying characteristics.In order to set appropriate hopping parameters to improve the performance of the system in the electromagnetic environment with various types of jamming,a heuristically accelerated Q-learning(HAQL)method is proposed in this paper.Firstly,a theoretical model for the parameter decision-making of FH system is made,and the key parameters affecting the energy efficiency of the system are analyzed.Secondly,a Q-learning model in complex electromagnetic environment is proposed,which includes setting states,actions and rewards,as well as a HAQL-based decisionmaking algorithm is put forward.Lastly,simulations are carried out under different jamming environments,and simulation results show that the average energy efficiency of HAQL algorithm is higher than that of the SARSA algorithm,the e-greedy QL algorithm and the HQL-OSGM algorithm,respectively.
基金funded by State Grid Corporation of China,grant number DQ30DK24001L。
文摘When the converter bus voltage of a voltage source converter-based high voltage direct current(VSC-HVDC)system drops below a certain predetermined threshold,the system enters low-voltage ride-through(LVRT)mode to avoid overcurrent and potential equipment failure,during which it operates as a controlled current source.The influence mechanism of LVRT control strategies on short-circuit current and overall system stability remains not yet fully and systematically investigated.First,this paper provides an overview of several LVRT strategies for VSC-HVDC systems and examines their effects on short-circuit current contribution.Next,it analyzes in detail the mechanisms through which active and reactive currents injected during LVRT impact system frequency stability,voltage stability,and synchronization stability.To address these interrelated issues,an optimized and comprehensive LVRT strategy incorporating short-circuit current constraints is proposed.The approach determines the active current ratio based on system frequency stability requirements and dynamically adjusts the active current recovery rate via phase control of the VSC-HVDC bus.The remaining capacity is allocated to reactive current support,thereby enhancing voltage and synchronization stability while maintaining sufficient short-circuit current margin and system frequency stability.Finally,simulations conducted on the PSS/E platform,using actual grid data from a selected cross-section system,validate convincingly the effectiveness of the proposed parameter optimization strategy for VSC-HVDC low-voltage ride-through.
基金supported by the National Natural Science Foundation of China(Grant Nos.52222810 and 52178383).
文摘Dynamic disturbances with various frequencies could trigger different failure modes of deep excavations.Superimposed on this static stress are dynamic disturbances due to various dynamic vibrations,e.g.excavation blasting,blasting,tunnel boring machine(TBM)vibration,rockburst wave,earthquakes.Specifically,these dynamic sources are characterized by a wide range of wave frequencies f,resulting in differences in failure modes.A series of true-triaxial compression tests were conducted on granite to simulate the excavation-induced stress path in three-dimensional(3D)stresses.Subsequently,a dynamic disturbance with various frequencies was applied to a cuboid specimen,to reveal the behavior associated with brittle failure.The dynamic disturbance with frequencies f of 5 Hz,10 Hz,and 40 Hz generates less disturbed energy components in the granite together with higher peak strength.However,dynamic disturbances with f of 20 Hz and 30 Hz resulted in a lower peak strength;the peak strength of the rock increases sp albeit it decreases at first,then increases.This U-shaped phenomenon relates to the natural frequency of the granite under such stress conditions.Different rock lithologies consisting of diverse mineral composition,respond differently to each sensitive resonance frequency.Interestingly,the weak disturbance stress with a high frequency f and low amplitude A increases the ratio of crack damage to peak strength(scd/sp)in the granite.This leads to the inhibition of the expansion of the granite during the dynamic disturbance process.Multiple penetrating tensileeshear cracks appear in the s3-direction as the disturbance frequency f increases.
基金supported by China Southern Power Grid Corporation(036000KC23090005(GDKJXM20231027)).
文摘This paper presents a programmable frequency scan algorithm based on harmonic balance.The core idea involves treating systems under perturbation as nonlinear time-periodic(NTP)systems.Steady-state harmonics are first solved via Newton-Raphson iteration through a set of nonlinear equations,and then input-output variables are selected to estimate the linear transfer function of the original NTP system without perturbations.The applications and insights of the proposed algorithm are discussed,particularly in guiding existing frequency scan algorithms,which are restricted by time-domain signal generation or measurement.This improvement is achieved through linear stability analysis of NTP systems with perturbations.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20240723011National Natural Science Foundation of China under Grant No.62371123+1 种基金Young Elite Scientists Sponsorship Program of the Beijing High Innovation Plan under Grant No.20251077Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2023A03。
文摘The radio frequency(RF)fingerprint technique is a robust method for security enhancement of the physical layer by leveraging the unique RF imperfections inherent in various wireless devices.Among these imperfections,the carrier frequency offset(CFO)stands out as a primary RF fingerprint(RFF)of the transmitter,offering the potential to distinguish among different transmitters.However,accurately estimating CFO in time-varying channels poses significant challenges due to multipath effects and Doppler shifts.In this paper,we focus on estimating CFO for wireless device identification in the orthogonal frequency division multiplexing(OFDM)communication system.To achieve precise CFO estimation under time-varying channels,we propose a frequency domain correlation and spline interpolation(FCSI)algorithm.This approach utilizes pilots distributed across different subcarriers to correlate with prior local sequences,facilitating accurate CFO estimation.Classification is then performed based on the Euclidean distance between the prior RFF and the tested RFF dataset.Simulation results demonstrate that the proposed Mconsecutive average method effectively reduces the classification error rate in the challenging high-frequency(HF)skywave channel environment.
基金funded by Anhui Province University Key Science and Technology Project(2024AH053415)Anhui Province University Major Science and Technology Project(2024AH040229)+3 种基金Talent Research Initiation Fund Project of Tongling University(2024tlxyrc019)Tongling University School-Level Scientific Research Project(2024tlxyptZD07)TheUniversity Synergy Innovation Programof Anhui Province(GXXT-2023-050)Tongling City Science and Technology Major Special Project(Unveiling and Commanding Model)(200401JB004).
文摘In the image fusion field,fusing infrared images(IRIs)and visible images(VIs)excelled is a key area.The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image.Accordingly,efficiently combining the advantages of both images while overcoming their shortcomings is necessary.To handle this challenge,we developed an end-to-end IRI andVI fusionmethod based on frequency decomposition and enhancement.By applying concepts from frequency domain analysis,we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information from the VIs,respectively,significantly boosting the image fusion quality and effectiveness.In addition,the backbone network combined Restormer Blocks and Dense Blocks;Restormer blocks utilize global attention to extract shallow features.Meanwhile,Dense Blocks ensure the integration between shallow and deep features,thereby avoiding the loss of shallow attributes.Extensive experiments on TNO and MSRS datasets demonstrated that the suggested method achieved state-of-the-art(SOTA)performance in various metrics:Entropy(EN),Mutual Information(MI),Standard Deviation(SD),The Structural Similarity Index Measure(SSIM),Fusion quality(Qabf),MI of the pixel(FMI_(pixel)),and modified Visual Information Fidelity(VIF_(m)).
文摘This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.
基金supported in part by the National Natural Science Foundation of China(62472146)the Key Technologies Research Development Joint Foundation of Henan Province of China(225101610001)。
文摘Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.
基金supported by the Major Program of Xiangjiang Laboratory(No.22XJ01009)National Natural Science Foundation of China(Grant Nos.52227815,52078065,and 52178414)the Postgraduate Scientific Research Innovation Project of Hunan Province(Nos.CX20230852 and CX20230848).
文摘Ground penetrating radar(GPR)offers a rapid and non-destructive approach to evaluating asphalt mixtures by capturing variations in their dielectric constant.As a critical electromagnetic parameter,the dielectric constant demonstrates significant potential for assessing the material composition and mechanical properties of asphalt mixtures.However,the relationship between the dielectric constant and mechanical properties remains unclear.To investigate the factors affecting the dielectric constant and its correlation with the mechanical properties of asphalt mixtures,a systematic analysis of the influencing parameters was conducted.Fitting equations were established to quantify the relationships between the dielectric constant and mechanical properties.Firstly,the effects of compaction state,testing frequency,and testing temperature on the dielectric constant were evaluated.Subsequently,forward simulations of GPR were executed on asphalt pavements with diverse air voids and detection frequencies.Finally,a fitting analysis was performed to determine the correlation between the dielectric constant and the dynamic modulus,compressive strength,and splitting tensile strength.The results indicated that the dielectric constant increased with the compaction state,decreased with increasing testing frequency until stabilized,and was insignificantly affected by changes in testing temperature.The change of air void in asphalt pavement has significantly affected the amplitude and timing of electromagnetic wave reflection.A linear positive correlation was identified between the dielectric constant and dynamic modulus as well as compressive strength,while a quadratic positive correlation existed with splitting tensile strength.This study provided theoretical and practical foundations for enhancing the reliability and accuracy of non-destructive testing in asphalt pavement.
基金supported in part by the National Natural Science Foundation of China[Grant number 62471075]the Major Science and Technology Project Grant of the Chongqing Municipal Education Commission[Grant number KJZD-M202301901].
文摘Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater image enhancement methods,although they can improve the image quality to some extent,often lead to problems such as detail loss and edge blurring.To address these problems,we propose FENet,an efficient underwater image enhancement method.FENet first obtains three different scales of images by image downsampling and then transforms them into the frequency domain to extract the low-frequency and high-frequency spectra,respectively.Then,a distance mask and a mean mask are constructed based on the distance and magnitude mean for enhancing the high-frequency part,thus improving the image details and enhancing the effect by suppressing the noise in the low-frequency part.Affected by the light scattering of underwater images and the fact that some details are lost if they are directly reduced to the spatial domain after the frequency domain operation.For this reason,we propose a multi-stage residual feature aggregation module,which focuses on detail extraction and effectively avoids information loss caused by global enhancement.Finally,we combine the edge guidance strategy to further enhance the edge details of the image.Experimental results indicate that FENet outperforms current state-of-the-art underwater image enhancement methods in quantitative and qualitative evaluations on multiple publicly available datasets.
基金sponsored by the National Natural Science Foundation of China(Grant No.52438002)the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘This study investigates the influence of loading frequency on the fatigue behavior of ballastless track concrete for high-speed railways,aiming to support the development of concrete capable of withstanding higher operational speeds.Fatigue tests were conducted at loading frequencies ranging from 5 to 40 Hz,with a focus on fatigue life,damage evolution,energy dissipation,and residual fatigue strain in the concrete.The results indicate that between 5 and 15 Hz,the fatigue life and energy dissipation remain relatively stable,with minimal damage evolution and small residual strains.As the frequency increases to 15-20 Hz,the fatigue life and energy dissipation gradually decrease,while damage accumulation and residual strain increase.Beyond 20 Hz,both fatigue life and energy dissipation decrease rapidly,damage accumulation becomes more pronounced,and residual strain continues to rise.These phenomena are primarily attributed to the increased strain rate and load change rate at higher frequencies,which affect the microstructure evolution and lead to reduced fatigue performance.
基金supported by the National Natural Science Foundation of China(Grant Nos.52379098,52274075)the Project of Xingliao Talents Program(XLYC2203008)the Science and Technology Program Project of Liaoning Province(2025JH2/101900011).
文摘Understanding how rock slopes respond to blasting loads is crucial for maintaining excavation safety and slope stability.Nevertheless,the spatiotemporal evolution,nonlinear dependence on blasting parameters,and predictive behavior of dominant frequency responses in slope vibrations remain insufficiently understood and quantified.This study combines time-frequency analysis with machine learning to explore how the dominant frequency(f_(d))evolves in slopes under blasting.Continuous Wavelet Transform(CWT)was employed to characterize the temporal-frequency evolution of vibration signals,revealing that the dominant frequency exhibits strong spatial dependence and nonlinear variability influenced by blasting parameters and rock mass structures.Three machine learning models,namely Back Propagation Neural Network(BP),Support Vector Machine(SVM),and Random Forest(RF),were developed to predict f_(d) based on 1,000 monitoring samples obtained from numerical and field simulations.Among them,the RF model achieved the highest prediction accuracy,with mean absolute percentage errors(MAPE)below 15%,demonstrating strong robustness and generalization capability.Our analysis shows that external excitation factors,especially the loading frequency(f_(d)),mainly control the frequency response,while internal controlling factors,such as spatial position,lithological variation,and mechanical heterogeneity,modulate localized frequency amplification and energy redistribution.The results reveal that f_(d) tends to decrease with elevation and distance from the blasting source,whereas structural planes and weathered zones induce high-frequency amplification due to scattering and modal coupling effects.This study offers a new framework combining time-frequency analysis and machine learning to measure the nonlinear interaction between blasting and rock mass response,offering new insights for dynamic stability evaluation and hazard mitigation in complex rock slope systems.
文摘Take care of your hair to help it stay clean,strong and healthy.Wash your hair when it gets dirty,but not too often.For most people,that means every two to three days.People with oily hair wash it every one to two days.Use a brush or comb to keep your hair neat and smooth.It's also important to be gentle so you don't pull or break your hair.Never go to bed with wet hair.It can break easily when you sleep.Dry it before bed!
文摘Objective: To develop an evidence-based plan for cleaning operating room and evaluate the impact on high-frequency contact surfaces. Method: The evidence application model of the JBI Evidence-Based Nursing Center was utilized to create a strategy, which was implemented in a tertiary-level hospital in Yunnan Province. The adenosine triphosphate (ATP) biological biofluorescence detection method was used to assess the quality of cleaning before and after the intervention. Results: A total of 17 quality review indicators were established in this study. Following the application of evidence, the implementation rate for 16 quality review indicators increased significantly, from a range of 0-65.8% to 81.5-100%. Moreover, the pass rate of ATP bioluminescence detection on high-frequency contact surfaces increased from 14.07% to 47.19%, with significant difference (p < 0.05). Conclusion: The evidence-based environmental cleaning program proved to enhance the overall cleanliness of operating room and reduce the risk of surgical infections. This strategy holds promise for effective cleaning of operating room.
基金supported by the National Natural Science Foundation of China General Program(No.52277106)the Project funded by China Postdoctoral Science Foundation(No.2022M721773).
文摘The large-scale integration of power electronic interface-based renewable energy with intermittency and uncertainty poses severe challenges for power system secure operation,especially frequency security.Determining the system frequency regulation ability under contingency is an open problem.To bridge this gap,a unit commitment(UC)to concentrate solar power considering operational risk and frequency dynamic constraints(RFUC-CSP)is proposed in this paper.A concentrating solar power(CSP)plant with renewable energy characteristics and synchronous units is employed to improve renewable energy utilization and provide frequency support.Firstly,an analytical operational risk model is established to quantify the operational risk under renewable energy integration.Then,the frequency dynamic response characteristic of the system is considered to construct frequency security constraints.A novel RFUC-CSP framework is formulated by incorporating operational risk and frequency security constraints into the UC model,which can allocate operational flexibility of power systems by optimizing the admissible uncertainty level to reduce operational risk.The effectiveness of the proposed RFUC-CSP model is demonstrated by case studies on the modified IEEE 30-bus and IEEE RTS-79 system,and the cost-effectiveness of the CSP plant is quantified.
