The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sus...The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sustained combustion,which can easily lead to serious electrical fire accidents.To address this issue,this paper establishes a fault arc prototype experimental platform,selects multiple commonly used loads for fault arc experiments,and collects data in both normal and fault states.By analyzing waveform characteristics and selecting fault discrimination feature indicators,corresponding feature values are extracted for qualitative analysis to explore changes in timefrequency characteristics of current before and after faults.Multiple features are then selected to form a multidimensional feature vector space to effectively reduce arc misjudgments and construct a fault discrimination feature database.Based on this,a fault arc hazard prediction model is built using random forests.The model’s multiple hyperparameters are simultaneously optimized through grid search,aiming tominimize node information entropy and complete model training,thereby enhancing model robustness and generalization ability.Through experimental verification,the proposed method accurately predicts and classifies fault arcs of different load types,with an average accuracy at least 1%higher than that of the commonly used fault predictionmethods compared in the paper.展开更多
Against the backdrop of new quality productivity driving high-quality economic development,this paper examines how technological innovation,digital transformation,and green development reshape the competencies and tra...Against the backdrop of new quality productivity driving high-quality economic development,this paper examines how technological innovation,digital transformation,and green development reshape the competencies and training models of highly skilled talent.It analyzes multidimensional characteristics,including knowledge structure,innovation awareness,digital literacy,and cross-boundary collaboration,revealing a shift towards“innovative,composite,and intelligent”profiles.The study identifies misalignments in current vocational education,such as outdated curricula and insufficient industry-education integration.It proposes innovative training paths,including deep industry-education collaboration,digital-intelligent teaching,and lifelong learning ecosystems.Case studies validate the feasibility of aligning talent development with new quality productivity demands.展开更多
In order to study the time-frequency characteristics of blasting vibration signals, measured in milliseconds, we carried out site blasting vibration tests at an open pit of the Jinduicheng Mine. Based on recorded fiel...In order to study the time-frequency characteristics of blasting vibration signals, measured in milliseconds, we carried out site blasting vibration tests at an open pit of the Jinduicheng Mine. Based on recorded field data and applying a combination of RSPWVD and wavelet, we analyzed the time-fre- quency characteristics of recorded field data, summarized the time-frequency characteristics of blasting vibration signals in different frequency bands and present detailed information of blasting vibration sig- nals in milliseconds of high time-frequency resolutions. Because RSPWVD can be seen as of definite physical significance to signal energy distribution in time and frequency domains, we studied the energy distribution of blasting vibration signals for various milliseconds intervals from a perspective of energy distribution. The results indicate that the effect of milliseconds intervals on time-frequency characteris- tics of blasting vibration signals is significant; the length of delay time directly affects the energy distri- bution of blasting vibration signals as well as the duration of energy in ffeauencv bands.展开更多
Through analyzing the near-field hydrophone records of the airgun experiment in the Jiemian reservoir,Fujian,we study the time-frequency characteristic of airgun source wavelet and the influence of gun depth and firin...Through analyzing the near-field hydrophone records of the airgun experiment in the Jiemian reservoir,Fujian,we study the time-frequency characteristic of airgun source wavelet and the influence of gun depth and firing pressure,and explain the process of bubble oscillation based on the Johnson( 1994) bubble model. The data analysis shows that:( 1) Airgun wavelet is composed of primary pulse and bubble pulse. The primary pulse,which is of large amplitude,short duration and wide frequency band,is usually used in shallow exploration. The bubble pulse,which is concentrated in the low-frequency range,is usually used in deep exploration with deep vertical penetration and far horizontal propagation.( 2) The variation of primary pulse amplitude with gun depth is very small,bubble pulse amplitude and the dominant frequency increase,and peak-bubble ratio and bubble period decrease. When the gun depth is 10 m,primary pulse amplitude and peakbubble ratio are maximum,which is suitable for shallow exploration; when gun depth is25 m,bubble pulse amplitude is large, and peak-bubble ratio is minimum, which is suitable for deep exploration.( 3) The primary pulse amplitude,bubble pulse amplitude,peak-bubble ratio,and bubble period increase and the dominant frequency decreases with increased firing pressure.展开更多
According to the Chapman multi-scale rock physical model, the seismic response characteristics vary for different fluid-saturated reservoirs. For class I AVO reservoirs and gas-saturation, the seismic response is a hi...According to the Chapman multi-scale rock physical model, the seismic response characteristics vary for different fluid-saturated reservoirs. For class I AVO reservoirs and gas-saturation, the seismic response is a high-frequency bright spot as the amplitude energy shifts. However, it is a low-frequency shadow for the Class III AVO reservoirs saturated with hydrocarbons. In this paper, we verified the high-frequency bright spot results of Chapman for the Class I AVO response using the frequency-dependent analysis of a physical model dataset. The physical model is designed as inter-bedded thin sand and shale based on real field geology parameters. We observed two datasets using fixed offset and 2D geometry with different fluid- saturated conditions. Spectral and time-frequency analyses methods are applied to the seismic datasets to describe the response characteristics for gas-, water-, and oil-saturation. The results of physical model dataset processing and analysis indicate that reflection wave tuning and fluid-related dispersion are the main seismic response characteristic mechanisms. Additionally, the gas saturation model can be distinguished from water and oil saturation for Class I AVO utilizing the frequency-dependent abnormal characteristic. The frequency-dependent characteristic analysis of the physical model dataset verified the different spectral response characteristics corresponding to the different fluid-saturated models. Therefore, by careful analysis of real field seismic data, we can obtain the abnormal spectral characteristics induced by the fluid variation and implement fluid detection using seismic data directly.展开更多
Quantitative relationship between nanosecond pulsed laser parameters and the characteristics of laser-generated ultrasonic waves in polycrystalline materials was evaluated.The high energy of the pulsed laser with a la...Quantitative relationship between nanosecond pulsed laser parameters and the characteristics of laser-generated ultrasonic waves in polycrystalline materials was evaluated.The high energy of the pulsed laser with a large irradiation spot simultaneously generated ultrasonic longitudinal and shear waves at the epicenter under the slight ablation regime.An optimized denoising technique based on wavelet thresholding and variational mode decomposition was applied to reduce noise in shear waves with a low signal-to-noise ratio.An approach for characterizing grain size was proposed using spectral central frequency ratio(SCFR)based on time-frequency analysis.The results demonstrate that the generation regime of ultrasonic waves is not solely determined by the laser power density;even at high power densities,a high energy with a large spot can generate an ultrasonic waveform dominated by the thermoelastic effect.This is ascribed to the intensification of the thermoelastic effect with the proportional increase in laser irradiation spot area for a given laser power density.Furthermore,both longitudinal and shear wave SCFRs are linearly related to grain size in polycrystalline materials;however,the shear wave SCFR is more sensitive to finer-grained materials.This study holds great significance for evaluating metal material properties using laser ultrasound.展开更多
Objective:To analyze the pathological characteristics of patients with transient cerebral ischemic attack(TIA)through multidimensional laboratory indicators and explore their clinical significance.Methods:Patients who...Objective:To analyze the pathological characteristics of patients with transient cerebral ischemic attack(TIA)through multidimensional laboratory indicators and explore their clinical significance.Methods:Patients who visited the outpa-tient department or were hospitalized in Rongxian Hospital of Traditional Chi-nese Medicine from January to December 2024 were selected.TIA patients were set as the experimental group(n=31),and healthy physical examination subjects were set as the control group(n=50).Multidimensional laboratory indicators such as blood routine,liver function,kidney function,blood lipids,electrolytes,hemorheology and blood glucose were detected and compared between the two groups.Results:In the experimental group,the WBC and NEUT#indexes in the blood routine were significantly different from those in the control group(P<0.05);the AST,AST/ALT,TP,GLO and A/G indexes in liver function were sig-nificantly different between the two groups(P<0.05);the K and CA indexes in electrolytes were significantly different between the two groups(P<0.05).Alt-hough there were differences in other indexes,they did not reach statistical sig-nificance.Conclusion:Multidimensional laboratory indicator detection is help-ful in revealing the pathological characteristics of TIA patients,and the abnormal changes of some indicators can provide an important reference for clinical diag-nosis,disease assessment and treatment.展开更多
In non-Hermitian systems,the dynamic encircling of exceptional points(EPs)engenders intriguing chiral phenomena,where the resultant state characteristics are intrinsically dependent upon the encircling handedness.An i...In non-Hermitian systems,the dynamic encircling of exceptional points(EPs)engenders intriguing chiral phenomena,where the resultant state characteristics are intrinsically dependent upon the encircling handedness.An ingenious approach using simple leaky optical elements has been presented to emulate this chiral behavior without physically encircling an EP.This innovative simplification of EP properties enables a more straightforward implementation of asymmetric switching of polarization and path.Given that photons inherently possess multiple physical degrees of freedom,the research focus has shifted from single-dimensional to multidimensional asymmetric switching.Hence,there is a fundamental challenge of how to achieve multidimensional asymmetric switching through a simple and universally applicable architecture.Here,we propose and experimentally demonstrate a novel topology-optimized architecture,termed EP-encirclement emulation tailoring,enabling multidimensional asymmetric switching.Theoretical analysis reveals that our architecture eliminates the 3-dB inherent loss in conventional architecture by replacing couplers with(de)multiplexers.Building upon this architecture,we harness all-fiber devices to implement a high-performance asymmetric switching of polarization,mode,and orbital angular momentum(OAM).To our knowledge,this is the first experimental demonstration of asymmetric OAM switching to date.Our work provides an efficient topology architecture for emulating dynamic EP encirclement,paving the way for universal and flexible asymmetric switching devices.展开更多
The mechanism of the human auditory system in detecting sound signals with complex time frequency charcteristics in a white noise background was reviewed and discussed.The efficiency of such auditory detection was ass...The mechanism of the human auditory system in detecting sound signals with complex time frequency charcteristics in a white noise background was reviewed and discussed.The efficiency of such auditory detection was assessed by comparing it with that of parallel visual detection of the output of an analogous model displayed on the oscilloscope screen. The results suggest that the detection model of the human auditory system is quite similar to a tone correlator when the time frequency characteristics of the signal are known and to an energy detector when the signal is unknown. The relationship between the threshold signal to noise ratio and the signal duration is derived for different time frequency characteristics.展开更多
新型配电系统柔性消弧装置及定位技术均需充分挖掘相电流暂态特征来实现选相、选线和故障定位。针对此问题,对新型配电系统单相接地故障相电流暂态分布特性进行分析,提出了一种基于相电流多维时频分布特征差异的新型配电系统单相接地故...新型配电系统柔性消弧装置及定位技术均需充分挖掘相电流暂态特征来实现选相、选线和故障定位。针对此问题,对新型配电系统单相接地故障相电流暂态分布特性进行分析,提出了一种基于相电流多维时频分布特征差异的新型配电系统单相接地故障定位新方法。依据故障相电流故障暂态量与非故障相电流故障暂态量的差异性,通过灰色关联度算法完成故障选相;对各出线始端监测点以及疑似故障馈线分支监测点的相电流暂态波形进行26维多维时频特征的提取,通过经方差优化的t-分布近邻嵌入算法(variance-optimized t-distributed stochastic neighbor embedding,VTSNE)进行筛选和降维,并对处理后的特征数据进行基于密度的有噪空间聚类算法(density-based special clustering of application with noise,DBSCAN)聚类完成故障选线和故障区段定位。该方法在某绿色港口10 kV新型配电系统模型中得到验证,在不同故障初相角、不同过渡电阻等故障场景下均可准确可靠定位故障位置,对采样同步精度及采样频率要求低,易于工程实现。展开更多
基金This work was funded by Beijing Key Laboratory of Distribution Transformer Energy-Saving Technology(China Electric Power Research Institute).
文摘The load types in low-voltage distribution systems are diverse.Some loads have current signals that are similar to series fault arcs,making it difficult to effectively detect fault arcs during their occurrence and sustained combustion,which can easily lead to serious electrical fire accidents.To address this issue,this paper establishes a fault arc prototype experimental platform,selects multiple commonly used loads for fault arc experiments,and collects data in both normal and fault states.By analyzing waveform characteristics and selecting fault discrimination feature indicators,corresponding feature values are extracted for qualitative analysis to explore changes in timefrequency characteristics of current before and after faults.Multiple features are then selected to form a multidimensional feature vector space to effectively reduce arc misjudgments and construct a fault discrimination feature database.Based on this,a fault arc hazard prediction model is built using random forests.The model’s multiple hyperparameters are simultaneously optimized through grid search,aiming tominimize node information entropy and complete model training,thereby enhancing model robustness and generalization ability.Through experimental verification,the proposed method accurately predicts and classifies fault arcs of different load types,with an average accuracy at least 1%higher than that of the commonly used fault predictionmethods compared in the paper.
基金Research Project of Humanities and Social Sciences by the Ministry of Education:Exploration on the Reshaping of High-Quality Technical and Skilled Talent Cultivation System for the Development of Emerging Productive Forces(24YJA880042)2024 Vocational Education Theory and Practice Research Support Project Funded by the National Center for Vocational Education Development,Ministry of Education:Research on the Multidimensional Portrayal and Innovative Training Paths of Highly Skilled Talents from the Perspective of New Quality Productivity(JZYY25010)+1 种基金Shanghai Education Scientific Research Project“Special Project of Philosophy and Social Sciences in Universities and Colleges”:Exploration on the Cultivation Path of Integrating the“Scientist Spirit”into the“Three-Dimensional Education”System in Higher Vocational Colleges(2024ZSD023)Research Startup Funding Projects for High-Level and Scarce Talents in Shanghai Electronic and Information Vocational College of Technology(GCC2024016 and GCC2023013)。
文摘Against the backdrop of new quality productivity driving high-quality economic development,this paper examines how technological innovation,digital transformation,and green development reshape the competencies and training models of highly skilled talent.It analyzes multidimensional characteristics,including knowledge structure,innovation awareness,digital literacy,and cross-boundary collaboration,revealing a shift towards“innovative,composite,and intelligent”profiles.The study identifies misalignments in current vocational education,such as outdated curricula and insufficient industry-education integration.It proposes innovative training paths,including deep industry-education collaboration,digital-intelligent teaching,and lifelong learning ecosystems.Case studies validate the feasibility of aligning talent development with new quality productivity demands.
基金supported by the Fundamental Research Funds for Central Universities (No.2010-Ia-060)
文摘In order to study the time-frequency characteristics of blasting vibration signals, measured in milliseconds, we carried out site blasting vibration tests at an open pit of the Jinduicheng Mine. Based on recorded field data and applying a combination of RSPWVD and wavelet, we analyzed the time-fre- quency characteristics of recorded field data, summarized the time-frequency characteristics of blasting vibration signals in different frequency bands and present detailed information of blasting vibration sig- nals in milliseconds of high time-frequency resolutions. Because RSPWVD can be seen as of definite physical significance to signal energy distribution in time and frequency domains, we studied the energy distribution of blasting vibration signals for various milliseconds intervals from a perspective of energy distribution. The results indicate that the effect of milliseconds intervals on time-frequency characteris- tics of blasting vibration signals is significant; the length of delay time directly affects the energy distri- bution of blasting vibration signals as well as the duration of energy in ffeauencv bands.
基金jointly sponsored the Special Fund for Earthquake Scientific Research of China Earthquake Administration(2015419015)the National Natural Sciences Foundation of China(41474071)
文摘Through analyzing the near-field hydrophone records of the airgun experiment in the Jiemian reservoir,Fujian,we study the time-frequency characteristic of airgun source wavelet and the influence of gun depth and firing pressure,and explain the process of bubble oscillation based on the Johnson( 1994) bubble model. The data analysis shows that:( 1) Airgun wavelet is composed of primary pulse and bubble pulse. The primary pulse,which is of large amplitude,short duration and wide frequency band,is usually used in shallow exploration. The bubble pulse,which is concentrated in the low-frequency range,is usually used in deep exploration with deep vertical penetration and far horizontal propagation.( 2) The variation of primary pulse amplitude with gun depth is very small,bubble pulse amplitude and the dominant frequency increase,and peak-bubble ratio and bubble period decrease. When the gun depth is 10 m,primary pulse amplitude and peakbubble ratio are maximum,which is suitable for shallow exploration; when gun depth is25 m,bubble pulse amplitude is large, and peak-bubble ratio is minimum, which is suitable for deep exploration.( 3) The primary pulse amplitude,bubble pulse amplitude,peak-bubble ratio,and bubble period increase and the dominant frequency decreases with increased firing pressure.
基金supported by the National Science and Technology Major Project (No. 2011ZX05019-008)the National Natural Science Foundation of China (No. 41074080)+1 种基金the Science Foundation of China University of Petroleum, Beijing (No. KYJJ2012-05-11)supported by the CNPC international collaboration program through the Edinburgh Anisotropy Project (EAP) of the British Geological Survey (BGS) and the CNPC Key Geophysical Laboratory at the China University of Petroleum and CNPC geophysical prospecting projects for new method and technique research
文摘According to the Chapman multi-scale rock physical model, the seismic response characteristics vary for different fluid-saturated reservoirs. For class I AVO reservoirs and gas-saturation, the seismic response is a high-frequency bright spot as the amplitude energy shifts. However, it is a low-frequency shadow for the Class III AVO reservoirs saturated with hydrocarbons. In this paper, we verified the high-frequency bright spot results of Chapman for the Class I AVO response using the frequency-dependent analysis of a physical model dataset. The physical model is designed as inter-bedded thin sand and shale based on real field geology parameters. We observed two datasets using fixed offset and 2D geometry with different fluid- saturated conditions. Spectral and time-frequency analyses methods are applied to the seismic datasets to describe the response characteristics for gas-, water-, and oil-saturation. The results of physical model dataset processing and analysis indicate that reflection wave tuning and fluid-related dispersion are the main seismic response characteristic mechanisms. Additionally, the gas saturation model can be distinguished from water and oil saturation for Class I AVO utilizing the frequency-dependent abnormal characteristic. The frequency-dependent characteristic analysis of the physical model dataset verified the different spectral response characteristics corresponding to the different fluid-saturated models. Therefore, by careful analysis of real field seismic data, we can obtain the abnormal spectral characteristics induced by the fluid variation and implement fluid detection using seismic data directly.
基金supported in part by the Natural Science Foundation of Shandong Province,China (Grant No.ZR2023ME073)the National Natural Science Foundation of China (Grant No.51805304)+1 种基金the Education Department of Shandong Province,China (Grant No.2022KJ130)Qilu University of Technology (Shandong Academy of Sciences),China (Grant Nos.2023PY009,2021JC02008 and 2022GH005)。
文摘Quantitative relationship between nanosecond pulsed laser parameters and the characteristics of laser-generated ultrasonic waves in polycrystalline materials was evaluated.The high energy of the pulsed laser with a large irradiation spot simultaneously generated ultrasonic longitudinal and shear waves at the epicenter under the slight ablation regime.An optimized denoising technique based on wavelet thresholding and variational mode decomposition was applied to reduce noise in shear waves with a low signal-to-noise ratio.An approach for characterizing grain size was proposed using spectral central frequency ratio(SCFR)based on time-frequency analysis.The results demonstrate that the generation regime of ultrasonic waves is not solely determined by the laser power density;even at high power densities,a high energy with a large spot can generate an ultrasonic waveform dominated by the thermoelastic effect.This is ascribed to the intensification of the thermoelastic effect with the proportional increase in laser irradiation spot area for a given laser power density.Furthermore,both longitudinal and shear wave SCFRs are linearly related to grain size in polycrystalline materials;however,the shear wave SCFR is more sensitive to finer-grained materials.This study holds great significance for evaluating metal material properties using laser ultrasound.
文摘Objective:To analyze the pathological characteristics of patients with transient cerebral ischemic attack(TIA)through multidimensional laboratory indicators and explore their clinical significance.Methods:Patients who visited the outpa-tient department or were hospitalized in Rongxian Hospital of Traditional Chi-nese Medicine from January to December 2024 were selected.TIA patients were set as the experimental group(n=31),and healthy physical examination subjects were set as the control group(n=50).Multidimensional laboratory indicators such as blood routine,liver function,kidney function,blood lipids,electrolytes,hemorheology and blood glucose were detected and compared between the two groups.Results:In the experimental group,the WBC and NEUT#indexes in the blood routine were significantly different from those in the control group(P<0.05);the AST,AST/ALT,TP,GLO and A/G indexes in liver function were sig-nificantly different between the two groups(P<0.05);the K and CA indexes in electrolytes were significantly different between the two groups(P<0.05).Alt-hough there were differences in other indexes,they did not reach statistical sig-nificance.Conclusion:Multidimensional laboratory indicator detection is help-ful in revealing the pathological characteristics of TIA patients,and the abnormal changes of some indicators can provide an important reference for clinical diag-nosis,disease assessment and treatment.
基金supported by the National Key R&D Program of China(2025YFE0102200)the National Natural Science Foundation of China(NSFC)(62125503,62261160388)+3 种基金the Natural Science Foundation of Hubei Province of China(2023AFA028)the Technology Innovation Program of Hubei Province(Major Science and Technology Project)(2024BAA001,2024BAA005)the Hubei Optical Fundamental Research Center(HBO2025TQ004)the High Quality Development Special Project of the Ministry of Industry and Information Technology,and the China Association for Science and Technology Youth Talent Support Engineering Doctoral Program.
文摘In non-Hermitian systems,the dynamic encircling of exceptional points(EPs)engenders intriguing chiral phenomena,where the resultant state characteristics are intrinsically dependent upon the encircling handedness.An ingenious approach using simple leaky optical elements has been presented to emulate this chiral behavior without physically encircling an EP.This innovative simplification of EP properties enables a more straightforward implementation of asymmetric switching of polarization and path.Given that photons inherently possess multiple physical degrees of freedom,the research focus has shifted from single-dimensional to multidimensional asymmetric switching.Hence,there is a fundamental challenge of how to achieve multidimensional asymmetric switching through a simple and universally applicable architecture.Here,we propose and experimentally demonstrate a novel topology-optimized architecture,termed EP-encirclement emulation tailoring,enabling multidimensional asymmetric switching.Theoretical analysis reveals that our architecture eliminates the 3-dB inherent loss in conventional architecture by replacing couplers with(de)multiplexers.Building upon this architecture,we harness all-fiber devices to implement a high-performance asymmetric switching of polarization,mode,and orbital angular momentum(OAM).To our knowledge,this is the first experimental demonstration of asymmetric OAM switching to date.Our work provides an efficient topology architecture for emulating dynamic EP encirclement,paving the way for universal and flexible asymmetric switching devices.
文摘The mechanism of the human auditory system in detecting sound signals with complex time frequency charcteristics in a white noise background was reviewed and discussed.The efficiency of such auditory detection was assessed by comparing it with that of parallel visual detection of the output of an analogous model displayed on the oscilloscope screen. The results suggest that the detection model of the human auditory system is quite similar to a tone correlator when the time frequency characteristics of the signal are known and to an energy detector when the signal is unknown. The relationship between the threshold signal to noise ratio and the signal duration is derived for different time frequency characteristics.
文摘新型配电系统柔性消弧装置及定位技术均需充分挖掘相电流暂态特征来实现选相、选线和故障定位。针对此问题,对新型配电系统单相接地故障相电流暂态分布特性进行分析,提出了一种基于相电流多维时频分布特征差异的新型配电系统单相接地故障定位新方法。依据故障相电流故障暂态量与非故障相电流故障暂态量的差异性,通过灰色关联度算法完成故障选相;对各出线始端监测点以及疑似故障馈线分支监测点的相电流暂态波形进行26维多维时频特征的提取,通过经方差优化的t-分布近邻嵌入算法(variance-optimized t-distributed stochastic neighbor embedding,VTSNE)进行筛选和降维,并对处理后的特征数据进行基于密度的有噪空间聚类算法(density-based special clustering of application with noise,DBSCAN)聚类完成故障选线和故障区段定位。该方法在某绿色港口10 kV新型配电系统模型中得到验证,在不同故障初相角、不同过渡电阻等故障场景下均可准确可靠定位故障位置,对采样同步精度及采样频率要求低,易于工程实现。
