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Parameterized time-frequency analysis to separate multi-radar signals 认领 引用 被引量：2
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作者 Wenlong Lu Junwei Xie +1 位作者 Heming Wang Chuan Sheng 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2017年第3期493-502,共10页
Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The ... Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation. 展开更多
关键词 intercepted multi-radar signal parameterized time-frequency analysis demodulation adaptive filtering
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Dominant frequency response and dynamic mechanism of rock slopes under blasting loads:A machine learning-driven time-frequency analysis 认领 引用
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作者 MA Ke PENG Yilin +2 位作者 LIAO Zhiyi LUO Longlong HUANG Yinglu 《Journal of Mountain Science》 SCIE CSCD 2026年第3期1334-1354,共21页
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(fd)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 fd 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(fd),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 fd 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
关键词 Blasting vibration Time-frequency domain analysis Machine learning Dominant frequency
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A high-resolution time-frequency analysis tool for fault diagnosis of rotating machinery 认领 引用
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作者 Gang Yu Zhenghao Cui 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2026年第1期145-154,共10页
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
关键词 Time-frequency analysis S-transform Extractive reconstruction algorithm Mechanical systems
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Machine learning-driven reliability assessment of liquefaction probability based on state parameter analysis 认领 引用
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作者 Kishan Kumar Pijush Samui +1 位作者 S.S.Choudhary Hong-Hu Zhu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第4期2960-2979,共20页
The state parameter(ψ)utilising the concept of critical state soil mechanics integrates the effect of relative density and effective stress and offers notable advantages for liquefaction assessment.This study present... The state parameter(ψ)utilising the concept of critical state soil mechanics integrates the effect of relative density and effective stress and offers notable advantages for liquefaction assessment.This study presents aψ-based liquefaction analysis using the first-order reliability method(FORM)and second-order reliability method(SORM)to evaluate the liquefaction probability of failure(PL)considering the parametric uncertainty.Four machine learning(ML)models,which include long short-term memory(LSTM),bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and Bayesian non-parametric general regression(BNGR),were developed to predict PL.The reliability analysis confirmed the robustness of the results,with PL values consistent with those obtained by established methodologies.A mapping function relating the safety factor(SF)to the PL was developed using the cone penetration test(CPT)database.Performance evaluation using 15 statistical indices,alongside sensitivity and uncertainty analysis,demonstrates the relative significance of input parameters and prediction reliability.The GRU model outperformed other ML models in terms of overall performance.The BiLSTM model achieved the highest R² values of 0.976 in training,and the GRU model(0.961)in testing,with comparable root mean square error(RMSE)values of 0.046 and 0.065,respectively.Additionally,the BNGR model showed promising results in accuracy and model complexity with the lowest Akaike information criterion(AIC)value of 11.62.Williams plots were used to illustrate the models’applicability domain,while sensitivity analysis underscores the significance of input parameters,with ψ emerging as the most influential parameter.This research provides a comprehensive framework for enhancing the accuracy and reliability of liquefaction evaluation in engineering and infrastructure design. 展开更多
关键词 Liquefaction State parameter Machine learning(ML) Reliability analysis Deep learning Bayesian modelling
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Coupled TM-damage modeling and global sensitivity analysis of thermal spalling in heterogeneous rocks 认领 引用
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作者 Liyuan Liu Mingshan Shi +4 位作者 Derek Elsworth Tao Wang Hongguang Ji Le Zhang Yaohui Li 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2026年第3期535-552,共18页
Thermal spalling in heterogeneous rocks under rapid heating poses critical risks to deep mining and geothermal operations.In this study,we develop a coupled thermal-mechanical-damage(TM D)model that explicitly incorpo... Thermal spalling in heterogeneous rocks under rapid heating poses critical risks to deep mining and geothermal operations.In this study,we develop a coupled thermal-mechanical-damage(TM D)model that explicitly incorporates Weibull distributed heterogeneity to a single fracture in rock,and validate it against ceramic quenching and granite acoustic emission experiments.Distance based generalized sensitivity analysis(DGSA)is applied to quantify the influence and interactions of key parameters,revealing the dominant controls on spalling onset,severity,and damage morphology.The results demonstrate that thermal stress dominates crack initiation and propagation,that lateral constraints can significantly delay and suppress spalling,and that material heterogeneity markedly influences peak stress and damage modes within a certain range of thermal expansion coefficient and has multiple effects on thermal spalling.This study provides a theoretical basis for quantitative assessment and parameter optimization of thermal spalling processes in rock masses. 展开更多
关键词 Rock heterogeneity Thermal spalling Microstructure evolution Sensitivity analysis Parameter interaction effect
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A novel porous shock absorption layer for tunnels: Shock absorption performance and parameter analysis 认领 引用
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作者 Zhou Tonglai Dong Changsong +1 位作者 Li Shuang Sun Qiangqiang 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2025年第2期437-450,共14页
A novel porous shock absorption layer is put forward in this study, and the shock absorption performance of the porous shock absorption layer is evaluated based on three-dimensional pseudo-static analysis. The modifie... A novel porous shock absorption layer is put forward in this study, and the shock absorption performance of the porous shock absorption layer is evaluated based on three-dimensional pseudo-static analysis. The modified reaction acceleration method is adopted and validated in the three-dimensional model. Seven ground motions are selected and the peak ground acceleration is adjusted to 0.2 g, 0.4 g and 0.6 g. The impact of the void ratio and thickness of the porous shock absorption layer is studied, while the surrounding rock grade and tunnel depth are also investigated. The numerical results show that the porous shock absorption layer has good shock absorption performance and can effectively reduce the maximum internal force of the secondary lining, but it cannot reduce the maximum horizontal relative displacement of the secondary lining. The circumferential rubber strip in the porous shock absorption layer will reduce shock absorption performance. The results of parameter analysis indicate that the shock absorption performance of the porous shock absorption layer increases with the increase of the void ratio and thickness, and it has good shock absorption performance under different surrounding rock grades and tunnel depths. 展开更多
关键词 tunnel porous shock absorption layer shock absorption performance reaction acceleration method parameter analysis
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A Comparative Study Between SDP-CNN and Time-Frequency-CNN-Based Approaches for Fault Detection 认领 引用
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作者 Mario Spirto Francesco Melluso +4 位作者 Armando Nicolella Pierangelo Malfi Chiara Cosenza Sergio Savino Vincenzo Niola 《Journal of Dynamics, Monitoring and Diagnostics》 2026年第1期25-37,共13页
The image-based approach is widely used in fault detection(FD)algorithms of mechanical systems.The images are derived from the vibrational signals transformed from the time to time–frequency domain,and they are used ... The image-based approach is widely used in fault detection(FD)algorithms of mechanical systems.The images are derived from the vibrational signals transformed from the time to time–frequency domain,and they are used to develop a convolutional neural network(CNN)to automate the FD process.Nowadays,images are also obtained from the transformation of vibrational signals from the time domain to symmetrized dot pattern(SDP)coordinates,achieving high CNN testing accuracy.This paper shows a comparison of image-CNN approaches for FD using images obtained from time–frequency transforms and those obtained from the SDP transform as input.The comparison was conducted using experimental data from two publicly available bearing datasets,examining both the accuracy of the CNNs and the computational time required for the vibrational signal transformations.The results show that the SDP-CNN approach achieves the same accuracy as spectrogram-CNN approaches but with a significantly reduced computational time.These results support the future real-time implementation of the SDPCNN approach for FD in mechanical systems such as bearings. 展开更多
关键词 ball bearings CNN fault detection symmetrized dot pattern time-frequency analysis
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Time-frequency analysis of Li solid-phase diffusion in spherical active particles under typical discharge modes 认领 引用 被引量：4
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作者 Qiu-An Huang Yuxuan Bai +5 位作者 Liang Wang Juan Wang Fangzhou Zhang Linlin Wang Xifei Li Jiujun Zhang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2022年第4期209-224,共16页
Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact soluti... Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact solution obtained in the time/frequency domain is time-consuming and just as a reference value for approximate solutions;on the other hand, calculation errors and application range of approximate solutions not only rely on approximate algorithms but also on discharge modes. For the purpose to track the transient dynamics for Li solid-phase diffusion in spherical active particles with a tolerable error range and for a wide applicable range, it is necessary to choose optimal approximate algorithms in terms of discharge modes and the nature of active material particles. In this study, approximation methods,such as diffusion length method, polynomial profile approximation method, Padé approximation method,pseudo steady state method, eigenfunction-based Galerkin collocation method, and separation of variables method for solving Li solid-phase diffusion in spherical active particles are compared from calculation fundamentals to algorithm implementation. Furthermore, these approximate solutions are quantitatively compared to the quasi-exact/exact solution in the time/frequency domain under typical discharge modes, i.e., start-up, slow-down, and speed-up. The results obtained from the viewpoint of time-frequency analysis offer a theoretical foundation on how to track Li transient concentration profile in spherical active particles with a high precision and for a wide application range. In turn, optimal solutions of Li solid diffusion equations for spherical active particles can improve the reliability in predicting safe operating regime and estimating maximum power for automotive batteries. 展开更多
关键词 Li solid-phase diffusion Discharge mode Approximate algorithm Quasi-exact/exact solution Time-frequency analysis
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A Comprehensive Framework for Nature-Inspired Photovoltaic Model Calibration and Explainable Surrogate-Based Sensitivity Analysis 认领 引用
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作者 Yan-Hao Huang Chung-Ming Kao 《Computers, Materials & Continua》 SCIE EI 2026年第6期2354-2379,共26页
Photovoltaic(PV)equivalent-circuit models are widely used for performance evaluation and diagnostics,but their usefulness relies on both accurate calibration and interpretable understanding of how parameters shape cur... Photovoltaic(PV)equivalent-circuit models are widely used for performance evaluation and diagnostics,but their usefulness relies on both accurate calibration and interpretable understanding of how parameters shape current-voltage(Ⅰ-Ⅴ)behavior.For nonlinear and strongly coupled PV models,conventional global sensitivity analysis can be computationally demanding and offer limited insight into effect direction and operating-point dependence.This study presents an method-oriented framework that integrates nature-inspired optimization with surrogate-based explainable global sensitivity analysis under a specified operating condition.The Starfish Optimization Algorithm(SFOA)is first used for parameter identification by searching for the optimal parameter set that minimizes the discrepancy between measured and model-predicted Ⅰ-Ⅴ data for the Single-Diode Model(SDM)and Double-Diode Model(DDM).A Random Forest(RF)surrogate is trained to approximate the mapping from voltage and parameters to output current.Its accuracy is evaluated on an independent test set,achieving RMSE/R2 of 0.001331/0.999366 for SDM and 0.003090/0.999394 for DDM.Sensitivity is quantified primarily using Shapley Additive Explanations(SHAP),with mean decrease in impurity(MDI)and one-factor-at-a-time(OFAT)analysis used for cross-validation.Under identical settings,SFOA achieves the best accuracy among competing optimizers,with best root-mean-square error(RMSE)values of 0.0008818 for SDM and 0.0008811 for DDM.The integrated SHAP,MDI,and OFAT analyses yield consistent importance structures,and the overall ranking for DDM follows the same trend as that for SDM.Within the examined±5%neighborhood around the calibrated optimum,the photocurrent is the dominant factor governing Ⅰ-Ⅴ behavior,whereas diode-branch parameters show secondary and condition-dependent effects,and resistive parameters mainly contribute fine-scale adjustments within the examined neighborhood.Overall,the proposed framework provides accurate calibration and interpretable global sensitivity insights that can support a practical workflow for model-based PV analysis under the considered condition. 展开更多
关键词 Photovoltaic parameter identification sensitivity analysis starfish optimization algorithm random forest nature-inspired algorithms
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The W transform and its improved methods for time-frequency analysis of seismic data 认领 引用 被引量：3
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作者 WANG Yanghua RAO Ying ZHAO Zhencong 《Petroleum Exploration and Development》 SCIE 2024年第4期886-896,共11页
The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improv... The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra. 展开更多
关键词 time-frequency analysis W transform Wigner-Ville distribution matching pursuit energy focusing resolution
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Novel Doppler Frequency Extraction Method Based on Time-Frequency Analysis and Morphological Operation 认领 引用 被引量：2
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作者 侯舒娟 吴嗣亮 《Journal of Beijing Institute of Technology》 EI CAS 2006年第4期443-447,共5页
A novel method of Doppler frequency extraction is proposed for Doppler radar scoring systems. The idea is that the time-frequency map can show how the Doppler frequency varies along the time-line, so the Doppler frequ... A novel method of Doppler frequency extraction is proposed for Doppler radar scoring systems. The idea is that the time-frequency map can show how the Doppler frequency varies along the time-line, so the Doppler frequency extraction becomes curve detection in the image-view. A set of morphological operations are used to implement curve detection. And a map fusion scheme is presented to eliminate the influence of strong direct current （DC） component of echo signal during curve detection. The radar real-life data are used to illustrate the performance of the new approach. Experimental results show that the proposed method can overcome the shortcomings of piecewise-processing-based FFT method and can improve the measuring precision of miss distance. 展开更多
关键词 Doppler frequency time-frequency analysis morphological operation miss distance
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A Recursive Method of Time-Frequency Analysis for the Signal Processing of Flutter Test with Progression Variable Speed 认领 引用 被引量：4
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作者 宋叔飚 裴承鸣 《Chinese Journal of Aeronautics》 EI CAS 2005年第3期213-217,共5页
Focused on the non-statlonarity and real-time analysis of signal in flutter test with progression variable speed （FTPVS）, a new method of recursive time-frequency analysis is presented. The time-varying system is tr... Focused on the non-statlonarity and real-time analysis of signal in flutter test with progression variable speed （FTPVS）, a new method of recursive time-frequency analysis is presented. The time-varying system is tracked on-line by building a time-varying parameter model, and then the relevant parameter spectrum can be obtained. The feasibility and advantages of the method are examined by digital simulation. The results of FTPVS at low-speed wind-tunnel promise the engineering application perspective of the method. 展开更多
关键词 flutter test with progression variable speed （FTPVS） non-stationary signal processing recursive time-frequency analysis （RTFA）
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NEW SAR IMAGE INTERPRETATION METHOD OF AIRCRAFT BASED ON JOINT TIME-FREQUENCY ANALYSIS 认领 引用 被引量：1
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作者 Zhu Jiwei Qiu Xiaolan Lei Bin 《Journal of Electronics(China)》 2014年第4期325-333,共9页
With the continuous improvement of Synthetic Aperture Radar(SAR) resolution, interpreting the small targets like aircraft in SAR images becomes possible and turn out to be a hot spot in SAR application research. Howev... With the continuous improvement of Synthetic Aperture Radar(SAR) resolution, interpreting the small targets like aircraft in SAR images becomes possible and turn out to be a hot spot in SAR application research. However, due to the complexity of SAR imaging mechanism, interpreting targets in SAR images is a tough problem. This paper presents a new aircraft interpretation method based on the joint time-frequency analysis and multi-dimensional contrasting of basic structures. Moreover, SAR data acquisition experiment is designed for interpreting the aircraft. Analyzing the experiment data with our method, the result shows that the proposed method largely makes use of the SAR data information. The reasonable results can provide some auxiliary support for the SAR images manual interpretation. 展开更多
关键词 Synthetic Aperture Radar （SAR） image interpretation Joint time-frequency analysis Scattering centers Basic structureCLC number：TN957
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Transient analysis of functionally graded curved shells using a nonuniform shape parameter integrated radial basis function approach 认领 引用
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作者 Vay Siu Lo Andrzej Katunin Thien Tich Truong 《Theoretical & Applied Mechanics Letters》 EI CAS CSCD 2025年第3期296-308,共13页
In this study,an improved integrated radial basis function with nonuniform shape parameter is introduced.The proposed shape parameter varies in each support domain and is defined byθ=1/dmax,where dmaxis the max... In this study,an improved integrated radial basis function with nonuniform shape parameter is introduced.The proposed shape parameter varies in each support domain and is defined byθ=1/dmax,where dmaxis the maximum distance of any pair of nodes in the support domain.The proposed method is verified and shows good performance.The results are stable and accurate with any number of nodes and an arbitrary nodal distribution.Notably,the support domain should be large enough to obtain accurate results.This method is then applied for transient analysis of curved shell structures made from functionally graded materials with complex geometries.Through several numerical examples,the accuracy of the proposed approach is demonstrated and discussed.Additionally,the influence of various factors on the dynamic behavior of the structures,including the power-law index,different materials,loading conditions,and geometrical parameters of the structures,was investigated. 展开更多
关键词 Integrated radial basis function Shape parameter Functionally graded material Curved shell Transient analysis
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Time-Frequency Analysis of EEG Signals Evoked by Voluntary, Stimulated and Imaginary Motions 认领 引用
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作者 明东 李南南 +6 位作者 付安爽 徐瑞 邱爽 徐强 周鹏 张力新 万柏坤 《Transactions of Tianjin University》 EI CAS 2014年第3期210-214,共5页
In order to investigate the characteristics of sensorimotor cortex during motor execution(ME), voluntary, stimulated and imaginary finger flexions were performed by ten volunteer subjects. Electroencephalogram(EEG) da... In order to investigate the characteristics of sensorimotor cortex during motor execution(ME), voluntary, stimulated and imaginary finger flexions were performed by ten volunteer subjects. Electroencephalogram(EEG) data were recorded according to the modified 10-20 International EEG System. The patterns were compared by the analysis of the motion-evoked EEG signals focusing on the contralateral(C3) and ipsilateral(C4) channels for hemispheric differences. The EEG energy distributions at alpha(8—13 Hz), beta(14—30 Hz) and gamma(30—50 Hz) bands were computed by wavelet transform(WT) and compared by the analysis of variance(ANOVA). The timefrequency(TF) analysis indicated that there existed a contralateral dominance of alpha post-movement event-related synchronization(ERS) pattern during the voluntary task, and that the energy of alpha band increased in the ipsilateral area during the stimulated(median nerve of wrist) task. Besides, the contralateral alpha and beta event-related desynchronization(ERD) patterns were observed in both stimulated and imaginary tasks. Another significant difference was found in the mean power values of gamma band(p<0.01)between the imaginary and other tasks. The results show that significant hemispheric differences such as alpha and beta band EEG energy distributions and TF changing phenomena(ERS/ERD) were found between C3 and C4 areas during all of the three patterns. The largest energy distribution was always at the alpha band for each task. 展开更多
关键词 electroencephalogram motor execution wavelet transform time-frequency analysis analysis of vari-ance event-related synchronization event-related desynchronization
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Parameter influence analysis and optimization of wheel–rail creepage characteristics in high-speed railway curves 认领 引用
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作者 Bolun An Jiapeng Liu +3 位作者 Guang Yang Feng shou Liu Tong Shi Ming Zhai 《Railway Sciences》 2025年第1期37-51,共15页
Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated opt... Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.Design/methodology/approach–Taking a small-radius curve of a high-speed railway as the research object,field measurements were conducted to obtain track parameters and wheel–rail profiles.A coupled vehicle-track dynamics model was established.Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.Findings–Key service parameters affecting wheel–rail creepage were identified,including the matching relationship between curve geometry and vehicle speed and rail profile parameters.The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis,leading to the establishment of parameter optimization criteria.Originality/value–This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves.A response surface-based parameter-creepage relationship model was established,and a multi-parameter coordinated optimization strategy was proposed.The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves. 展开更多
关键词 High-speed railway Curve track Wheel-rail creepage Parameter analysis Response surface methodology Optimization design
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The combined time-frequency analysis of the acoustic signals backscattered from ultrasonic contrast agents in the evaluation of the blood perfusion 认领 引用
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作者 李彬 万明习 王素品 《Journal of Medical Colleges of PLA(China)》 2004年第4期222-224,共3页
Objective: To analyze the non-periodic, unstable and even chaotic echoes scattered from microbubbles which are extremely sensitive and may easily collapse, fragment or shrink when ultrasound contrast agents are expose... Objective: To analyze the non-periodic, unstable and even chaotic echoes scattered from microbubbles which are extremely sensitive and may easily collapse, fragment or shrink when ultrasound contrast agents are exposed to ultrasound (US) irradiation. Methods: The combined time-frequency analysis was applied to the original signals instead of the traditional Fourier spectral analysis technique. Results: The results obtained from simulation as well as experiment showed that the subharmonic, 2nd harmonic and ultra harmonic of the microbubbles occurred during the oscillation and varied with time. The dependence on the incident ultrasonic amplitude and microbubble parameters were established. Conclusion: The transient echoes backscattered from the ultrasound agent in the evaluation of the blood perfusion can be analyzed thoroughly by the technique of combined-frequency analysis and the time detail of the frequency contents can be revealed. 展开更多
关键词 ultrasound contrast agent harmonic combined time-frequency analysis
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Factor analysis and machine learning for predicting endpoint carbon content in converter steelmaking 认领 引用 被引量：3
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作者 Lihua Zhao Shuai Yang +3 位作者 Yongzhao Xu Zhongliang Wang Xin Liu Yanping Bao 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2025年第10期2469-2482,共14页
The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.Howev... The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content. 展开更多
关键词 converter endpoint carbon content parameter classification factor analysis improved particle swarm optimization support vector machine
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Simulation Study on Multi-Rate Time-Frequency Analysis of Non-Stationary Signals 认领 引用
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作者 LIN Haibo GAO Zhibin +1 位作者 YI Chuijie LIN Tianran 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第6期798-802,共5页
A new time-frequency analysis method is proposed in this study using a multi-rate signal decomposition technique for the analysis of non-stationary signals. The method uses a multi-rate filter bank for an improved non... A new time-frequency analysis method is proposed in this study using a multi-rate signal decomposition technique for the analysis of non-stationary signals. The method uses a multi-rate filter bank for an improved non-stationary signal decomposition treatment, and uses the Wigner-Ville distribution(WVD) analysis for signal reconstruction. The method presented in this study can effectively resolves the time and frequency resolution issue for non-stationary signal analysis and the cross-term issue typically encountered in time-frequency analysis.The feasibility and accuracy of the proposed method are evaluated and verified in a numerical simulation. 展开更多
关键词 non-stationary signals time-frequency analysis multi-rate decomposition Wigner-Ville distribution (WVD)
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Application of Wavelet Packet De-noising in Time-Frequency Analysis of the Local Wave Method 认领 引用
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作者 LI Hong kun, MA Xiao jiang, WANG Zhen, ZHU Hong Institute of Vibration Engineering, Dalian University of Technology, Dalian 116024, P.R.China 《International Journal of Plant Engineering and Management》 EI 2003年第4期233-238,共6页
The local wave method is a very good time-frequency method for nonstationaryvibration signal analysis. But the interfering noise has a big influence on the accuracy oftime-frequency analysis. The wavelet packet de-noi... The local wave method is a very good time-frequency method for nonstationaryvibration signal analysis. But the interfering noise has a big influence on the accuracy oftime-frequency analysis. The wavelet packet de-noising method can eliminate the interference ofnoise and improve the signal-noise-ratio. This paper uses the local wave method to decompose thede-noising signal and perform a time-frequency analysis. We can get better characteristics. Finally,an example of wavelet packet de-noising and a local wave time-frequency spectrum application ofdiesel engine surface vibration signal is put forward. 展开更多
关键词 local wave time-frequency analysis wavelet packet de-noising signal-noise-ratio
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