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Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rail corrugation, one of the most common track damage problems in metro lines, has yet to be fundamentally resolved. To study the time-frequency domain characteristics of vehicle interior vibration and noise, as well as track structure vibration after rail corrugation occurs in different track structure types, and to investigate the effect of rail corrugation on vehicles and tracks, dynamic and static tests were conducted on a metro line. These tests measured the vibration and noise response inside the vehicle and the vibration response of track components under the rail corrugation excitation. Methods such as time-domain indicator statistics and 1/3-octave spectral analysis were used to analyze track vibration response characteristics and in-vehicle vibration and noise response characteristics. The results showed that on small radius curve sections, the floating slab track produced rail corrugation with a characteristic wavelength of about 200 mm, while the overall track bed produced rail corrugation with a characteristic wavelength of about 60 mm. The root mean square (RMS) value of the rail, slab, and tunnel wall vibration acceleration in the floating slab track were 1. 8, 5. 8, and 0. 3 times those of the overall track bed, respectively. The influence of rail corrugation on track vibration was mainly reflected in the mid-to-high frequency range. Around 300~400 Hz, the vibration level of floating slab track attenuated by 66 dB from the rail to the tunnel wall, while the overall track bed attenuated by 49 dB. When the train passed through the test area, the RMS values of vertical and longitudinal vibration acceleration above the bogie and in the middle of the carriage were almost the same, while the RMS value of lateral vibration acceleration in the middle of the carriage was about twice that above the bogie. The abnormal vibration at the bogie position inside the vehicle mainly originated from the excitation of the rail corrugation, and the vehicle's vibration and noise were more intense under the excitation of shortwavelength corrugation. Therefore, rail corrugation in metro systems becomes a major component in both the vibration and noise response of tracks and vehicles after it occurs, and rails should be ground in time. The research results can provide theoretical guidance for metro maintenance. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study of fearful emotions has important implications for animal emotional control and development. Current effects of fearful emotions on the behavior and brain activity of animals (especially birds) are mostly biased towards behavioral and physiological phenomena, and there is a lack of studies involving dynamic analysis of the patterns of neural electrical activity within specific relevant nuclei. In order to understand the rule of change of neural signals in pigeons under the fear emotion, taking pigeons as a model animal and its stratum griseum periventriculare (SGP) nuclei as the target brain area, adopting the experimental method of gradual approach of danger to study the pattern of change of neural activities under different fear proximity, the rhythmic differences of frequency domain, time-frequency energy, and functional connectivity based on the signal of Local field potential (LFP) were analyzed in-depth. The LFP signals of 2 pigeons in the resting state and the fear looming experiment were firstly collected and the four characteristic rhythmic components, Delta, Theta, Beta and Gamma, were extracted. The autoregressive modeling method was used to calculate the difference in the percentage of power spectral density between the quiet and fearful states at each rhythm. Next, the idiosyncratic change in time-frequency energy in the fear state with change in looming distance was analyzed. A coherence-based functional brain network was also constructed, and the local network connectivity characteristics of pigeons in both quiet and fearful states were statistically analyzed using a two-factor analysis of variance (ANOVA) method. Finally, a linear fitting analysis was performed to analyze the relationship between the network topological characteristics and the looming distance. The results show that the power spectral occupancy of the Theta band and the strength of brain functional network connections are significantly increased in the fear looming state of pigeons. With the shortening of the looming distance, the time-frequency energy variations within the Theta and Beta bands show a gradual upward trend, and there is a significant negative correlation between the strength of the local network connections and the looming distance. It suggests that the Theta frequency band may be related to the representation of fearful emotions, and that the difference in neuroelectric signal characteristics between the Theta and Beta frequency bands can characterize changes in fear looming distance. It can be seen that these results can provide valuable references for further exploring the study of the neural coding mechanism of fear emotion and its neural regulation in birds. [ABSTRACT FROM AUTHOR]

Copyright of CT Theory & Applications is the property of Editorial Department of CT Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The portrayal of sand cusp extinction is the key to evaluating the effectiveness of tectonic-lithological composite confinement, and it is difficult to accurately identify the location of sand cusp extinction due to the influence of seismic data band limitations. In order to effectively solve the problem of inaccurate identification of cusp extinction on seismic sections, this paper innovatively introduces the dual advantages of time-frequency resolution and energy focusing of synchronous compression match tracing to carry out the sand-cusp extinction identification research. Firstly, the time-frequency domain pleated-product operator is used to construct the redundancy dictionary of match tracing with the constraints of the initial model, and all the possible matching atoms are screened out to form the alternative atom bank in the time-frequency domain. The initial model constraints and the time-frequency domain joint inversion method are introduced into the inversion framework, which can obtain more accurate inversion results. Then, the dominant frequencies are extracted by channel-by-channel analysis using the simultaneous compressive match-tracking transform, and the time-frequency transient spectra are screened to obtain the single-frequency spectral profile with the optimal frequencies. The two-dimensional model and actual data testing of the proposed method show that the high-resolution seismic spectral decomposition sand-cusp identification method based on synchronous compression and matching tracking can obtain richer time-frequency domain information and get the single-frequency spectral profile with the optimal frequency, thus accurately identifying the location of cusps of subsurface geological bodies, which is of great significance for the depiction of cusps of overburden-type and erosion-type lithological confinement.

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.

The imaging of aerial targets using Inverse Synthetic Aperture Radar (ISAR) is affected by micro-Doppler effects resulting from localized micromotions, such as rotation and vibration. These effects introduce additional Doppler frequency modulation into the echo, leading to spectral broadening. Under ultrahigh-resolution conditions, these micromotions interfere with the focusing process of subject scatterers, resulting in images with poor focus showing significantly reduced quality. Furthermore, micro-Doppler signals exhibit temporal variability and nonstationary characteristics, posing difficulties in their estimation and differentiation from the echo. To address these challenges, this paper proposes a nonparametric method based on Variational Mode Decomposition (VMD) and mode optimization to separate the echo of the subject from micro-Doppler components. This separation is achieved by utilizing differences in their respective time-frequency distributions. This methodology mitigates the effect of micro-Doppler signals on the echo and obtains imaging results of a drone with ultrahigh-resolution. The VMD algorithm is introduced and subsequently extended to the complex domain. The method entails the decomposition of the ISAR echo along the azimuth direction into several mode functions distributed uniformly across the Doppler sampling bandwidth. Subsequently, image entropy indices are employed to optimize the decomposition parameters and select the imaging modes. This ensures the effective suppression of micro-Doppler signals and preservation of the subject echo. Compared to existing methods based on Empirical Mode Decomposition (EMD) and Local Mean Decomposition (LMD), the proposed method exhibits superior performance in suppressing image blurring caused by micro-Doppler effects while ensuring complete retention of fuselage details. Furthermore, the effectiveness and advantages of the proposed method are validated through simulations and processing of ultrawideband microwave photonic data obtained from drone measurements.

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Beijing University of Civil Engineering & Architecture is the property of Journal of Beijing University of Civil Engineering & Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the time-frequency analysis of the echoes from targets with composite micro-motions, there is a problem that the energy of time-frequency strip is difficult to focus, which affects the extraction and analysis of the target's micro-Doppler feature. To solve this problem, this paper proposes the concept of time-frequency harmonic stripes and corresponding time-frequency transformation methods. Based on the assumption that the composite micro-motions include central motion components and high-frequency motion components, firstly, spline function is used to fit the frequency curve of the central motion component, and therefore construct the time-frequency transform kernel is constructed. Then, parameterized time-frequency transform is used to convert the composite micro-Doppler signal in the time domain to harmonic stripes on the time-frequency plane. Compared with traditional methods such as short-time Fourier transform and pseudo Wigner-Ville distribution, the proposed method can significantly improve the energy aggregation and spur suppression of time-frequency transform of radar echoes from composite micro-motion targets. Simulation results verify the effectiveness of the proposed method and its adaptability to low signal-to-noise ratio (SNR) conditions. [ABSTRACT FROM AUTHOR]

Current hydrological prediction model studies lack analysis of the differential selection of modeling parameters for neural networks in different watersheds, and the adaptability of the model is low, which is not conducive to the promotion and application of the model. In this study, three sub-basins of the Yellow River Basin were selected as the research objects, and the parameter differences of hydrological stations in different characteristic sub-basins were modeled based on the discrete wavelet algorithm and Long Short-Term Memory (LSTM) model. The aim was to improve the adaptability of hydrological prediction models. The results show that for hydrological stations with good periodicity of historical flow and less human influence, a prediction model can be built based on the historical flow of the station. For mainstream hydrological stations with greater influence from upstream flow, the predictive power of the model based solely on the historical flow of the station is lower. Combining the upstream flow, it can improve the prediction accuracy of the model. Moreover, the farther the upstream hydrological station considered is from the predicted hydrological station, the longer the flow can be predicted by the model. For basins with small river flow and significant influence from groundwater and precipitation, the predictive power of the model based solely on the historical flow of the station is lower, but incorporating rainfall can improve the prediction accuracy. [ABSTRACT FROM AUTHOR]

In order to study the effect of unbalance loading on the stiffness of rhombic negative stiffness vibration isolation system, based on the mechanical analysis method, the mathematical model of the vibration isolation system under unbalance loading was established, the dimensionless stiffness-displacement nonlinear curves were obtained, and the influence of unbalance loading on its quasi-zero stiffness characteristics was analyzed. Simulation experiments were carried out using simulink to apply excitation to the vibration base of the vibration isolation system under unbalance loading, and the time-varying stiffness of the vibration isolation system under different excitations was obtained. Combined with Fourier transform, the time-varying and amplitude-frequency characteristics of the stiffness of the vibration isolation system were discussed. The results show that the higher the unbalance loading, the narrower the low stiffness interval and the weaker the quasi-zero stiffness characteristic. The fluctuation range and peak value of the time-varying stiffness increase larger with the increase of unbalance loading, but the fluctuation trend of the time-varying stiffness is not affected by unbalance loading. The amplitude of the time-varying stiffness is mainly concentrated in the low-frequency interval, which decreases with the increase of the frequency, and eventually approaches 0. Stiffness of the vibration isolation system will be influenced by unbalance loading. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When lightning strikes the outgoing lines of a hydropower station， it induces severe overvoltages. Then， the operation of gas-insulated switchgear （GIS） and circuit breakers within the station also triggers very fast transient overvoltages （VFTO）， posing a significant threat to the insulation safety of GIS and transformer equipment. To address this， an ultra-wideband transient voltage sensor is installed on the high-voltage side of the GIS equipment at the main transformer of the hydropower station. This establishes an online monitoring system for transient voltages， capturing the transient response process in the hydropower station during lightning strikes on its outgoing lines. Through the analysis of time domain and frequency domain characteristics of transient voltage， it is observed that when the outgoing lines of the hydropower station experience a lightning-induced ground fault， fracture reignition may occur in the circuit breaker. Based on the waveform of the lightning transient voltage infiltrating the hydropower station， accurate single-end fault location can be achieved. When the lightning strike on lines occurs within 10 km of the hydropower station， the transient voltage infiltrating the station poses a threat to transformer insulation. The ultra-wideband transient voltage monitoring system accurately records abnormal transient events within the hydropower station. Comparative analysis of the time domain and frequency domain characteristics of transient waveforms at various measurement points facilitates the localization of transient excitation sources. This aids in the early detection of equipment anomalies， providing timely warnings and ensuring the reliability of equipment operation and stable hydropower dispatch.

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem that it was difficult for traditional signal processing methods to extract fault features that could fully and accurately reflect the running state of bearings from bearing vibration signals, and the amount of data collected in practical engineering was difficult to meet the requirement of large data amount in deep learning, a bearing fault identification model based on time-frequency graph and dual-channel convolutional neural network(CNN) was proposed. Firstly, a new objective function was constructed based on sample entropy and kurtosis, the grey wolf optimization algorithm(GWO) was used to optimize the parameters of variational mode decomposition(VMD); when the objective function reached the minimum value, the optimal parameter combination was obtained. Secondly, the optimized VMD was used to process the bearing signal, and the obtained modal components were calculated by smoothing pseudo-Wigner Ville distribution(SPWVD), and the time-frequency graph of the bearing was obtained by summing the calculated results. Thirdly, the continuous wavelet transform(CWT) was used to process the original signal directly to obtain the time-frequency graph. Finally, the time-frequency graphs obtained by the two methods were respectively used as the input of dual-channel CNN to train the network, and the features of the time-frequency graphs were extracted by CNN and faults were classified. The experimental results show that the accuracy rate of the proposed method is 99.29% in the bearing fault experiments, and the average accuracy rate is 99.61% in ten experiments. Comparing with the single-channel CNN and support vector machine(SVM), the proposed method has higher accuracy and better stability. The results show that this method has the characteristics of high accuracy and strong stability in the field of bearing fault diagnosis, and can effectively diagnose bearing faults. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Petroleum Geology & Oilfield Development in Daqing is the property of Editorial Department of Petroleum Geology & Oilfield Development in Daqing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Natural Gas Geoscience is the property of Natural Gas Geoscience and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to remove interference from hybrid signals and sort each frequency hopping station signal, a multi frequency hopping network station sorting algorithm based on joint feature clustering was proposed.Firstly, short-time Fourier transform was applied to the sorted hybrid signals to obtain the time-frequency matrix, and adaptive threshold denoising was carried out according to the energy distribution histogram of time-frequency matrix.Secondly, the sweep interference was removed by morphological filtering.Thirdly, the connected domain was labeled, the duration and average energy of each signal were calculated to remove the fixed frequency interference, and the joint feature vector for each frequency hop was formed.Finally, the MeanShift algorithm was used to cluster and analyze the joint feature vectors of each segment of the signal, completing the sorting of each frequency hopping signal.The simulation results show that the proposed algorithm has higher sorting rate, stronger anti-interference ability and wider applicability to hybrid signals compared with the traditional algorithm.

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of National University of Defense Technology / Guofang Keji Daxue Xuebao is the property of NUDT Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For the intelligent fault diagnosis algorithm of wind turbine gearbox (WTG), the isolated fault classification results often faced the question of confidence. In order to provide more information besides diagnosis conclusion while fault classification, based on the vibration time- frequency information, a two, stage framework for vibration time-frequency analysis and fault diagnosis of wind turbine gearbox was proposed. Firstly, at the first stage, the feature areas related to fault in the time frequency image were marked using the U-net model without manually setting the segmentation parameters. Then, the feature extraction method based on region shape feature was utilized to extract valuable information from the analyzed binary images. Finally, at the second stage, using these shape features based on region information, the random forest algorithm was used to complete the automatic fault identification of the WTGs. The proposed two stage pipeline was used to identify the fault conditions of in-service WTGs located in North China to verify its effectiveness. The experimental results show that the F1 score of the analysis algorithm reaches 0. 942, while the diagnostic accuracy of the diagnosis algorithm reaches 97. 4% . Comparing with existing methods, U-net method shows higher comprehensive diagnosis performance and computational efficiency. The results show that the proposed method can accurately mark the feature patches and feature bands in time frequency images and quickly and effectively diagnose the WTG faults. [ABSTRACT FROM AUTHOR]

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automotive Engineer (1674-6546) is the property of Auto Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: Under the background of the nanosecond or even sub-nanosecond requirements for timing accuracy proposed by the new generation of communication technology, precise measurement and control as well as military weapon platforms, the wide-area precise timing (WPT) system based on BeiDou satellite navigation system (BDS) is built with sub-nanosecond time service capability. Methods: Based on the WPT prototype system, we further extend the BDS high-precision time-frequency service, including time reference traceability, real-time clock comparison and online monitoring of timing terminal performance, which are of great significance for high-precision timing, real-time comparison and the reliability of timing terminals. The timing performance of BDS high-precision timing terminals in short baseline, mediumlength baseline and long baseline is evaluated. Results: The results show that: (1) The accuracy of GPS timing based on WPT service system accuracy is better than 0.1 ns, while the accuracy of BDS-3 is 0.15 ns. The frequency stability of timing results after traceability can reach 1×10-15 at ten thousand averaging. (2) The performance of real-time comparison for BRUX-SPT0 link based on WPT is better than 0.1 ns. (3) The difference between the terminal time and the system time is less than 1 ns. (4) The accuracy of real-time time synchronization for short and medium baseline is within 0.1 ns. The frequency stability can reach 1× 10-15 level at ten thousand averaging. (5) The accuracy of real-time time synchronization using BeiDou high precision timing terminal for long baseline is better than 1 ns. Conclusions: The WPT service system can provide time and frequency services of better than 100 picoseconds and 1×10－15 magnitude. On this basis, we investigate three application research on BDS high-precision time-frequency services, online metrology of time-frequency terminals, time synchronization of low-orbit constellations and time-frequency test analysis, which are of great significance for BDS innovative applications in the time-frequency field. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Northeast Petroleum University is the property of Journal of Northeast Petroleum University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Geomechanics is the property of Journal of Geomechanics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Dalian Polytechnic University is the property of Journal of Dalian Polytechnic University Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)