Analysis of coordinate time series of DORIS stations on Eurasian plate and the plate motion based on SSA and FFT

This study focuses on analyzing the time series of DORIS beacon stations and plate motion of the Eurasian plate by applying Singular Spectrum Analysis(SSA)and Fast Fourier Transform(FFT).First,the rend terms and periodic signals are accurately separated by SSA,then,the periodic seasonal signals are detected using SSA,and finally,the main components of the time series are reconstructed successfully.The test results show that the nonlinear trends and seasonal signals of DORIS stations are detected successfully.The periods of the seasonal signals detected are year,half-year,and 59 days,etc.The contribution rates and slopes in E,N,and U directions of the trend items of each beacon station after reconstruction are obtained by least-square fitting.The velocities of these stations are compared with those provided by the GEODVEL2010 model,and it is found that they are in good agreement except the DIOB,MANB,and PDMB stations.Based on the DORIS coordinate time series,the velocity field on the Eurasian plate is constructed,and the test shows that the Eurasian plate moves eastward as a whole with an average velocity of 24.19±0.11 mm/y in the horizontal direction,and the average velocity of it is1.74±0.07 mm/y in the vertical direction.

A new method for coseismic offset detection from GPS coordinate time series

Currently,the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes.This is followed by the process of differencing the average GPS coordinate time series data,with a time interval of 3 to 5 days before and after the earthquake.In the face of the huge amount of GPS coordinate time series data today,the conventional approach of relying on earthquake catalog data to assist in obtaining coseismic offset signals has become increasingly burdensome.To address this problem,we propose a new method for automatically detecting coseismic offset signals in GPS coordinate time series without an extra earthquake catalog for reference.Firstly,we pre-process the GPS coordinate time series data for filtering out stations with significant observations missing and detecting and removing outliers.Secondly,we eliminate other signals and errors in the GPS coordinate time series,such as trend and seasonal signals,leaving the coseismic offset signals as the primary signal.The resulting coordinate time series is then modeled using the first-order difference and data stacking method.The modeling method enables automatic detection of the coseismic offset signals in the GPS coordinate time series.The aforementioned method is applied to automatically detect coseismic offset signals using simulated data and the Searles Valley GPS data in California,USA.The results demonstrate the efficacy of our proposed method,successfully detecting coseismic offsets from vast amounts of GPS coordinate time series data.

Study of the effects on GPS coordinate time series caused by higher-order ionospheric corrections calculated using the DIPOLE model

As one of the main error sources in high-precision Global Positioning System （GPS） data processing, higher-order ionospheric （HOI） delays cause significant effects on coordinate time series that cannot be ignored in analyses of long time series. Typically two geomagnetic models, DIPOLE model and Inter- national Geomagnetic Reference Field （IGRF） model, are used for calculating HOI corrections. This paper investigates the effects of HOI correction caused by the DIPOLE model on coordinate time series. GPS data from 104 globally distributed International GNSS Service （IGS） stations spanning from January, 1999 to December, 2003 were reprocessed following up-to-date processing strategies utilizing GAMIT and GLOBK software. Two coordinate time series solutions before and after applying HOI corrections using the DIPOLE model were derived for studying the effects in terms of seasonal variations and noise amplitudes. The results show that after applying the HOI corrections calculated with DIPOLE, the noise amplitudes of the coordinate time series increased, especially in the north and east directions, and the increased amplitudes of the flicker noise were larger than those of the white noise. Furthermore, spurious periodic signals that were probably introduced by the HOI corrections from the DIPOLE model were also found. Moreover, an apparent increase was confirmed for the power spectra of most of the stations, especially in the north direction, and the amplitudes of both the annual and semi-annual signals also increased in the north and east directions. It can be inferred that the quality of the external data sources such as the geomagnetic model might be the key factors that lead to the above results. The results also suggest that we should be very careful when the DIPOLE model is used for HOI corrections.

Effect of solid-earth-tide on GPS time series

The solid-earth-tide models IERS1992 and IERS2003 are used to analyze some GPS-baseline,vertical-component and zenith-tropospheric-delay data from the Crustal Movement GPS Continuous Observation Net-work of Shandong and IGS stations. The results show that the differences between the baselines computed with the different models are at sub-millimeter level, and the differences in vertical component is direct proportional to station latitude. Also the amplitude of ZTD differences is about 0. 6-1.0 mm, which is 6% -8% of the amplitude of solid-earth-tide differences. Although these effects are quite small, to analyze non-tidal deformation correctly, we should still use a single standard for processing GPS data.

Rapid Fault Analysis by Deep Learning-Based PMU for Smart Grid System

Smart Grids(SG)is a power system development concept that has received significant attention nationally.SG signifies real-time data for specific communication requirements.The best capabilities for monitoring and controlling the grid are essential to system stability.One of the most critical needs for smart-grid execution is fast,precise,and economically synchronized measurements,which are made feasible by Phasor Measurement Units(PMU).PMUs can pro-vide synchronized measurements and measure voltages as well as current phasors dynamically.PMUs utilize GPS time-stamping at Coordinated Universal Time(UTC)to capture electric phasors with great accuracy and precision.This research tends to Deep Learning(DL)advances to design a Residual Network(ResNet)model that can accurately identify and classify defects in grid-connected systems.As part of fault detection and probe,the proposed strategy uses a ResNet-50 tech-nique to evaluate real-time measurement data from geographically scattered PMUs.As a result of its excellent signal classification efficiency and ability to extract high-quality signal features,its fault diagnosis performance is excellent.Our results demonstrate that the proposed method is effective in detecting and classifying faults at sufficient time.The proposed approaches classify the fault type with a precision of 98.5%and an accuracy of 99.1%.The long-short-term memory(LSTM),Convolutional Neural Network(CNN),and CNN-LSTM algo-rithms are applied to compare the networks.Real-world data tends to evaluate these networks.

Underdetermined Blind Source Separation of Adjacent Satellite Interference Based on Sparseness

The problem of underdetermined blind source separation of adjacent satellite interference is proposed in this paper. Density Clustering algorithm(DC-algorithm) presented in this article is different from traditional methods. Sparseness representation has been applied in underdetermined blind signal source separation. However, some difficulties have not been considered, such as the number of sources is unknown or the mixed matrix is ill-conditioned. In order to find out the number of the mixed signals, Short Time Fourier Transform(STFT) is employed to segment received mixtures. Then, we formulate the blind source signal as cluster problem. Furthermore, we construct Cost Function Pair and Decision Coordinate System by using density clustering. At the end of this paper, we discuss the performance of the proposed method and verify the novel method based on several simulations. We verify the proposed method on numerical experiments with real signal transmission, which demonstrates the validity of the proposed method.

Multi-scale interactions in interpersonal coordination

Background:Interpersonal coordination is an essential aspect of daily life,and crucial to performance in cooperative and competitive team sports.While empirical research has investigated interpersonal coordination using a wide variety of analytical tools and frameworks,to date very few studies have employed multifractal techniques to study the nature of interpersonal coordination across multiple spatiotemporal scales.In the present study we address this gap.Methods:We investigated the dynamics of a simple dyadic interpersonal coordination task where each participant manually controlled a virtual object in relation to that of his or her partner.We tested whether the resulting hand-movement time series exhibits multi-scale properties and whether those properties are associated with successful performance.Results:Using the formalism of multifractals,we show that the performance on the coordination task is strongly multi-scale,and that the multi-scale properties appear to arise from interaction-dominant dynamics.Further,we find that the measure of across-scale interactions,multifractal spectrum width,predicts successful performance at the level of the dyad.Conclusion:The results are discussed with respect to the implications of multifractals and interaction-dominance for understanding control in an interpersonal context.

An Improved Inventory Coordination Model in a Multi-stage Multi-customer Supply Chain

To solve the inventory coordination model in a multi-stage, multi-customer supply chain, this paper first analyzes the third model （integer powers of two multipliers at each firm） studied by Moutaz Khouja （2003）, and the authors take a numerical example to prove that the third model is irrational to miss feasible solution. Then this paper puts up a new improved model （integer multiplier at each firm）, and takes the example to prove it gives better results than the integer powers of two multipliers at each firm.

A Novel Multi-objective Protection Coordination Scheme for a Microgrid with Optimal Deployment of Dual-setting ROCOV Based Relays

Relay coordination is crucial in electrical power systems to protect against malfunctions and damage caused by unexpected events like short circuits.To address the challenge associated with the reverse direction of fault current,dual-setting(DS)directional over-current relays have evolved but failed to provide proper coordination during changes of load,generation,and network.In the meantime,with the increasing number of DS relays,the total relay operating time tends to saturate.Therefore,this paper proposes a protection scheme based on the optimal deployment of conventional and dual-setting rate of change of voltage(DS-ROCOV)relays in distribution systems.This holds true for varying network topologies and is unaffected by variations in load and generation.The objective of the proposed scheme is to ensure reliable and efficient protection against faults in distribution systems by minimizing the overall operating time with the optimal number of DS-ROCOV relays.The proposed protection scheme’s performance is evaluated for different coordination time interval values as well as in different microgrid scenarios.This paper outlines the design and implementation of the proposed protection scheme which is validated on the modified IEEE 14-bus system using simulations in Matlab/Simulink.

Coordination of dual setting overcurrent relays in microgrid with optimally determined relay characteristics for dual operating modes

Fault current magnitude in a microgrid depends upon its mode of operation,namely,grid-connected mode or islanded mode.Depending on the type of fault in a given mode,separate protection schemes are generally employed.With the change in microgrid operating mode,the protection scheme needs to be modified which is uneconomical and time inefficient.In this paper,a novel optimal protection coordination scheme is proposed,one which enables a common optimal relay setting which is valid in both operating modes of the microgrid.In this con-text,a common optimal protection scheme is introduced for dual setting directional overcurrent relays(DOCRs)using a combination of various standard relay characteristics.Along with the two variables,i.e.,time multiplier setting(TMS)and plug setting(PS)for conventional directional overcurrent relay,dual setting DOCRs are augmented with a third variable of relay characteristics identifier(RCI),which is responsible for selecting optimal relay characteristics from the standard relay characteristics according to the IEC-60255 standard.The relay coordination problem is formulated as a mixed-integer nonlinear programming(MINLP)problem,and the settings of relays are optimally determined using the genetic algorithm(GA)and the grey wolf optimization(GWO)algorithm.To validate the superiority of the pro-posed protection scheme,the distribution parts of the IEEE-14 and IEEE-30 bus benchmark systems are considered.

Identification and optimization of traffic bottleneck with signal timing

In urban transportation network, traffic congestion is likely to occur at traffic bottlenecks. The signal timing at intersections together with static properties of left-turn and straight-through lanes of roads are two significant factors causing traffic bottlenecks. A discrete-time model of traffic bottleneck is hence developed to analyze these two factors, and a bottleneck indicator is introduced to estimate the comprehensive bottleneck degree of individual road in regional transportation networks universally, the identification approaches are presented to identify traffic bottlenecks, bottleneck-free roads, and bottle- neck-prone roads. Based on above work, the optimization method applies ant colony algorithm with ef- fective green time as decision variables to find out an optimal coordinated signal timing plan for a re- gional network. In addition, a real experimental transportation network is chosen to verify the valida- tion of bottleneck identification. The bottleneck identification approaches can explain the features of oc- currence and dissipation of traffic congestion in a certain extent, and the bottleneck optimization meth- od provides a new way to coordinate signal timing at intersections to mitigate traffic congestion.