Optimal Time Shifts Research Articles

Fault Location Based on Comprehensive Grey Correlation Degree Analysis for Flexible DC Distribution Network

Flexible DC distribution networks have a strong capacity for new energy consumption and have received extensive attention from scholars in recent years, but fault location for DC distribution lines is a difficult task. To solve this problem, we propose using a comprehensive grey correlation degree analysis to analyze the similarity of aerial mode traveling differential current waveforms at the first and last ends of a DC line, thus achieving fault location by obtaining the optimal time shift. Additionally, we built a six-terminal flexible DC distribution network model in Matlab/Simulink for simulation and validation, showing that the method can complete the rapid and accurate location of all types of faults on a DC line, and that it possesses an anti-transition resistance capability, making it suitable and highly reliable for cases of low sampling frequency.

Shape Dynamic Time Warping for Seismic Waveform Inversion

ABSTRACT We illustrate shape dynamic time warping (ShapeDTW) for 1D structure waveform inversion with examples from Tanzania, East Africa, and Northeastern Oklahoma. Seismograms of the Mw 5.9 Lake Rukwa, Tanzania, earthquake (18 August 1994) recorded by regional broadband seismographic stations of the Tanzania Broadband Seismic Experiment are used to demonstrate the method. We also test the inversion through solving for 1D crustal velocity structure of the Cherokee Platform in Oklahoma using seismograms of the 2011 Mw 5.7 Prague, Oklahoma, earthquake recorded by the EarthScope Transportable Array. Dynamic time warping (DTW) bypasses the time expense required for manual identification of seismic phases and shows potential for linking discrete seismic phases between two similar waveforms. ShapeDTW improves inversion performance by characterizing the character of the time series near each amplitude point. Applying Sakoe-Chiba band limits to ShapeDTW and an additional amplitude constraint improves the overfitting problem that occurs with the classic DTW method. We apply ShapeDTW to estimate optimal time shifts between observed and synthetic waveforms with time shifts reduced through inversion. The crustal velocity model of Tanzania found using ShapeDTW is close to that found using “phase time inversion” of numerous regional seismic phases observed in the three-component waveforms in a previous study but avoids the necessity of isolating and interpreting different seismic phases in the waveforms. Reducing the ShapeDTW functional misfits can overcome the cycle-skipping problem that often occurs with direct comparison of amplitudes in waveform inversion. This method may be useful in generating starting models for other 1D and 3D inversion methods.

Phased Array Analysis Incorporating the Continuous Wavelet Transform

ABSTRACT Nonlinear block thresholding of the continuous wavelet transform (CWT) of 2D phased array signals offers high time-resolution solutions for analyzing seismograms of local and regional seismic events. An initial denoising step on an array ensemble reveals the regions of the scale-time plane that contain high signal-to-noise arrivals. Individual seismic phase arrivals in ensemble, denoised seismograms can be partitioned using scale-time gating in which CWT wave packets of an individual seismic phase on the scale-time plane for a reference array element are time-correlated with all other elements to find an optimum time shift for the phase across all elements. The seismic phase is then clipped out of the CWT of each array element using this optimal time shift for further analysis. The seismogram can be separated into component seismic waves for a detailed view of wave characteristics such as slowness and arrival azimuth using conventional frequency–wavenumber methods. However, the process can be taken further using the CWT of each phase to construct high time-resolution signal beams over the CWT scale. Local explosion data from the 2016 Incorporated Research Institutions for Seismology (IRIS) Wavefields Community Experiment in northern Oklahoma are used to demonstrate these techniques in separating surface-wave modes and body waves and to examine the scattering of regional phases. High-resolution CWT processing in the 1–3 Hz band for northern Oklahoma reveals horizontal Rayleigh-wave refraction and multipathing. Rayleigh-wave phase-velocity dispersion measurements are used to construct a 1D velocity model under the IRIS experiment. Scale-time gating helps expose near-source surface reflections from a local M 3.6 earthquake that are used to verify the 4 km source depth obtained from a published regional moment tensor solution.

On the Calculation of the Geometric Resolution and Energy Potential of a Bistatic Synthetic Aperture Radar in Geosynchronous Orbit

A model and a software module were developed to analyze the shape of the trajectory described by the subsatellite point on the Earth’s surface depending on eccentricity, perigee angle, and inclination of the geosynchronous orbit (GEO). For various parameters of the satellite’s orbit and synthetic aperture radar (SAR) equipment, we built the dependences of the geometric resolution in the longitudinal (azimuthal) and transverse (relative to the trajectory of the subsatellite point) direction, as well as the radiometric sensitivity of a SAR operating in GEO in the bistatic oblique quasi-specular mode of wave reflection from the Earth’s surface. The optimal time shifts of the orbital positions of two satellites constituting a bistatic pair were found, at which the specified restrictions on the SAR parameters are fulfilled for observation points in a wide area of ​​the Earth’s surface for a long time interval. A generalized assessment of a set of SAR parameters (transmitter and receiver antenna areas, size of the resolution element, and average transmitter power) that provides a given level of radiometric sensitivity is performed.

METHANE IN THE SURFACE LAYER OF THE ATMOSPHERE: CURRENT CONTENT, LONG-TERM TRENDS, AND INTRA-ANNUAL VARIABILITY

The article deals with the empirical analysis of series of monthly mean concentrations of methane in the near-surface layer of the atmosphere from the global network of monitoring stations. They operate within the Global Atmosphere Watch (GAW) under the auspices of the World Meteorological Organization (WMO). The data is freely available at the World Data Center for Greenhouse Gases GAW/WMO (WDCGG) on its website https://gaw.kishou.go.jp/. The temporal coverage is from the 1980s. Data series from 69 stations are considered, of which 22 stations represent global background conditions. The rest of the stations are regional. Long-term trends in concentrations and the intra-annual (inter-monthly) deviations of monthly mean concentrations from long-term trends were studied. The multi-year trend was estimated using a series of 12-month running averages. To exclude systematic differences in methane concentrations, these series were adjusted to the series for the high-latitude Arctic station Alert (82° 30' N, 62° 21' W). The analysis showed that long-term trends are non-linear (in particular, a known pause in the growth of methane levels in 1999-2006 is observed), but are similar at most stations under consideration. Exceptions are six regional stations classified as “abnormal” in terms of methane. Possibly, this abnormality is due to the influence of certain sources of methane (anthropogenic or natural). Long-term trends at the rest of the stations just slightly differ from the average trend for the global stations. The series of intra-annual (inter-monthly) deviations of monthly mean concentrations from long-term trends for many stations (even those located at very significant distances from each other) show high correlative similarity. However, this similarity manifests itself at an optimal time shift from 5 months towards earlier dates up to 6 months towards later dates. The results of the analysis are consistent with the assumption that the intra-annual variability in methane concentration is largely driven by seasonal factors that are significantly related to latitude, such as vertical mixing in the atmosphere and destruction in the troposphere in reactions with hydroxyl. The root-mean-square values of intra-annual (inter-monthly) fluctuations in methane concentration depend significantly on latitude. In general, the higher the latitude is, the greater is the value. The maximum values are reached in the latitudinal belt within 45-50° N, and further to the North the values decrease. This feature of intra-annual fluctuations in the level of methane content may be explained, among other things, by significant inter-seasonal fluctuations in anthropogenic methane emissions occurring at the indicated latitudes in the countries with developed economies located in North America and Western Europe. The correlations of the series of intra-annual (inter-monthly) fluctuations of the monthly mean concentrations of CH4 and CO2 were estimated as rather high, about 0.8, at optimal time shifts, which is observed both at some polar stations and at tropical ones. This confirms the assumption that natural seasonal biogeochemical and geophysical processes play a significant role in the formation of intra-annual (inter-monthly) deviations of methane and carbon dioxide content in the near-surface layer from long-term trends. These processes include vertical mixing of air, CO2 absorption on the Earth’s surface, and destruction of methane in the troposphere in reactions with hydroxyl.

МЕТАН В ПРИПОВЕРХНОСТНОМ СЛОЕ АТМОСФЕРЫ: СОВРЕМЕННОЕ СОДЕРЖАНИЕ, МНОГОЛЕТНИЕ ТРЕНДЫ И ВНУТРИГОДОВАЯ ИЗМЕНЧИВОСТЬ

The article is devoted to the empirical analysis of series of monthly mean concentrations of methane in the near-surface layer of the atmosphere from the global network of monitoring stations. They operate within the Global Atmosphere Watch (GAW) under the auspices of the World Meteorological Organization (WMO). The data is freely available at the World Data Center for Greenhouse Gases GAW/WMO (WDCGG) on its website https://gaw.kishou.go.jp/ . The temporal coverage is from the 1980s. Data series from 69 stations are considered, of which 22 stations represent the global background conditions. The rest of the stations are regional. Long-term trends in concentrations and intraannual (inter-monthly) deviations of mean monthly concentrations from long-term trends were studied. The multi-year trend was estimated using a series of 12-month running averages. To exclude systematic differences in methane concentrations, these series were adjusted to the series for the high-latitude Arctic station Alert (82° 30' N, 62° 21' W). The analysis showed that long-term trends are non-linear (including with a known pause in the growth of methane levels in 1999-2006), but are similar at most of the stations under consideration. Exceptions are 6 regional stations classified as ‘abnormal’ for methane. A possible cause of the abnormality is being under the influence of certain sources of methane (anthropogenic or natural). Long-term trends at the rest of the stations are just slightly differ from the average trend for global stations. The series of intra-annual (inter-monthly) deviations of mean monthly concentrations from long-term trends for many stations, even those located at very significant distances from each other, show high correlative similarity. However, it manifests itself at an optimal time shift from 5 months. towards earlier dates up to 6 months. towards later dates. The results of the analysis are consistent with the assumption that the intra-annual variability in methane concentration is largely driven by seasonal factors that are significantly related to latitude, including vertical mixing in the atmosphere and destruction in the troposphere in reactions with hydroxyl. The root-mean-square values of the intra-annual (inter-monthly) fluctuations in methane concentration significantly depend on latitude. The higher the latitude, the greater the overall value. Maximum values are reached in the latitudinal belt 45-50° N, and further, to the north, the Кузовкин В.В., Семенов С.М. 20 values decrease. This character of intra-annual fluctuations in the level of methane content may be explained, among other things, by significant inter-seasonal fluctuations in anthropogenic methane emissions at the indicated latitudes in countries with developed economies located in North America and Western Europe. The estimates of correlations of the series of intra-annual (inter-monthly) fluctuations of the average monthly concentrations of CH4 and CO2 showed that at optimal time shifts, they are rather high, about 0.8. Moreover, this is observed both at some polar stations and at tropical ones. This confirms the assumption that natural seasonal biogeochemical and geophysical processes play a significant role in the formation of intra-annual (inter-monthly) deviations of the methane and carbon dioxide content in the near-surface layer from long-term trends, namely, vertical mixing of air, CO2 absorption on the Earth's surface, destruction of methane in the troposphere in reactions with hydroxyl.

Noise suppression of microseismic data based on a fast singular value decomposition algorithm

Raw data from microseismic monitoring is usually contaminated with ambient noise, which severely decreases the quality of the data and further affects the accuracy of arrival-based or amplitude-based source imaging performance., and thusThus, noise suppression of microseismic data plays an indispensable role in event detection during hydraulic fracturing. We investigatedeveloped a new way to effectively suppress noise from microseismic data via cross-correlation of traces from multiple microseismic channels. The cross-correlation between a reference trace and all available traces is computed to estimated the optimal time shifts between the waveforms in different channels. When the time shifts are estimated, the microseismic data can be rearranged to enhance the spatial correlation of the microseismic events. Next, a singular value decomposition (SVD) step is applied to extract the eigen-components or eigen-images of the noisy traces and to reject the noise in the data. When neighbor waveforms are too close, a windowed processing strategy is required to obtain well-flattened gather for the SVD processing. Considering that the SVD calculation is computationally expensive, we propose a fast SVD decomposition algorithm by derivation. The proposed method is easy to implement and can obtain robust performance in denoising multi-channel microseismic dataset. We validate the performance on both synthetic and real microseismic datasets. The proposed method can also be combined with active-source seismic data to efficiently suppress strong random background noise.

SkyTEM system calibration: Two systems, one dataset

An extensive AEM survey recently commissioned by Geoscience Australia involved the use of two separate SkyTEM helicopter airborne electromagnetic (AEM) systems collecting data simultaneously. In order to ensure data consistency between the two systems, we follow the Danish example (conceived by the hydrogeophysics group from Aarhus University) of using a hover test site to calibrate the AEM data to a known reference. Since 2001, Denmark has employed a national test site for all electromagnetic (EM) instruments that are used there, including the SkyTEM system. The Lyngby test-site is recognised as a well-understood site with a well-described layered-earth structure of 5 layers. The accepted electrical structure model of the site acts as the reference model, and all instruments are brought to it in order to produce consistent results from all EM systems. Using a ground-based time-domain electromagnetic (TEM) system which has been calibrated at the Lyngby test site, we take EM measurements at a site selected here in Australia. With sufficient information of the instrument, we produce a layered-earth model that becomes the reference model for the two AEM systems used in the survey. We then bring the SkyTEM systems to the hover site and take soundings at multiple altitudes. From the hover test data and the ground based model, we calculate an optimal time shift and amplitude scale factor to ensure that both systems are able reproduce the accepted reference model. Conductivity sections produced with and without calibration factors show noticeably different profiles.

Periodic Flexible Demand: Optimization and Phase Management in the Smart Grid

Based on measurements obtained by commodity wireless sensors, we observe that the majority of thermostatic loads in a user premise are described by periodic pulse waves. We propose a novel first stage of optimization in the smart grid which reduces external on/off command flow for demand response between the controller and the smart appliances. A phase management scheme is developed that defines optimal time shifts on the periodic loads in order to provide peak power and energy cost reduction over a limited time horizon. A gradient descent optimization technique, based on Taylor series, is applied to determine the phases of the pulses in discrete time steps. Three optimization strategies and two control schemes are explored. Minimization of peak power loads, minimization of energy costs and flattening of the power curve are modeled. A centralized and a distributed control scheme are explored. It is found that respectable peak power and cost reduction can be achieved in the centralized control scheme but redundant data transfer in the network and increased complexity is necessary. On the other hand, the distributed control scheme reduces the overall complexity but does not present significant savings.

The effect of rising vs. falling glucose level on amperometric glucose sensor lag and accuracy in Type 1 diabetes

Because declining glucose levels should be detected quickly in persons with Type 1 diabetes, a lag between blood glucose and subcutaneous sensor glucose can be problematic. It is unclear whether the magnitude of sensor lag is lower during falling glucose than during rising glucose. Initially, we analysed 95 data segments during which glucose changed and during which very frequent reference blood glucose monitoring was performed. However, to minimize confounding effects of noise and calibration error, we excluded data segments in which there was substantial sensor error. After these exclusions, and combination of data from duplicate sensors, there were 72 analysable data segments (36 for rising glucose, 36 for falling). We measured lag in two ways: (1) the time delay at the vertical mid-point of the glucose change (regression delay); and (2) determination of the optimal time shift required to minimize the difference between glucose sensor signals and blood glucose values drawn concurrently. Using the regression delay method, the mean sensor lag for rising vs. falling glucose segments was 8.9 min (95%CI 6.1-11.6) vs. 1.5 min (95%CI -2.6 to 5.5, P<0.005). Using the time shift optimization method, results were similar, with a lag that was higher for rising than for falling segments [8.3 (95%CI 5.8-10.7) vs. 1.5 min (95% CI -2.2 to 5.2), P<0.001]. Commensurate with the lag results, sensor accuracy was greater during falling than during rising glucose segments. In Type 1 diabetes, when noise and calibration error are minimized to reduce effects that confound delay measurement, subcutaneous glucose sensors demonstrate a shorter lag duration and greater accuracy when glucose is falling than when rising.

Efficient wavelet prefilters with optimal time-shifts

A wavelet prefilter maps sample values of an analyzed signal to the scaling function coefficient input of standard discrete wavelet transform (DWT) algorithms. The prefilter is the inverse of a certain postfilter convolution matrix consisting of integer sample values of a noninteger-shifted wavelet scaling function. For the prefilter and the DWT algorithms to have similar computational complexity, it is often necessary to use a enough approximation of the prefilter. In addition to well-known quadrature formula and identity matrix prefilter approximations, we propose a Neumann series approximation, which is a band matrix truncation of the optimal prefilter, and derive simple formulas for the operator norm approximation error. This error shows a dramatic dependence on how the postfilter noninteger shift is chosen. We explain the meaning of this shift in practical applications, describe how to choose it, and plot optimally shifted prefilter approximation errors for 95 different Daubechies, Symlet, and B-spline wavelets. Whereas the truncated inverse is overall superior, the Neumann filters are by far the easiest ones to compute, and for some short support wavelets, they also give the smallest approximation error. For example, for Daubechies 1-5 wavelets, the simplest Neumann prefilter provide an approximation error reduction corresponding to 100-10 000 times oversampling in a nonprefiltered system.

Energetic electrons, 50 keV to 6 MeV, at geosynchronous orbit: Their responses to solar wind variations

Using simultaneous measurements of the upstream solar wind and of energetic electrons at geosynchronous orbit, we analyze the response of electrons over a wide energy range, 50 keV to 6 MeV, to solar wind variations. Enhancements of energetic electron fluxes over this whole energy range are modulated by the solar wind speed and the polarity of the interplanetary magnetic field (IMF). The solar wind speed seems to be a dominant controlling parameter for electrons of all energy. Electron enhancements occur after solar wind speed enhancements with a time delay that increases with energy and that also depends on the average polarity of the IMF. The electron enhancements have a shorter delay if the IMF Bz &lt; 0 and a longer delay if the IMF Bz &gt; 0 during the solar wind speed enhancement. The dependence on solar wind condition varies for different energy electrons, with lower‐energy electrons (&lt;200 keV) responding more to the polarity of the IMF and higher energy electrons (&gt;1 MeV) responding more to the solar wind speed. The variations of different energy electrons are well correlated among themselves. For five years, 1995–1999, the correlation coefficients of 1.1–1.5 MeV electrons with lower‐energy electrons, 50–75, 105–150, 225–315, and 500–750 keV, are 0.55, 0.64, 0.74, and 0.90. This correlation is enhanced if a time shift proportional to their energy difference is included. The optimal time shifts and the corresponding correlation coefficients for the four lower energy electrons are 36, 32, 13, and 7 hours and 0.75, 0.77, 0.81, and 0.92, respectively.

ON-LINE MEASUREMENT OF GRAIN QUALITY WITH NIR TECHNOLOGY

A feasibility study was conducted to measure grain quality (moisture and protein content) with near-infrared reflection(NIR) technology on a conventional New Holland TX64 combine harvester. A Zeiss Corona NIR sensor was installedon a bypass unit of the clean grain elevator, and reference samples were taken at the end of the bubble-up auger, which transportsthe grain from the clean grain elevator to the grain bin. Measured signals at the diode array of the spectrophotometerwere highly variable in time, and an appropriate low-pass filter was designed to extract relevant spectra at a sampling rateof 1 Hz. In addition, an optimal time shift was calculated between the location of the NIR measurement and the referencesampling to guarantee an optimal synchronization between the measured spectra and reference values. Preprocessing, calibration,and validation were executed using the PLSplus/IQ module of the GRAMS/32 software package. The calibrationmodels were developed using the PLS algorithm and validated through cross-validation. Cross-validation errors of 0.57%and 0.31% were achieved for the on-line protein and moisture content measurements, respectively. These accuracies are comparablewith the prediction accuracy that was achieved on a similar, but stationary, unit and prove the technical feasibilityof estimating grain quality on-the-go with NIR technology.

Place cells recorded in the parasubiculum of freely moving rats.

Previous studies have identified neurons in the hippocampus, subiculum, and entorhinal cortex which discharge as a function of the animal's location in the environment. In contrast, neurons in the postsubiculum and anterior thalamic nucleus discharge as a function of the animal's head direction in the horizontal plane, independent of its behavior and location in the environment. Because the parasubiculum (PaS) has extensive connections, either directly or indirectly, with these structures, it is centrally located to influence the neuronal activity in these areas. This study was therefore designed to determine the types of behavioral and spatial correlates in neurons from the PaS. Single unit recordings were conducted in the PaS of freely moving rats trained to retrieve food pellets thrown randomly into a cylindrical apparatus. A total of 10.3% of the cells were classified as place cells because they discharged in relation to the animal's location in the cylinder. A large percentage of cells (41.4%) were classified as theta cells. The remaining cells had nondiscernable behavioral correlates. Quantitative analysis of the firing rate maps for the place cells showed they had higher levels of background activity and contained larger firing fields than values reported previously for hippocampal place cells. Directional analysis showed that only three out of 16 cells contained a secondary directional correlate; the firing rate for the remaining cells was not affected by the animal's directional heading within the firing field. A time shift analysis, which shifted the spike time series relative to the animal location series, was conducted to determine whether the quality of the location-specific firing could be improved. The time shifts for three different spatial parameters were optimal when cell discharge led the animal's position. Furthermore, the optimal time shifts for two of these parameters (firing area and information content) were less than the optimal shift reported for hippocampal place cells and suggested that PaS cell discharge lagged behind hippocampal place cell activity. Rotation of the cue card with the animal out of view led to near equal rotation of the firing field when the animal was returned to the apparatus. These results indicate that a small population of cells in the PaS encode the animal's location in its environment, although the representation of space encoded by these cells is different from the type of representation encoded by hippocampal place cells.