40 research outputs found

    Researches on Key Algorithms in Analogue Seismogram Records Vectorization

    Get PDF
    Abstract: History paper seismograms are very important information for earthquake monitoring and prediction, and the vectorization of paper seismograms is a very import problem to be resolved. In our study, a new tracing algorithm for simulated seismogram curves based on visual filed feature is presented. We also give out the technological process to vectorizing simulated seismograms, and an analog seismic record vectorization system has been accomplished independently. Using it, we can precisely and speedy vectorize analog seismic records (need professionals to participate interactively)

    Coordinated cyber-physical attack on power grids based on malicious power dispatch

    Get PDF
    This paper proposes a new mode of cyber-physical attack based on injecting false commands, which poses an increasing risk to modern power systems as a typical example of Cyber-Physical Systems (CPS). Such attacks can trigger physical attacks by driving the system into vulnerable states. To address the critical issues arising from this new mode, we define an inverse-community (IC) in power flow distribution and evaluate it using inverse-modularity. To identify the most vulnerable state of the IC that represents the inherent vulnerability of the system, we employ a full malicious power dispatch problem. We also analyze an example of the proposed mode, where a partial malicious power dispatch that maximizes inverse-modularity is combined with physical attacks aimed at disconnecting vulnerable IC boundary lines, making cascading failures highly likely. To demonstrate the potential impact of this coordinated cyber-physical attack, we use the IEEE-118 and IEEE-300 bus systems for simulation. The results show the effectiveness of this attack strategy and provide a new perspective to analyze cyber-physical security issues in modern power systems

    Activity Analysis of the Fuyu North Fault, China: Evidence from the Time-Series InSAR, GNSS, Seismic Reflection Profile, and Plate Dynamics

    Get PDF
    AbstractEarthquake disasters are frequent, and the seismic intensity is large in Northeast China. Earthquake activity research is an important aspect of earthquake disaster management. We chose some unconventional means to study fault activity, to find updated activity evidence. The Ms 5.3 earthquake occurred near the Fuyu North Fault (FNF) of China on May 27, 2018. Using the Sentinel-1B descending orbit data from 2016 to 2019, the line-of-sight (LOS) surface deformation in the study area was calculated by using the small baseline subset (SBAS) method. After transforming to the horizontal EW deformation, the variance component estimation method was used for fusion reconstruction with the EW data of the surrounding GNSS stations. The polynomial least square method is used to fit the fault slip rate of three EW data on the surface trace of the FNF. The fitting results of the three regions show that the horizontal eastward distribution rate of the upper plate is significantly greater than that of the lower plate, which is left-lateral clockwise torsion. The vertical structural deformation caused by the growth strata of the upper and lower plates of the upper SYT2 seismic profile of the FNF is quantitatively calculated, and the thrust rate of the upper plate is 0.2 mm/y relative to that of the lower plate. Based on the Li Siguang chessboard structure model, we found that the compression stress in the north-south direction is gradually weakened, and the compression stress in the east-west direction is gradually enhanced. Through the Coulomb stress analysis, the three events of CMT only induced the historical focal location of the surrounding part. The events of 2017 did not induce the events of 2018, but the events of 2019 were related to the induced effects of 2017 and 2018

    Improving Rock Classification with 1D Discrete Wavelet Transform Based on Laboratory Reflectance Spectra and Gaofen-5 Hyperspectral Data

    No full text
    The high intra-class variability of rock spectra is an important factor affecting classification accuracy. The discrete wavelet transform (DWT) can capture abrupt changes in the signal and obtain subtle differences between the spectra of different rocks. Taking laboratory spectra and hyperspectral data as examples, high-frequency features after DWT were used to improve the discrimination accuracy of rocks. Various decomposition levels, mother wavelet functions, and reconstruction methods were used to compare the accuracy. The intra-class variability was measured using the intra-class Spectral Angle Mapper (SAM). Our results show that the high-frequency features could improve the discrimination accuracy of laboratory spectra by 13.4% (from 46.5% to 59.9%), compared to the original spectral features. The accuracy of image spectra in two study areas increased by 8.6% (from 68.3% to 76.9%) and 7.2% (from 81.3% to 88.5%), respectively. Haar wavelets highlighted the spectral differences between different rocks. After DWT, intra-class SAM reduced and intra-class variability of rocks decreased. The Pearson correlation coefficient indicated a negative correlation between intra-class variability and overall accuracy. It suggested that improving classification accuracy by reducing intra-class variability was feasible. Though the result of lithological mapping still leaves room for improvement, this study provides a new approach to reduce intra-class variability, whether using laboratory spectra or hyperspectral data

    Integrating CFD and GIS into the Development of Urban Ventilation Corridors: A Case Study in Changchun City, China

    No full text
    Given the situation of urban expansion and environmental deterioration, the government and researchers are paying considerable attention to ventilation corridors. The construction of urban ventilation corridors requires quantitative data support. Computational fluid dynamics (CFD) has advantages in the fine assessment of wind environment, and a geographic information system (GIS) has excellent performance in spatial analysis. With Changchun City used as an example, this study proposes the establishment of ventilation corridors on an urban scale to mitigate the urban-heat-island effect, and to accelerate the diffusion of air pollution. CFD simulations provided detailed spatiotemporal characteristics of wind speed and wind direction at various heights. These simulations were useful for identifying potential ventilation corridors. In general, the wind-speed and wind-direction characteristics at a height of 30 m clearly indicated potential ventilation corridors. Potential paths existed in the leading wind and south–north directions. The areas that required improvement were favorably situated in the path of potential ventilation corridors. The main roads, green spaces, and water had good connectivity. A total of five ventilation corridors were constructed, and they will directly affect the poor urban thermal environment, and enhance the mobility of air

    Evaluation of the Performance of Time-Series Sentinel-1 Data for Discriminating Rock Units

    No full text
    The potential use of time-series Sentinel-1 synthetic aperture radar (SAR) data for rock unit discrimination has never been explored in previous studies. Here, we employed time-series Sentinel-1 data to discriminate Dananhu formation, Xinjiang group, Granite, Wusu group, Xishanyao formation, and Diorite in Xinjiang, China. Firstly, the temporal variation of the backscatter metrics (backscatter coefficient and coherence) from April to October derived from Sentinel-1, was analyzed. Then, the significant differences of the time-series SAR metrics among different rock units were checked using the Kruskal–Wallis rank sum test and Tukey’s honest significant difference test. Finally, random forest models were used to discriminate rock units. As for the input features, there were four groups: (1) time-series backscatter metrics, (2) single-date backscatter metrics, (3) time-series backscatter metrics at VV, and (4) VH channel. In each feature group, there were three sub-groups: backscatter coefficient, coherence, and combined use of backscatter coefficient and coherence. Our results showed that time-series Sentinel-1 data could improve the discrimination accuracy by roughly 9% (from 55.4% to 64.4%), compared to single-date Sentinel-1 data. Both VV and VH polarization provided comparable results. Coherence complements the backscatter coefficient when discriminating rock units. Among the six rock units, the Granite and Xinjiang group can be better differentiated than the other four rock units. Though the result still leaves space for improvement, this study further demonstrates the great potential of time-series Sentinel-1 data for rock unit discrimination
    corecore