An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

With the rapid development of electric power systems,load estimation plays an important role in system operation and planning.Usually,load estimation techniques contain traditional,time series,regression analysis-based,and machine learning-based estimation.Since the machine learning-based method can lead to better performance,in this paper,a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed.First,an image fingerprint construction is proposed for training data.After the data preprocessing,the training data matrix is constructed by the cyclic shift and cubic spline interpolation.Then,the linear mapping and the gray-color transformation method are proposed to form the color image fingerprint.Second,a convolutional neural network(CNN)combined with an attentionmechanism is proposed for training performance improvement.At last,an experiment is carried out to evaluate the estimation performance.Compared with the support vector machine method,CNN method and long short-term memory method,the proposed algorithm has the best load estimation performance.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

Stereo particle image velocimetry measurement of 3D soil deformation around laterally loaded pile in sand

A developed stereo particle image velocimetry(stereo-PIV) system was proposed to measure three-dimensional(3D) soil deformation around a laterally loaded pile in sand.The stereo-PIV technique extended 2D measurement to 3D based on a binocular vision model,where two cameras with a well geometrical setting were utilized to image the same object simultaneously.This system utilized two open software packages and some simple programs in MATLAB,which can easily be adjusted to meet user needs at a low cost.The failure planes form an angle with the horizontal line,which are measured at 27°-29°,approximately three-fourths of the frictional angle of soil.The edge of the strain wedge formed in front of the pile is an arc,which is slightly different from the straight line reported in the literature.The active and passive influence zones are about twice and six times of the diameter of the pile,respectively.The test demonstrates the good performance and feasibility of this stereo-PIV system for more advanced geotechnical testing.

Adaptive diagonal loaded minimum variance beamforming applied to medical ultrasound imaging

In order to enhance the robustness and contrast in the minimum variance(MV) beamformer, adaptive diagonal loading method was proposed. The conventional diagonal loading technique has already been used in the MV beamformer, but has the drawback that its level is specified by predefined parameter and without consideration of input-data. To alleviate this problem, the level of diagonal loading was computed appropriately and automatically from the given data by shrinkage method in the proposed adaptive diagonal loaded beamformer. The performance of the proposed beamformer was tested on the simulated point target and cyst phantom was obtained using Field II. In the point target simulation, it is shown that the proposed method has higher lateral resolution than the conventional delay-and-sum beamformer and could be more robust in estimating the amplitude peak than the MV beamformer when acoustic velocity error exists. In the cyst phantom simulation, the proposed beamformer has shown that it achieves an improvement in contrast ratio and without distorting the edges of cyst.

Porosity Analysis Based on CT Images of Coal Under Uniaxial Loading

According to the character of CT image, surface porosity and voxel porosity are defined from pixel and voxel scale respectively. Digital Terrain Model (DTM) method is applied to calculate the surface porosity, and the method of voxel porosity is also presented based on Industrial CT grey image. With proposed methods, CT images of coal under differ-ent uniaxial loading are analyzed, and the relation curves between two kinds of porosity and stress separately are shown. All of these porosities reflect inner damage of coal. The surface porosity shows the pore with pixel scale, and voxel porosity denotes the pore inner pixel. The voxel porosity reflects the character of CT image better.

Compressional Punch Loading Test of a Polymer Bonded Explosive Simulant Using Digital Image Correlation Method

Punch loading is a loading scenario to study the fracture mechanism of materials at low strain rates.In this paper,three punch loading experimental patterns were chosen for the study of compressional punch loading.A polymer bonded explosive（PBX） simulant was experimentally studied using the digital image correlation（DIC） method.The displacement and strain fields were obtained and the fracture behavior and failure mechanisms of samples were investigated under different punch loading conditions.Moreover,scanning electron microscope（SEM） was used to examine the region of the plastic flow and the damage in the material.The formation of slip bands,shear displacement and fracture of the hard phase particle,were observed on the boundary of the dead zone due to the large shear strains.

Application of Digital Image Correlation and Geodetic Displacement Measuring Methods to Monitor Water Dam Behavior under Dynamic Load

This paper presents experiment results of the measurement conducted at the Roznew Dam power plant. For a course of starting and operating of turbo-plants, downstream face of the dam was monitored in relation to its eventual displacements on direction parallel to the construction axis. For the purpose of the experiment, geodetic measurement techniques and 2D DIC （digital image correlation） method （utilizing photographs of the object recorded with digital camera） were compared with regard to credibility, efficiency and accuracy. The vertical and horizontal displacements were monitored by tachometers measurements. The deformations in x-axis and y-axis on the wall surface was monitored by 2D DIC. It has been noticed that 2D DIC method is a surface method, continuous--not discreet. It allows for continuous observations of surface deformations, which is not possible in case of tachemetric measurements. Despite many advantages, the 2D DIC method lacks unambiguous evaluation of precision and relevance of designated displacements, which is rather significant for possibilities of utilization in technical control of large engineered objects. It should be also marked that the tachometric method is more reliable but is more laborious. Research of this type might comprise additional element for the assessment of the influence of dynamic loads, such as activating turbine water flow, onto the overall condition of the surveyed structure.

Storage and Parallel Loading System Based on Mode Network for Multimode Medical Image Data

Since Multimode data is composed of many modes and their complex relationships,it cannot be retrieved or mined effectively by utilizing traditional analysis and processing techniques for single mode data.To address the challenges,we design and implement a graph-based storage and parallel loading system aimed at multimode medical image data.The system is a framework designed to flexibly store and rapidly load these multimode data.Specifically,the system utilizes the Mode Network to model the modes and their relationships in multimode medical image data and the graph database to store the data with a parallel loading technique.

High-resolution,three-dimensional magnetic resonance imaging axial load dynamic study improves diagnostics of the lumbar spine in clinical practice

BACKGROUND The response to axial physiological pressure due to load transfer to the lumbar spine structures is among the various back pain mechanisms.Understanding the spine adaptation to cumulative compressive forces can influence the choice of personalized treatment strategies.AIM To analyze the impact of axial load on the spinal canal’s size,intervertebral foramina,ligamenta flava and lumbosacral alignment.METHODS We assessed 90 patients using three-dimensional isotropic magnetic resonance imaging acquisition in a supine position with or without applying an axial compression load.Anatomical structures were measured in the lumbosacral region from L1 to S1 in lying and axially-loaded magnetic resonance images.A paired t test atα=0.05 was used to calculate the observed differences.RESULTS After axial loading,the dural sac area decreased significantly,by 5.2%on average(4.1%,6.2%,P<0.001).The intervertebral foramina decreased by 3.4%(2.7%,4.1%,P<0.001),except for L5-S1.Ligamenta flava increased by 3.8%(2.5%,5.2%,P<0.001),and the lumbosacral angle increased.CONCLUSION Axial load exacerbates the narrowing of the spinal canal and intervertebral foramina from L1-L2 to L4-L5.Cumulative compressive forces thicken ligamenta flava and exaggerate lumbar lordosis.

Generalized load graphical forecasting method based on modal decomposition

In a“low-carbon”context,the power load is affected by the coupling of multiple factors,which gradually evolves from the traditional“pure load”to the generalized load with the dual characteristics of“load+power supply.”Traditional time-series forecasting methods are no longer suitable owing to the complexity and uncertainty associated with generalized loads.From the perspective of image processing,this study proposes a graphical short-term prediction method for generalized loads based on modal decomposition.First,the datasets are normalized and feature-filtered by comparing the results of Xtreme gradient boosting,gradient boosted decision tree,and random forest algorithms.Subsequently,the generalized load data are decomposed into three sets of modalities by modal decomposition,and red,green,and blue(RGB)images are generated using them as the pixel values of the R,G,and B channels.The generated images are diversified,and an optimized DenseNet neural network was used for training and prediction.Finally,the base load,wind power,and photovoltaic power generation data are selected,and the characteristic curves of the generalized load scenarios under different permeabilities of wind power and photovoltaic power generation are obtained using the density-based spatial clustering of applications with noise algorithm.Based on the proposed graphical forecasting method,the feasibility of the generalized load graphical forecasting method is verified by comparing it with the traditional time-series forecasting method.

Mechanical properties and failure behavior of rock with different flaw inclinations under coupled static and dynamic loads

The deep fissured rock mass is affected by coupled effects of initial ground stress and external dynamic disturbance.In order to study the effect of internal flaw on pre-stressed rock mechanical responses and failure behavior under impact loading,intact granite specimens and specimens with different flaw inclinations are tested by a modified split Hopkinson pressure bar(SHPB)and digital image correlation(DIC)method.The results show that peak strain and dynamic strength of intact specimens and specimens with different flaw angles(α)decrease with the increase of axial static pressure.The 90°flaw has weak reduction effect on peak strain,dynamic strength and combined strength,while 45°and 0°flaws have remarkable reduction effect.Specimens with 90°flaw are suffered combined shear and tensile failure under middle and low axial static pre-stresses,and suffered shear failure under high axial static pre-stresses.Specimens with 45°and 0°flaws are suffered oblique shear failure caused by pre-existing flaw under different axial static pre-stresses.Besides,based on digital image correlation method,it is found that micro-cracks before formation of macro fractures(include shear and tensile fractures)belong to tensile cracks.Tensile and shear strain localizations at pre-existing flaw tip for specimen with 45°and 0°flaws are produced much earlier than that at other positions.

Bearing characteristics and fatigue damage mechanism of multi-pillar system subjected to different cyclic loads

Aiming to investigate the fatigue damage mechanism and bearing characteristics of multi-pillar system under cyclic loading,a series of axial cyclic loading tests with different cyclic amplitudes were carried out on triple-pillar marble specimens.The acoustic emission(AE)and digital image correlation(DIC)were jointly applied to monitoring and recording damage evolution and failure behavior of each pillar,which reproduced the cataclysmic instability process of underground pillar groups.Experimental results indicated that the cyclic amplitude exceeding the threshold of damage initiation weakened the resistance to deformation,resulting in obvious release of dissipated energy and the reduction of bearing capacity.Conversely,after low-amplitude cyclic loading,both the pre-peak bearing capacity and the post-peak ductility of the pillar system increased due to the compaction of initial defects,indicating that the peak bearing capacity was closely related to the extent of pre-peak fatigue damage.The axial strain of each pillar was measured by DIC virtual extensometer to present the damage extent during cyclic loading phase.Meanwhile,fracture evolution of typical load drop points was also characterized by transverse strain fields(εxx),and observations showed that the damage extent of key pillar undergoing high-amplitude cyclic loads was more serious and violent,accompanied by the ejection of rock debris and loud noises.

Direct loading of atoms from a macroscopic quadrupole magnetic trap into a microchip trap

We demonstrate the direct loading of cold atoms into a microchip 2-mm Z-trap, where the evaporative cooling can be performed efficiently, from a macroscopic quadrupole magnetic trap with a high loading efficiency. The macroscopic quadrupole magnetic trap potential is designed to be moveable by controlling the currents of the two pairs of anti-Helrnholtz coils. The cold atoms are initially prepared in a standard six-beam magneto-optical trap and loaded into the macroscopic quadrupole magnetic trap, and then transported to the atom chip surface by moving the macroscopic trap potential. By means of a three-dimensional absorption imaging system, we are able to optimize the position alignment of the atom cloud in the macroscopic trap and the microchip Z-shaped wire. Consequently, with a proper magnetic transfer scheme, we load the cold atoms into the microchip Z-trap directly and efficiently. The loading efficiency is measured to be about 50%. This approach can be used to generate appropriate ultracold atoms sources, for example, for a magnetically guided atom interferometer based on atom chip.

Morphological evolution and flow conduction characteristics of fracture channels in fractured sandstone under cyclic loading and unloading

In coal mining,rock strata are fractured under cyclic loading and unloading to form fracture channels.Fracture channels are the main flow narrows for gas.Therefore,expounding the flow conductivity of fracture channels in rocks on fluids is significant for gas flow in rock strata.In this regard,graded incremental cyclic loading and unloading experiments were conducted on sandstones with different initial stress levels.Then,the three-dimensional models for fracture channels in sandstones were established.Finally,the fracture channel percentages were used to reflect the flow conductivity of fracture channels.The study revealed how the particle size distribution of fractured sandstone affects the formation and expansion of fracture channels.It was found that a smaller proportion of large blocks and a higher proportion of small blocks after sandstone fails contribute more to the formation of fracture channels.The proportion of fracture channels in fractured rock can indicate the flow conductivity of those channels.When the proportion of fracture channels varies gently,fluids flow evenly through those channels.However,if the proportion of fracture channels varies significantly,it can greatly affect the flow rate of fluids.The research results contribute to revealing the morphological evolution and flow conductivity of fracture channels in sandstone and then provide a theoretical basis for clarifying the gas flow pattern in the rock strata of coal mines.

Exploring CNN Model with Inrush Current Pattern for Non-Intrusive Load Monitoring

Non-Intrusive Load Monitoring(NILM)has gradually become a research focus in recent years to measure the power consumption in households for energy conservation.Most of the existing algorithms on NILM models independently measure when the total current load of appliances occurs,and NILM usually undergoes the problem of signatures of the appliance.This paper presents a distingue NILM design to measure and classify the appliances by investigating the inrush current pattern when the alliances begin.The proposed method is implemented while the five appliances operate simultaneously.The high sampling rate of field-programmable gate array(FPGA)is used to sample the inrush current,and then the current is converted to be image patterns using the kurtogram technique.These images are arranged to be four groups of data set depending on the number of appliances operating simultaneously.Furthermore,the five proposed modifications convolutional neural networks(CNN),which is based on very deep convolutional networks(VGGNet),are designed by adjusting the size to decrease the training time and increase faster operation.The proposed CNNs are then implement as a classification model to compare with the previous models.The F1 score and Recall are used to measure the accuracy classification.The results showed that the proposed system could be achieved at 99.06 accuracy classification.

Modeling Loads Caused by Breaking Waves Striking Vertical Walls

Breaking waves can have tremendous destructive impact on vertical walls, yet they are poorly understood. By using particle imaging velocimetry （PIV） technology and high-precision pressure transducers, actual breaking wave loads on vertical walls were studied. By simultaneously comparing the flow field structure and wave pressure, the mechanisms of breaking wave pressure could be analyzed. The probability distribution of the peak value of the first impact of a breaking wave was investigated. The results showed that the impact pressure p is mainly distributed in the range of 0.25-2.75 pv2, with the greatest possible probability at p/pv2 = 0.75.

Digital Beamforming by Multiple Chirp Zeta Transforms for 3-D Sonar Imaging Systems

The computational load is prohibitive for real-time image generation in 3-D sonar systems, particularly when the steering angle approximation is required. In this paper, a novel multiple Chirp Zeta Transforms （MCZT） beamforming method in frequency domain is being proposed. The single long-length Chirp Zeta Transform （CZT） in the original CZT beamforming is replaced by several CZTs with smaller lengths for different partitions along each dimension. The implementing routine of the algorithm is also optimized. Furthermore, an avenue to evaluate the estimating error for the angle approximation in 3-D imaging applications is presented, and an approach to attain valid partitions for the steering angles is also flhistrated. This paper demonstrates a few advantages of the proposed frequency-domain beamforming method over existing methods in terms of the computatianal complexity.

不同应力路径及围压下煤岩损伤能量演化

为研究煤岩体损伤演化过程中能量的转化机制,以王庄煤矿9105工作面原煤为研究对象,利用HC-SPT-100型高压三轴试验机、HC-U7型非金属超声波探测仪、4K科研相机等仪器,采用非接触式数字图像处理技术开展了不同应力路径及围压下三轴加载试验.研究结果表明:(1)不同应力路径及围压下三轴加载过程中煤岩损伤能量演化可分为压密、弹性与脆性跌落3个阶段;(2)试件在不同加载路径与不同初始围压下各阶段能量值相差较大,表现为在同一初始围压下,常规三轴加载路径下试件的弹性能、耗散能、总能量均大于三轴循环加载路径下试件的弹性能、耗散能、总能量;(3)三轴加载过程中,不同加载路径下试件轴向应变从压密到破坏阶段表现为整体波动与局部集中→局部集中→局部集中→整体波动与局部集中的发展规律;(4)不同加载路径及围压下破坏阶段试件的应力集中不同,常规三轴加载路径下破坏阶段试件的应力集中在低围压下以新生应力集中为主、高围压下以继承应力集中为主,三轴循环加载路径下破坏阶段试件的应力集中在高、低围压下主要以继承应力集中为主.

全景影像快速加载与精确量测算法研究

针对全景影像加载速度慢及量测精度低的问题,提出一种全景球金字塔切片模型动态约束加载算法。首先,基于格网球体投影模型构建三维全景场景;其次,对全景影像进行压缩与切片,并设计全景切片金字塔模型;然后,采用逆向墨卡托投影将全景切片作为纹理映射到球体内表面进行渲染,形成全景球金字塔切片模型;最后,按照可视区域约束对金字塔模型切片进行快速加载实现动态可视化,并结合深度图像实现全景影像的精确量测。实验结果表明,选用顶点数量为11904的全景球金字塔切片模型,量测中误差小于3 cm,同时提高了加载速度。