Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

High-precision automatic measurement of two-dimensional geometric features based on machine vision

To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view （FOV） images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0. 03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.

Two-dimensional regularized inversion of AMT data based on rotation invariant of Central impedance tensor

Considering the uncertainty of the electrical axis for two-dimensional audo-magnetotelluric(AMT) data processing, an AMT inversion method with the Central impedance tensor was presented. First, we present a calculation expression of the Central impedance tensor in AMT, which can be considered as the arithmetic mean of TE-polarization mode and TM-polarization mode in the twodimensional geo-electrical model. Second, a least-squares iterative inversion algorithm is established, based on a smoothnessconstrained model, and an improved L-curve method is adopted to determine the best regularization parameters. We then test the above inversion method with synthetic data and field data. The test results show that this two-dimensional AMT inversion scheme for the responses of Central impedance is effective and can reconstruct reasonable two-dimensional subsurface resistivity structures. We conclude that the Central impedance tensor is a useful tool for two-dimensional inversion of AMT data.

Comparison of different inversion methods of D-T_(2)two-dimensional nuclear magnetic resonance logging and applicability analysis

D-T_(2)two-dimensional nuclear magnetic resonance(2D NMR)logging technology can distinguish pore fluid types intuitively,and it is widely used in oil and gas exploration.Many 2D NMR inversion methods(e.g.,truncated singular value decomposition(TSVD),Butler-Reds-Dawson(BRD),LM-norm smoothing,and TIST-L1 regularization methods)have been proposed successively,but most are limited to numerical simulations.This study focused on the applicability of different inversion methods for NMR logging data of various acquisition sequences,from which the optimal inversion method was selected based on the comparative analysis.First,the two-dimensional NMR logging principle was studied.Then,these inversion methods were studied in detail,and the precision and computational efficiency of CPMG and diffusion editing(DE)sequences obtained from oil-water and gas-water models were compared,respectively.The inversion results and calculation time of truncated singular value decomposition(TSVD),Butler-Reds-Dawson(BRD),LM-norm smoothing,and TIST-L1 regularization were compared and analyzed through numerical simulations.The inversion method was optimized to process SP mode logging data from the MR Scanner instrument.The results showed that the TIST-regularization and LM-norm smoothing methods were more accurate for the CPMG and DE sequence echo trains of the oil-water and gas-water models.However,the LM-norm smoothing method was less time-consuming,making it more suitable for logging data processing.A case study in well A25 showed that the processing results by the LM-norm smoothing method were consistent with GEOLOG software.This demonstrates that the LM-norm smoothing method is applicable in practical NMR logging processing.

Application of Automatic Diagnostic Analysis on Atmospheric Horizontal Inversion Area and Freezing Rain Falling Area

The automatic diagnostic analysis on atmospheric horizontal inversion area is realized through changing the single atmospheric inversion into horizontal one based on the sounding data in Micaps system;the basic conceptual model INCLUDING atmospheric horizontal inversion area,ground 0 ℃ line,high altitude wet area,extreme point 0 ℃ line in inversion layer is buillt after the research on relationship between atmospheric horizontal inversion area and freezing rain falling area;automatic diagnostic analysis on freezing rain falling area is developed based on the conceptual model,the method is in accord well with the actual situation (freezing rain disaster weather occurred in most part of the south in beginning of 2008) and fitting rate reaches 94.4%,quantitative correlation coefficient between the area of freezing rain falling area and stations reporting freezing rain is 0.839.

An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

This study presents a method for the inverse analysis of fluid flow problems.The focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like viscosity.The primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and grains.The lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end backpropagation.Our AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid viscosity.The method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

Research into the inversion of the induced polarization relaxation time spectrum based on the uniform amplitude sampling method

The induced polarization relaxation time spectrum（RTS） reflects the distribution of rock pore size,which is a key factor in estimating the oil or water storage capacity of strata.However,as the data acquisition and transmission abilities of well logging instruments are much limited due to the underground environment,it is necessary to explore suitable sampling methods which can be used to obtain an accurate RST with less sampling data.This paper presents a uniform amplitude sampling method（UASM）,and compares it with the conventional uniform time sampling method（UTSM） and logarithm time sampling method（LTSM） in terms of the adaptability to different strata,RTS inversion accuracy,and stratum vertical resolution.Numerical simulation results show that the UASM can obtain high inversion accuracy of RTS with different kinds of pore size distribution formation,with high dynamic ranges of pore size,and with a small number of sampling points.The UASM,being able to adapt to the attenuation speed of polarization curve automatically,thus has the highest vertical resolution.The inversion results of rock samples also show that the UASM is superior to the UTSM and LTSM.

THE TRANSIENT TWO-DIMENSIONAL FLOW THROUGH DOUBLE POROUS MEDIA

This paper presents the analytical solutions in Laplace domain for two-dimensional nonsteady flow of slightly compressible liquid in porous media with double porosity by using the methods of integral transforms and variables separation. The effects of the ratio of storativities to , interporosity flow parameter on the pressure behaviors for a vertically fractured well with infinite conductivity are investigated by using the method of numerical inversion. The new log-log diagnosis graph of the pressures is given and analysed.

Automatic Optimization of Chirp Setting Parameters in Medical Ultrasound Contrast Imaging

Medical ultrasound contrast imaging is a powerful modality undergoing successive developments in the last decade to date Lately, pulse inversion has been used in both ultrasound tissue harmonic and contrast imaging. However, there was a tradeoff between resolution and penetration. Chirp excitations partially solved the tradeoff, but the chirp setting parameters were not optimized. The present work proposes for the first time combining chirp inversion with ultrasound contrast imaging, with the motivation to improve the contrast, by automatically optimizing the setting parameters of chirp excitation, it is thus an optimal command problem. Linear chirps, 5 μm diameter microbubbles and gradient ascent algorithm were simulated to optimize the chirp setting parameters. Simulations exhibited a gain of 5 dB by automatic optimization of chirp inversion relative to pulse inversion. The automatic optimization process was quite fast. Combining chirp inversion with ultrasound contrast imaging led to a maximum backscattered power permitting high contrast outcomes and optimum parameters.

基于双阵元天线的ADS-B解交织投影算法

随着广播式自动相关监视(Automatic Dependent Surveil lance-Broadcast,ADS-B)技术的普及,交通密集区域内多条ADS-B信号的交织问题难以避免。为了降低设备成本并提高系统在低成本条件下的可用性,针对双阵元天线三条ADS-B信号交织问题,提出了双阵元天线投影算法。首先,上述方法基于频域插值理论与最小描述长度准则进行信源数估计;然后,采用功率倒置算法进行空域滤波,在未知信号波达方向的条件下抑制非期望信号,从而将双天线三信号的解交织问题转化为单天线双信号的解交织问题;最后,由虚拟多通道法扩维后,基于改进的投影算法分离交织信号。仿真验证了以上算法的有效性。

Atomscopic of ripple origins for two-dimensional monolayer transition metal dichalcogenides

During the development of ultrathin two-dimensional(2D)materials,the appearance of ripples has been widely observed.However,the formation mechanisms and their influences are still rarely investigated,especially their contributions to the electronic structures and optical properties.To compensate for the knowledge gap,we have carried out comprehensive theoretical studies on the monolayer WSe_(2) with a series of ripple structures from 0 to 12Åin different lattice sizes.The sensitivity of the formation energy,band structures,electronic structures,and optical properties to the ripple structures have been performed systematically for the first time.The formation of ripples in Armchair and zigzag simultaneously are more energetically favorable,leading to more flexible optimizations of the optoelectronic properties.The improved charge-locking effect and extension of absorption ranges indicate the significant role of ripple structures.The spontaneous formation of ripples is associated with orbital rearrangements and structural distortions.This leads to the unique charge carrier correlate inversion between W-5d and Se-4p orbitals,resulting in the pinning of the Fermi level.This work has supplied significant references to understand ultrathin 2D structures and benefit their future developments and applications in high-performance optoelectronic devices.

Deep learning in two-dimensional materials:Characterization,prediction,and design

Since the isolation of graphene,two-dimensional(2D)materials have attracted increasing interest because of their excellent chemical and physical properties,as well as promising applications.Nonetheless,particular challenges persist in their further development,particularly in the effective identification of diverse 2D materials,the domains of large-scale and highprecision characterization,also intelligent function prediction and design.These issues are mainly solved by computational techniques,such as density function theory and molecular dynamic simulation,which require powerful computational resources and high time consumption.The booming deep learning methods in recent years offer innovative insights and tools to address these challenges.This review comprehensively outlines the current progress of deep learning within the realm of 2D materials.Firstly,we will briefly introduce the basic concepts of deep learning and commonly used architectures,including convolutional neural and generative adversarial networks,as well as U-net models.Then,the characterization of 2D materials by deep learning methods will be discussed,including defects and materials identification,as well as automatic thickness characterization.Thirdly,the research progress for predicting the unique properties of 2D materials,involving electronic,mechanical,and thermodynamic features,will be evaluated succinctly.Lately,the current works on the inverse design of functional 2D materials will be presented.At last,we will look forward to the application prospects and opportunities of deep learning in other aspects of 2D materials.This review may offer some guidance to boost the understanding and employing novel 2D materials.

基于ARD-AVA反演的含气性预测技术及应用

为进一步优化AVA反演技术以提高储层含气性预测精度,需要解决反演方法中先验的选择和AVA反演近似式与部分叠加策略的选择两个关键问题。为此,利用自动相关判别(ARD)先验中的超参数从不同地震道估计可变的特定值,而不再用固定值(如高斯先验、柯西先验等)约束反演过程,可以在含气性预测时更好地反映储层地质特征的横向变化,获得高精度预测结果;在AVA反演近似式与部分叠加策略的选择时,参考了两个标准(参数灵敏度和条件数),给出反演近似式和最大、最小角度与角度间隔的选择建议。提出的ARD-AVA反演方法和近似式与部分叠加优选策略,在河道类型气藏含气性预测中效果很好。通过与传统方法的预测结果对比,结合测井和生产数据,证明了该方法的可行性和优势。

Real-Time Automatic Scaling Method of Oblique Ionogram Parameters Based on Morphological Operator and Inversion Technique

Automatic scaling ionogram can get the parameters of ionogram which are vital to ionosphere detecting. In this paper, a new method is proposed to scale F2 layer trace automatically from oblique ionogram based on morphological operator and inversion technique. This method is verified through the comparison of actual detecting data with statistical analysis. The results show that the proposed automatic scaling method has high acceptable rate and is suitable for scaling oblique ionogram with different high angle wave states. It is fast and precise to fit O-mode echoes in F2 layer without the influence from F1 layer. This method could be applied in real-time ionospheric oblique sounding research with high reliability and versatility.

APPLICATION OF DIRECT BTT GUIDANCE LAW BASED ON NONLINEAR INVERSE SYSTEM THEORY TO INTEGRATED FIRE／FLIGHT SYSTEMS（IFFS）

To counter BTT guidance mode, new relative motion equations of the targetaircraft and the attack aircraft are proposed. The inverse system theory of the nonlinearcontrol is used, and the direct BTT-180 guidance command is solved, which can operatethe attack aircraft to automatically complete the flight mission of the preceding stage ofthe terminal weapon delivery, and thus the automatic attack is extended from the stage ofthe terminal weapon delivery to the preceding stage of the terminal weapon delivery.

Dynamic inverse control of feedback linearization in ballistic correction based on nose cone swinging

It is a complicated nonlinear controlling problem to conduct a two-dimensional trajectory correction of rockets.By establishing the aerodynamic correction force mathematical model of rockets on nose cone swinging,the linear control is realized by the dynamic inverse nonlinear controlling theory and the three-time-scale separation method.The control ability and the simulation results are also tested and verified.The results show that the output responses of system track the expected curve well and the error is controlled in a given margin.The maximum correction is about±314 m in the lengthwise direction and±1 212 m in the crosswise direction from the moment of 5 s to the drop-point time when the angle of fire is 55°.Thus,based on the dynamic inverse control of feedback linearization,the trajectory correction capability of nose cone swinging can satisfy the requirements of two-dimensional ballistic correction,and the validity and effectiveness of the method are proved.

基于AIS信号的低空大气波导监测试验分析

鉴于低空大气波导对海上工作的雷达、通信系统的显著影响,提出了基于实测船舶自动识别系统(automatic identification system, AIS)信号的海上低空大气波导遥感新方法.首先讨论了不同大气折射环境下的AIS信号传播特性,验证了低空大气波导尤其表面波导对海上实际VHF频段AIS信号的显著影响;然后给出了2018年4月20日以及22日岸基AIS接收机接收功率平面位置分布图结果,利用接收站附近探空站的修正大气折射率剖面验证了大气波导是形成AIS信号远距离传播的主要原因;最后给出了基于AIS信号反演低空大气波导的步骤,采用粒子群优化算法得到根据单一方位接收功率的反演结果.该方法具有被动接收、时空分辨率高的优点,是当前雷达海杂波、卫星导航信号遥感探测大气波导的有益补充.

基于改进PF算法的ADS-B风场反演

将装载自动相关监视广播(ADS-B)机载端的民航飞机视作传感器,利用ADS-B下行数据实施风场反演是近年来新颖的风场探测手段之一。现有的反演算法在飞机小角度转弯情况下存在精度不高的问题,大面积空间风场重建也对风场探测提出了新的挑战。针对上述问题,利用数据的几何结构和Kullback-Leibler Divergence(KLD)采样对粒子滤波(Particle Filter,PF)算法进行改进,该算法通过结合ADS-B数据对航线上的固定位置不同高度层上风矢量进行反演,构造垂直风廓线,并与欧洲中期天气预报中心气象数据作对比,验证了算法的可行性与准确性;最后,利用气象粒子(Meteo-Particle,MP)模型对航线外大面积的风矢量进行估计。实验结果表明,该方法能够反映真实的风场。

基于STM32的柑橘采摘机器人

为了提高农业自动化程度,设计一款柑橘采摘机器人.机械结构由串口舵机控制的六轴机械臂和履带车底盘组成,在夹爪处安装双摄像头分别实现无线图传、柑橘识别及定位,在摄像头集成板上设计光照检测和灯光控制电路对识别环境进行自动调光.设计了遥控手柄,可对机器人进行手动控制和参数校正,采用PID算法和运动学逆解并通过与摄像头通讯实现目标自动抓取.反复实验验证表明,该柑橘采摘机器人抓取成功率高,稳定性好、适应性强.

智能锚注一体台车钻臂运动学研究

为实现在作业过程中的钻臂自动定位,对智能锚注一体台车钻臂运动学进行研究。以钻臂机械结构为依据,运用D-H方法建立了8自由度钻臂的运动学方程。基于蒙特卡洛法分析钻臂的可达工作空间,在MATLAB中仿真出钻臂的工作空间云图和投影图。根据钻臂的结构特点和关节运动范围提出了一种钻臂运动学逆解算法。针对大断面隧道锚杆作业过程,在台车理想状态和倾斜状态下对钻臂运动学逆解算法进行验证。结果表明:(1)智能锚注一体台车钻臂可达工作空间可以满足大部分隧道施工使用需求;(2)钻臂逆运动学算法计算效率高,在台车理想状态和倾斜状态下均表现良好。