Parameter estimation of maneuvering targets in OTHR based on sparse time-frequency representation

This paper proposes a new method for estimating the parameter of maneuvering targets based on sparse time-frequency transform in over-the-horizon radar（OTHR）. In this method, the sparse time-frequency distribution of the radar echo is obtained by solving a sparse optimization problem based on the short-time Fourier transform. Then Hough transform is employed to estimate the parameter of the targets. The proposed algorithm has the following advantages： Compared with the Wigner-Hough transform method, the computational complexity of the sparse optimization is low due to the application of fast Fourier transform（FFT）. And the computational cost of Hough transform is also greatly reduced because of the sparsity of the time-frequency distribution. Compared with the high order ambiguity function（HAF） method, the proposed method improves in terms of precision and robustness to noise. Simulation results show that compared with the HAF method, the required SNR and relative mean square error are 8 dB lower and 50 dB lower respectively in the proposed method. While processing the field experiment data, the execution time of Hough transform in the proposed method is only 4% of the Wigner-Hough transform method.

Effect of Process Parameters on Morphology and Grain Refinement Efficiency of TiAl_3 and TiB_2 in Alumimum Casting

This paper presents the effects of different process parameters in producing Al-STi-1B grain refiner,i.e.various sequences and reaction time,on grain refinement efficiency of aluminum castings.It was found that different process parameters resulted in different morphology and size distribution of TiAl-3 and TiB-2 in grain refiner. The experiment was carried out by adding KBF-4 and K-2TiF-6 to molten aluminum.The melting temperature was controlled at 800℃in an electric resistance furnace.Three different sequences of KBF-4 and K-2TiF-6 additions were applied,i.e.,adding KBF-4 before K-2TiF-6,adding K-2TiF-4 before KBF-4 and mixing both KBF-4 and K-2TiF-6 before adding to molten aluminum.Three different holding time at 1 min,30 min and 60 min were applied.The results showed that no significant difference of morphology and size distribution was found by varying three different sequences.Whereas,the different holding time provided major differences in both morphology and size distribution,which are technically expectable from diffusion and agglomeration between particles resulting in larger particle size and wider range of size distribution of TiAI3 and TiB2.If the reaction time was longer than 30 rain,morphology of both TiAl-3 and TiB-2 became too large.If the reaction time was too short,less reaction between TiAl-3 and TiB2 to form would be obtained.For grain refinement efficiency, it was found that mixing KBF-4 and K-2TiF-6 before adding to molten aluminum with a holding time of 30 min resulted in best grain refinement efficiency.

Refined Anam-Net:Lightweight Deep Learning Model for Improved Segmentation Performance of Optic Cup and Disc for Glaucoma Diagnosis

In this work,we aim to introduce some modifications to the Anam-Net deep neural network(DNN)model for segmenting optic cup(OC)and optic disc(OD)in retinal fundus images to estimate the cup-to-disc ratio(CDR).The CDR is a reliable measure for the early diagnosis of Glaucoma.In this study,we developed a lightweight DNN model for OC and OD segmentation in retinal fundus images.Our DNN model is based on modifications to Anam-Net,incorporating an anamorphic depth embedding block.To reduce computational complexity,we employ a fixed filter size for all convolution layers in the encoder and decoder stages as the network deepens.This modification significantly reduces the number of trainable parameters,making the model lightweight and suitable for resource-constrained applications.We evaluate the performance of the developed model using two publicly available retinal image databases,namely RIM-ONE and Drishti-GS.The results demonstrate promising OC segmentation performance across most standard evaluation metrics while achieving analogous results for OD segmentation.We used two retinal fundus image databases named RIM-ONE and Drishti-GS that contained 159 images and 101 retinal images,respectively.For OD segmentation using the RIM-ONE we obtain an f1-score(F1),Jaccard coefficient(JC),and overlapping error(OE)of 0.950,0.9219,and 0.0781,respectively.Similarly,for OC segmentation using the same databases,we achieve scores of 0.8481(F1),0.7428(JC),and 0.2572(OE).Based on these experimental results and the significantly lower number of trainable parameters,we conclude that the developed model is highly suitable for the early diagnosis of glaucoma by accurately estimating the CDR.

Optimization of processing parameters for preparation of Al-3Ti-1B grain refiner

Al-3Ti-1B master alloys were prepared at different processing parameters by the reaction of halide salts,and the grain refining response of Al-7Si alloy was investigated with Al-3Ti-B master alloy.The microstructure of master alloy and its grain refining effect on Al-7Si alloy were investigated by means of OM,XRD and SEM.Experimental results show that,the size of Al3Ti particles presented in Al-3Ti-1B master alloys increases with the increase of reaction temperature and decreases with the increase of cooling rate.The grain refining efficiency of Al-3Ti-1B master alloy on Al-7Si alloy is mainly attributed to heterogeneous nucleation of Al3Ti particles,and the morphology ofα(Al)changes from coarse dendritic to fine equiaxed.As a result,Al-3Ti-1B master alloy is prepared by permanent mold,and holding at 800 ℃for 30min,which has better grain refining performance on Al-7Si alloy.

Semiparametric Regression and Model Refining

This paper presents a semiparametric adjustment method suitable for general cases.Assuming that the regularizer matrix is positive definite,the calculation method is discussed and the corresponding formulae are presented.Finally,a simulated adjustment problem is constructed to explain the method given in this paper.The results from the semiparametric model and G_M model are compared.The results demonstrate that the model errors or the systematic errors of the observations can be detected correctly with the semiparametric estimate method.

Research on LPI radar signal detection and parameter estimation technology

Modern radar signals mostly use low probability of intercept(LPI)waveforms,which have short pulses in the time domain,multicomponent properties,frequency hopping,combined modulation waveforms and other characteristics,making the detection and estimation of LPI radar signals extremely difficult,and leading to highly required significant research on perception technology in the battlefield environment.This paper proposes a visibility graphs(VG)-based multicomponent signals detection method and a modulation waveforms parameter estimation algorithm based on the time-frequency representation(TFR).On the one hand,the frequency domain VG is used to set the dynamic threshold for detecting the multicomponent LPI radar waveforms.On the other hand,the signal is projected into the time and frequency domains by the TFR method for estimating its symbol width and instantaneous frequency(IF).Simulation performance shows that,compared with the most advanced methods,the algorithm proposed in this paper has a valuable advantage.Meanwhile,the calculation cost of the algorithm is quite low,and it is achievable in the future battlefield.

The Time-frequency Characteristic of a Large Volume Airgun Source Wavelet and Its Influencing Factors

Through analyzing the near-field hydrophone records of the airgun experiment in the Jiemian reservoir,Fujian,we study the time-frequency characteristic of airgun source wavelet and the influence of gun depth and firing pressure,and explain the process of bubble oscillation based on the Johnson( 1994) bubble model. The data analysis shows that:( 1) Airgun wavelet is composed of primary pulse and bubble pulse. The primary pulse,which is of large amplitude,short duration and wide frequency band,is usually used in shallow exploration. The bubble pulse,which is concentrated in the low-frequency range,is usually used in deep exploration with deep vertical penetration and far horizontal propagation.( 2) The variation of primary pulse amplitude with gun depth is very small,bubble pulse amplitude and the dominant frequency increase,and peak-bubble ratio and bubble period decrease. When the gun depth is 10 m,primary pulse amplitude and peakbubble ratio are maximum,which is suitable for shallow exploration; when gun depth is25 m,bubble pulse amplitude is large, and peak-bubble ratio is minimum, which is suitable for deep exploration.( 3) The primary pulse amplitude,bubble pulse amplitude,peak-bubble ratio,and bubble period increase and the dominant frequency decreases with increased firing pressure.

Adaptive Time-Frequency Distribution Based on Time-Varying Autoregressive and Its Application to Machine Fault Diagnosis

The time-varying autoregressive （TVAR） modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-invariant problem by introducing a set of basic functions. Then, the parameters are estimated by using a recursive least square algorithm with a forgetting factor and an adaptive time-frequency distribution is achieved. The simulation results show that the proposed approach is superior to the short-time Fourier transform and Wigner distribution. And finally, the proposed method is applied to the fault diagnosis of a bearing , and the experiment result shows that the proposed method is effective in feature extraction.

Rotary impeller refinement of 7075Al alloy

The effects of four parameters, gas flow, rotational speed, refining time, and stewing time, on the rotary impeller refinement of 7075 Al were studied. The effects of C2Cl6 refining, rotary impeller refining, and composite refining of 7075 Al alloy were compared with each other. The results showed that the greatest impact parameter of rotary impeller refinement was rotational speed, followed by gas flow, refining time, and stewing time. The optimum purification parameters obtained by orthogonal analysis were as follows： rotor speed of 400 r/min, inert gas flow of 0.4 mL/h, refining time of 15 min, and stewing time of 6 min. The best degassing effect can be obtained by the composite refining of C2Cl6 and rotary impeller. The degassing rate of C2Cl6, rotary impeller, and composite refining was 34.5%, 69.2%, and 78%, respectively. The mechanical properties of the specimen refined by rotary impeller were higher than those by C2Cl6 refining, but lower than those by composite refining.

Carbide precipitation and microstructure refinement of Cr-Co-Mo-Ni bearing steel during hot deformation

The dynamic recrystallization and carbides precipitation of the Cr-Co-Mo-Ni bearing steel were investigated by hot compression tests performed at temperatures ranging from 850 ℃to 1080 ℃ with strain rate of 1-20 s-1. The activation energy（Q） for the tested steel is calculated to be around 682.99 k J/mol at a deformation strain of 0.6. Microstructural analysis by SEM shows that the dynamic recrystallization（DRX） behavior is dependent sensitively on the deformation strain, temperature and strain rate, while an exponential relationship between DRX grain size and Z parameter is obtained from the computational formula. Moreover, the M6C-type carbides（〈1 μm） act as the main prohibitor of grain coarsening, and the polynomial regression relationship between them is worked out. With electron backscatter diffraction（EBSD） observation, DRX is the main nucleation mechanism responsible for the formation of new grains during hot compression. In conclusion, the interaction between DRX affected by hot deformation parameters and carbides precipitation determines the ultimate grain size refinement.

Refinement of austenite grain using uniform experiment design for AISI H13

The uniform experiment design is an effective way of optimizing technology scheme for refining the grain size during multistage deformation. In this paper, it is adopted to evaluate the effect of each technology parameter on final grain size of AISI H13 hot work tool steel during multistage deformation. It has been verified that the technology scheme for refining the final grain size can be determined rapidly and efficiently with the aid of the uniform design. The results show that the deformation parameters and the intermission time after deformation of the first stage affect the final grain size remarkably. For AISI H13 hot work tool steel, the final grain size can be refined notably when deformation parameters for the first stage are set as follows: a deformation temperature range of 1?025 1?085 ℃; a true strain of above 0.26 and the interpass time between the first and the second stage of deformation less than 10 s.

Productivity simulation of hydraulically fractured wells based on hybrid local grid refinement and embedded discrete fracture model

Using current Embedded Discrete Fracture Models(EDFM) to predict the productivity of fractured wells has some drawbacks, such as not supporting corner grid, low precision in the near wellbore zone, and disregarding the heterogeneity of conductivity brought by non-uniform sand concentration. An EDFM is developed based on the corner grid, which enables high efficient calculation of the transmissibility between the embedded fractures and matrix grids, and calculation of the permeability of each polygon in the embedded fractures by the lattice data of the artificial fracture aperture. On this basis, a coupling method of local grid refinement(LGR) and embedded discrete fracture model is designed, which is verified by comparing the calculation results with the Discrete Fracture Network(DFN) method and fitting the actual production data of the first hydraulically fractured well in Iraq. By using this method and orthogonal experimental design, the optimization of the parameters of the first multi-stage fractured horizontal well in the same block is completed. The results show the proposed method has theoretical and practical significance for improving the adaptability of EDFM and the accuracy of productivity prediction of fractured wells, and enables the coupling of fracture modeling and numerical productivity simulation at reservoir scale.

炼油化工装置PID性能评测与优化系统的设计与实现

根据对装置对象定义分区与KPI,并通过管理端和控制端2个工作平台进行集中、分散部署的方案设计思想,研究开发炼化装置PID性能评测与优化系统,为企业重点生产装置建立PID回路多尺度性能监测与预警、PID控制故障诊断与预知性维护、PID参数自动调优以及PID回路档案等功能应用。该系统能够实时监控PID性能KPI指标值,并智能推荐最优PID参数。试点装置应用效果的标定测试结果表明,PID系统的实际应用效果达到了技术设计指标,模型和算法的适用性、软件的成熟度得到了验证,具备在炼化装置中规模化扩展应用的条件,具有很好的推广应用价值。

安百拓液压凿岩机活塞受力面积分析与三段法述评

搜集了11个安百拓双控式凿岩机和4个后控式凿岩机冲击活塞的直径数据,计算得到在凿岩机冲击运动周期中,回程与冲程活塞受力面积的比值范围。根据比值数据的分析,指出基于三段法理论的设计变量作为凿岩机性能评价指标的普适性较差。据此,本文强调了数据分析在凿岩机研究中的重要作用。文中还介绍了改进的三段法理论及其计算实例,论述了改进的三段法的优点与缺点。

Target parameter estimation for OTFS-integrated radar and communications based on sparse reconstruction preprocessing

Orthogonal time-frequency space(OTFS)is a new modulation technique proposed in recent years for high Doppler wireless scenes.To solve the parameter estimation problem of the OTFS-integrated radar and communications system,we propose a parameter estimation method based on sparse reconstruction preprocessing to reduce the computational effort of the traditional weighted subspace fitting(WSF)algorithm.First,an OTFS-integrated echo signal model is constructed.Then,the echo signal is transformed to the time domain to separate the target angle from the range,and the range and angle of the detected target are coarsely estimated by using the sparse reconstruction algorithm.Finally,the WSF algorithm is used to refine the search with the coarse estimate at the center to obtain an accurate estimate.The simulations demonstrate the effectiveness and superiority of the proposed parameterestimation algorithm.

天然气制乙二醇工艺的模拟与改进优化研究

为提高合成乙二醇(EG)的纯度,减少能源消耗,利用Aspen Plus模拟软件对EG工艺精制段进行模拟和优化。结果表明:(1)利用隔壁塔(DWC)代替常规的双共沸精馏塔对乙二醇、丁二醇(BD)二元体系进行共沸精馏,得到隔壁塔的最佳工艺参数为:原料进料位置25板块、共沸剂进料位置6板块、回流比为5。(2)在隔壁塔最佳工艺参数下,隔壁塔共沸精馏制备的EG纯度与双共沸精馏塔相同,均为99.91%,分离效果较好,同时,可降低能耗44.1%。通过隔壁塔对天然气制乙二醇工艺进行改进,可保证目标产物EG的纯度和产量,并降低能耗。

基于卷积神经网络的水下地形测量误差校正方法

水下地形测量精度对于水下地貌的判断及水下航行安全具有重要意义,测量误差会直接影响对水下地形的判断。因此,本文提出基于卷积神经网络的水下地形测量误差校正方法,对水下地形测量数据误差进行自动识别和校正,从而改善水下地形测量结果。该方法首先依据水下地形测量原理,统计水下地形测量的特征参数,形成特征向量;其次,将其作为基于改进卷积神经网络的输入,通过不断学习和训练,输出变换参数结果,生成新的水下地形测量图像;最后,引入多尺度注意力机制,细化测量图像空间,并对测量图像与标签图像之间的相似度进行计算,依据最大化图像相似度计算结果,校正水下地形测量图像生成过程中的参数。测试结果表明,该方法测量误差均在1.7%以下,能够有效校正测量结果中存在的畸变和误差,精准测量水下地形情况,测量结果与实际结果吻合程度较高。

某电厂1000 MW汽机基础动力参数优化设计研究

以某电厂2×1000 MW汽轮发电机组为工程背景,开展汽机基础动力参数优化设计研究。针对汽机转子动力响应过大而不利于汽机正常工作的问题,采用ANSYS软件建立汽机基础结构整体有限元模型,依次开展汽机基础动力特性和强迫振动响应分析,分别讨论增加短柱、短柱宽度和L型梁高度对汽机基础动力响应产生的影响。结果表明:在汽机基础有限元建模中可采用增加附加质量及刚域的方式模拟转子和静子的刚度、质量贡献;分别增设梁间短柱和增加横梁高度,能够有效降低转子动力响应;研究结果可为汽机基础精细化建模与降低汽机转子振动响应提供参考。

精碲生产脱锡工艺改进研究

针对原料含锡升高,采用电解废液脱锡无法满足4N精碲生产要求,通过试验研究,改进脱锡工艺,降低进入碲电积过程的锡量。与传统脱锡工艺相比,新工艺符合生产控制要求,达到了脱除锡的目的,避免了碲电积过程中锡不断富集可能造成的产品品质波动,同时简化工艺流程,提高碲直收率,降低碱耗。

一种炼化装置控制回路与工艺参数故障预警系统

针对炼化装置中关键回路和关键工艺参数的异常,构建了一套故障预警系统。该系统由两部分组成:基于支持向量描述的控制回路异常诊断,基于参数平稳性判定和滚动数据SVDD的参数趋势诊断。前者通过建立支持向量数据描述的超球异常检测模型来诊断控制回路的工况变化和异常工况;后者通过构建滚动矩阵进行特征提取,再进行标准差计算和波动相似性的比较,用于检测工艺参数在短期时间内的异常波动和异常趋势。所建立的系统能够快速发现控制回路因工况变化导致的异常参数实时极端趋势和大幅度波动,并动态显示于DCS界面提示工艺人员进行紧急维护和故障处理。