Selection and modification of ground motion records using Newmark-Hall spectrum as target spectrum for long-period structures

Input ground motions have significant impacts on the uncertainty of structural responses in time-history analysis.In this study,records were selected and scaled for the evaluation of mean structural responses according to the target spectrum.The Newmark-Hall spectrum is closely related to seismic response of short,medium and long-period structures,so it was taken as the target spectrum here.The nonlinear time-history analyses of 9-story and 20-story steel moment-resisting frame structures were carried out as examples.They represent medium and long-period buildings,respectively.Three target spectra with risk of 50%,10%and 2%probabilities for exceedance in 50 years were calculated by the average Newmark-Hall spectrum method for three ground motion sets developed in the SAC Steel Project.The predicted structural mean responses of these Newmark-Hall spectra were compared with those calculated by the average spectral acceleration method for the same record set.It is found that both methods have similar accuracy for estimating the structural mean response.However,the method proposed herein is more effective in reducing the variability of the structural responses.Also,the proposed method is more advantageous for the time-history analysis of long-period structures or structures with more severe nonlinear responses under strong seismic excitations.

Line spectrum detection algorithm based on the phase feature of target radiated noise

In order to improve the performance of line spectrum detection,according to the feature that the underwater target radiated noise containing stable line spectrum,the differences of the phase difference between line spectrum and background noise,a weighted line spectrum detection algorithm based on the phase variance is proposed in frequency domain.After phase difference alignment,the phase variance of line spectrum and the phase of background noise,respectively,are small and big in frequency domain,this method utilizes the weighted statistical algorithm to cumulate the frequency spectrum based on the phase variance,which can restrain the background noise disturbance,and enhance the signal to noise ratio（SNR）.The theory analysis and experimental results both verify that the proposed method can well enhance the energy of line spectrum,restrain the energy of background noise,and have better detection performance under lower SNR.

A method of line spectrum extraction based on target radiated spectrum feature and its post-processing

To improve the ability of detecting underwater targets under strong wideband interference environment,an efficient method of line spectrum extraction is proposed,which fully utilizes the feature of the target spectrum that the high intense and stable line spectrum is superimposed on the wide continuous spectrum.This method modifies the traditional beam forming algorithm by calculating and fusing the beam forming results at multi-frequency band and multi-azimuth interval,showing an excellent way to extract the line spectrum when the interference and the target are not in the same azimuth interval simultaneously.Statistical efficiency of the estimated azimuth variance and corresponding power of the line spectrum band depends on the line spectra ratio(LSR)of the line spectrum.The change laws of the output signal to noise ratio(SNR)with the LSR,the input SNR,the integration time and the filtering bandwidth of different algorithms bring the selection principle of the critical LSR.As the basis,the detection gain of wideband energy integration and the narrowband line spectrum algorithm are theoretically analyzed.The simulation detection gain demonstrates a good match with the theoretical model.The application conditions of all methods are verified by the receiver operating characteristic(ROC)curve and experimental data from Qiandao Lake.In fact,combining the two methods for target detection reduces the missed detection rate.The proposed post-processing method in2-dimension with the Kalman filter in the time dimension and the background equalization algorithm in the azimuth dimension makes use of the strong correlation between adjacent frames,could further remove background fluctuation and improve the display effect.

Target tracking based on frequency spectrum amplitude

The amplitude of frequency spectrum can he integrated with prohabilisfic data association （PDA） to distinguish the target with clutter echoes, especially in low SNR underwater environment. A new target-tracking algorithm is presented which adopts the amplitude of frequency spectrum to improve target tracking in clutter. The prohabilisfic density distribution of frequency spectrum amplitude is analyzed. By simulation, the results show that the algorithm is superior to PDA. This approach enhances stability for the association probability and increases the performance of target tracking.

EFFICIENT STRIP-MODE SAR RAW SIGNAL SIMULATION OF MIXED TARGETS BASED ON ACCURATE 2-D SPECTRUM

An accurate and efficient Synthetic Aperture Radar(SAR)raw data generator is of considerable value for testing system parameters and verifying imaging algorithms.Nevertheless,the existing simulator cannot exactly handle the case of the fast moving targets in high squint geometry.As for the issue,the analytical expression for the two Dimensional(2-D)signal spectrum of moving targets is derived and a fast raw echo simulation method is proposed in this study.The proposed simulator can accommodate the moving targets in the high squint geometry,whose processing steps of the simulation are given in detail and its computational complexity is analyzed.The simulation data for static and moving targets are processed and analyzed,and the results are given to validate the effectiveness of the proposed approach.

Special algorithm of enhancing underwater targetradiated dynamic line spectrum

Performance of traditional adaptive line enhancer （ALE） in suppressing Gaussian noise is low and can get worse at low input signal-to-noise ratio（SNR）. For greatly overcoming these disadvantages, feature of fourth-order cumulant （FOC） different slices for quasi-stationary random process is analyzed, fourth order cumulant（FOC） different slice-based adaptive dynamic line enhancer is presented, and output SNR of the proposed enhancer is derived and bigger than that of the ALE via theoretical analysis. Simulation tests with the underwater moving target-radiated data have shown that the proposed enhancer outperforms the ALE in suppressing Gaussian noise and enhancing dynamic line spectrum feature.

阿南德氏链霉菌FXJ-25的鉴定及对烟草靶斑病的防效

为筛选烟草靶斑病菌拮抗菌,丰富烟草靶斑病生防资源,采用稀释涂布法和平板对峙法进行放线菌分离,筛选得到一株具有明显拮抗效果的菌株FXJ-25。基于培养特性、生理生化特性及16S rDNA基因序列分析相结合的方法对该菌株进行鉴定,分析了其诱导烟草抗性的能力,并通过盆栽试验对其防效进行了研究。结果表明,拮抗菌FXJ-25对烟草靶斑病菌的抑菌率为74.14%,可引起菌丝畸形,经鉴定该菌株为阿南德氏链霉菌(Streptomyces anandii)。FXJ-25具有广谱抗真菌活性,对瓜类蔓枯病菌(Stagonosporopsis cucurbitacearum)、烟草喀斯特炭疽菌(Colletotrichum karstii)和小麦赤霉病菌(Fusarium graminearum)等15种植物病原真菌均具有较好的拮抗作用,抑菌率在53.43%~100%之间。菌株发酵液还可显著提高烟苗苯丙氨酸解氨酶(PAL)、过氧化物酶(POD)、多酚氧化酶(PPO)和过氧化氢酶(CAT)等防御相关酶的活性。盆栽防效中,菌株FXJ-25活菌液(108孢子/mL)对烟草靶斑病具有78.81%的防效。因此,FXJ-25可作为烟草靶斑病的生防材料进一步开发利用。

基于功率谱流形的信息几何DP-TBD算法

针对复杂杂波背景下目标信杂比起伏而导致的漏检问题,本文结合信息几何检测器的性能优势与动态规划检测前跟踪(Dynamic Programming Track Before Detect,DP-TBD)的多帧信息积累能力,提出了基于功率谱流形的信息几何DP-TBD算法.该算法利用功率谱流形与矩阵流形对偶关系,设计了功率谱信息几何检测器,将信息几何检测器的计算复杂度降低了近两个数量级.通过实测数据实验验证,功率谱DP-TBD算法可实现与矩阵DP-TBD算法相近的检测性能,并将运算时间降低为矩阵DP-TBD算法的3%~8%.此外,相较于信息几何检测器,功率谱DP-TBD可将检测信杂比(Signal-to-Clutter Ratio,SCR)提高2~3 dB.

基于CNN和DCGAN的小样本船舶辐射噪声识别方法

文中建立一种基于卷积神经网络(convolutional neural networks,CNN)和深度卷积生成对抗网络(deep convolutional generative adversarial networks,DCGAN)的船舶目标识别方法.通过采集的船舶辐射噪声数据,以梅尔频谱(Mel spectrogram)作为网络的输入特征,使用DCGAN网络对频谱变换后的样本进行扩充,利用微调的VGG16(visual geometry group)网络实现船舶目标分类,实现了网络收敛速度的提升和训练时间的减少.结果表明:采用所提方法可以生成较高质量的频谱样本,提高船舶辐射噪声识别的准确率.

基于时-频注意力机制网络的水声目标线谱增强

为提高被动声纳对水下低噪声安静型目标的检测,研究者开始关注基于深度学习的线谱增强方法,其中,基于LSTM的线谱增强网络由于同时具有时域和频域的非线性处理能力,具有很强的灵活性,然而其性能还需要进一步提升。为此,该文提出了基于时-频注意力机制的网络模型(TFA-Net),通过在LSTM模型的基础上同时增加时域注意力机制和频域注意力机制,充分利用了目标信号在时域和频域的双重重要特征,提升了对LOFAR谱的线谱增强效果。TFA-Net中的时域注意力机制利用LSTM隐藏状态之间的关联性,增加了模型在时域的注意力,频率注意力机制通过将深度残差收缩网络中收缩子网络的全链接层设计为1维卷积层,增加了模型在频域的注意力。相比于LSTM,TFA-Net具有更高的系统信噪比增益:在输入信噪比为–3 dB的情况下,将系统信噪比增益由2.17 dB提升到12.56 dB;在输入信噪比为–11 dB的情况下,将系统信噪比增益由0.71 dB提升到10.6 dB。仿真和实测数据的实验结果表明,TFA-Net可以有效提升LOFAR谱的线谱增强效果,解决低信噪比下水下目标的检测问题。

基于功率谱熵的无线电引信目标与干扰信号分类方法

无线电调频引信在战场环境容易受到干扰信号的干扰导致早炸,丧失打击能力。为提升无线电调频引信抗干扰能力,准确识别引信目标与干扰信号,提出一种基于功率谱熵特征的无线电调频引信目标与干扰信号分类识别方法。利用实测采集的无线电引信检波端输出信号,通过提取目标和干扰信号的功率谱指数熵和Renyi熵特征构成特征向量,作为K邻近(KNN)分类器的输入进行目标和干扰信号分类识别,并利用5-折交叉检验方法对其进行验证。结果表明:目标和干扰信号的功率指数熵和Renyi熵具有显著差异性,使用KNN分类器对其进行分类识别时,最高的识别准确率可达99.47%。

基于肠道菌群和代谢组学探讨“脑肠共治”电针对孤独症大鼠的作用机制

目的观察“脑肠共治”电针对孤独症大鼠的社交能力及对肠道菌群、代谢产物的影响。方法采用丙戊酸钠腹腔注射法制备孤独症大鼠模型,选取造模成功的大鼠随机分为4组,每组10只,分别为模型组、基础电针组、针药结合组、脑肠共治电针组。另外选取10只正常大鼠为对照组。基础电针组予以电针百会、神庭、心俞;针药结合组在基础电针组的基础上再予以益生菌灌胃治疗;脑肠共治电针组在基础电针组基础上再结合电针足三里、曲池。均每日1次,连续4周。采用三箱社交实验评估行为学改变,16S rDNA测序分析肠道菌群分布情况,超高效液相色谱串联质谱分析血浆中的差异代谢组分,并结合Spearman相关性分析进行肠道菌群与代谢组学之间的关联分析。结果与对照组相比,模型组大鼠社交能力和社交新颖性均减弱(P<0.01);与模型组相比,基础电针组、针药结合组、脑肠共治电针组的社交新颖性增强(P<0.01);与基础电针组比较,针药结合组、脑肠共治电针组社交新颖性增强(P<0.01)。肠道菌群研究发现,与对照组比较,模型组的弯曲菌门相对丰度上调,嗜黏蛋白阿克曼菌相对丰度下调;而与模型组相比,针药结合组、脑肠共治电针组的弯曲菌门相对丰度下调,嗜黏蛋白阿克曼菌相对丰度上调。LEfSe分析发现,脑肠共治电针组与模型组共筛选出嗜黏蛋白阿克曼菌等21个关键菌,如与模型组比较,脑肠共治电针组可上调嗜黏蛋白阿克曼菌、卷曲乳杆菌,同时下调梭状芽胞杆菌等。代谢组学分析共筛选出12个差异代谢物,通路分析显示,其主要与氨基酸代谢、磷酸盐代谢、嘌呤代谢、花生四烯酸代谢等通路相关。结论电针百会、神庭、心俞、足三里、曲池对孤独症大鼠社交能力有明显的改善作用,调控肠道菌群如嗜黏蛋白阿克曼菌等菌属丰度,同时影响代谢物水平,且部分代谢物的改变与肠道菌群存在复杂相关性,可能与氨基酸代谢、磷酸盐代谢、嘌呤代谢、花生四烯酸代谢等通路相关。

水通道蛋白4抗体阳性的视神经脊髓炎谱系疾病的防复发治疗

视神经脊髓炎谱系疾病(neuromyelitis optica spectrum disorders,NMOSD)是一种自身免疫介导的主要以视神经炎和横贯性脊髓炎为特征的中枢神经系统疾病。NMOSD的发病主要由水通道蛋白4(aquaporin-4,AQP4)抗体引起,具有高复发、高致残的特点,每次复发都可能导致神经损伤和残疾逐步累积,因此应尽早使用有效的预防复发的药物,从而减少复发率、改善患者的长期预后。目前,随着对NMOSD致病机制的研究不断深入,新兴治疗靶点单克隆抗体药物不断涌现。本文主要就AQP4抗体阳性的NMOSD的慢性期防复发治疗展开综述。

基于信标导引的目标方位估计方法

基于准确测量目标方位进而快速实施救援的需要,采用无线信标、电子磁罗盘和卫导组合技术,设计了一种集发射端信标信号全向发射、接收端信标信号定向接收、数字化声谱处理、干扰野值剔除、信标方位精确测量、信标距离概略估计等功能于一体的户外搜救导引系统;并研究分析了一种基于信标导引的目标方位估计方法,该方法通过接收远程、配属在合作目标端信标发射的声波脉冲信号并进行FFT变换,进而通过分析频谱的特征参数来对目标的方位进行准确测量,对目标的距离进行概略估计;测试结果表明该方法比较适合郊区和城市等户外环境中对合作目标进行快速探测搜救和远程监视的需要。

基于频谱细化和二阶同步压缩变换的船载地波雷达目标检测方法

受船载平台运动、海杂波、多目标聚集以及环境干扰等的影响,海上船只目标的雷达回波极易被遮蔽和淹没,导致船载地波雷达的目标监视监测能力大幅减弱。为提高船载地波雷达对船只目标的检测与发现性能,提出了一种基于频谱细化和二阶同步压缩变换的目标检测方法。该方法首先对船载地波雷达的回波信号进行频率细化处理,提高频率分辨率;然后,通过二阶同步压缩变换的时频分析方法来提取目标的时频分布特征;最终,根据得到的时频分布特征来实现目标检测。实验结果表明:与短时傅里叶变换、小波变换等传统的时频分析方法相比,本文提出的方法不仅具有更好的时频聚集性,而且能有效检测海杂波附近的运动目标以及回波多普勒频率相近的多船只聚集目标。

Spectral Target-Detecting System Using Sine-Wave Modulation

Target detection is one of the key technology of precision chemical application.Previously the digital coding modulation technique was commonly used to emit and receive the optical signal in the target detection systems previously in China.It was difficult to adjust the output power,and the anti-interference ability was weak in these systems.In order to resolve these problems,the target detection method based on analog sine-wave modulation was studied.The spectral detecting system was set up in the aspects of working principle,electric circuit,and optical path.Lab testing was performed.The results showed that the reflected signal from the target varied inversely with detection distances.It indicated that it was feasible to establish the target detection system using analog sine-wave modulation technology.Furthermore,quantitative measurement of the reflected optical signal for near-infrared and visible light could be achieved by using this system.The research laid the foundation for the future development of the corresponding instrument.

MEASUREMENT OF NEUTRON SPECTRA FROM THICK Be TARGET BOMBARDED WITH DEUTERONS

ＭＥＡＳＵＲＥＭＥＮＴＯＦＮＥＵＴＲＯＮＳＰＥＣＴＲＡＦＲＯＭＴＨＩＣＫＢｅＴＡＲＧＥＴＢＯＭＢＡＲＤＥＤＷＩＴＨＤＥＵＴＥＲＯＮＳＷａｎｇＸｉａｏｚｈｏｎｇ（王效忠）；ＢａｉＸｉｘｉａｎｇ（白希祥）；ＬｉＡｎｌｉ（李安利）；ＬｉｕＷｅｉｐｉｎｇ（柳...

基于小波变换的长周期桥梁选波方法研究

时程分析输入地震波的选取对长周期大跨度桥梁影响显著。本文基于规范目标谱,以MATLAB为依托,通过选取最优小波基并利用小波系数迭代法实现频域调整,使地震波反应谱不断逼近给定目标谱,最后结合相对误差和长周期拟合参数两个指标进行综合评价,选取适用于长周期大跨度桥梁的时程分析地震波,提出长周期桥梁全过程批量选波方法。将该方法应用于奉节长江大桥,与基于时域调整方法的Seismo Match选波软件对比选波效果,并将选波结果应用于背景桥梁的时程分析。结果表明,利用本文选波方法所得结构关键截面响应与软件选波所得响应在横桥向和竖桥向存在一定差异。本文方法可为长周期大跨度桥梁时程分析选波提供参考。

Experimental investigation of laser-produced-plasma EUV source based on liquid target

A laser-produced plasma(LPP) source was built using liquid as target and a Nd:YAG laser as the irradiation laser, and the LPP source's radiation with ethanol and acetone target respectively was measured by an AXUV100 silicon photodiode combined with a McPHERSON model 247 grazing incidence monochromator of the resolution Δλ≤0.075 nm and the wavelength scanning interval 0.5 nm. Both ethanol and acetone target LPP source had EUV emission at 11～20 nm wavelength. The comparison between the spectra of the two kinds of target materials shows that all the two kinds of target source's spectra are the result of oxygen ions' transitions under current source's parameters, but the spectrum intensity from different target sources is different. The spectra intensity from the ethanol target is higher than that from the acetone target. In addition, the target liquid is forced into the vacuum chamber by the background pressure supported by the connected external high pressure gas, and the influence of the background pressure on the source's intensity is investigated.

基于多重分形关联和深度CNN的常规雷达目标分类方法

针对传统分类方法中飞机雷达回波信号识别分类精度低、人工定义特征稳定性差的问题,提出基于多重分形关联特征和深度卷积神经网络(convolutional neural network,简称CNN)的雷达目标分类方法.首先,对输入训练数据进行多重分形关联分析,将多重分形关联谱的投影图作为输入特征图;然后,利用深度卷积神经网络对特征进行训练,得到训练模型;最后,使用训练后的模型对目标进行分类.实验结果表明:相对于其他3种方法,该文方法有更强的飞机分类性能.