A reweighted damped singular spectrum analysis method for robust seismic noise suppression

(Multichannel)Singular spectrum analysis is considered as one of the most effective methods for seismic incoherent noise suppression.It utilizes the low-rank feature of seismic signal and regards the noise suppression as a low-rank reconstruction problem.However,in some cases the seismic geophones receive some erratic disturbances and the amplitudes are dramatically larger than other receivers.The presence of this kind of noise,called erratic noise,makes singular spectrum analysis(SSA)reconstruction unstable and has undesirable effects on the final results.We robustify the low-rank reconstruction of seismic data by a reweighted damped SSA(RD-SSA)method.It incorporates the damped SSA,an improved version of SSA,into a reweighted framework.The damping operator is used to weaken the artificial disturbance introduced by the low-rank projection of both erratic and random noise.The central idea of the RD-SSA method is to iteratively approximate the observed data with the quadratic norm for the first iteration and the Tukeys bisquare norm for the rest iterations.The RD-SSA method can suppress seismic incoherent noise and keep the reconstruction process robust to the erratic disturbance.The feasibility of RD-SSA is validated via both synthetic and field data examples.

基于多模型组合和EIS的锂电池SOH和RUL预测

电池健康状态(state of health, SOH)和剩余使用寿命(remaining useful life, RUL)是评价电池健康程度和剩余寿命的重要技术指标。SOH和RUL的估计是电池管理系统的重要组成部分,是实现电池管理系统智能监控和科学运营的基础。电池电化学阻抗谱(electrochemical impedance spectroscopy, EIS)是一种用于表征电池内部电化学过程的测试方法,它具备精度高和非侵入性损害等优点。多种研究表明,电池阻抗谱EIS与电池的SOH和RUL存在一些内在的联系,因此成为电化学领域的研究热点。基于EIS预测SOH和RUL,传统机器学习方法比较成熟,但预测精度和稳定性仍有局限,难以完全挖掘电池衰减规律。因此,需要与深度学习等方法相结合才能提高预测性能。将降维模型和多种深度学习模型引入SOH和RUL预测领域,并对模型进行有效组合,取得了很好的效果。将EIS所有频率对应的实部和虚部数据依次排列作为频率特征,首先使用主成分分析(principle component analysis, PCA)模型对EIS值进行降维,提炼出10个精炼的主成分,然后使用卷积神经网络(convolution neural network, CNN)模型提取EIS的空间特征,使用双向长短期记忆网络(bidirectional long short-term memory, BiLSTM)模型提取EIS时间序列变化规律,使用注意力(attention)机制进一步选取EIS数据的时空特征中的重要部分,共同预测SOH和RUL。在测试数据上进行实验表明,SOH预测的均方误差(root mean square error, RMSE)达到0.146 8,RUL预测的均方误差达到2.614 5,效果均好于传统的方法。

Periodic signal extraction of GNSS height time series based on adaptive singular spectrum analysis

Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites.

Wideband spectrum sensing using step-sampling based on the multipath nyquist folding receiver

Wideband spectrum sensing with a high-speed analog-digital converter(ADC) presents a challenge for practical systems.The Nyquist folding receiver(NYFR) is a promising scheme for achieving cost-effective real-time spectrum sensing,which is subject to the complexity of processing the modulated outputs.In this case,a multipath NYFR architecture with a step-sampling rate for the different paths is proposed.The different numbers of digital channels for each path are designed based on the Chinese remainder theorem(CRT).Then,the detectable frequency range is divided into multiple frequency grids,and the Nyquist zone(NZ) of the input can be obtained by sensing these grids.Thus,high-precision parameter estimation is performed by utilizing the NYFR characteristics.Compared with the existing methods,the scheme proposed in this paper overcomes the challenge of NZ estimation,information damage,many computations,low accuracy,and high false alarm probability.Comparative simulation experiments verify the effectiveness of the proposed architecture in this paper.

从灰色到绿色 Beton Eisack总部办公室

在2002年的扩建过程中,位于意大利克劳森的Beton-Eisack公司总部加盖了一栋引人注目的办公楼。这栋加盖的办公楼由建筑师Armin Blasbichler和Matthias Rainer设计,从那时起,它便以悬浮的方式成了该公司极具标识性的入口。而本次改建的目标则是希望该办公楼能为公司营造功能高效且体验舒适的办公空间,以满足公司不断变化的需求,同时为公司正在开发和生产的混凝土业务提供合适的舞台。这个全新的空间将主要用于举办研讨会和公司其他活动的开展。

An extended multiple-support response spectrum method incorporating fluid-structure interaction for seismic analysis of deep-water bridges

The effects of ground motion spatial variability(GMSV)or fluid-structure interaction(FSI)on the seismic responses of deep-water bridges have been extensively examined.However,there are few studies on the seismic performance of bridges considering GMSV and FSI effects simultaneously.In this study,the original multiple-support response spectrum(MSRS)method is extended to consider FSI effect for seismic analysis of deep-water bridges.The solution of hydrodynamic pressure on a pier is obtained using the radiation wave theory,and the FSI-MSRS formulation is derived according to the random vibration theory.The influence of FSI effect on the related coefficients is analyzed.A five-span steel-concrete continuous beam bridge is adopted to conduct the numerical simulations.Different load conditions are designed to investigate the variation of the bridge responses when considering the GMSV and FSI effects.The results indicate that the incoherence effect and wave passage effect decrease the bridge responses with a maximum percentage of 86%,while the FSI effect increases the responses with a maximum percentage of 26%.The GMSV and FSI effects should be included in the seismic design of deep-water bridges.

2016—2020年长江科学院发表的科技论文被SCI、EI和CPCI收录情况分析

利用SCI、EI和CPCI三大索引数据库对2016—2020年长江科学院所发表论文进行检索统计,运用文献计量法,从所收录论文的数量、专业、著者、作者群分布情况包括作者群年龄、学历、职称等方面进行统计、归纳和分析,并与前5 a统计数据比较,从产出论文这一侧面了解和反映长江科学院近几年来科研、专业和人才结构情况:科研实力和国际影响力得到较大增强,在保持传统专业科研实力的同时,新兴专业的科研实力也迅速提升,对外合作加强,拥有较高层次的科研人才队伍且趋于年轻化。研究结果可为长江科学院学科建设和科研绩效评估提供数据参考。

基于VBA语言的EI论文跨库引文检索软件的设计与实现

从文献研究来看,国内对于EI文章引用的相关研究缺失。文章介绍了基于VBA语言开发,并通过SeleniumBasic技术实现了EI论文跨库批量引文检索软件的详细设计、实现过程和关键代码,软件填补了国内EI论文跨库批量引文索引软件的空白。

EI/P25/Zr-MOFs异质结的构筑及催化产氢性能

UiO-66-NH_(2)(NUO)因具有优异的水稳定性被用于光催化分解水制氢,但其制氢效率仍有待提升.本文在NUO前驱体溶液中加入2-(2-芴基)-4,5-1-溴二苯基-咪唑(EI)和二氧化钛P25,采用水热法合成EI/P25/NUO异质结.与单一Zr-MOFs和二元EI/NUO相比,EI/P25/NUO异质结可见光驱动的光催化产氢速率可达6530.60μmol·g^(-1)·h^(-1),分别为NUO和EI/NUO产氢速率的304倍和34倍.这是由于EI的引入可有效提高体系中光生载流子的浓度,电子传输层P25则可促进EI产生的光生电子向NUO间的转移,降低光生载流子的复合几率,从而进一步提升光催化分解水制氢性能.

Research on Narrowband Line Spectrum Noise Control Method Based on Nearest Neighbor Filter and BP Neural Network Feedback Mechanism

Thefilter-x least mean square(FxLMS)algorithm is widely used in active noise control(ANC)systems.However,because the algorithm is a feedback control algorithm based on the minimization of the error signal variance to update thefilter coefficients,it has a certain delay,usually has a slow convergence speed,and the system response time is long and easily affected by the learning rate leading to the lack of system stability,which often fails to achieve the desired control effect in practice.In this paper,we propose an active control algorithm with near-est-neighbor trap structure and neural network feedback mechanism to reduce the coefficient update time of the FxLMS algorithm and use the neural network feedback mechanism to realize the parameter update,which is called NNR-BPFxLMS algorithm.In the paper,the schematic diagram of the feedback control is given,and the performance of the algorithm is analyzed.Under various noise conditions,it is shown by simulation and experiment that the NNR-BPFxLMS algorithm has the following three advantages:in terms of performance,it has higher noise reduction under the same number of sampling points,i.e.,it has faster convergence speed,and by computer simulation and sound pipe experiment,for simple ideal line spectrum noise,compared with the convergence speed of NNR-BPFxLMS is improved by more than 95%compared with FxLMS algorithm,and the convergence speed of real noise is also improved by more than 70%.In terms of stability,NNR-BPFxLMS is insensitive to step size changes.In terms of tracking performance,its algorithm responds quickly to sudden changes in the noise spectrum and can cope with the complex control requirements of sudden changes in the noise spectrum.

Energy‐based analysis of seismic damage mechanism of multi‐anchor piles in tunnel crossing landslide area

To study the damage mechanism of multi‐anchor piles in tunnel crossing landslide area under earthquake,the damping performance of multi‐anchor piles was discussed.The energy dissipation springs were used as the optimization device of the anchor head to carry out the shaking table comparison test on the reinforced slope.The Hilbert spectrum and Hilbert marginal spectrum were proposed to analyze the seismic damage mechanism of the multi‐anchor piles,and the peak Fourier spectrum amplitude(PFSA)was used to verify the effectiveness of the method.The results show that the seismic energy is concentrated in the high‐frequency component(30-40Hz)of the Hilbert spectrum and the low‐frequency component(12-30 Hz)of the marginal spectrum.This indicates that they can be combined with the distribution law of the PFSA to identify the overall and local dynamic responses of the multi‐anchored piles,respectively.The stretchable deformation of the energy‐dissipation springs improves the coordination of the multi‐anchor piles,resulting in better pile integrity.The damage mechanism of the multi‐anchor piles is elucidated based on the energy method:local damage at the top and middle areas of the multi‐anchor piles is mainly caused by the low‐frequency component(12-30 Hz)of the marginal spectrum under the action of 0.15g and 0.20g seismic intensities.As the seismic intensity increases to 0.30g,the dynamic response of the slope is further amplified by the high‐frequency component(30-40 Hz)of the Hilbert energy spectrum,which leads to the overall damage of the multi‐anchor piles.

Phase spectrum estimation of the seismic wavelet based on a criterion function

Phase spectrum estimation of the seismic wavelet is an important issue in high-resolution seismic data processing and interpretation. On the basis of two patterns of constant-phase rotation and root transform for wavelet phase spectrum variation, we introduce six sparse criteria, including Lu’s improved kurtosis criterion, the parsimony criterion, exponential transform criterion, Sech criterion, Cauchy criterion, and the modified Cauchy criterion, to phase spectrum estimation of the seismic wavelet, obtaining an equivalent effect to the kurtosis criterion. Through numerical experiments, we find that when the reflectivity is not a sparse sequence, the estimated phase spectrum of the seismic wavelet based on the criterion function will deviate from the true value. In order to eliminate the influence of non-sparse reflectivity series in a single trace, we apply the method to the multi-trace seismogram, improving the accuracy of seismic wavelet phase spectrum estimation.

Seismic design or retrofit of buildings with metallic structural fuses by the damage-reduction spectrum

Recently, the structural fuse has become an important issue in the field of earthquake engineering. Due to the trilinearity of the pushover curve of buildings with metallic structural fuses, the mechanism of the structural fuse is investigated through the ductility equation of a single-degree-of-freedom system, and the corresponding damage-reduction spectrum is proposed to design and retrofit buildings. Furthermore, the controlling parameters, the stiffness ratio between the main frame and structural fuse and the ductility factor of the main frame, are parametrically studied, and it is shown that the structural fuse concept can be achieved by specific combinations of the controlling parameters based on the proposed damage-reduction spectrum. Finally, a design example and a retrofit example, variations of real engineering projects after the 2008 Wenchuan earthquake, are provided to demonstrate the effectiveness of the proposed design procedures using buckling restrained braces as the structural fuses.

Improving the resolution of seismic traces based on the secondary time-frequency spectrum

The resolution of seismic data is critical to seismic data processing and the subsequent interpretation of fine structures. In conventional resolution improvement methods, the seismic data is assumed stationary and the noise level not changes with space, whereas the actual situation does not satisfy this assumption, so that results after resolution improvement processing is not up to the expected effect. To solve these problems, we propose a seismic resolution improvement method based on the secondary time-frequency spectrum. First, we propose the secondary time-frequency spectrum based on S transform （ST） and discuss the reflection coefficient sequence and time-dependent wavelet in the secondary time frequency spectrum. Second, using the secondary time frequency spectrum, we design a two- dimensional filter to extract the amplitude spectrum of the time-dependent wavelet. Then, we discuss the improvement of the resolution operator in noisy environments and propose a novel approach for determining the broad frequency range of the resolution operator in the time- fi＇equency-space domain. Finally, we apply the proposed method to synthetic and real data and compare the results of the traditional spectrum-modeling deconvolution and Q compensation method. The results suggest that the proposed method does not need to estimate the Q value and the resolution is not limited by the bandwidth of the source. Thus, the resolution of the seismic data is improved sufficiently based on the signal-to-noise ratio （SNR）.

Frequency spectrum analysis on micro-seismic signal of rock bursts induced by dynamic disturbance

Blasting and breaking of hard roof are main inducing causes of rock bursts in coal mines with danger of rock burst,and it is important to find out the frequency spectrum distribution laws of these dynamic stress waves and rock burst waves for researching the mechanism of rock burst.In this paper,Fourier transform as a micro-seismic signal conversion method of amplitude-time character to amplitude-frequency character is used to analyze the frequency spectrum characters of micro-seismic signal of blasting,hard roof breaking and rock bursts induced by the dynamic disturbance in order to find out the difference and relativity of different signals.The results indicate that blasting and breaking of hard roof are high frequency signals,and the peak values of dominant frequency of the signals are single.However,the results indicate that the rock bursts induced by the dynamic disturbance are low frequency signals,and there are two obvious peak values in the amplitude-frequency curve witch shows that the signals of rock bursts are superposition of low frequency signals and high frequency signals.The research conclusions prove that dynamic disturbance is necessary condition for rock bursts,and the conclusions provide a new way to research the mechanism of rock bursts.

Seismic performance evaluation of steel frame-steel plate shear walls system based on the capacity spectrum method

This paper presents some methods that the standard acceleration design response spectra derived from the present China code for seismic design of buildings are transformed into the seismic demand spectra, and that the base shear force-roof displacement curve of structure is converted to the capacity spectrum of an equivalent single-degree-of-freedom （SDOF） system. The capacity spectrum method （CSM） is programmed by means of MATLABT.0 computer language. A dual lateral force resisting system of 10-story steel frame-steel plate shear walls （SPSW） is designed according to the corresponding China design codes. The base shear force-roof displacement curve of structure subjected to the monotonic increasing lateral inverse triangular load is obtained by applying the equivalent strip model to stimulate SPSW and by using the finite element analysis software SAP2000 to make Pushover analysis. The seismic performance of this dual system subjected to three different conditions, i.e. the 8-intensity frequently occurred earthquake, fortification earthquake and seldom occurred earthquake, is evaluated by CSM program. The excessive safety of steel frame-SPSW system designed according to the present China design codes is pointed out and a new design method is suggested.

Deep Reinforcement Learning Based Spectrum Prediction for Bursty Bands

Spectrum prediction plays an important role for the secondary user(SU)to utilize the shared spectrum resources.However,currently utilized prediction methods are not well applied to spectrum with high burstiness,as parameters of prediction models cannot be adjusted properly.This paper studies the prediction problem of bursty bands.Specifically,we first collect real Wi Fi transmission data in 2.4GHz Industrial,Scientific,Medical(ISM)band which is considered to have bursty characteristics.Feature analysis of the data indicates that the spectrum occupancy law of the data is time-variant,which suggests that the performance of commonly used single prediction model could be restricted.Considering that the match between diverse spectrum states and multiple prediction models may essentially improve the prediction performance,we then propose a deep-reinforcement learning based multilayer perceptron(DRL-MLP)method to address this matching problem.The state space of the method is composed of feature vectors,and each of the vectors contains multi-dimensional feature values.Meanwhile,the action space consists of several multilayer perceptrons(MLPs)that are trained on the basis of multiple classified data sets.We finally conduct experiments with the collected real data and simulations with generated data to verify the performance of the proposed method.The results demonstrate that the proposed method significantly outperforms the stateof-the-art methods in terms of the prediction accuracy.

基于EIS的质子交换膜燃料电池输出性能优化

质子交换膜燃料电池(proton exchange membrane fuel cell, PEMFC)输出性能的影响是多方面的,极化曲线仅能反映燃料电池稳态外输出特性,不能充分反映具体影响因素及规律,因此需研究其内部物理参数的动态变化。通过建立电堆内阻和交流阻抗特性模型,利用电化学交流阻抗谱(electrochemical impedance spectroscopy, EIS)分析不同温度和湿度下燃料电池的内阻动态特性。结果表明,在333~353 K温度范围内,随着温度的增加,燃料电池的内阻减小;当温度不变时,相对湿度的增加能减小电堆内阻,燃料电池输出性能增强。最后,基于15 kW燃料电池测试平台进行性能试验,验证了燃料电池动态特性分析的正确性,为进一步优化PEMFC输出性能提供理论支持。

Efficacy of Children Neuropsychological and Behavioral Scale in Screening for Autism Spectrum Disorders through a Combination of Developmental Surveillance

Objective This study aimed to explore the clinical value of Children Neuropsychological and Behavioral Scale-Revision 2016(CNBS-R2016)for Autism Spectrum Disorder(ASD)screening in the presence of developmental surveillance.Methods All participants were evaluated by the CNBS-R2016 and Gesell Developmental Schedules(GDS).Spearman’s correlation coefficients and Kappa values were obtained.Taking GDS as a reference assessment,the performance of the CNBS-R2016 for detecting the developmental delays of children with ASD was analyzed with receiver operating characteristic(ROC)curves.The efficacy of the CNBS-R2016 to screen for ASD was explored by comparing Communication Warning Behavior with Autism Diagnostic Observation Schedule,Second Edition(ADOS-2).Results In total,150 children aged 12–42 months with ASD were enrolled.The developmental quotients of the CNBS-R2016 were correlated with those of the GDS(r=0.62–0.94).The CNBS-R2016 and GDS had good diagnostic agreement for developmental delays(Kappa=0.73–0.89),except for Fine Motor.There was a significant difference between the proportions of Fine Motor,delays detected by the CNBS-R2016 and GDS(86.0%vs.77.3%).With GDS as a standard,the areas under the ROC curves of the CNBS-R2016 were above 0.95 for all the domains except Fine Motor,which was 0.70.In addition,the positive rate of ASD was 100.0%and 93.5%when the cut-off points of 7 and 12 in the Communication Warning Behavior subscale were used,respectively.Conclusion The CNBS-R2016 performed well in developmental assessment and screening for children with ASD,especially by Communication Warning Behaviors subscale.Therefore,the CNBS-R2016 is worthy of clinical application in children with ASD in China.

Study of seismic spectrum decomposition based on CEEMD

Empirical mode decomposition( EMD) is a powerful tool of time-frequency analysis. EMD decomposes a signal into a series of sub-signals,called Intrinsic mode functions( IMFs). Each IMF contains different frequency components which can deal with the nonlinear and non-stationary of signal. Complete ensemble empirical mode decomposition( CEEMD) is an improved algorithm,which can provide an accurate reconstruction of the original signal and better spectral separation of the modes. The authors studied the decomposition result of a synthetic signal obtained from EMD and CEEMD. The result shows that the CEEMD has suitability in spectrum decomposition time-frequency analysis. Compared with traditional methods,a higher time-frequency resolution is obtained through verifying the method on both synthetic and real data.