A time domain induced polarization relaxation time spectrum inversion method based on a damping factor and residual correction

Relaxation time spectra （RTS） derived from time domain induced polarization data （TDIP） are helpful to assess oil reservoir pore structures. However, due to the sensitivity to the signal-to-noise ratio （SNR）, the inversion accuracy of the traditional singular value decomposition （SVD） inversion method reduces with a decrease of SNR. In order to enhance the inversion accuracy and improve robustness of the inversion method to the SNR, an improved inversion method, based on damping factor and spectrum component residual correction, is proposed in this study. The numerical inversion results show that the oscillation of the RTS derived from the SVD method increased with a decrease of SNR, which makes it impossible to get accurate inversion components. However, the SNR has little influence on inversion components of the improved method, and the RTS has high inversion accuracy and robustness. Moreover, RTS derived from core sample data is basically in accord with the pore-size distribution curve, and the RTS derived from the actual induced polarization logging data is smooth and continuous, which indicates that the improved method is practicable.

Time-frequency response spectrum of rotational ground motion and its application

The rotational seismic motions are estimated from one station records of the 1999 Jiji （Chi-Chi）, Taiwan, earthquake based on the theory of elastic plane wave propagation. The time-frequency response spectrum （TFRS） of the rotational motions is calculated and its characteristics are analyzed, then the TFRS is applied to analyze the damage mechanism of one twelve-storey frame concrete structure. The results show that one of the ground motion components can not reflect the characteristics of the seismic motions completely; the characteristics of each component, especially rotational motions, need to be studied. The damage line of the structure and TFRS of ground motion are important for seismic design, only the TFRS of input seismic wave is suitable, the structure design is reliable.

Time frequency spectrum of atmospheric turbulence and sweeping hypothesis

The present study is focused on the structure of time frequency spectrum.A scaling law for Eulerian time frequency spectrum and the corresponding temporal structure function are calculated from the sweeping hypothesis and Kolmogorov’s similarity law regarding spatial structure function.An experiment is designed to study this scaling law in the atmospheric turbulent boundary layer.The results well support the conclusion derived from relevant theoretical analysis.

TIME DOMAIN PROCESSING MODE SPREAD SPECTRUM SYSTEM

The construction and specifications of a surface acoustic wave storage correlator are described. A time domain processing mode spread spectrum system is presented. An analysis of the interference rejection for this system is provided. The formula for calculating the probability of error of the system is given. The experimental results agree with the theoretical analysis.

Narrow-band interference excision in spread-spectrum systems using new N-sigma algorithm based on fuzzy threshold

The key to narrow-band interference excision in frequency domain is to determine the excision thresh- old in direct-sequence spread-spectrum （DS-SS） systems. The excision threshold is a non-linear function related to the number and the power of interference, and attempting to get the exact relation of threshold related to the number and the power of interference is almost impossible. The N-sigma algorithm determines the excision threshold using subsection function; however, the excision threshold determined by this method is not exact. A new method to determine the threshold of N-sigma algorithm is proposed. The new method modifies the scale factor N by use of the membership function. The threshold determined by this method is consecutive and smooth, and it is closer to the fact than that of the initial N-sigma algorithm. The GPS signal and single-tone （CW） interference （that is, typical narrow-band interference） are implemented in the simulation, and the results are presented to demonstrate the validity of the new algorithm.

Harmonicity Spectrum

Perceiving harmonic information (especially weak harmonic information) in time series has important scientific and engineering significance. Fourier spectrum and time-frequency spectrum are commonly used tools for perceiving harmonic information, but they are often ineffective in perceiving weak harmonic signals because they are based on energy or amplitude analysis. Based on the theory of Normal time-frequency transform (NTFT) and complex correlation coefficient, a new type of spectrum, the Harmonicity Spectrum (HS), is developed to perceive harmonic information in time series. HS is based on the degree of signal harmony rather than energy or amplitude analysis, and can therefore perceive very weak harmonic information in signals sensitively. Simulation examples show that HS can detect harmonic information that cannot be detected by Fourier spectrum or time-frequency spectrum. Acoustic data analysis shows that HS has better resolution than traditional LOFAR spectrum.

Dynamics of Sea Ice and Spectrum of Ice Force

Spectrum and self-excite characters are the two significant characters of the dynamics of sea ice. The spectrum character of sea ice is mainly shown by the spectrum of ice force. The spectrum character of the sea ice is its intrinsic attributes. When the spectrum of ice force from the dynamic response of ice and structure interaction are evaluated, the effect of dynamic character of the structure must be eliminated. In this paper, the ice force spectrum at Bohai Bay and Liaodong Bay is evaluated from the displacement and strain responses of a single degree and a multi-degree freedom structure. The evaluated ice force spectrum can be used to define the spectrum character of ice in the analysis of ice induced vibration.

Terahertz Time-Domain Spectroscopy and Its Applications

The terahertz time-domain spectroscopy （THz-TDS） system and the related technology and the applications in Capital Normal University are presented. The most often used THz-TDS system as a spectroscopic measurement setup in our lab is introduced in detail, including the THz radiation source, the THz detection method and its measurement, and the control system. THz spectra of various materials is summarized and discussed. These materials include but not limited to two kinds of typical matter-the illegal drugs and explosives. The biological macro-molecules, cosmetics and fine chemical materials, edible pigments and food additives, homocysteic acid and related compounds, heavy ions in soil, Chinese medicines, tobacco and crops, oil and chemical products, carbon nanotubes, superconductors, and various semiconductors and their heterojunctions, are presented. THz emissions from the InAs and InN semiconductors surface are compared. THz spectral investigation of metallic mesh structures is summarized. Finally, an outlook of THz spectroscopic applications is given.

Spectrum Sensing and AM-FM Decomposition through Synchrosqueezing

In this paper we have accomplished one of the tasks of cognitive radio i.e. dynamic spectrum sensing by using wavelet based Synchrosqueezing transform [1], a novel technique, which was proposed to analyze a signal in time-frequency plane. The distinctive feature of this transform compared to other techniques is that it enables us to decompose amplitude and frequency modulated signals and allows individual reconstruction of these components. The objective is also to separate the occupied band into amplitude modulated and frequency modulated bands.

Time-Frequency Signal Processing for Gas-Liquid Two Phase Flow Through a Horizontal Venturi Based on Adaptive Optimal-Kernel Theory

为通过一个水平液体流动测量器的二阶段的流动的一个时间频率信号处理方法基于适应最佳核(AOK ) 在这份报纸被介绍。第一，收集了煤气液体的二阶段的流动的动态微分压力信号是 preprocessed，然后 AOK 理论被用来分析动态微分压力信号。二阶段的流动的机制通过时间频率光谱被讨论。在稳定的水流动率的条件上，与增加煤气的流动率，蛞蝓的从冒泡的流动的流动模式变化流动，同时，然后流动插信号变化表演的精力分发重要变化从 1535 Hz 乐队的那精力转移到 08 Hz 乐队；而且当流动模式是蛞蝓流动时，有二，挥动在时间频率光谱显示出的山峰。最后，很多个典型变量被使用时间频率光谱和 AOK 的山脉定义。当典型变量视觉上被分析时，在典型变量和流动模式的不同联合之间的关系将被得到。结果显示出那，这个方法能在不同流动模式解释流动的法律。并且典型变量，由这个方法定义，能得到对流动信息的清楚的描述。这个方法为流动模式鉴定提供一个新方法，并且正确预言的百分比直到 91.11% 。

Research on Strong Pulsed Electromagnetic Field Test Method by Time-frequency Combination

Many conventional methods of testing strong and pulsed electromagnetic fields,the ones used in radars for example,had deficiencies due to the difficulty in obtaining simultaneous information about the electromagnetic field's peak both in the time domain and in the frequency domain.With regard to this problem,after analyzing the time-domain and the frequency-domain characteristics of radar pulsed signals,we propose a new time-frequency combination test method based on the correction of the test parameters,as well as its correction method at different bandwidths.The test method is applied in a quick test of a high-power pulsed radar signal,and the corrected results have error less than 1 dB in both the time domain and the frequency domain,which indicates that the proposed time-frequency combined method is effective in testing strong and pulsed electromagnetic fields.

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.

Short-time Lv transform and its application for non-linear FM signal detection

A new time-frequency transform, known as short-time Lv transform （STLVT）, is proposed by applying the inverse Lv distribution to process consecutive segments of long data sequence. Compared with other time-frequency representations, the STLVT is able to achieve better energy concentration in the time-frequency domain for signals containing multiple linear and/or non-linear frequency modulated components. The merits of the STLVT are demonstrated in terms of the effects of window length and overlap length between adjacent segments on signal energy concentration in the time-frequency domain, and the required computational complexity. An application on the spectrum sensing for cognitive ratio （CR） by using a joint use of the STLVT and Hough transform （HT） is proposed and simulated.

Adjustable transmission properties through ring-shaped nanotube arrays using finite-difference time-domain method

Metallic ring-shaped nanotube arrays are proposed and its optical transmission properties are studied by using finite-difference time-domain(FDTD) method.Compared with the transmission spectra of conventional circular nanotube arrays,two photonic band gaps are emerged in the transmission spectra of ring-shaped nanotube arrays,the two band gaps and transmission spectra are adjusted by the length,inner radius,intertube spacing and the dielectric constants of the core and embedding medium,and magnitude modification,redshift and blueshift of the resonance modes are observed.A metallic ring-shaped nanotube arrays for subwavelength band-stop filter in the range of visible light can be achieved.To understand its physical origin,field-interference mechanism was suggested by the field distributions.The proposed nanostructures and results may have great potential applications in subwavelength near-field optics.

Effects of sampling frequency on node mobility prediction in dynamic networks: A spectral view

The field of mobility prediction has been widely investigated in the recent past,especially the reduction of the coverage radius of cellular networks,which led to an increase in hand-over events.Changing the cell coverage very frequently,for example,may lead to service disruptions if a predictive approach is not deployed in the system.Although several works examined mobility prediction in the new-generation mobile networks,all of these studies focused on studying the time features of mobility traces,and the spectral content of historical mobility patterns was not considered for prediction purposes as yet.In the present study,we propose a new approach to mobility prediction by analyzing the effects of a proper mobility sampling frequency.The proposed approach lies in the mobility analysis in the frequency domain,to extract hidden features of the mobility process.Thus,we proposed a new methodology to determine the spectral content of mobility traces(considered as signals)and,thus,the appropriate sampling frequency,which can provide numerous advantages.We considered several types of mobility models(e.g.pedestrian,urban,and vehicular),containing important details in the time and frequency domains.Several simulation campaigns were performed to observe and analyze the characteristics of mobility from real traces and to evaluate the effects of sampling frequency on the spectral content.

高速铁路0.01~1 m波段高低轨道不平顺特性分析

随着我国高速铁路发展规模的不断扩大及运营速度的不断提升,轨道短波不平顺引起的振动与噪声问题日益严重。深入研究高速铁路短波不平顺的时域、频域与时频域特征,对精准掌握高速铁路轨道短波平顺状态及其引起的车-轨系统振动、伤损等一系列问题具有重要的参考价值。以某高速铁路实测0.01~1 m波段轨面高低不平顺数据为研究对象,经过数据预处理剔除异常值并消除趋势项后,对实测不平顺数据进行时域分析,得到该高铁线路短波不平顺数据的统计与分布特性。采用平均周期图法计算该高铁线路轨道短波不平顺功率谱密度,应用非线性最小二乘拟合优化算法进行拟合,提出高速铁路轨道短波不平顺谱。从时频域角度对该段数据进行经验模态分解与希尔伯特变换,分析该高铁线路短波不平顺的希尔伯特谱与边际谱。研究结果表明:该高铁线路轨道短波不平顺数据各统计量幅值都较小,且近似服从正态分布;该高铁线路轨道短波不平顺功率谱密度存在与钢轨波磨有关的多个周期性成分,提出的高速铁路短波不平顺谱函数能够很好地对实测功率谱密度进行拟合,且拟合效果优于经典的SATO建议的短波谱与50 kg/m钢轨的短波谱;对该高铁线路轨道可能存在的短波病害进行识别与定位,时频域分析的方法可以较好地应用于高速铁路轨道平顺性的分析与日常的管理维护。

基于STFT-AOK的星箭力学环境等效频谱分析

星箭力学环境的频谱特性研究对于力学试验环境条件设计非常重要。工程上通常基于冲击响应谱变换获得力学环境参数等效频谱,然而该方法受稳态放大系数Q取值的影响较大。为此,文章提出一种基于短时傅里叶变换–自适应优化核函数(STFT-AOK)融合技术的星箭力学环境等效频谱分析方法。研究结果表明:STFT-AOK方法可在AOK准确定位频率成分和瞬态特征时频区域的基础上,结合STFT的准确幅值,构造出频率分辨率高且幅值准确的时频分布,实现力学环境等效频谱的有效获取,适用于各种复杂瞬态星箭力学环境参数的频谱分析。

基于多模态神经网络的微地震事件检测

针对微地震有效信号时序特征存在的局限导致微地震事件识别准确率不高的问题,提出了一种基于多模态学习的神经网络微地震事件检测方法。首先,利用道集数据的相关性以目标道为轴对称制作多道时域模态,对目标道进行时频分析得到S域模态特征;然后,联合时域模态和S域模态设计微地震事件检测神经网络,综合多模态的特征进行训练学习,提高微地震事件识别的精度;最后,为验证方法的有效性,对合成微地震信号进行低信噪比数据分析、小幅值数据分析以及实际油井微地震监测信号事件分析。结果表明,该方法可以有效检测低信噪比及微弱的微地震事件;与支持向量机、卷积神经网络、基于监督机器学习方法的对比实验结果表明该方法具有更高的抗噪性与准确率。

基于界面电荷极化特性的变压器油纸绝缘寿命预测方法研究

准确预测变压器油纸绝缘寿命对于保障电力系统安全稳定运行具有重要意义。根据微观介电响应机制剖析界面极化与油纸绝缘老化的内在机理联系,并基于混合极化模型——一种在扩展德拜模型基础上引入界面极化支路的等效电路拓扑,探究界面电荷极化特性在油纸绝缘寿命预测中的应用。首先,分析温升过程中频谱特性变化背后蕴含的普适弛豫极化规律,基于混合极化模型重构回复电压极化谱。结合温度对主时间常数和模型参数的影响规律,提出一种单一温度测试下的油纸绝缘活化能计算方法,通过界面极化电容构建出频温平移因子。其次,剖析介质损耗因数随老化加深的变化规律,探究损耗峰偏移现象与界面极化弛豫时间的内在联系,凝练全新表征油纸绝缘聚合度含量的频域特征参量——界面极化支路极点Ph2。最后,联合界面极化支路极点Ph2、频温平移因子和损失累积动力学方程构建油纸绝缘寿命预测模型,并将不同运行年限变压器现场实测数据代入模型验证实效性,为油纸绝缘寿命预测提供了一种新思路。

基于频域介电谱曲线分解的氧化锌避雷器老化状态评估

氧化锌避雷器是电力系统的重要组成设备,其老化状态直接关系到对过电压的防护效果,开展氧化锌避雷器的老化状态评估具有重要意义。该文针对氧化锌避雷器内部不均匀老化分布,提出一种基于频域介电谱曲线分解的氧化锌避雷器老化状态评估方法。首先,通过构建氧化锌避雷器介电响应等效电路,研究了氧化锌避雷器频域介电谱分解方法,根据整支避雷器频域介电谱分解可以得到避雷器内部各区域氧化锌阀片的频域介电曲线;其次,利用Havriliak-Negami方程对氧化锌阀片频域介电谱特征参数进行了提取,基于极限学习机建立了氧化锌阀片老化状态评估模型,提出氧化锌避雷器老化评估方法流程;最后,通过多重雷击模拟实验,制备了不同老化状态的氧化锌阀片与避雷器实物样本,对所提老化评估方法进行了分析与验证。结果表明,整支避雷器频域介电谱分解与测试结果的平均误差小于3%,所提方法能够有效地对避雷器频域介电谱进行分解并获取各区域的频域介电谱;针对整支避雷器,该文所提方法对各区域老化状态的评估准确率为93.3%,能够有效地对避雷器进行老化评估。