基于试验的电动舵机模型辨识

目前电动舵机模型的建立基本上是基于理论的数学推导,所建立的舵机模型与实际舵机模型存在一定的误差。针对此问题,提出一种基于试验实测数据建立舵机模型的方法,搭建自动数据采集试验平台,采用组合窗法对实测数据进行频域转换,得到舵机的频率响应函数并采用非线性最小二乘法辨识舵机模型。对辨识得到的数学仿真结果与实际舵机响应比较,在频域,整个频段内幅频特性最大绝对误差1.9 dB;在时域,仿真模型跟踪实际舵机角度的最大误差1.5°,延迟时间10 ms。结果表明,基于试验数据建立的舵机仿真模型能很好地模拟实际舵机。     

Detrend effect on the scalograms of GPS power scintillation

The study of amplitude scintillation on GPS radio links is usually done after detrending the time series of the transmitted power so to define scintillations as the chaotic fluctuation around a unitary value. In a sense, the choice of how to detrend the time series is part of the definition of scintillation.     

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10?Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.     

Characterization of ionospheric amplitude scintillations using wavelet entropy detrended GNSS data

The extensive monitoring networks of Global Navigation Satellite System (GNSS) ionospheric scintillation have been established to continuously log observation data. Further, the amplitude scintillation index and the phase scintillation index, which are derived from scintillation observations, are anticipated to accommodate the accuracy requirement of both the user level and the monitoring station level. However, raw scintillation observations essentially measure superposed waveform impairments of GNSS signals propagating through ionosphere and troposphere. It implies that fluctuations of raw scintillation observations are caused by multiple factors from the entire radio propagation environment. Hence, it is crucial to characterize ionospheric scintillations from GNSS observation data. And the characterization is implemented through extracting fluctuations of raw observations merely induced by ionospheric scintillations. Designed to address this problem by means of Fourier filtering detrending, the present work investigates the influence of varying detrending cutoff frequencies on wavelet statistical energy and wavelet entropy distributions of scintillation data. It consequently derives criteria on the optimum detrending cutoff frequency for three types of raw amplitude scintillation data, which are classified by their wavelet energy distributions. Results of the present work verify that detrending with specific optimum cutoff frequencies rather than the fixed and universally applicable one renders the validity and credibility of characterizing ionospheric scintillations as the part of GNSS observation fluctuations purely induced by ionosphere electron density irregularities whose scale sizes are comparable with or smaller than the Fresnel scale.     

基于小波变换和核独立分量分析的遥感图像变化检测

为了进一步提高基于独立分量分析(IndependentComponentAnalysis,ICA)的遥感图像变化检测精确度,并解决ICA分离的图像分量排序不确定问题,提出了基于小波变换和核独立分量分析(KernelIndependentComponentAnalysis,KICA)的遥感图像变化检测方法。首先通过小波变换对遥感图像进行分解,得到由图像的高频分量和低频分量组成的分块向量,然后利用核函数将分块向量映射到高维特征空间中,再在该空间中用ICA方法分离出互相独立的向量,最后根据分离出的向量中高频分量的差异自动分辨出变化分量。文章给出了遥感图像变化检测方法及近年提出的基于主分量分析(PrincipalComponentAnalysis,PCA)、基于ICA、基于KICA三种变化检测方法的试验结果,并进行了分析和定量比较。试验结果表明,文中方法能更好地分离出遥感图像的变化信息,具有更高的精确度,并实现了变化检测的智能化。     

子带自适应阵列处理的实现与性能分析

针对空频自适应滤波处理中节拍样点两端的输出信干噪比急剧下降的问题,建立了子带自适应阵列处理与空时自适应阵列处理等效关系的数学模型,指出了变换正交基函数的影响,提出利用时频分析特性优良的小波包变换取代傅立叶变换形成新的子带自适应阵列处理,减少子带间的频谱混叠,从而提高系统节拍样点两端的输出信干噪比。对基于不同窗函数的空频自适应处理和基于小波包变换的子带自适应处理进行了性能仿真,验证了小波包相对于加窗空频自适应处理的优越性。     

菜园坝长江大桥主拱节段风洞试验及分析

中承式拱桥属于柔性空间结构,主拱上承受的脉动风荷载相互干扰。以重庆菜园坝长江大桥为研究对象,进行了湍流下的主拱单拱及双拱节段模型风洞试验。对模型表面脉动压力的功率谱、相关系数、水平和竖向相干函数进行了细致分析,讨论了双拱间距宽度比对脉动压力频域特性的影响。当间距宽度比大于5时,后拱风荷载受到前拱的干扰作用。当两拱间距宽度比小于5时,前后拱风荷载特性类似于组合截面。随间距宽度比变小,主拱涡脱落折算频率和压力功率谱逐渐增大,前后拱迎风面和背风面的相关系数及相干系数均逐步降低。     

大跨悬挑屋盖风压分布风洞试验分析

通过大跨悬挑曲面屋盖刚性模型风洞试验,分析各风向角风压系数均值等值线图及跨中区域时体型系数以确定最不利风向角,研究跨中迎风边缘及顺风测点功率谱及相干特性,最后针对跨中不同位置测点风压概率分布密度特性探讨峰值因子合理取值。     

一种运载火箭时变结构模态参数辨识的确定性演化方法

针对运载火箭的时变结构模态参数辨识问题进行研究，基于时变自回归滑动平均(TARMA)模型，提出一种时变结构模态参数辨识的确定性演化方法。该方法利用小波基函数的良好局部函数拟合能力，将墨西哥帽小波函数作为TARMA模型时变系数的空间基底，构建了基于小波函数的泛函序列时变自回归滑动平均(FS-TARMA)模型，并发展了两步最小二乘估计方法，实现了时变系数的解耦估计。通过有限单元法，建立了阿里安V号芯级运载火箭时变有限元模型，对所提辨识方法进行了验证，结果表明：墨西哥帽小波基FS-TARMA方法能够有效地辨识系统的时变模态参数；与传统傅里叶基FS-TARMA方法相比，具有更好的辨识精度，并且能够准确地反映出模态局部细节特征。