Dynamic response of multi-scale structure in flexible pavement to moving load

In order to study the dynamic responses in the microstructures of the pavement structure, the multi-scale modeling subjected to moving load is analyzed using the discrete element method （DEM）. The macro-scale discrete element model of the flexible pavement structure is established. The stress and strain at the bottom of the asphalt concrete layer under moving load are calculated. The DEM model is validated through comparison between DEM predictions and the results from the classical program. Based on the validated macro-scale DEM model, the distribution and the volumetric fraction of coarse aggregate, mastics and air voids at the bottom of the asphalt layer are modeled, and then the multi-scale model is constructed. The dynamic response in the microstructures of the multi-scale model are calculated and compared with the results from the macro model. The influence of mastic stiffness on the distribution of dynamic response in the microstructures is also analyzed. Results show that the average values and the variation coefficient of the tensile stress at the aggregate-mastic interface are far more than those within the mastics. The dynamic response including stress and strain distributes non-uniformly in both mastics and the interface. An increase in mastic stiffness tends to a uniform distribution of tensile stress in asphalt concrete.

State Estimation Moving Window Gradient Iterative Algorithm for Bilinear Systems Using the Continuous Mixed p-norm Technique

This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output data.Based on the bilinear state observer,a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost function.The gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise disturbance.Furthermore,to improve the performance of the proposed algorithm,a dynamicmoving window is designed which can update the dynamical data by removing the oldest data and adding the newestmeasurement data.A numerical example of identification of bilinear systems is presented to validate the theoretical analysis.

Fast Face Detection with Multi-Scale Window Search Free from Image Resizing Using SGI Features

Face detection is applied to many tasks such as auto focus control, surveillance, user interface, and face recognition. Processing speed and detection accuracy of the face detection have been improved continuously. This paper describes a novel method of fast face detection with multi-scale window search free from image resizing. We adopt statistics of gradient images (SGI) as image features and append an overlapping cell array to improve detection accuracy. The SGI feature is scale invariant and insensitive to small difference of pixel value. These characteristics enable the multi-scale window search without image resizing. Experimental results show that processing speed of our method is 3.66 times faster than a conventional method, adopting HOG features combined to an SVM classifier, without accuracy degradation.

On-line Fault Diagnosis in Industrial Processes Using Variable Moving Window and Hidden Markov Model

An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.

Online Wavelet Denoising via a Moving Window

在这份报纸，在即时信号处理降噪的传统的小浪的缺点被讨论，联机降噪的要求被考虑，并且一扇动人的窗户被介绍进传统的小浪变换。用动人的窗户，降噪途径的联机小浪被建议。联机降噪的一些问题例如边阶失真和 pseudo-Gibbs 现象，被讨论。为了解决这些问题，窗户延期和窗户，周期旋转也被建议。不同途径被广泛地在降噪域使用的信号测试。视觉结果和量的措施被介绍加亮新途径的可获得性。

Double Moving Window MPCA for Online Adaptive Batch Monitoring

Online monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide applications in process performance analysis, monitoring and fault diagnosis using existing rich historical database.In this paper, we propose a simple and straight forward multivariate statistical modeling based on a moving window MPCA (multiway principal component analysis) model along the time and batch axis for adaptive monitoring the progress of batch processes in real-time. It is an extension to minimum window MPCA and traditional MPCA.The moving window MPCA along the batch axis can copy seamlessly with variable run length and does not need to estimate any deviations of the ongoing batch from the average trajectories. It replaces an invariant fixed-model monitoring approach with adaptive updating model data structure within batch-to-batch, which overcomes the changing operation condition and slows time-varying behaviors of industrial processes. The software based on moving window MPCA has been successfully applied to the industrial polymerization reactor of polyvinyl chloride (PVC) process in the Jinxi Chemical Company of China since 1999.

Land use induced blurring of forest-grassland transition in north-west Himalaya-A case study using Moving Split Window boundary detection technique

Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes.These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity,phyto-sociology,boundary detection and even impact of change in land use pattern(anthropogenic activity).The most accepted and widespread technique called as Moving Split Window(MSW) technique is used for detection of vegetation and environmental boundaries at four different sites in the lesser stratum of north-west Himalaya.All the four sites were at different distances from the nearest human inhabited area.Anthropogenic activities like grazing,herb collection,wood collection etc.were common at proximal sites.Such activities have led to the change in land use pattern.In this study,we have tried to work out the impact of the change in land use pattern(human interference) on the vegetation and basic environmental parameters like soil pH,electrical conductivity and moisture on forestgrassland ecotone in north-west Himalaya.Data on mountain steepness was also collected and analyzed.The dissimilarity profile using the statistical tool Squared Euclidian Distance(SED) indicated that species turnover locations increase with the increase in distance of ecotones from human settlements.The ecotones at distant locations from human villages are characterized with blunt as well as sharp peaks for vegetation data,however,conditions are reverse in case of the proximal sites.The study also reveals that as the distance between the ecotone and human settlements increases,the complex conditions like multiple vegetation boundaries prevails on the transitions.In this regard,land use induced blurring of forest-grassland transition in north-west Himalaya is summed up in the study.

Analysis of Landscape Patterns in the Urban-Rural Integrated Area Based on Moving Window: A Case Study of Sanshui District in Foshan City

The urban-rural integrated area in Sanshui District of Foshan City was selected for research, and the impact of landscape pattern around the No.269 provincial highway was analyzed based on the land-use data in 2014 using the spatial analysis in GIS and the moving window method. The results showed that:(1) within the scope of a 2 km-range buffer zone, with a low degree of heterogeneity, land for construction use and water area were the dominant land-use types, while with a high degree of fragmentation, cultivated land, wooded land, grassland, garden land, land for other farm uses, and land unused were scattered;(2) the 250-m square moving window could well detect the change characteristics of landscape pattern on both sides of the road;(3) the gradient analysis of landscape pattern in urban-rural integrated area, which was conducted with the aid of a 750-m transect on both sides of the road, indicated that there were significant differences between landscape indexes both in the urban-rural integrated area and on both sides of the road;(4) the road that had an obvious cutting and fragmentation impact on the landscape was an important factor leading to the increasing fragmentation and heterogeneity to regional landscapes.

Discriminant Analysis of Liquor Brands Based on Moving-Window Waveband Screening Using Near-Infrared Spectroscopy

Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.

High-Dimensional Regression on Sparse Grids Applied to Pricing Moving Window Asian Options

The pricing of moving window Asian option with an early exercise feature is considered a challenging problem in option pricing. The computational challenge lies in the unknown optimal exercise strategy and in the high dimensionality required for approximating the early exercise boundary. We use sparse grid basis functions in the Least Squares Monte Carlo approach to solve this “curse of dimensionality” problem. The resulting algorithm provides a general and convergent method for pricing moving window Asian options. The sparse grid technique presented in this paper can be generalized to pricing other high-dimensional, early-exercisable derivatives.

伊犁河三角洲水资源条件变化对景观格局演变的影响

在分析1992—2020年伊犁河三角洲水资源条件和定量评估研究期内土地利用变化的基础上,选取景观类型水平和景观水平指数解析景观格局变化特征,采用皮尔逊相关系数分析了水资源条件变化对景观格局指数的影响。结果表明:乌斯热尔玛水文站年径流总体偏大,巴尔喀什湖年平均水位在2002年发生突变,三角洲水资源补给总体处于增加状态;湿地和稀疏植被面积增大且聚集性增强,裸地向稀疏植被转化且优势度不断下降,林地破碎程度剧烈;景观水平指数在时程上呈阶段性变化,2016年伊犁河三角洲破碎化程度最低,在空间上伊犁河沿岸连通性增强,巴尔喀什湖沿岸景观多样性增加;景观水平指数与巴尔喀什湖年平均水位相关性最高,与乌斯热尔玛水文站年径流量的相关性次之,与伊犁河三角洲年降水量的相关性最低,且景观水平指数对三角洲水资源条件变化存在迟滞响应。

航天器轨道机动自适应逆向移动滑窗检测方法

以两行轨道根数为数据来源,提出采用逆向移动滑窗的自适应轨道机动检测方法。建立检测窗口的自适应配置模型以获得不同目标的检测窗口,采用交叉弧段预报思想更精确地估计机动时刻,通过逆向移动滑窗方法实现近实时机动检测。将检测结果与真实机动以及已有文献中的检测结果进行比较,结果表明:新方法能够适应不同轨道空间目标机动检测的窗口配置,且在给定仿真条件下检测成功率可以达到90%以上,机动时刻估计准确度与已有方法对比有显著的提升;仿真结果表明新方法可以应用于近实时的轨道机动检测。

滚动窗口的动态避障路径规划方法及优化

针对目前移动机器人在复杂环境例如存动态障碍物的环境下路径规划能力较弱的情况,提出一种基于优化后的滚动窗口法进行动态避障。首先对滚动窗口法的基础理论进行介绍并分析其在应用中存在的问题,得出该方法中局部子目标点的选取方式有可能使得机器人的规划出的路径陷入极小值点。在此基础上,对选择局部子目标点的方法进行了优化。然后为了防止随时可能出现的障碍物,基于动态障碍物的运行机理建立对应的数学模型,对障碍物的运行轨迹进行预测,从而根据不同的运动轨迹来设计避障对策。最后根据设计的优化方案,对预期目标进行仿真测试。在将仿真测试数据与实验结果进行验证,发现该算法能够实现在复杂的运行环境下,机器人自动规避动态障碍物具有较高的适用性。

基于改进遥感生态指数的尾矿库及周边区域生态环境质量分析

以广西武宣三里沙安尾矿库及周边区域为研究区,整合实测数据与遥感数据,在兼顾尾矿库及周边区域植被、地表湿润程度、地表温度及地表裸露度和建筑用地信息的基础上,考虑了选矿厂、尾矿库及周边区域的土壤重金属污染情况,将土壤重金属污染指标纳入遥感生态指数RSEI中,从而构建改进的遥感生态指数IRSEI,并结合移动窗口算法与主成分分析模型,构建了一种改进的遥感生态指数IRSEI_mw。结果表明:增加内梅罗综合指数有利于更精细地对金属矿区及周边区域的生态环境质量进行评估;相比于整体研究区,尾矿库内部生态质量整体较差,整个研究区内RSEI、IRSEI及IRSEI_mw的均值分别为0.53、0.52和0.58,尾矿库内三个生态指数的均值分别是0.29、0.27和0.22;相比RSEI及IRSEI,IRSEI_mw指数计算的区域生态质量结果的区分度有所增加,尾矿区内生态质量等级为差的区域范围大幅增加,尾矿区外部等级为优的面积大幅增加。总体而言,IRSEI_mw指数可有效量化尾矿库及周边区域生态环境质量,有利于更精细地对金属矿区及周边区域的生态环境质量进行评估。

基于多子空间加权移动窗主成分分析的全厂流程早期故障检测

早期故障的特征不明显,在全厂流程中比常规故障难检测.为了提高全厂流程中早期故障的检测率和灵敏度,将检测视角由全局转移至局部,提出基于多子空间加权移动窗主成分分析(PCA)的早期故障检测方法.使用结合过程知识和数据驱动的双层子空间划分方法,将过程变量划分到不同子空间中.使用加权的移动窗口增大早期故障的偏移量,将局部离群因子(LOF)算法引入PCA,以便进一步关注数据的局部特征,在每个子空间中建立故障检测模型.通过贝叶斯推理融合法对各子空间的监测结果进行信息融合,获得分布式监测结果.通过工业实例验证所提方法的性能.结果表明,所提方法在全厂流程中有效提升了早期故障检测的准确率和灵敏度.

基于增广SVD-MWKF的激励识别与结构响应重构

针对传统卡尔曼滤波算法在结构响应重构应用中需要外部激励及测量噪声方差先验已知的问题,提出一种基于增广SVD-MWKF(Singular Value Decomposition-Moving Window Kalman Filter)的激励识别与结构响应重构方法。首先,引入奇异值分解降噪技术以优化移动窗口法对测量噪声方差的实时估计。随后使用基于增广状态空间方程的卡尔曼滤波算法并结合部分测点的加速度测量数据,实现对结构外部激励的识别及各位置的速度、加速度响应的重构。最后,对起重机桁架和简支梁分别进行数值模拟和试验分析,结果表明,相较于移动窗口法,所提方法对测量噪声方差估计更加准确,且对外部激励能进行有效识别。

基于移动窗口法的库尔勒市土地利用景观格局特征分析

绿洲城市是干旱区人类生产和生活的中心,作为绿洲城市,库尔勒市人地关系同样敏感。了解土地利用景观格局的时空演变对于改善该区域的人地关系与生态安全、促进高质量发展具有重要意义。运用景观生态学原理,根据各类景观参数从景观水平与类别上分析库尔勒市土地利用景观格局并用地理探测器模型来分析驱动力。结果表明,1)未利用地依旧为景观的基质。2)景观类型的转移特征在景观面积与类型间的转换上有较显著的时空变化。3)PD、NP、DIV、SHDI和SHEI逐渐增加;CONTAG减少,城郊的破碎化程度均呈持续增大趋势,人类活动影响不断增强,城市化水平提高,库尔勒市处于高速发展时期。4)影响库尔勒市土地覆被/土地利用时空变化分异的主导影响因子是归一化植被指数(NDVI),其贡献率最高;在交互因子探测结果中,NDVI与降水量与气温共同作用时,呈现双因子增强,解释力最大。气温年平均变化与降水量在总体上处于波动上升的阶段,这对提升绿地林地面积以及进行进一步的生态修复都产生了积极的影响。景观破碎化格局的研究利于领会大城市快速成长阶段的景观格局变化规律,为城市生境保护,生态功能修复提供基础。

机械比能模型在潜山储集层评价中的改进与应用

渤海油田潜山储层岩性多样、地质条件复杂、非均质性强,传统机械比能模型对潜山储层储集性能响应的敏感性较差,难以高效指导勘探作业决策。为此,基于微钻头钻进实验和滑动窗口理论,分析了机械比能对工程参数的响应规律,构建了机械比能标准化模型和改进型机械比能模型,形成了潜山储层储集性能解释标准。结果表明:渤海油田潜山储层钻压系数为0.309~0.605;改进型机械比能小于0.80时为Ⅰ、Ⅱ类储层,改进型机械比能为0.80~1.15时为Ⅲ类储层,改进型机械比能大于1.15时为致密储层。研究成果在渤海油田36口潜山探井作业中进行了应用,储层储集性能解释符合率平均值为80.2%。该研究可为中途测试、完钻等勘探作业决策提供技术支持,具有很好的借鉴意义。

移动窗口下的LiDAR点云区域生长滤波算法

LiDAR滤波的方法中最小二乘内插法能够较好地获取地形趋势面,但是算法中无法根据地形自适应设置参数,在地形起伏较大的地区提取结果精度低,无法剔除大型建筑物和大面积且穿透率较低的植被,可能存在接收负粗差点、计算时间长等问题,利用最小二乘内插法滤波方法难以获取较高精度的结果。因此,本文提出了一种基于移动窗口加权迭代最小二乘拟合的区域生长滤波,即移动窗口下的区域生长滤波对LiDAR数据进行滤波。

半航空瞬变电磁干扰特征与降噪研究

为了验证多旋翼无人机在半航空瞬变电磁勘探作业中产生的电磁干扰影响,笔者等开展了一系列实验,包括在无人机不同工作状态下进行时频噪声分析,以及研究噪声源与接收点之间距离对噪声水平的影响。实验发现,大疆T20无人机电机转动产生的周期性电磁干扰频段在550~900 Hz,当接收线圈与无人机的距离为10 m时此干扰可被忽略。针对剩余的其他噪声,笔者等提出了基于移动窗口的递归最小二乘法自适应降噪方法。通过降噪实验,验证了该方法能够有效压制干扰,还原出信号的原始特征。将此降噪方法应用于香格里拉安乐铅锌矿实测半航空瞬变电磁信号处理,取得了显著的降噪效果。