Feedback nonlinear discrete-time systems

In this paper, we design an adaptive iterative learning control method for a class of high-order nonlinear output feedback discrete-time systems with random initial conditions and iteration-varying desired trajectories. An n-step ahead predictor approach is employed to estimate future outputs. The discrete Nussbaum gain method is incorporated into the control design to deal with unknown control directions. The proposed control algorithm ensures that the tracking error converges to zero asymptotically along the iterative learning axis except for the beginning outputs affected by random initial conditions. A numerical simulation is carried out to demonstrate the efficacy of the presented control laws.     

EFFECT OF VOLUME FRACTION AND SIZE OF FINE γ' ON CREEP STRENGTH OF A DS NICKEL-BASE SUPERALLOY

本文研究了定向凝固K3镍基高温合金的蠕变强度与细小γ′粒子的数置和尺寸的关系。实验结果证明,随着固溶温度升高,铸态粗大γ′逐步溶解并在随后冷却过程重新析出均匀细小正方形的γ′粒子。细小γ′体积分数(v_f)和尺寸(α)都随固溶温度的升高而增大,当固溶温度从1100℃升至1230℃,v_f从0.25增至0.63,α从0.10μm增至0.32μm。随着固溶温度的升高,第二阶段蠕变速率降低,持久寿命延长,大幅度提高合金的蠕变性能。适当的高温固溶加时效处理(如1210—1230℃,4h+900℃,32h)可提高定向凝固合金的中温(760℃,73.8kgf/mm~2)持久寿命10倍左右。 合金的中温蠕变性能取决于细小γ′的体积分数(v_f),尺寸(α)及其间距(λ),在固定温度和应力下,第二阶段蠕变速率((?))与它们之间符合以下关系。 (?)∝ λ~2/α或(?)∝ α/v_f~(2/3)(1-v_f~(1/3))~2 用透射电镜观察了合金三个蠕变阶段位错亚结构的变化,据此提出蠕变的位错模型和合金的强化机制,并导出第二阶段蠕变速率与γ′体积分数、尺寸和间距之间的关系式,与实验结果完全符合。     

基于视频图像的输变电设备外部缺陷检测技术及其应用现状

基于视频图像的电力设备缺陷检测技术是实现电力智慧运维的关键技术之一,可解决电力设备故障自动诊断、主动预警和在线运维中存在的外部缺陷智能识别问题,减少人力资源浪费,提高电力系统巡检智能运维的频率与效率,从而弥补传统输变电设备巡检运维方式的不足。该文详细综述了当前典型的基于视频图像的输变电设备缺陷检测算法及图像处理技术,分析了传统图像处理方法及深度学习方法在电力设备缺陷检测领域应用的优缺点,总结了当前算法应用及开发平台的现状,指出了基于视频图像的输变电设备缺陷检测技术存在的问题,并展望了未来发展方向。     

Mapping coastal floods induced by hurricane storm surge using ATMS data

The coastal floods induced by hurricane storm surge are frequent, costly, and deadly hazards. Accurately and quickly estimating the spatial extent of floods is highly important for relief and rescue operations. In this study, we present an approach to estimate the extent of large-scale coastal floods caused by Hurricane Sandy in late October 2012 using passive microwave remote-sensing data. The approach estimates the water fraction from coarse-resolution Advanced Technology Microwave Sounder (ATMS) data through mixed-pixel linear decomposition. Land and water sample regions generated by river density and land-cover data, the relationship of channels 3, 4, and 16, neighbourhood pixel searching, and the difference of ATMS channels 4 and 3 are all comprehensively taken into account to dynamically determine water and land end members. The difference in the water fraction at the basin scale before and after flooding is calculated to reduce the impacts of soil and vegetation and to avoid pixel-to-pixel errors. Based on the water fraction difference, using the physical characteristics of water inundation that always proceed from the lowest to the highest elevation points in a basin, the flood map derived from the coarse-resolution ATMS measurements was extrapolated to a higher spatial resolution of 100 m using topographic information. Together, these steps represent a water fraction and high-resolution flood (WFHF) mapping process. To evaluate the WFHF mapping methodology presented in this study, the corresponding ground observations (storm-tide sites and high-water-mark data) and the Federal Emergency Management Agency 3 m resolution Hurricane Sandy storm surge flooding (SSF) products are used. The results show that 88% of the storm-tide and high-water-mark sites were located within the WFHF-mapped flood area. There was also good agreement between our WFHF and the SSF areas, with an accuracy of 88% and a correlation of 0.94. Overall, the proposed WFHF methodology was able to produce high-quality and high-resolution flood maps over large-scale coastal areas.     

Object-based automatic terrain shadow removal from SNPP/VIIRS flood maps

Terrain shadow is a big challenge to land products such as flood extent and snow cover from moderate-resolution optical satellite data. Because terrain shadows share similar spectral features with floodwaters, they can be easily detected as floodwaters by flood detection algorithms based on spectral features in visible, near-infrared, and short-wave infrared channels, which decreases the accuracy of flood detection substantially. However, because terrain shadows appear in mountainous areas with large surface roughness while floodwaters accumulate in low-lying areas with small surface roughness, analysis on surface roughness between terrain shadows and floodwaters can be very effective to distinguish one from the other. Root-mean-square height, internal height difference, and external height difference are used as principal quantitative surface roughness parameters in this study and calculated upon water objects that are clustered from a group of adjacent water pixels. This object-based method is applied in terrain shadow removal from SNPP/VIIRS (Suomi National Polar Orbit Partnership/Visible Infrared Imager Radiometer Suite) near-real-time flood maps and shows promising results according to the tests with 10,000+ VIIRS granules across global areas. Quantitative evaluation in the northwest of the USA also indicates that more than 99% terrain shadow pixels could be removed from VIIRS flood maps by this method, which significantly improves the accuracy of near-real-time flood detection from SNPP/VIIRS imagery.     

Evaluation of 10 year AQUA/MODIS land surface temperature with SURFRAD observations

As the 10 year Moderate Resolution Imaging Spectroradiometer Land Surface Temperature MODIS LST becomes available, it is significant to perform a comprehensive evaluation on the long-term product before downstream users use it for climate studies and atmospheric models. In this study, a validation is carried out using observations from the US Surface Radiation budget (SURFRAD) network. Strict quality control removes cloud-contaminated samples from MODIS LST collection and decreases noise information from SURFRAD measurements, thereby making the validation more persuasive. With analysis on 19,735 valid samples, Aqua/MODIS LST from a split-window algorithm shows retrieval errors from –14 K to 17 K with a bias of –0.93 K, an RMSE of 2.65 K, and a standard deviation of 2.48 K. The errors also show strong seasonal signals. With correlation tests between LST errors and several other factors, it is disclosed that LST retrieval errors mainly come from atmospheric effects and surface emissivity uncertainties, which are closely related to relative air humidity, absolute air humidity, sensor zenith angle, wind speed, normalized difference vegetation index (NDVI), and soil moisture. In addition, the impacts from these factors may not be independent. These impact factors suggest a deficiency of the split-window algorithm in dealing with atmospheric and surface complexity and variety.     

硫化铜精矿制硫酸铜工艺试验研究

硫化铜精矿经浓硫酸用量为１．０－１．４ｋｇ／ｋｇ，在１０５－１４５℃条件下熟化１０－２０ｈ，添加复合氧化剂和催化剂，在一定温度下浸１２０ｍｉｎ，液固比为６，当复合氧化剂ＦＳ３２用量为３７．５－５０．０ｇ／ｋｇ、催化剂ＣＨ１０用量为５ｇ／ｋｇ时，通过溶铜沉铁浸出，其最高浸出率可达９８．４６％，化学浓缩结晶可得到高纯度硫酸铜晶体。     

硫化铜精矿的硫酸铵焙烧浸出

将硫化铜精矿与硫酸铵混合进行硫酸化焙烧,不仅有利于铜的浸出,而且硫酸铵分解出的氨用于提铜废酸液的中和处理,可以实现硫酸铵的循环利用。结果表明,在硫酸铵用量为1.5n(n为硫酸铵与黄铜矿的摩尔比)、420℃焙烧180min的条件下,铜硫酸盐化的效果最好,硫酸铵基本上完全分解,产生的氨97%左右可用稀硫酸液吸收。烧渣按液固比为4在80℃浸出90 min时,铜的浸出率可达89.96%。     

香榧果实生长后期油脂及脂溶性活性物质的动态变化规律北大核心CSCD

为探究香榧果实生长后期油脂及脂溶性活性物质的动态变化规律,以20年生香榧为研究对象,分析测定了香榧果实生长后期种仁中油脂含量、香榧籽油中脂肪酸组成及脂溶性活性物质(角鲨烯、菜油甾醇、豆甾醇、β-谷甾醇、α-生育酚、β-生育酚)的动态变化规律,构建了香榧果实生长后期香榧籽油中脂溶性活性物质的动态积累模型。结果表明:在香榧果实生长后期种仁中油脂含量由(35.65±0.02)%增长为(54.50±0.01)%,脂肪酸组成比例变化显著,其中油酸增幅最大;角鲨烯和植物甾醇含量呈下降趋势,生育酚呈增长趋势,完熟前变化趋势均变缓;香榧果实生长过程中香榧籽油中角鲨烯、豆甾醇、β-谷甾醇含量的动态积累模型符合倒数函数方程,菜油甾醇及生育酚含量的动态积累模型符合多项式函数方程。综上,香榧果实生长后期,种仁中油脂含量增加,脂溶性活性成分均处于动态变化中。