惠州 LNG 电厂二期冷却水工程物理模型试验研究

通过LNG电厂二期工程温排水试验研究,对工程近区的水力热力特性进行了分析,对电厂设计方案的合理性进行了论证,并提出了推荐方案,为工程的设计和环评工作提供了科学的依据。     

UWB定位系统FPGA基带处理设计

基于到达时间差(TDOA)算法,设计了一个脉冲超宽带(IR-UWB)室内定位系统的原理验证样机。主要介绍传感器捕捉标签发送的IR-UWB窄脉冲,进而测出窄脉冲到达传感器时刻的方法。利用FPGA中数字时钟管理器(DCM)的相移器功能模块(PS)构成延迟锁相环(DLL),测得到达传感器的窄脉冲相对于同步时钟的时刻。原理验证系统定位精度优于40cm,达到设计要求。     

基于测量电参数实时求解道岔阻力方法的研究

目前,道岔阻力的测量是采用销式力传感器代替转辙机动作杆与道岔之间的连接销的方法.该方法操作复杂且存在安全隐患,只能进行临时测量,不能达到实时监测的目的.提出了以三相交流异步电机为基础,通过在信号室内对S700K转辙机的输入参数(功率、电流、电压)与转辙机输出力之间的关系进行研究,建立以功率、电流、电压、线路电缆长度、环境温度为自变量,转辙机输出力为因变量的NWPU数学模型.经与国内公开发表的数学模型对比,该数学模型误差最小,在构建道岔阻力实时监测系统方面有着非常重要的应用价值.     

具有温度补偿的膜片型光纤光栅温度压力传感器

阐述了具有温度补偿结构的膜片型光纤光栅温度压力传感器。传感器以弹性膜片为感压元件,在压力作用下产生轴向位移来压缩压力敏感光栅以实现压力传感;通过结构温度补偿消除压力敏感光栅的温度漂移,同时串入感温光栅进行实时修正并实现温度测量。对传感器的压力和温度特性进行了测量。试验结果表明:压力灵敏度为528 pm/MPa,温度灵敏度为8 pm/℃。     

Using artificial neural networks to map the spatial distribution of understorey bamboo from remote sensing data

Understorey vegetation is a critical component of biodiversity and an essential habitat component for many wildlife species. However, compared to overstorey, information about understorey vegetation distribution is scant, available mainly over small areas or through imprecise large area maps from tedious and time-consuming field surveys. A practical approach to classifying understorey vegetation from remote sensing data is needed for more accurate habitat analyses and biodiversity estimates. As a case study, we mapped the spatial distribution of understorey bamboo in Wolong Nature Reserve (south-western China) using remote sensing data from a leaf-on or growing season. Training on a limited set of ground data and using widely available Landsat TM data as input, a nonlinear artificial neural network achieved a classification accuracy of 80% despite the presence of co-occurring mid-storey and understorey vegetation. These results suggest that the influences of understorey vegetation on remote sensing data are available to practical approaches to classifying understorey vegetation. The success here to map bamboo distribution has important implications for giant panda conservation and provides a good foundation for developing methods to map the spatial distributions of other understorey plant species.     

Estimating above-ground net primary productivity of the tallgrass prairie ecosystem of the Central Great Plains using AVHRR NDVI

Above-ground net primary productivity (ANPP) is indicative of an ecosystem's ability to capture solar energy and convert it to organic carbon (or biomass), which may be used by consumers or decomposers, or stored in the form of living and nonliving organic matter. Annual and interannual variation in ANPP is often linked to climate dynamics and anthropogenic influences, such as fertilization, irrigation, above-ground biomass harvest, and so on. The Central Great Plains grasslands occupy over 1.5 million km² and are a primary resource for livestock production in North America. The tallgrass prairies are the most productive grasslands in this region, and the Flint Hills of North America represent the largest contiguous area of unploughed tallgrass prairie (1.6 million ha). Measurements of ANPP are of critical importance to the proper management and understanding of climatic and anthropogenic influences on tallgrass prairie. Yet, accurate, detailed, and systematic measurements of ANPP over large geographic regions do not exist for this ecosystem. For these reasons, this study was conducted to investigate the use of the normalized difference vegetation index (NDVI) to model ANPP of the tallgrass prairie. Many studies have established a positive relationship between the NDVI and ANPP, but the strength of this relationship is influenced by vegetation types and can vary significantly from year to year depending on land use and climatic conditions. The goal of this study was to develop a robust model using the Advanced Very High Resolution Radiometer (AVHRR) biweekly NDVI values to predict tallgrass ANPP. This study was conducted using ANPP measurements from a watershed within the Konza Prairie Biological Station (KPBS) as the primary study area, with additional measurements from the Rannells Flint Hills Prairie Preserve (RFHPP) and biennial ANPP measurements by Kansas State University (KSU) students from tallgrass areas near Manhattan, Kansas. Data from the primary study site covered the period of 1989–2005. The optimal period for estimating ANPP using AVHRR NDVI composite data sets was found to be late July. The Tallgrass ANPP Model (TAM) explained 54% (coefficient of determination, R ² = 0.54, p < 0.001) of the year-to-year variation in ANPP. The creation of 1.0 km × 1.0 km resolution ANPP maps for a four-county (～7000 ha) area for years 1989–2007 showed considerable variation in annual and interannual ANPP spatial patterns, suggesting complex interactions among factors influencing ANPP spatially and temporally.     

基于硅压阻式压力传感器的TPMS无线传感器节点设计

针对量程在800kPa以上进口TPMS传感器芯片价格非常昂贵和目前大客/货车安装胎压监测的必要性之间的矛盾,本文使用TI公司生产的处理器MSP430F2112,提出了一种高性价比的TPMS无线传感器节点设计方案,包括总体方案、压力传感器非线性补偿算法、详细的硬件设计、软件控制策略.最后通过实验室测试表明:该设计的硬件电...     

An improved selective attention model considering orientation preferences

An improved selective attention model is proposed in this paper, which is designed as a network of spiking neurons of Hodgkin--Huxley type with star-like connections between the central units and peripheral neurons. In this model, peripheral neurons represent the neurons located in the primary visual cortex. Since orientation preference is an important property of neurons in primary visual cortex, it should be considered except for external stimuli intensity. Simulation results show that the improved model can sequentially select objects with different orientation preferences and has a reliable shift of attention from one object to another, which are consistent with the experimental results that the neurons with different orientation preferences are laid out in pinwheel patterns.     

含氟丙烯酸酯树脂的合成及其在氟碳涂料中的应用

以过氧化苯甲酰(BPO)为引发剂,将甲基丙烯酸十二氟庚酯(RfAA)、丙烯酸丁酯(BA)、丙烯酸羟丙酯(HPAA)、丙烯酸(AA)和苯乙烯(ST)采用溶液聚合方法合成一种含氟丙烯酸酯树脂(PFBSH),并通过红外光谱(IR)对PFBSH进行了结构表征。将此树脂应用在双组份氟碳涂料中,该氟碳涂层的水接触角达到110.5°,其附着力、硬度、光泽和耐水性等都获得了令人满意的应用效果。另外讨论了固化温度和纳米TiO2对涂料应用性能的影响。