基于CPG的双足机器人多层步行控制器设计

针对双足机器人步行控制器的设计问题,基于生物学启发原理,提出一种基于中枢模式发生器(CPG)与稳定性分析相结合的多层次结构控制器设计方法。分析机器人的步行运动,给出双足运动描述。基于CPG理论设计多层次结构的步行控制器,应用极限环理论方法分析运动稳定性。在保证步行稳定的前提下,所提出的控制方法具有结构简单、通用性好、方便在线平滑修正等优点,步行仿真实验验证了所提出算法的有效性。     

Agro-ecosystem modeling can aid in the optimization of biomass feedstock supply

Recent European Directives promoted the development of biofuels, requesting mandatory limits to their emissions ot greenhouse gases (GHG). Second-generation biofuels based on lignocellulosic biomass are prime candidates but their GHG emissions are variable and uncertain. Agro-ecosystem modeling can capture them and the performance of biofuel feedstocks.This study aimed at optimizing feedstock supply for a bioethanol unit in France, from agricultural residues, annual and perennial crops. Their productivity and environmental impacts were modelled on a regional scale using geo-referenced data on soil properties, crop management, land-use and future weather data. Several supply scenarios were tested. Cereal straw was the most efficient feedstock but had a low availability, and only miscanthus could meet the bioethanol plant's demand. Sorghum combined poor yields and high GHG emissions compared by miscanthus and triticale. A mix of three biomass sources used less than 3% of the regional agricultural land while abating GHG emissions by 60%.     

基于变周期技术的自适应数据采集算法

在数据采集系统中,按需采集是平衡数据数量、提高数据质量的有效手段。本文所提出的自适应数据采集算法是基于有限采样点的一元线性回归拟合,通过实时地对采集到的数据进行分析,不断修正采样周期,使得采样周期能够快速、准确地适应被测对象的动态变化。MATLAB软件仿真表明,本方法对于被测量加速变化具有较强的动态捕捉能力,能够在降低平均采样频率的前提下减小采样失真度,且与同类方法相比失真度低,稳定性高,是测控系统中实时数据采集的一种较好的代替方案。     

热释电传感器的非接触式测控系统设计

介绍了利用热释电红外传感器进行非接触式测温的基本原理、红外测温系统结构和信号处理电路的组成。以此为基础,设计了一套非接触式红外测温装置,用该装置测定了移动目标表面温度。在模拟实际场景应用时,实现了对较远距离的运动行人体温的准确测量;装置还增加了高温报警电路和蓝牙无线通信模块,丰富了使用功能。     

INFORMATION LITERACY IN A RESEARCHER'S LEARNING LIFE: THE SEVEN AGES OF RESEARCH

This article uses data from research conducted in the course of writing a book on the needs, wants and characteristics of researchers to examine how researchers view themselves and the research process. As a result of this, the Seven Ages of Research model was developed which categorises a researcher's learning life into a series of discrete stages. The article explores learning needs relevant to each age in the learning life and links them to the development of information literacy. The authors explore the polarisation that exists between what researchers think research is about and what they believe the library can offer them, and suggest that information literacy needs to be seen as involving a change in understanding of, and attitude to, the world of information, as well as the nature of those information needs. Finally, they explore the librarian's role in an e-environment which has changed the way researchers work and identify some of the challenges facing library and information services professionals in the future in supporting researchers throughout their learning lives.     

瓦斯突变预警上限值确定方法的研究

针对现有煤矿安全监控系统采用超限原理,以瓦斯传感器测量值为判断依据,无法及时发现预定报警值以下范围内瓦斯异常变化的问题,提出了一种不超限瓦斯突变预警方法,介绍了静态预警和动态预警两种不超限瓦斯突变报警方法。结合余吾煤业N2202工作面探头数据,分别对不超限瓦斯突变预警基础数据的静态数据和动态数据进行了分层抽样及分布的验证和拟合,得出静态预警和动态预警的基础数据基本符合正态分布的结论。提出采用假设检验和区间估计等实时计算静态预警和动态预警上限值的方法,并采用N2202工作面探头数据进行了验证。     

核电站数字化反应堆保护系统停堆响应时间分析

为了评价出核电站数字化反应堆保护系统停堆响应的最大时间,根据数字化反应堆保护系统结构,分析出保护系统的响应过程须经过AI输入、IO总线通讯、CPU运算、网络通讯、DO输出处理。并基于DCS定周期扫描的运行方式,得出了各处理过程所需最大响应时间的计算方法,DCS停堆响应时间的评价值就是各部分最大响应时间的累加。最后提出了可缩短响应时间的改进方法。     

一种改进编码器角度解算过程的方法与实现

在机械电子一直是一个热门学科,其目的是通过软件控制机械操作来代替机械的哑巴解决方案。DS-25旋转电子编码器能够很好地与机械电子应用相匹配,其输出为两路标准的sine和cosine曲线,通过分析sine和cosine数值来计算编码器所对应的绝对角度位置。通过对DS-25的工作模式分析和实际应用情况提出角度解算的改进方案,该方案利用DS-25工作于粗略模式下测试到的角度值来推算精确模式下的信号周期,结合精确模式下测试到的角度值来计算编码器所对应的绝对角度。摒弃其原有的复杂查表过程进而节省电子表格的存储空间,在降低硬件成本的同时提升了软件灵活性。实验证明,算法的改进能够节省约2KB的存储空间,角度位置误差能控制在1‰以内。     

Spacebased estimation of moisture transport in marine atmosphere using support vector regression

An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere (Θ) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data (Θ calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of Θ derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation compared with rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.     

Neural networks in process life cycle profit modelling

Changes in operational environment of the process industry such as decreasing selling prices, increased competition between companies and new legislation, set requirements for performance and effectiveness of the industrial production lines and processes. For the basis of this study, a life cycle profit (LCP) model of a pulp process was constructed using different kind of process information including chemical consumptions and production levels of material and energy flows in unit processes. However, all the information needed in the creation of relevant LCP model was not directly provided by information systems of the plant. In this study, neural networks was used to model pulp bleaching process and fill out missing information and furthermore to create estimators for the alkaline chemical consumption. A data-based modelling approach was applied using an example, where factors affecting the sodium hydroxide consumption in the bleaching stage were solved. The results showed that raw process data can be refined into new valuable information using computational methods and moreover to improve the accuracy of life cycle profit models.