基于视频图像的交通枢纽综合体人体检测

针对交通枢纽综合体人体检测的问题,提出一种基于梯度方向直方图(HOG)人体模型特征的检测算法。该方法通过提取人体样本库的HOG特征,用支持向量机算法(SVM)对样本的HOG特征进行分类训练。为了提高算法的精确度和适用性,以南京南站的监控视频为依据建立交通枢纽综合体人体样本库。并以南京南站监控视频和校园拍摄的人员视频作为测试集。结果证明,本算法可以有效识别交通枢纽综合体各种特征人体。     

污水生物处理建模水质数据误差来源分析与影响评价

为进一步提高国内基础建模数据质量,降低建模实践中的数据清洗难度,本研究以北京龙庆再生水厂生物建模过程中的实际数据问题为例,基于数理统计理论及国内污水水质特征分别构建误差来源分析方法与误差影响评价方法.通过设计补充采样与实验排查方案,成功识别数据误差来源并实现不同类型误差对数据准确性的影响量化评价.研究结果表明,污水处理厂日常的取样与化验过程中产生的随机误差不可忽视,特别是当大量随机误差存在时,对数据总体造成的波动影响无法通过数据量的积累而消除;而不同的采样位置与不当的样品保存方式则会引起水质发生变化,由此产生的系统误差将导致测量结果长期偏高/偏低.因此,在依赖人工测量数据进行建模的国内实践中,应首先对历史数据进行误差检验,再进行必要的建模补充采样,以避免补充数据质量受相同误差影响,减少非必要的人力、物力浪费.     

土工膜渗漏检测系统的开发

通过比较国外多种填埋场渗漏检测方法,成功地研制了基于高压直流电法的渗漏检测系统.该系统利用CAN总线技术,解决了由于填埋场检测面积大所带来的采集数据量大、传输距离远的问题;利用低频脉冲供电方式,将正负半周采集的数据相减,大大减小了低频地电噪声的影响;通过建立合理的地电模型,解决了非均匀介质条件下的电势分布问题,进而提高了系统的检测精度.通过实践检验,表明该系统在检测电极间距为4 m时,误差超过0.4 m的概率低于10%.      

广州垃圾填埋渗滤液中有机污染物的去除效果

采用同时好氧厌氧生物反应器处理广州市大田山垃圾填埋渗滤液,平均出水浓度COD_Cr为131mg·L^-1,氨氮为7mg·L^-1,达到了同类废水的国家二级排放标准.同时选择GC-MS联用仪对垃圾渗滤液中的有机物进行测定,测得有机污染物87种,其中16种有机污染物被列入美国EPA环境优先控制污染物,31种有机物被完全去除,14种有机物去除率可达80%以上,25种有机物去除率达50%以上.     

Evaluating the sampling pattern when detecting Zones of Abrupt Change

We present a method for detecting the zones where an irregularly sampled variable changes abruptly in the plane. Such zones are called Zones of Abrupt Change (ZACs). This method not only allows estimation of ZACs, but also testing of their statistical significance against the null hypothesis of a stationary correlated random field. The sampling pattern, in particular its local density, is crucial in the detection of potential ZACs. In this paper, we address the problem of evaluating the sampling pattern by assessing the power of the local test used for detecting ZACs. It is shown that mapping the power allows us to identify zones where ZACs may or may not be detected. The methodology is applied to a soil data set sampled at eight different dates in an agricultural field. Detecting ZACs for the soil water content allowed us to identify permanent structures in the agricultural field related to the boundaries between different soil types. Mapping the power for various sampling densities proved to be useful to determine the minimal sampling density necessary for detecting ZACs.

Roadside Measurements of Deforestation in the Amazon Area of Bolivia

This study describes the deforestation impact from three settlements, 5 de Junio, El Tigre, and 30 de Agosto, near the Madidi National Park in Bolivia. First deforestation rates along the road that connects the settlements and then deforestation within each settlement are examined. Landsat Thematic Mapper (TM) imagery from 1987, 1997, and 2000 were used to measure the deforestation. Face-to-face interviews were also used to collect detailed social and land-use information. Road-building and farming have been the major causes of deforestation in this region. The TM measurements indicate a high increase in the deforestation rate along the road in the area of study. The results also show a rapidly escalating deforestation rate in 5 de Junio, a potential high future deforestation rate in El Tigre, and a gradual deforestation increase in 30 de Agosto. The information provided by the settlers about clearing was compared with the imagery analysis. Generally, the settlers estimates were lower than the deforestation as derived from the imagery.     

气象雷达新技术及其在防灾减灾中的应用

新型气象雷达在国外越来越多地应用于大型外场试验和业务探测网中,我国也将在灾害性天气监测网中引入新型气象雷达。简要介绍了气象雷达的发展历史和国内外发展现状,阐述了气象雷达探测新技术,包括双线偏振雷达、双(多)基地雷达、相控阵天气雷达技术、激光天气雷达技术、风廓线雷达等的探测原理及其在气象中的应用,这对于我国新型雷达的应用和根据实际需求选择雷达类型等具有一定的指导和借鉴意义。     

An integrated off-on line approach for increasing stability and effectiveness of automated controlled systems based on pump dependability—case study: Offshore industry

Automated controlled systems are vulnerable to faults. Faults can be amplified by the closed loop control systems and they can develop into malfunction of the loop. A control loop failure will easily cause production stop or malfunction at a petrochemical plant. A way to achieve a stable and effective automated system is to enhance equipment dependability. This paper presents a standard methodology for the analysis and improvement of pump performance to enhance total operational effectiveness and stability in offshore industry based on dependability. Furthermore, it is shown how a reliability–safety analysis can be conducted through equipment dependability indicators to facilitate the mitigation of hazard frequency in a plant. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the pumps performance. The pumps of offshore industries are considered according to OREDA classification. The approach identifies the critical pump and their fault through which the major hazards could initiate in the process. At first PCA is used for assessing the performance of the pumps and ranking them. IA is then performed for the worst pump which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward improving pump performance through design optimization and online fault detection which ultimately enhance overall operational effectiveness.     

图像识别技术及其在机械零件无损检测中的应用

无损检测法是一种常用的故障诊断技术,故障诊断从本质上来讲就是模式识别问题,而模式识别又可以狭义地理解为图像识别。从介绍图像、图像识别、图像识别过程和图像识别系统的基本概念着手,就几种常用图像识别方法的原理和特点进行比较,给出了CCD图像获取系统的组成。最后,结合发动机曲轴的一种自动磁粉探伤系统实例,对系统的图像处理和识别流程进行详细的讨论,并针对一般无损检测系统难以满足曲轴的检测要求和精度要求的状况,提出经过改进的一种适用于曲轴的整体无损检测系统。该系统有助于高效和完整地获取整个曲轴的图像,提高图像信息的质量,从而提高发动机曲轴表面缺陷检测的准确性和可靠性。