A new wavelet based fault detection,classification and location in transmission lines

This paper deals with the application of wavelet transforms for the detection, classification and location of faults on transmission lines. A Global Positioning System clock is used to synchronize sampling of voltage and current signals at both the ends of the transmission line. The detail coefficients of current signals of both the ends are utilized to calculate fault indices. These fault indices are compared with threshold values to detect and classify the faults. Artificial Neural Networks are employed to locate the fault, which make use of approximate decompositions of the voltages and currents of local end. The proposed algorithm is tested successfully for different locations and types of faults.     

我国建筑石油沥青标准的沿革及现状

论述了我国建筑沥青标准的变化历程及现状,对我国建筑沥青的生产、产品质量情况及现行国家标准GB/T 494-1998《建筑石油沥青》的不足之处进行了分析。提出了今后应生产的建筑沥青品种及应参照美国材料与试验协会标准ASTM D312《屋顶用沥青的标准规格》、我国石化行业标准SH/T0002-1990(1998)《防水防潮石油沥青》,修订GB/T494- 1998的建议。以进一步达到增加建筑沥青牌号,提高建筑沥青质量和使用性能的目的,满足建筑工业的发展对沥青多牌号、高质量、使用性能好的要求。     

矿山岩土工程系统环境质量评价指标体系

矿山现行的环境影响评价及其提交的环境影响报告书,是将矿山开发视为单个建设项目且只注重污染物排放和简单数量分析的单要素评价.本文将矿山开发视为统一系统,充分考虑系统内矿石开采、废石场、尾矿库等岩土工程及其矿岩氧化淋滤产生的毒害物质对矿区及其区域水土环境潜在而长期的影响,建立矿山岩士工程系统环境质量评价的指标体系,以改变矿山环境评价的传统旧式,规范和监督矿山开采行为,实现矿业开发与环境保护的协调发展.     

Prediction and quality control of the melt index during production of high-density polyethylene

In polyolefin processes the melt index (MI) is the most important control variable indicating product quality. Because of the difficulty in the on-line measurement of MI, a lot of MI estimation and correlation methods have been proposed. In this work a new dynamic MI estimation scheme is developed based on system identification techniques. The empirical MI estimation equation proposed in the present study is derived from the 1 ^st -order dynamic models. Effectiveness of the present estimation scheme was illustrated by numerical simulations based on plant operation data including grade change operations in high density polyethylene (HDPE) processes. From the comparisons with other estimation methods it was found that the proposed estimation scheme showed better performance in MI predictions. The virtual sensor model developed based on the estimation scheme was combined with the virtual on-line analyzer (VOA) to give a quality control system to be implemented in the actual HDPE plant. From the application of the present control system, significant reduction of transition time and the amount of off-spec during grade changes was achieved     

Effect of sampling density on the measurement of stream condition indicators in two lowland Australian streams

There is widespread application of indicators to the assessment of environmental condition of streams. These indicators are intended for use by managers in making various comparative and absolute assessments and often have a role in resource allocation and performance assessment. Therefore, the problem of formally defining confidence in the results is important but difficult because the sampling strategies used are commonly based on a compromise between the requirements of statistical rigour and the pragmatic issues of access and resources. It is rare to see this compromise explicitly considered and consequently there is seldom quantification of the uncertainty that could affect the confidence a manager has in an indicator. In this paper, we present a method for quantitatively assessing the tradeoffs between sampling density and uncertainty in meeting various monitoring objectives. Assessments using judgement‐based representative reaches are shown to be unreliable; instead a sampling approach is recommended based on the random selection of measuring sites. A detailed dataset was collected along two streams in Victoria, Australia, and the effect of sampling density was assessed by subsampling from this dataset with precision related to the number of sites assessed per reach length and the intensity of the sampling at each site. The sampling scheme to achieve a given precision is shown to depend on the monitoring objective. In particular, three objectives were considered: (1) making a baseline assessment of current condition; (2) change detection; and (3) detection of a critical threshold in condition. Change detection is shown to be more demanding than assessing baseline condition with additional sampling effort required to achieve the same precision. Sampling to detect a critical threshold depends on nominating acceptable values of Type I and II error and the size of the effect to be detected. Copyright © 2006 John Wiley & Sons, Ltd.     

区域内旱情监测站点的布设研究

本文对北京通州辖区范围内组织的大规模的土壤墒情调查数据进行总结。基于地理统计、空间分析以及统计学知识，分析了北京通州旱情分布形势。运用数值分类学的知识对测量数据进行了聚类分析，同时用DB(DaviesBouldin)指标准则研究了区域内合理布设旱情监测站的数量及位置，为建立旱情监测站点提供了理论依据。     

关于统一冶金矿山采矿工序能耗指标的看法

对原有的冶金矿山设计和生产不同能耗指标，提出统一为一个指标体系的设想，并提出了指标体系的计算公式以及各系数的选取意见。     

On the cost of searching signature trees

A precise analysis of the retrieval of signature trees is presented. A signature tree is a data structure constructed over a signature file to speed up searching all those signatures, which match a given query signature. The methods used include a detailed study of probabilistic analysis in conjunction with suitable contour integration of complex variabled functions.     

纺织信息的网上检索方法

主要介绍在网上检索纺织信息的几种方法和处理技术，为人们检索纺织信息提供了方便快捷的途径。     

Burned area forecasting using past burned area records and Southern Oscillation Index for tropical Africa (1981-1999)

An 18-year time series of monthly NOAA-AVHRR Pathfinder Land burned area was analyzed for the region of tropical Africa, from July 1981 to June 1999. The transition period between NOAA-11 and NOAA-14 platforms from July 1993 to June 1995 was not included due to missing and outlier data. Stability of the time series was addressed for the input variables in the burned area algorithm, reflectance and temperature channels.A Seasonal AutoRegressive Integrated Moving-Average (SARIMA) model was developed for forecasting potential burned area. The SARIMA model identified an autoregressive regular term with 1-month lag and an autoregressive 12-month seasonal term with one season (12 months) component. A cross-correlation between Southern Oscillation Index (SOI) and burned area was statistically significant predictor variable in a time series with 20-month lag. Results show that the SARIMA model with this predictor improved both, fitting and forecasting, residual variance, by 4.1% and 5.6%, respectively, thereby, demonstrating potential relationship between SOI and burned area for the study region. Forecasting was estimated by considering only the first 16 years of the monthly burned area in the time series, from July 1981 to June 1997. The prediction for the following 24 months (from July 1997 to June 1999) was within the 95% confidence level indicating that the forecast was a valid characterization of the modeled process.