基于非线性技术锅炉故障分析*

为预测和判断锅炉故障的发生,完善锅炉故障检测技术,基于锅炉运转具有非线性特点,提出将非线性评价指标应用于锅炉故障诊断。研究特征信号的非线性特性,通过确定延迟时间和嵌入维数来重构相空间;采用混沌分形理论研究非线性评价指标;提取最大Lyapunov指数和关联维数,并为收集的每种特征信号选择最合适的非线性指标。结果表明:蒸汽压力的非线性特征指标应选择关联维数,烟气温度1、烟气温度2、水管温度1和水管温度2的非线性特征指标应当选择最大Lyapunov指数。     

水资源生态足迹分析——以安康市为例

根据生态足迹分析方法,建立了水资源生态足迹概念模型,确定了计算水资源帐户生态足迹所需的3个关键参数,即平均水资源产量、均衡因子和地区产量因子,计算了安康市1996—2007年水资源生态足迹和生态承载力。引入水资源生态足迹压力指数、万元GDP水资源生态足迹、累积水资源生态足迹等指标,利用水足迹模型评价水资源可持续发展程度的全面性和对比性。结果表明,计算结果可客观评价安康市水资源可持续发展与利用情况,为地区水资源的可持续利用与管理提供了科学的依据。     

A NEW LOOK AT FLOOD RISK DETERMINATION1

ABSTRACT: The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.     

FRACTIONAL DIFFERENCING MODELING IN HYDROLOGY1

ABSTRACT: Fractional differencing is a tool for modeling time series which have long-term dependence; i.e., series in which the correlation between distant observations, though small, is not negligible. Fractionally differenced ARIMA models are formed by permitting the differencing parameter d in the familiar Box-Jenkins ARIMA(p, d, q) models to take nonintegral values; they permit the simultaneous modeling of the long-term and short-term behavior of an observed time series. This paper discusses the usefulness of fractional differencing to time-series modeling, with emphasis on hydrologic applications. A methodology for fitting fractionally differenced ARIMA models is described, and examples are presented.     

基于卫星遥感的浙北平原气溶胶光学特性长期变化分析

利用MOD04 C051气溶胶产品,以浙江北部平原为主要研究区,开展区域气溶胶光学特性长期(2000年3月—2013年12月)变化分析.长期逐月时间序列显示,区域气溶胶光学特性具有年内周期性变化规律,AOD(Aerosol Optical Depth)峰值多出现在5月或6月;Angstrom Exponent(α指数)峰值多出现在3月或4月.在空间分布上,研究区中部地区气溶胶污染较重且粗粒子成分较高.研究区气溶胶光学特性长期变化特征主要体现在:1气溶胶污染总体减轻但细粒子成分增加,复合污染加重;2008年以来区域AOD年均值总体呈下降趋势;2007—2013年α指数年均值显著高于2000—2006年;区域α指数月均值增长趋势显著,近14年的总倾向率为0.125(p0.05);2AOD和α指数的季节差异呈减小趋势,AOD的季节变化规律由2000年的春夏≈冬秋转变为2013年的春冬秋≥夏;α指数虽仍以夏秋季高于冬春季,但春秋两季α指数相对增大;3以污染较轻的湖州市和污染较重的嘉兴市为例的原因分析显示,AOD变化与SO2排放量具有一定相关性,α指数变化与民用汽车拥有量变化趋势一致,相关性较高.     

Estimation and inter-comparison of dust aerosols based on MODIS, MISR and AERONET retrievals over Asian desert regions

This study presents detailed analysis of spatiotemporal variations and trend of dust optical properties i.e., Aerosol Optical Depth(AOD) and Angstrom component over Asian desert regions using thirteen years of data(i.e., 2001–2013) retrieved from Aerosol Robotic Network(AERONET), Moderate Resolution Imaging Spectroradiometer(MODIS) and Multi-angle Imaging Spectroradiometer(MISR). These regions include Solar Village, Dunhuang and Dalangzadgad and are considered as origin of desert aerosols in Asia. Mann–Kendall trend test was used to show the trend of AOD. The relationship of AOD with weather parameters and general AOD trend over different wavelengths has also been shown. AOD's trend has been observed significant throughout the year in Solar Village, while in Dunhuang and Dalanzadgad the significant trend has been found only in peak period(March–June).Analysis show high values of AOD and low values of angstrom in Solar Village during peak period. In Chinese desert regions, high values of AOD have been found during peak period and low values in pre-peak period. Significant relationship has been observed between AOD and average temperature in Solar Village and Dalanzadgad whereas rainfall and wind speed showed no significant impact on AOD in all desert regions.     

烟气羽流时空混沌行为的耦合映象格子模型研究

为研究烟气羽流的时空混沌行为,本文从烟气羽流的N-S动量方程出发,根据浮力羽流的半经验公式,对方程中相应的项进行替代、化简,然后无量纲化,得到了以烟气羽流的动量通量m为系统状态矢量的单向耦合映象格子模型.计算了不同参数变化时,耦合周期窗口的时空行为发展,并且进行了李雅普诺夫指数λ计算.分析表明,开放系统中的烟气羽流会出现形态的多重性,包括时空混沌行为.这是由于烟气羽流系统内各种非线性作用的相互影响,也就是方程粘性项、浮力项和惯性项作用强弱对比的变化,以及系统行为发展的不可逆性所导致.     

Trends of air pollution in the Fichtelgebirge Mountains, Bavaria

We analyzed 13 years of hourly measurements of SO₂, NO_x, and O₃, at forest ecosystem research sites in SE Germany. A quasi-continuous data record was obtained by combining data sets from two locations. Before interpreting trends in the combined data set, we analyzed if the change of location introduced a systematic bias. We employed autocorrelation functions, Hurst statistics, complexity analysis, and recurrence quantification and found that the partial data sets exhibited no indication of the presence of any bias. For SO₂, we also compared the data from the forest sites with data obtained in nearby cities and also found no indications for any systematic effects. Applying nonparametric trend statistics we found a significant decrease of the SO₂. Most of the observed decrease is due to the reductions of SO₂ emissions in eastern Germany, but reductions in western Germany and the Czech Republic also played important roles. For O₃, we observed a significant increase, the causes of which are unclear from our data alone. No trend was identified for NO_x.     

混沌理论在水质预测中的应用初探

基于混沌理论、相空间重构思想和嵌入理论分析涟水流域溶解氧的时间序列,计算吸引子维数和最大的Lyapunov指数,研究河流水质系统的复杂性特征。结果表明,河流水质时间序列具有混沌特性,其外在表现为貌似随机的无规则特点;但系统本身内在的、固有的规律(表现在最大的Lyapunov指数),表明短期预测河流水质变化是可行的,并应用混沌相空间模线性回归模型进行了短期预测,其预测结果对涟水流域的水质管理和控制具有一定的参考价值。     

西南地区旱涝特征及其趋势预测

应用Z指数和标准化降水指数SPI,结合REOF方法和Hurst 指数对西南地区旱涝等级及其时空分布规律、演变趋势进行分析和预测,结果表明:SPI 和Z指数的计算结果和现实情况较一致,从多年平均值来看,云南的中甸及四川的石渠、德格等地干旱指数处于低值区,属重旱区。贵州和广西及云南南部部分地区属易涝区。逐年的SPI 和Z指数结果大体一致,2000 年以后,干旱指数波动较大。通过REOF分析,Z指数的分布大致分为川西区、川东(包括渝)区、云贵(包括广西北部)区、广南四个区域。云贵区Z指数总体呈下降趋势,涝情呈减弱趋势;川西区在1964 年至1973 年间干旱严重,1995 年以后变化相对稳定,但干旱也时有发生;川东区旱涝变化不显著。经Hurst 指数分析,西南五省市未来的旱涝情况大致为干旱程度呈逐步加大的态势,洪涝程度呈较弱的逐步减小态势。