基于AVMD与DPC-FCM的旋转机械无监督故障诊断方法

目的 针对旋转机械故障诊断过程中存在故障信号特征提取困难、故障诊断过程有标签数据较少、故障诊断准确率低等问题,提出自适应变分模态分解算法(Adaptive Variational Mode Decomposition, AVMD)与密度峰值算法优化的模糊C均值算法(Clustering by Fast Search and Find of Density Peaks Optimizing Fuzzy C-Means,DPC-FCM)结合的无监督诊断方法。方法 首先,将多尺度排列熵与峭度相结合的综合系数作为适应度函数,对VMD算法的惩罚因子alpha和模态个数K进行参数寻优,提取分解后本征模态函数(Intrinsic Mode Function,IMF)的平均样本熵与平均模糊熵,并输入至聚类算法中。其次,提出利用密度峰值聚类算法确定FCM的初始聚类中心,降低聚类结果的随机性。结果 将提出的无监督故障诊断模型应用到滚动轴承试验信号中,实现了准确的故障诊断。结论 AVMD在故障提取方面具有优越性,同时DPC算法可以有效提高FCM算法无监督聚类的准确性,二者结合可以有效实现旋转机械故障的智能分类。     

EVALUATION OF METHODS FOR ESTIMATING STREAM WATER QUALITY PARAMETERS IN A TRANSIENT MODEL FROM STOCHASTIC DATA1

ABSTRACT: In this study the estimation of parameters in water quality models represented by linear first order partial differential equations is investigated. Two sets of simulated input-output data, one with input noise and the other with output measurement error, were used. The parameters were estimated by a gradient technique (Bard's method) and a pattern search technique. The results indicate that the output measurement error significantly affects the values of parameter estimates as compared to the noise added to the input. Bard's method consistently gave results with a smaller sum of square value.     

基于智能优化算法的河流水质模型参数的优化

为探索河流水质模型参数新的求解方法,根据有限的实测数据,分别应用免疫进化优化算法和免疫进化优选的捕食搜索算法,对河流水质模型计算公式中的多参数进行优化。将优化得到的计算公式用于国内外若干河流的河段中DO浓度值的拟合,并与实测结果进行了比较。结果表明,将免疫进化优化算法或免疫进化优选的捕食搜索算法优化得到的水质模型参数精度不仅较高,而且相对稳定,从而为河流水质模型参数的优化提供了一种新方法。     

基于免疫禁忌优化算法的生态环境评价指数公式及其应用

通过模拟流域生态环境自然发展的演化过程,结合巢湖流域的具体情况,提出了适用于多个指标的巢湖流域生态环境评价指数公式。通过设定公式中生态环境指标“参照”值,采用免疫禁忌搜索算法对公式中的待定参数进行优化,使生态环境评价指数公式形式简单、方便实用,并具有一定的普适性。生态环境质量评价结果表明,合肥市和巢湖流域整体生态环境质量为Ⅲ级(及格),而巢湖市和六安市生态环境质量较差。     

地震灾害紧急救援队伍救援行动的规范

介绍了制定地震灾害紧急救援队伍行动规范的背景,阐述了地震灾害紧急救援队伍行动的阶段,给出了地震现场灾害紧急救援队伍行动规范的内容。该规范将有效地规范和协调地震灾害紧急救援队伍的救援行动,提高救援能力与效率,最大限度地减少人员伤亡。     

Role of information in collective action in dynamic disaster environments

This study explores the major issues facing collective response operations after destructive earthquakes. The small-n case study design employs qualitative and quantitative methods to investigate the decision-making process in a context of seismic risk to exemplify how public managers can utilise information and communication systems to ensure collaborative actions in managing an extreme event. Fifty-eight semi-structured interviews with 39 key decision-makers and researchers and content analyses of daily reports from Cumhuriyet comprise the main data sources. The study compares and contrasts the Turkish disaster management system following the Marmara and Duzce earthquakes of 1999. It addresses whether the use of information and communication technologies significantly affected its performance. The study's findings reveal that difficulties in accessing and exchanging timely and accurate disaster-relevant information inhibited coordination during the Marmara response while increased communication functions improved coordination and search-and-rescue activities during the Duzce response.     

昆明“3·29”森林火灾对防控林区火灾的启示

介绍昆明的“3·29”森林火灾基本情况。在对该火烧迹地进行3年跟踪调研的基础上,总结了该火灾对防控西南林区森林火灾的6点启示：（1）紫茎泽兰入侵区应慎修生土隔火带;（2）通过发挥山沟的阻火作用、营林防火、森林可燃物制炭等技术措施构建阻火林分;（3）重视森林火灾次生灾害;（4）开发新型森林灭火剂及施用技术;（5）适时运用以火灭火战术;（6）探索与集体林权制度改革相适应的森林消防对策。     

基于网络搜索行为的公众环境关心指标体系构建研究

利用环境相关的网络搜索数据构建指标体系,对中国公众环境关心程度进行评价.构建的环境关心指标体系包括环境污染关心、环境知识关心、环境法规关心和环境行为关心4分类指数和42具体指标.分析结果表明,环境关心指数主要受节能、减排、绿色出行等环境行为关心类指标影响;2011年以来,中国公众环境关心指数取值集中在100~200之间,且呈稳步上升趋势,并具有明显的季节性变动特征.     

互联网与环境科学技术

互联网的普及对推动环境科学技术发展起着很大作用 ,一方面 ,合理利用网络的资源可以使科研工作事半功倍 ;另一方面 ,互联网逐渐成为环境技术的推广应用、环保设备产品宣传和销售中的重要环节。本文介绍与环境科学技术相关的网络资源 ,包括文献检索、软件和环境科学讨论组、数据库、环保技术设备信息平台等     

A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.