单片机在噪声自动监测系统中的应用研究

研究设计用80C31单片机为控制核心的噪声自动监测系统,该系统以多台网络方式进行噪声的自动、定时监测,量程范围可达20分贝至140分贝、实现了采集、处理、显示、打印、量程切换及远距离向主控制机进行数据传送、统计报表,解决软、硬件的具体设计制作工艺,能够在各种条件下进行野外自动监测,具有良好的价格性能比,有推广实用价值。     

构建环境监测业务网络化管理系统的思考

通过环境监测业务网络化管理系统的基本流程、主要功能和保障措施三个方面,详细论述了系统的构建思路、主要内容和运行途径。对环境监测任务的下达、质量保证、原始数据传输、三级审核,以及监测数据、报告的查询等一系列环节进行了设计上的介绍,同时对维持系统正常运行的组织机构、工作文件、工作制度、监测人员也进行了概括的论述。经过实际运行检验,本系统具有强化管理水平、规范工作程序、明确工作责任、提高服务质量等效果。     

灰色神经网络模型在油气管道腐蚀速度预测中的应用

简要说明了GM(1,1)模型和BP神经网络模型预测过程,提出了灰色神经网络组合模型,用此方法对某原油长输管道腐蚀速度进行了预测,并用MatLab语言编程的方法对数据做了处理,结果表明用该方法预测得到的数据与实测值非常接近。     

Modelling radionuclide transport for time varying flow in a channel network

Water flowrates and flow directions may change over time in the subsurface for a number of reasons. In fractured rocks flow takes place in channels within fractures. Solutes are carried by the advective flow. In addition, solutes may diffuse in and out of stagnant waters in the rock matrix and other stagnant water regions. Sorbing species may sorb on fracture surfaces and on the micropore surfaces in the rock matrix. We present a method by which solute particles can be traced in flowing water undergoing changes in flowrate and direction in a complex channel network where the solutes can also interact with the rock by diffusion in the rock matrix. The novelty of this paper is handling of diffusion in the rock matrix under transient flow conditions. The diffusive processes are stochastic and it is not possible to follow a particle deterministically. The method therefore utilises the properties of a probability distribution function for a tracer moving in a fracture where matrix diffusion is active. The method is incorporated in a three dimensional channel network model. Particle tracking is used to trace out a multitude of flowpaths, each of which consists of a large number of channels within fractures. Along each channel the aperture and velocity as well as the matrix sorption properties can vary. An efficient method is presented whereby a particle can be followed along the variable property flowpath. For stationary flow conditions and a network of channels with advective flow and matrix diffusion, a simple analytical solution for the residence time distribution along each pathway can be used. Only two parameter groups need to be integrated along each path. For transient flow conditions, a time stepping procedure that incorporates a stochastic Monte-Carlo like method to follow the particles along the paths when flow conditions change is used. The method is fast and an example is used for illustrative purposes. It is exemplified by a case where land rises due to glacial rebound. It is shown that the effects of changing flowrates and directions can be considerable and that the diffusive migration in the matrix can have a dominating effect on the results.     

网络技术在环境保护中的应用

探讨开发基于新一代B／S计算模式的环保信息管理系统，增强信息技术在环保中的应用，最大限度地实现信息资源共享，为环保管理与决策提供数据支持与服务。     

不同营养程度湖泊中细菌群落组成及其分子生态网络特征

长江中下游地区是我国淡水湖泊的主要集中区，随着社会和经济的快速发展，该地区绝大部分湖泊正处于富营养状态.作为湖泊生态系统中的分解者和生产者，细菌群落在维持物质循环和能量流动中扮演着极为重要的角色，然而其组成及种间关系对富营养化过程的响应机制仍不明确.利用16S rDNA测序技术和分子生态网络技术探讨了长江中下游10个湖泊水体中细菌群落的组成、结构及其网络拓扑关系等特征.结果表明:①根据湖泊水体的富营养化指数，长江中下游地区的湖泊可分为中度富营养湖泊和重度富营养湖泊两种，并且这两种湖泊中细菌群落的α多样性均无显著性差异.②在这两种湖泊中细菌群落的优势类群基本一致，如在纲水平上均以Actinobacteria、Acidimicrobiia、Sphingobacteriia和Betaproteobacteria为主，在属水平上均以Hgcl_clade和CL500-29_marine-group为主.然而，与丰富种亚群落相反，稀有种亚群落在这两种湖泊中具有显著的区别.③中度富营养湖泊中细菌群落生态网络的节点和边的数量均小于重度富营养湖泊，并且前者网络具有更多的物种协作关系，其网络的中心性也显著大于后者.研究显示，湖泊富营养化的加剧使得水体中细菌群落的组成，尤其是稀有种亚群落发生了显著的演替，并且明显地削弱了细菌群落物种之间的协作关系.      

人工神经网络法在大气污染预报中的应用

以鞍山市为例,应用人工神经网络方法,模拟人脑的思维方式,建立了大气污染物浓度的神经网络预报模型,并将计算结果与监测值进行了对比验证,计算结果表明,BP模型应用于大气污染物浓度预报具有较高的预报精度。     

窖水中微生物降解污染物的关键细菌

为探究以氮、磷及有机物污染为主要特征的、窖水中参与污染物降解的关键细菌及它们之间潜在的相关关系,基于16S rRNA的微生物组学截面数据,分析了窖水中细菌群落结构与功能及其与水质因子间的相关性,并通过微生物物种的同现或相关种间作用推断模型,构建了7个微生物菌属间的共现性关联网络.结果表明,窖水中存在具有相对特定生态功能的细菌,进行着诸多活跃的与新陈代谢功能基因相关的代谢活动;窖水微生物类群共现性关联网络中大部分节点的菌属营互利共生类型的生态关系;Lacibacter、Arthrobacter、Candidatus Protochlamydia、Methylocaldum、Sulfuritalea、Mycobacterium、Aquirestis、Rhodobacter、Methylotenera等菌属拥有较高的点度中心度;较强的互作关系发生在Sulfuritalea-Rhodobacter、Azospirillum-Rhodobacter、Methylocaldum-Rhodobacter、Arthrobacter-Rhodobacter、Rhodoplanes-Rhodobacter、Candidatus Protochlamydia-Rhodobacter、Methylotenera-Rhodobacter、Rhodobacter-Aquirestis、Mycobacterium-Rhodobacter、PlanctomycesCandidatus Solibacter、Planctomyces-Legionella、Hymenobacter-Adhaeribacter、Luteolibacter-Crenothrix之间.综合分析节点微生物相关性、点度中心度及菌属间的互作强度,认为Rhodobacter、Methylocaldum、Methylotenera、Acinetobacter、Novosphingobium、Planctomyces、Hymenobacter、Luteolibacter为参与窖水污染物微生物降解的关键细菌,Rhodobacter为关键细菌的代表属.研究结果加深了对窖水中污染物微生物降解机制的认识.     

Accurate power-sharing,voltage regulation,and SOC regulation for LVDC microgrid with hybrid energy storage system using artificial neural network

ABSTRACT

In this paper, an artificial neural network-based control strategy is proposed for low voltage DC microgrid (LVDC microgrid) with a hybrid energy storage system (HESS) to improve power-sharing between battery and supercapacitor (SC) to suit the demand-generation imbalance, maintain state-of-charge (SOC) within boundaries and thereby to regulate the dc bus voltage. The conventional controller cannot track the SCs current rapidly with the high-frequency component that will place dynamic stress on the battery, further resulting in shorter battery life. The significant advantage is that in the proposed control strategy, redirections of unwaged battery currents to SCs for fast compensations enhance battery life span. The proposed control strategy effectiveness was investigated by simulations, including a comparison of overshoot/undershoot and settling time in dc bus voltage with a conventional control strategy. The results have been experimentally verified by hardware-in-loop (HIL) on a field-programmable gate array (FPGA)-based real-time simulator.     

澜沧江硅藻的地理分布模式与关键驱动因素

硅藻作为重要的初级生产者,在水域生态系统中发挥重要作用,然而目前对于大型河流中硅藻的地理分布特征和驱动因素知之甚少.本文以我国西南地区典型大河澜沧江干流1200 km河段为研究区域,基于真核微生物高通量测序数据集,探究浮游硅藻和底栖硅藻在不同河段的分布特征和关键驱动因子.结果表明,澜沧江浮游硅藻和底栖硅藻的物种多样性在上游自然河段较高,两类硅藻的群落结构在不同河段间存在显著差异,建坝对两类硅藻的优势属相对丰度均产生显著影响.方差分解分析结果表明,扩散限制是浮游硅藻和底栖硅藻地理分布的主导驱动因子,解释率分别为16.7%和29.8%.共现网络分析结果表明,相比底栖硅藻,浮游硅藻的种间竞争关系和网络连通性较强;梯级库区段两类硅藻的网络连通性均高于上游自然河段.本研究补充了大型河流硅藻地理生态分布的认知不足,同时揭示了河流硅藻群落对水电开发的响应.