基于无线传感器网的噪声监测系统设计及应用

噪声污染严重危害着人类的身心健康与生活质量,基于物联网技术拓展噪声监测方法的研究对当前我国城市环境噪声污染控制具有重要的指导意义。从噪声监测同步、联动、实时的需求出发,利用无线传感器网络技术中的ZigBee技术,结合地理信息系统,设计了基于无线传感器网络的噪声监测系统,并将该系统应用于某科研单位园区噪声污染的联网监测。实验结果表明,基于无线传感器网络的噪声监测系统的监测结果可以反映噪声污染的真实情况,可以作为治理噪声污染对策的依据。     

基于模拟-优化方法的地下水污染源溯源辨识

以抚顺市某煤矸石堆放场为研究区,根据研究区的实际条件建立地下水污染质运移模拟模型,预测地下水污染质未来时空变化特征.基于正演预报结果构建了假想例子,应用模拟-优化方法对地下水污染源源强及场地的渗透系数进行反演识别.为减小优化模型反复调用模拟模型所产生的计算负荷,分别采用Kriging方法和BP神经网络方法建立了模拟模型的替代模型.最后运用模拟退火法求解优化模型,得到反演识别结果.研究表明：应用Kriging方法建立的替代模型输出结果的平均相对误差为0.3%;应用BP神经网络方法建立替代模型的输出结果平均相对误差为1.5%,应用两种替代模型对污染源源强识别的相对误差均小于0.5%,对场地两个参数分区渗透系数识别的相对误差均不大于5%.综上,应用Kriging方法建立的替代模型精度高于BP神经网络方法,利用基于两种替代模型的模拟-优化方法对污染源源强和渗透系数进行同步识别精度可以满足实际需求,是有效可行的.     

基于贝叶斯网络分类的土壤盐渍化遥感监测

贝叶斯网络是一种将贝叶斯概率方法和有向无环图的网络拓扑结构有机结合的概率模型。采用贝叶斯网络分类对具有典型干旱特征的库车县土壤盐渍化情况进行监测，首先应用条件独立性测试原理建立贝叶斯网络结构，把研究区遥感数据进行离散化，然后应用贝叶斯定理作为分类原则，将每个像元分为像元最大概率的类别。研究结果表明该方法分类6种地类的整体分类精度达到96％，为该区盐渍地面积、空间分布等特征监测提供了较好的依据。     

海洋环境中材料腐蚀数据采集处理网络系统的研究

介绍了利用电话公网为传输栽体建立以海洋腐蚀与防护国防科技重点实验室为中心辐射青岛、厦门和三亚3个海水试验站的材料腐蚀数据采集计算机网络平台。研发了具有自主知识产权的多通道电偶腐蚀数据自动采集系统,将该系统与网络平台相结合可实现远程实验数据自动采集。同时为了有效地管理、存储和实现数据的共享,研究建立了海洋环境材料腐蚀与防护数据库,收集和整理了大量的材料腐蚀数据。在分析研究大量腐蚀数据的基础上建立了误差反传（BP）人工神经网络预测模型和灰色GM（1,1）腐蚀预测模型。从而形成一套较完整的数据采集、处理和分析网络系统。     

Internal corrosion hazard assessment of oil & gas pipelines using Bayesian belief network model

A substantial amount of oil & gas products are transported and distributed via pipelines, which can stretch for thousands of kilometers. In British Columbia (BC), Canada, alone there are over 40,000 km of pipelines currently being operated. Because of the adverse environmental impact, public outrage and significant financial losses, the integrity of the pipelines is essential. More than 37 pipe failures per year occur in BC causing liquid spills and gas releases, damaging both property and environment. BC oil & gas commission (BCOGS) has indicated metal loss due to internal corrosion as one of the primary causes of these failures. Therefore, it is of a paramount importance to timely identify pipelines subjected to severe internal corrosion in order to improve corrosion mitigation and pipeline maintenance strategies, thus minimizing the likelihood of failure. To accomplish this task, this paper presents a Bayesian belief network (BBN)-based probabilistic internal corrosion hazard assessment approach for oil & gas pipelines. A cause-effect BBN model has been developed by considering various information, such as analytical corrosion models, expert knowledge and published literature. Multiple corrosion models and failure pressure models have been incorporated into a single flexible network to estimate corrosion defects and associated probability of failure (PoF). This paper also explores the influence of fluid composition and operating conditions on the corrosion rate and PoF. To demonstrate the application of the BBN model, a case study of the Northeastern BC oil & gas pipeline infrastructure is presented. Based on the pipeline's mechanical characteristics and operating conditions, spatial and probabilistic distributions of corrosion defect and PoF have been obtained and visualized with the aid of the Geographic Information System (GIS). The developed BBN model can identify vulnerable pipeline sections and rank them accordingly to enhance the informed decision-making process.     

A neuro-fuzzy algorithm for assessment of health,safety, environment and ergonomics in a large petrochemical plant

Process plants such as petrochemical units have been continuously trying to improve Health, Safety, Environment and Ergonomics (HSEE) programs. This study proposes an adaptive network-based fuzzy inference system (ANFIS) for assessment of HSEE programs in a petrochemical plant. The proposed neuro-fuzzy approach is applied to a set of operators in the petrochemical unit to show its applicability and superiority. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and accomplishment of HSEE programs is used as output for the algorithm. Moreover, this algorithm is used to rank operators performance with respect to HSEE. Finally, the algorithm identifies efficient operators with respect to HSEE. This is the first study that introduces an intelligence algorithm for assessment and improvement of HSEE program in a petrochemical plant.     

非线性理论在开采沉陷中的应用

简要介绍了近年来把非线性理论应用于矿山开采沉陷领域的一些研究成果,主要包括两大部分：（１）神经网络理论在开采沉陷中的应用;（２）离散单元法在开采沉陷中的应用     

大气环境质量综合评价的B－P网络模型

选取大气环境质量的三级标准作为３个学习样本，以ＳＯ＿２，ＮＯ＿ｘ和ＴＳＰ三种污染物的三级标准浓度限值作为样本的输入特征值，建立了三参数的Ｂ－Ｐ网络大气环境质量综合评价模型，用该模型对３１个测点的大气环境质量进行评价，并与模糊数学和灰色系统法的评价结果比较，表明Ｂ－Ｐ网络用于大气环境质量评价具有优越性。     

我校图书馆自动化建设的实践与思考

本文简述了我校图书馆自动化建设的历史进程，分析了图书馆自动化建设的现状、达到的效果和尚存在的问题，并针对这些问题，提出了相应的改进措施。     

北京市数字遥测地震台网技术系统

地球科学是一门观测科学,地震观测是研究与应用工作的基础。因此,布设科学合理、运行稳定可靠的观测台网,可更好地为地震监测预报、地震应急以及科学研究提供保障。本文较系统的介绍了北京市数字遥测地震台网,并就系统建设过程中的一些技术问题进行了论述。