城市燃气管道地震安全控制演示系统

介绍了一种用于展示城市燃气管道地震安全控制系统工作机理和控制效果的演示系统。对演示系统地震阀门的原理和性能作了阐述,对演示系统的组成、工作原理和效果做了较为详细的介绍。该系统可用于科普场馆或相关单位介绍城市燃气管道地震紧急处置的原理,系统已在唐山市地震博物馆安装应用。     

基于PLC的工业电雷管智能并行装配系统研究

针对国内工业电雷管装配生产过程中,因人工参与导致自动化技术水平低、危险系数高,造成生产效率低、安全事故频发等问题,将并行控制思想融入工艺模块划分、模块间的通信及PLC控制系统设计中,构建了一种基于PLC的工业电雷管智能并行装配系统,实现了工业电雷管并行装配,并使危险工作位置实现无人化,优化性能瓶颈从而提高了装配效率;设计了智能异常排除策略,实时监控和调整系统性能参数,使装配生产安全事故率大幅降低,增强了系统可靠性。实际应用表明,系统运行安全稳定、维护简便,实时预警及保护功能齐全,有效提高了工业电雷管自动装配的技术水平和产品质量。     

环境信息数据仓库建设及其相关的技术应用

阐述了环境信息数据仓库建设的需求和体系框架,介绍了环境信息数据仓库建设的关键技术和基于数据仓库的决策支持系统,列举了环境信息数据仓库在2000年2001年间对我国西部12个省、自治区和直辖市的大范围生态环境调查课题中的应用价值。     

Inorganic pollution in water—the analyst's viewpoint†

Inorganic pollution comprises both major and minor constituents, although only 12 chemical elements may be considered major components. Twenty‐eight elements constitute a group of common minor elements and an additional 13 elements comprise a group of less common minor constituents. Reliable quantitative data are required on the occurrence of these substances in a wide variety of water types, usually at extremely low concentrations. The analysis of standard reference water samples provides information on the overall reliability of water‐quality data. Although most major constituents may be determined with acceptable reliability, determinations of certain minor constituents lack comparable precision; for example, determinations of boron, nickel, and chromium. Few precision data are available on the determination of the less common trace elements. Several comparatively new analytical techniques, such as flameless atomic absorption spectrophotometry, voltammetry, and emission spectroscopy with plasma excitation, appear capable of providing improved sensitivity.     

危险化学品装卸运输一体化安全风险预警平台设计与研究

针对危险化学品装卸环节与运输环节安全事故频发,涉及监管部门较多,及危险化学品流转过程中多物态、跨地域、跨时空的特征通过调研和分析,得出运输介质不符、疲劳驾驶、超载、企业超资质营业、装卸操作不规范等是影响危险化学品装卸、运输环节的主要安全风险因素;另外,装卸、运输环节安全风险影响因素之间存在紧密的耦合关系。为更有效落实企业安全生产主体责任和政府监管职责,严格依据相关法律法规和标准,并融合互联网、物联网、人工智能、地理信息等新一代信息化技术和理念,设计并研究集危险化学品装卸与运输一体化的安全风险预警平台。目前该平台已在山东淄博上线试运行,取得了良好的运行效果,提高了该市危险化学品装卸运输过程本质安全水平,增强了政府危险化学品监管能力。     

消防部队灭火救援安全现状分析及对策

通过对"十五"期间我国消防队员伤亡数据及近年来部分消防队员在灭火救援过程中伤亡案例的剖析,造成消防队员伤亡既有救援对象复杂、救援工作固有危险性增大等客观原因,更重要的是由于部分消防队员安全观念滞后、安全防护措施落实不到位、安全训练不够而导致伤亡的发生。建立健全消防员伤亡事故调查制度、风险管理制度和专职安全员制度,提升灭火救援活动标准化管理水平,提高消防员综合素质,加强灭火救援现场的安全管理是减少消防员伤亡的有效措施。     

Analysis of laboratory incident database

With the growth of academic institutions, the number of labs handling hazardous chemicals has increased. Although the chemicals used in academic institutions are well-known, the dosage, usage, and management of these chemicals pose significant threat to researchers at all levels. As a step towards incident prevention, a laboratory incident database was developed to record incidents at universities and secondary schools. The data consisted of 128 entries occurring during the years 2012–2015. Incidents were classified by institution type, hazard type, consequences, substance type, body parts injured and direct causes. Of 128 incidents, 65% of the incidents were taking place in universities. Chemical spills were observed to be the most recurrent hazard type contributing to 45% of the incidents following by explosions (23%) and fires (21%). The consequence which most frequently occurred in incidents was personal injury and hazmat response contributing to 22% each. It was observed that in 41% of the incidents, the body parts injured in the incident was not known or reported. Of the total 128 incidents, about 50 incidents occurred due to improper storage and handling.     

A Comparison of Data Sets Varying in Spatial Accuracy Used to Predict the Occurrence of Wildlife-Vehicle Collisions

Wildlife-vehicle collisions (WVCs) pose a significant safety and conservation concern in areas where high-traffic roads are situated adjacent to wildlife habitat. Improving transportation safety, accurately planning highway mitigation, and identifying key habitat linkage areas may all depend on the quality of WVC data collection. Two common approaches to describe the location of WVCs are spatially accurate data derived from global positioning systems (GPS) or vehicle odometer measurements and less accurate road-marker data derived from reference points (e.g., mile-markers or landmarks) along the roadside. In addition, there are two common variable types used to predict WVC locations: (1) field-derived, site-specific measurements and (2) geographic information system (GIS)-derived information. It is unclear whether these different approaches produce similar results when attempting to identify and explain the location of WVCs. Our first objective was to determine and compare the spatial error found in road-marker data (in our case the closest mile-marker) and landmark-referenced data. Our second objective was to evaluate the performance of models explaining high- and low-probability WVC locations, using congruent, spatially accurate (<3-m) and road-marker (<800-m) response variables in combination with field- and GIS-derived explanatory variables. Our WVC data sets were comprised of ungulate collisions and were located along five major roads in the central Canadian Rocky Mountains. We found that spatial error (mean ± SD) was higher for WVC data referenced to nearby landmarks (516 ± 808 m) than for data referenced to the closest mile-marker data (401 ± 219 m). The top-performing model using the spatially accurate WVC locations contained all explanatory variable types, whereas GIS-derived variables were only influential in the best road-marker model and the spatially accurate reduced model. Our study showed that spatial error and sample size, using road-marker data for ungulate species, are important to consider for model output interpretation, which will impact the appropriate scale on which to apply modeling results. Using road-marker references <1.6 km or GPS-derived data locations may represent an optimal compromise between data acquisition costs and analytical performance. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Estimating an homogeneous series of a population abundance indicator despite changes in data collection procedure: A hierarchical Bayesian modelling approach

Abundance indicators are required both to assess and to manage wild populations. As new techniques are developed and teams in charge of gathering the data change, data collection procedures (DCPs) can evolve in space and time. How to estimate an homogeneous series of abundance indicator despite changes in DCP? To tackle this question a hierarchical Bayesian modelling (HBM) approach is proposed. It integrates multiple DCPs in order to derive a single abundance indicator that can be compared over space and time irrespective of the DCP used. Compared to single DCP models, it takes further advantage for abundance estimation of the joint treatment of a larger set of spatio-temporal units. After presenting the general formulation of our HBM approach, it is applied to the juvenile Atlantic salmon (Salmo salar L.) population of the River Nivelle (France). Posterior model checking, using χ² discrepancy measure, do not reveal any inadequacy between the model and the data. Despite a change in the DCP used (successive removals to catch-per-unit of effort), a unique abundance indicator for the 425 spatio-temporal units (site × year) sampled over twenty-four years (1985-2008) is estimated. The HBM approach allows the assessment of precision of the abundance estimates and shows variation between DCPs: a reduction in precision is observed during the most recent years (2005-2008) when only the catch-per-unit of effort DCP was used. The merits and generality of our HBM approach are discussed. We contend it extends previous single DCP models or inter-calibration of two DCPs, and it could be applied to a wide range of specific situations (taxon and DCPs).     

A data similarity based analysis to consequential alarms of industrial processes

The analysis of consequential alarms is beneficial to avoiding alarm flooding and finding out root alarms in an industrial process. In this context, a novel similarity computation method taking into account of correlation delays between process alarms is introduced firstly. Subsequently, the Granger causality method is suggested to further clarify mutual impacts of similar alarm variables based on process data. Through the combination of alarm data similarity analysis and process data causality analysis, the consequential alarms can be effectively identified along with their evolution paths. An industrial case is employed to illustrate the benefits of the contribution.