电能质量在线监测的供电可靠性提升策略探究

现代电力技术的发展,多种电网监测技术逐渐被应用于电力系统,用来监测电网的电能质量,其中具有自动化采集数据的在线监测系统能够确保监测质量。本文分析了电能质量在线监测系统的优势,并分析了其在电能质量监测的具体应用以及取得的成效。     

电能质量监测的现状及展望

电能作为走进市场的商品,与其他商品一样,无疑也应讲求质量。本文从衡量电能质量的主要指标、电能质量控制策略与技术、电能质量监测装置、电能质量分析方法等方面论述了日益引起人们关注的电能质量监测的现状,并从基础理论的研究、新型算法的开发、电能质量监测的网络化、智能化等方面对电能质量监测的发展进行了展望。     

提高环境监测工作质量的方法与实践

环境监测工作质量是指与监测结果有关的各项工作对监测结果质量的保证程度。提高监测结果质量的前提是提高监测工作质量。本文对环境监测工作质量的问题及其对策进行了探讨     

我国将构建国家粮食质量监测体系

日前,国家粮食局发布了“关于建立国家粮食质量监测体系的通知”,该《通知》对建立国家粮食质量监测体系的重要意义、基本原则、粮食质量监测机构的任务、基本条件和监测体系的管理等事项做出了明确规定。     

太湖饮用水源地蓝藻预警监测质量管理体系的构建

预警监测质量管理工作应贯穿预警监测工作的各个环节,从日常监测质量保障和预警监测质量管理两个方面,确保预警监测的顺利进行。     

浅谈水环境监测质量的有效控制

水环境是人们赖以生存的基础,保证水环境监测质量有着重要的意义。水环境监测质量的控制作为监测过程的关键环节,为水环境监测工作的顺利开展发挥积极作用。通过对水环境监测的质量控制进行深入研究,解决其中存在的问题,改进质量控制工作,以此提升水环境监测质量的控制水平,为水环境提供有效的保障。     

浅谈开展农村环境质量监测的必要性及建议

本文结合国家环境保护“十二五“规划中提出的关于提高农村环境保护工作水平的要求,结合现阶段开展的农村环境质量监测工作提出了需加快开晨农村环境质量监测的必要性,并对农村环境质量监测提出了一些合理化的建议。     

预浸料的质量控制

预浸料的原料质量尤其是树脂质量是保证预浸料性能的基础,在预浸料制备过程中,及时、有效、无损的在线监测是预浸料发挥性能的保证。简要介绍了几种常用的在线监测手段,包括β射线监测、超声波监测、红外光谱监测及近红外光谱监测等。此外,预浸料成品的质量控制是复合材料性能的关键,其中凝胶时间、树脂流动性、挥发分含量、树脂含量、单位面积纤维质量等是预浸料重要的质量指标。     

外照射个人剂量监测技术及质量控制

外照射个人剂量监测是个人辐射防护的一项重要工作 ,是为了监测和控制放射工作人员所接受的辐射剂量 ,是关系到放射工作人员安全健康的重要工作。本文着重从监测计划、测量系统质量控制、结果解释评价及整体综合质量控制四个方面介绍了开展外照射个人剂量监测工作的技术要求及质量控制问题。     

网络点击

<正>我国农产品质量安全保持较高水平农业部日前公布了2010年第二次农产品质量安全例行监测信息,监测结果显示,蔬菜、畜禽产品和水产品合格率分别为96.9%、99.8%和95.8%,我国农产品质量安全保持较高水平。农业部已将监测结果通报各地,要求对监测发现的突出问题进行认真整改,有针对性地跟进开展农产品质量安全监督抽查,加大对不合格农产品及其生产经营企业的     

质量保证和质量控制技术在茶园土壤重金属监测中的应用

质量控制不仅是一项具体的工作也是一项实验室管理工作,它要求有科学的实验室管理制度和正确的操作规程以及技术考核措施。在土壤环境监测中质量控制目的是为了保证土壤环境质量监测数据具有代表性、准确性、精密性、可比性和完整性。本文以福建省茶园土壤环境质量调查项目中重金属监测为例,建立了一套土壤中重金属监测的质量控制程序。在考虑经济成本和效益以及项目研究要求的基础上确定分析结果的质量要求,并根据实际情况采取有效的方法对分析结果进行质量评价,及时发现分析过程中的质量问题并纠正系统误差。     

Improving the Product Reliability in Multistage Manufacturing and Service Operations

Monitoring and improving the product reliability is of main concern in a large number of multistage manufacturing processes. The process output is commonly inspected under limited load conditions, and the tensile strength of reliability‐related quality characteristic is measured. This brings about censored observations that make the direct application of traditional control charts futile. The monitoring procedure becomes aggravated when the influence of variable competing risk is pronounced during the conducted test. To deal with this critical issue, we propose a regression‐adjusted cumulative sum (CUSUM) chart to effectively monitor a quality characteristic that may be right censored because of both fixed and variable competing risks. Moreover, two exponentially weighted moving average (EWMA) control charts on the basis of conditional expected values are devised to detect decreases in the tensile mean. The comparison of the three competing monitoring schemes confirms the superiority of the regression‐adjusted CUSUM procedure. Not only is the proposed control chart applicable to manufacturing processes with the aim of monitoring reliability‐related quality variables, it is also appropriate for monitoring similar quality measurements in service operations such as survivability measures in healthcare services. Copyright © 2011 John Wiley & Sons, Ltd.     

浅谈氢氧火箭发动机液流试验用水技术指标和质量控制

氢氧火箭发动机试验用水水质直接关系到产品试后性能和多余物控制预防.通过对试验用水存在的问题和影响的研究,结合实际运行中的水质化验实测数据,以相关国家标准为依据,分析了试验用水水质关键指标和限定范围并提出了相应的控制监测方法,具有较大的指导意义.     

Environmental management plan for port and harbour projects

Port activities can cause deterioration of air and marine water quality in the surrounding areas due to multifarious activities. Hence, for the determination of levels of pollution, identification of pollution sources, control and disposal of waste from various point and non-point sources and for prediction of pollution levels for future, regular monitoring and assessment are required during the entire construction and operation phase of a major port. It is extremely essential that port and harbour projects should have an environmental management plan (EMP), which also incorporates monitoring of air and marine water quality along with the collection of online meteorological data throughout the life of the project. This paper presents the environmental impacts due to various port activities and their sources and also discusses the EMP for different pollution prevention, protection and control measures.     

Bayesian monitoring of linear profile monitoring using DEWMA charts

Process monitoring is an essential element for an improved quality of final products. A variety of tools are used for it; control charts are one of these choices. Classical and Bayesian thoughts are 2 main aspects of statistics used in different areas of application. This study introduces an approach to existing theories in applied quality control: Bayesian double exponentially weighted moving average (DEWMA) control charts for monitoring the profiles of products and processes. Three novel univariate Bayesian DEWMA charting structures for the Y intercepts, slopes, and error variances are designed under phase 2 procedures. The performance of the designed structures of control charts is evaluated based on different run length measures. The comparative analysis revealed that Bayesian DEWMA control charts are efficient at identifying the sustainable shifts in the process parameters. Moreover, DEWMA control charts are more effective under classical and Bayesian methodologies for detecting smaller value shifts compared with exponentially weighted moving average charts. We have examined that acquiring extra information in the form of prior's about process parameters comes up with tangible benefits and enhances the detection potential of DEWMA charts for profiles monitoring. An example and case studies are provided to justify the above findings.     

Control charts for the queue length in a G/G/S system

Statistical-process-control-based monitoring of performance measures of queuing systems has so far eluded mainstream practices within the quality engineering discipline. There are two reasons for this. First, most measures have highly skewed distributions, and, secondly, no general theoretical formulae exist that may provide a platform to calculate control limits for the general G/G/S queue. In this paper, Shewhart-like general control charts for attributes, recently introduced, are combined with existent highly accurate approximations for the steady-state probabilities of the G/G/S queue, to develop control charts for the queue size in a G/G/S system. The effectiveness of this approach is discussed and demonstrated by applying the proposed control charts to a sample of queues with various inter-arrival time and service time distributions.     

Design issues for adaptive control charts

Adaptive control charts allow the components of the quality‐monitoring scheme to vary in order to obtain improved performance over non‐adaptive control charts. Research has centered on components such as the sample size, time between samples, warning limits, and control limits and has recommended a variety of schemes, many of which are optimal in some sense. In practice, there are many other adaptive schemes that are near optimal, which will still yield considerable improvement over non‐adaptive control charts. In addition, the impact of parameter estimation on adaptive control chart performance must be taken into consideration. Based on the simulation results shown here, adaptive control charts should only be used for mature processes, where a sufficient amount of Phase I data have been obtained to ensure that the estimated control limits are accurate. When evaluating control chart performance, we consider initial state performance measures for simplicity and note that the conclusions obtained here apply to steady‐state performance measures. The evaluation of performance measures is easily handled by the Markov chain approach detailed in the Appendix. Copyright © 2008 John Wiley & Sons, Ltd.     

A control chart for monitoring the lognormal process variation using repetitive sampling

Control charts are developed to make the specific quality measures for a successful production process and follow normal distribution behaviors. But some real-life practices do not match such practices and exhibit some positively skewed behavior like lognormal distribution. The present study has considered this situation and proposed a monitoring control chart based on lognormal process variation using a repetitive sampling scheme. This concept proved better for detecting shifts as quickly as possible, and compared with the existing concept, results are elaborated through extensive tables. The average run lengths and standard deviations of the run lengths are being used as a performance evaluation measures and computed by using Monte Carlo simulations performed in R language. A real-life situation has been discussed in the example section to strengthen the proposed control chart concept in a real-life situation.     

EWMA Dispersion Control Charts for Normal and Non‐normal Processes

Process monitoring through control charts is a quite popular practice in statistical process control. This study is planned for monitoring the process dispersion parameter using exponentially weighted moving average (EWMA) control chart scheme. Most of the EWMA dispersion charts that have been proposed are based on the assumption that the parent distribution of the quality characteristic is normal, which is not always the case. In this study, we develop new EWMA charts based on a wide range of dispersion estimates for processes following normal and non‐normal parent distributions. The performance of all the charts is evaluated and compared using run length characteristics (such as the average run length). Extra quadratic loss, relative average run length, and performance comparison index measures are also used to examine the overall effectiveness of the EWMA dispersion charts.Copyright © 2014 John Wiley & Sons, Ltd.