Bayesian decision threshold, detection limit and confidence limits in ionising-radiation measurement

Based on Bayesian statistics and the Bayesian theory of measurement uncertainty, characteristic limits such as the decision threshold, detection limit and limits of a confidence interval can be calculated taking into account all sources of uncertainty. This approach consists of the complete evaluation of a measurement according to the ISO Guide to the Expression of Uncertainty in Measurement (GUM) and the successive determination of the characteristic limits by using the standard uncertainty obtained from the evaluation. This procedure is elaborated here for several particular models of evaluation. It is, however, so general that it allows for a large variety of applications to similar measurements. It is proposed for the revision of those parts of DIN 25482 and ISO 11929 that are still based on conventional statistics and, therefore, do not allow to take completely into account all the components of measurement uncertainty in the calculation of the characteristic limits.     

基于贝叶斯理论的测量不确定度A类评定

文章介绍了贝叶斯理论，并利用此理论对测量不确定度A类评定进行分析，与基于经典统计方法的不确定度A类评定相比，该方法能充分利用历史测量数据所提供的信息，因此评定时信息量大，使评定更加合理。最后通过实例分析说明了基于贝叶斯理论的不确定度A类评定的合理性和优越性。     

复杂测试系统量值稳定性检查监控方法及模型

针对复杂测试系统量值稳定性检查的特殊需求,提出基于测量过程控制的复杂测试系统量值稳定性检查监控方法;针对传统统计控制方法在测量过程控制中容易出现"误发警报"问题,给出基于Bayes参数优良估计、控制限优化的小样本控制图模型.说明了模型在某复杂测试系统量值稳定性检查监控中的具体应用,证明了方法和模型的有效性.     

基于贝叶斯理论的热电偶合格判定风险

民用航空用易耗型廉金属热电偶的指标要求远高于其他行业,但在进行计量确认时,一般忽略了测量不确定度的影响,带来了较大的质量风险。本文基于贝叶斯理论,对测量过程和测量不确定度对易耗型廉金属热电偶符合性判断的特定消费者风险和全局消费者风险进行分析。探究不同测量过程和不确定度下的决策错误率风险,并提出了降低风险的方法,为易耗型廉金属热电偶的计量确认提供了参考。     

滑板式汽车侧滑检验台示值误差测量结果的不确定度评定

本文依据JJG908-1996滑板式汽车侧滑检验台检定规程和JJF1059-1999测量不确定度评定与表示,对滑板式汽车侧滑检验台示值误差测量结果进行了不确定度的评定,通过阐述测量过程中产生的各分量对测量结果的影响,得到了测量结果的扩展不确定度。     

不确定度的Bayes表征与分析

本给出了测量不确定度的Ｂａｙｅｓ表征方法，该方法是通过对待测对象的测量结果验后分布的分析，获得不确定度表征所需参数值。与古典统计方法相比，Ｂａｙｅｓ方法具有估计精度高，不确定度的表征更为客观的特点。     

Decision making with epistemic uncertainty under safety constraints: An application to seismic design

The problem of accounting for epistemic uncertainty in risk management decisions is conceptually straightforward, but is riddled with practical difficulties. Simple approximations are often used whereby future variations in epistemic uncertainty are ignored or worst-case scenarios are postulated. These strategies tend to produce sub-optimal decisions. We develop a general framework based on Bayesian decision theory and exemplify it for the case of seismic design of buildings. When temporal fluctuations of the epistemic uncertainties and regulatory safety constraints are included, the optimal level of seismic protection exceeds the normative level at the time of construction. Optimal Bayesian decisions do not depend on the aleatory or epistemic nature of the uncertainties, but only on the total (epistemic plus aleatory) uncertainty and how that total uncertainty varies randomly during the lifetime of the project.     

Decision Support System for Maintenance Management Using Bayesian Networks

The maintenance process has undergone several major developments that have led to proactive considerations and the transformation fiom the traditional ＂fail and fix＂ practice into the ＂predict and prevent＂ proactive maintenance methodology. The anticipation action, which characterizes this proactive maintenance strategy is mainly based on monitoring, diagnosis, prognosis and decision-making modules. Oil monitoring is a key component of a successful condition monitoring program. It can be used as a proactive tool to identify the wear modes of rubbing pans and diagnoses the faults in machinery. But diagnosis relying on oil analysis technology must deal with uncertain knowledge and fuzzy input data. Besides other methods, Bayesian Networks have been extensively applied to fault diagnosis with the advantages of uncertainty inference; however, in the area of oil monitoring, it is a new field. This paper presents an integrated Bayesian network based decision support for maintenance of diesel engines.     

The application of Bayesian techniques in the interpretation of bioassay data

The inverse problem of internal dosimetry is naturally posed as a problem of Bayesian inference. The Bayesian approach is of practical importance in three areas: (1) avoiding false positives in the detection of rare events, (2) the calculation of uncertainties, and (3) the calculation of multiple intakes, all of which are important for internal dosimetry. In this paper, the Bayesian approach to the interpretation of measurements is first reviewed using a simple conceptual example. Then, a simple 239Pu case using IMBA expert is discussed, and finally a current cutting-edge example is discussed involving real 238Pu data calculated with a Markov Chain Monte Carlo algorithm and with exact calculation of poisson likelihood functions.     

非自动衡器测量不确定度评估及其在符合性判定中的应用

以OIMLR76国际建议中非自动衡器的称量试验为例,列举了2种容易对非自动衡器称量性能做出误判的情形.结合电子天平称量试验的3个案例,分析了修正误差与最大允许误差限较为接近时,直接采用"简单判定原则"作出符合性判定的误判风险,通过对线性载荷误差测量不确定度评估,分别对3个案例给出了95.45％、80.6％和18.1％的...     

浊度计测量结果不确定度分析

本文介绍了用于测量悬浮于水(或其他透明液体)中的不溶性颗粒物质含量的仪器浊度计的测量原理和计量单位，并依据计量检定规程(JJG880-1994)中检定示值相对误差的方法，对示值相对误差的测量结果进行不确定度评定，具体分析了各个不确定度分量的产生，并合成标准不确定度及有效自由度。评定示值相对误差测量结果的不确定度为U95rel=3．3％。     

Intermittent failure process and false alarm interaction modelling of threshold-based monitoring built-in tests (BITs)

Built-in tests (BITs) are widely used in manufacturing and production systems to find whether system failures occur, whereas the problem of BIT false alarms caused by intermittent failures adds to much trouble for the precise failure detection and diagnosis. Fighting with false alarms caused by intermittent failures is an urgent issue. However, the nature and temporal regularity of intermittent failures are not fully exploited, as well as the relationship between intermittent failure and BIT false alarms. The present paper introduces the method of constructing failure test profile for false alarm assessments. Probabilistic models are proposed of the failure evolution process, as well as the interactions between intermittent failures and false alarms. The false alarm time expectation is derived with the given model, serving as the foundation for the optimisation problem to find the best test threshold to enable the highest BIT capability. A numerical analysis is made to illustrate the proposed model and examine the threshold determination method. An application study is also carried out to show how the model can be applicable in real engineering practices.     

室内200 m虚拟基线测量方法的研究

为了解决手持式激光测距仪50m以上检测基准建立的问题,在50m高精度导轨上利用3个平面反射镜进行光路折叠,实现4倍光程倍增,搭建了室内200m基线。并将Leica TS15型全站仪视为检定基准,对基线长度进行标定。最后对Leica DISTOTM D510型手持式激光测距仪开展了50~200m测段的示值误差检定实验。实验结果表明: 室内基线系统的测量范围可拓宽至200m,示值误差检定结果的扩展不确定度为2.2mm(k=2),满足检定规程要求,有利于将长基线压缩至室内有限空间完成。     

Calculation of Measurement Uncertainty Using Prior Information

We describe the use of Bayesian inference to include prior information about the value of the measurand in the calculation of measurement uncertainty. Typical examples show this can, in effect, reduce the expanded uncertainty by up to 85 %. The application of the Bayesian approach to proving workpiece conformance to specification (as given by international standard ISO 14253-1) is presented and a procedure for increasing the conformance zone by modifying the expanded uncertainty guard bands is discussed.     

Bayesian multiple testing procedures for hotspot identification

Ranking a group of candidate sites and selecting from it the high-risk locations or hotspots for detailed engineering study and countermeasure evaluation is the first step in a transport safety improvement program. Past studies have however mainly focused on the task of applying appropriate methods for ranking locations, with few focusing on the issue of how to define selection methods or threshold rules for hotspot identification. The primary goal of this paper is to introduce a multiple testing-based approach to the problem of selecting hotspots. Following the recent developments in the literature, two testing procedures are studied under a Bayesian framework: Bayesian test with weights (BTW) and a Bayesian test controlling for the posterior false discovery rate (FDR) or false negative rate (FNR). The hypotheses tests are implemented on the basis of two random effect or Bayesian models, namely, the hierarchical Poisson/Gamma or Negative Binomial model and the hierarchical Poisson/Lognormal model. A dataset of highway–railway grade crossings is used as an application example to illustrate the proposed procedures incorporating both the posterior distribution of accident frequency and the posterior distribution of ranks. Results on the effects of various decision parameters used in hotspot identification procedures are discussed.     

测功机转矩示值误差测量结果的不确定度评定

本文主要根据JJF 1059-1999测量不确定度评定与表示计量技术规范，对测功机转矩示值误差的测量结果进行不确定度评定。通过评定，以此作为对相同情况下的测功装置进行测量不确定度评定的一种模式，以便于今后工作的开展。     

GUM与基于观测方程的测量不确定度评估

比较了GUM系列文件与贝叶斯方法评估不确定度的过程,说明GUM是以测量方程为基础的前向分析方法,而贝叶斯分析是以观测方程为基础、以数据分析为主的一种后向不确定度评估方法。运用概率模型的描述方法对上述两种分析过程进行了分析与比较,说明了两种方法在线性测量模型的条件下,不考虑被测量先验分布时两种结果基本一致,对于非线性的测量模型,GUM S1得到的结果与一定先验分布条件下的贝叶斯分析的结果也基本一致。最后通过实例说明了该结论。     

Uncertainties in workplace external dosimetry--an analytical approach

The uncertainties associated with external dosimetry measurements at workplaces depend on the type of dosemeter used together with its performance characteristics and the information available on the measurement conditions. Performance characteristics were determined in the course of a type test and information about the measurement conditions can either be general, e.g. 'research' and 'medicine', or specific, e.g. 'X-ray testing equipment for aluminium wheel rims'. This paper explains an analytical approach to determine the measurement uncertainty. It is based on the Draft IEC Technical Report IEC 62461 Radiation Protection Instrumentation-Determination of Uncertainty in Measurement. Both this paper and the report cannot eliminate the fact that the determination of the uncertainty requires a larger effort than performing the measurement itself. As a counterbalance, the process of determining the uncertainty results not only in a numerical value of the uncertainty but also produces the best estimate of the quantity to be measured, which may differ from the indication of the instrument. Thus it also improves the result of the measurement.     

基于预测模型的虚拟试验不确定性分析方法

 工程系统中不可避免地存在各种参数不确定性,利用数值计算模型对系统进行虚拟试验时应进行不确定性分析.大型耗时计算模型的不确定性分析将面临严重的的计算复杂性问题,为此,针对工程应用中耗时计算模型,提出一种基于贝叶斯预测模型的不确定性分析仿真方法,采用概率分布为参数不确定性建模,研究系统响应预测不确定性的概率特征.泰勒杆撞击实例验证了该方法的高效性.