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Comparison of GUF and Monte Carlo methods to evaluate task-specific uncertainty in laser tracker measurement 被引量:1
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作者 杨景照 李国喜 +2 位作者 吴宝中 龚京忠 王杰 《Journal of Central South University》 SCIE EI CAS 2014年第10期3793-3804,共12页
Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplemen... Measurement uncertainty plays an important role in laser tracking measurement analyses. In the present work, the guides to the expression of uncertainty in measurement(GUM) uncertainty framework(GUF) and its supplement, the Monte Carlo method, were used to estimate the uncertainty of task-specific laser tracker measurements. First, the sources of error in laser tracker measurement were analyzed in detail, including instruments, measuring network fusion, measurement strategies, measurement process factors(such as the operator), measurement environment, and task-specific data processing. Second, the GUM and Monte Carlo methods and their application to laser tracker measurement were presented. Finally, a case study involving the uncertainty estimation of a cylindricity measurement process using the GUF and Monte Carlo methods was illustrated. The expanded uncertainty results(at 95% confidence levels) obtained with the Monte Carlo method are 0.069 mm(least-squares criterion) and 0.062 mm(minimum zone criterion), respectively, while with the GUM uncertainty framework, none but the result of least-squares criterion can be got, which is 0.071 mm. Thus, the GUM uncertainty framework slightly underestimates the overall uncertainty by 10%. The results demonstrate that the two methods have different characteristics in task-specific uncertainty evaluations of laser tracker measurements. The results indicate that the Monte Carlo method is a practical tool for applying the principle of propagation of distributions and does not depend on the assumptions and limitations required by the law of propagation of uncertainties(GUF). These features of the Monte Carlo method reduce the risk of an unreliable measurement of uncertainty estimation, particularly in cases of complicated measurement models, without the need to evaluate partial derivatives. In addition, the impact of sampling strategy and evaluation method on the uncertainty of the measurement results can also be taken into account with Monte Carlo method, which plays a guiding role in measurement planning. 展开更多
关键词 task-specific uncertainty laser tracker measurement uncertainty evaluation Monte Carlo method uncertainy framework(GUF)
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Data processing of small samples based on grey distance information approach 被引量:14
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作者 Ke Hongfa, Chen Yongguang & Liu Yi 1. Coll. of Electronic Science and Engineering, National Univ. of Defense Technology, Changsha 410073, P. R. China 2. Unit 63880, Luoyang 471003, P. R. China 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第2期281-289,共9页
Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is di... Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective. 展开更多
关键词 Data processing Grey theory Norm theory Small samples uncertainty assessments Grey distance measure Information whitening ratio.
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Possibilistic entropy-based measure of importance in fault tree analysis 被引量:1
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作者 He Liping Qu Fuzheng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第2期434-444,共11页
With respect to the subjective factors and nonlinear characteristics inherent in the important identification of fault tree analysis (FTA), a new important measure of FTA is proposed based on possibilistic informati... With respect to the subjective factors and nonlinear characteristics inherent in the important identification of fault tree analysis (FTA), a new important measure of FTA is proposed based on possibilistic information entropy. After investigating possibilistic information semantics, measure-theoretic terms, and entropy-like models, a two-dimensional framework has been constructed by combining both the set theory and the measure theory. By adopting the possibilistic assumption in place of the probabilistic one, an axiomatic index of importance is defined in the possibility space and then the modelling principles are presented. An example of the fault tree is thus provided, along with the concordance analysis and other discussions. The more conservative numerical results of importance rankings, which involve the more choices can be viewed as “soft” fault identification under a certain expected value. In the end, extension to evidence space and further research perspectives are discussed. 展开更多
关键词 importance measure information measure possibilistic entropy possibilistic uncertainty nonspeci-ficity
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Characterization of a Powertrain Test Bed in the Context of Virtual Validation of Drivability
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作者 Schmidt HENRIK Prokop GÜNTHER 《同济大学学报(自然科学版)》 EI CAS CSCD 北大核心 2024年第S01期9-19,共11页
Technological trends in the automotive industry toward a software-defined and autonomous vehicle require a reassessment of today’s vehicle development process.The validation process soaringly shapes after starting wi... Technological trends in the automotive industry toward a software-defined and autonomous vehicle require a reassessment of today’s vehicle development process.The validation process soaringly shapes after starting with hardware-in-the-loop testing of control units and reproducing real-world maneuvers and physical interaction chains.Here,the road-to-rig approach offers a vast potential to reduce validation time and costs significantly.The present research study investigates the maneuver reproduction of drivability phenomena at a powertrain test bed.Although drivability phenomena occur in the frequency range of most up to 30∙Hz,the design and characteristics substantially impact the test setup’s validity.By utilization of modal analysis,the influence of the test bed on the mechanical characteristic is shown.Furthermore,the sensitivity of the natural modes of each component,from either specimen or test bed site,is determined.In contrast,the uncertainty of the deployed measurement equipment also affects the validity.Instead of an accuracy class indication,we apply the ISO/IEC Guide 98 to the measurement equipment and the test bed setup to increase the fidelity of the validation task.In conclusion,the present paper contributes to a traceable validity determination of the road-to-rig approach by providing objective metrics and methods. 展开更多
关键词 powertrain test bed virtual validation modal analysis powertrain-hardware-in-the-loop DRIVABILITY measurement uncertainty
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