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Systematic errors and measurement uncertainty: An experimental approach
- Source :
- Measurement. 44:1781-1789
- Publication Year :
- 2011
- Publisher :
- Elsevier BV, 2011.
-
Abstract
- The paper discusses the problem of quantifying the contribution of systematic errors on the overall measurement uncertainty. After a brief review of the recommendations of the Guide to the Expression of Uncertainty in Measurement (GUM), and of some notable alternative methods already proposed in the literature, the authors outline a fully experimental approach, which is based on the ISO 5725 ideas, circumventing the adoption of the concepts of “degree of belief” and “subjective probability” which, instead, are central both in the GUM and in the proposed alternatives. As a matter of fact, the proposed experimental approach does not alter the mathematical framework of the GUM (differently from the alternative proposals), but imposes that the uncertainty is always an experimentally verifiable, or refutable, figure. Theoretical considerations are followed by the description of an experimental scheme to study the uncertainty due to systematic errors in generic instruments and, in particular, in ADC-based instruments. A major focus is given to experimental results obtained for the systematic gain error, which, in turn, plays a significant role in the overall error contribution. The ultimate goal of the paper is to provide a basis to promote reflections upon a central problem: how much subjectivity and objectivity should be allowed in an uncertainty evaluation.
- Subjects :
- Engineering
Observational error
business.industry
Applied Mathematics
Uncertainty
Data acquisition
Condensed Matter Physics
Expression (mathematics)
Measurement errors
Measurement error
Analog-to-digital conversion
Risk analysis (engineering)
Econometrics
Measurement uncertainty
Sensitivity analysis
Verifiable secret sharing
Electrical and Electronic Engineering
Uncertainty, Measurement errors, Analog-to-digital conversion, Data acquisition
Focus (optics)
Objectivity (science)
business
Instrumentation
Uncertainty analysis
Subjects
Details
- ISSN :
- 02632241
- Volume :
- 44
- Database :
- OpenAIRE
- Journal :
- Measurement
- Accession number :
- edsair.doi.dedup.....178ad15d8c9f2ef1d9d00dc2f3a488e1
- Full Text :
- https://doi.org/10.1016/j.measurement.2011.07.011