This volume contains original, refereed contributions by researchers from institutions and laboratories across the world that are involved in metrology and testing. They were adapted from presentations made at the eleventh edition of the Advanced Mathematical and Computational Tools in Metrology and Testing conference held at the University of Strathclyde, Glasgow, in September 2017, organized by IMEKO Technical Committee 21, the National Physical Laboratory, UK, and the University of Strathclyde. The papers present new modeling approaches, algorithms and computational methods for analyzing data from metrology systems and for evaluation of the measurement uncertainty, and describe their applications in a wide range of measurement areas.
This volume is useful to all researchers, engineers and practitioners who need to characterize the capabilities of measurement systems and evaluate measurement data. Through the papers written by experts working in leading institutions, it covers the latest computational approaches and describes applications to current measurement challenges in engineering, environment and life sciences.
Contents:- Analysis of Key Comparisons with Two Reference Standards: Extended Random Effects Meta-Analysis (O Bodnar and C Elster)
- Confirmation of Uncertainties Declared by KC Participants in the Presence of an Outlier (A G Chunovkina and A Stepanov)
- Quantity in Metrology and Mathematics: A General Relation and the Problem (V A Granovskii)
- Bayesian Analysis of an Errors-in-Variables Regression Problem (I Lira and D Grientschnig)
- Triangular Bézier Surface: From Reconstruction to Roughness Parameter Computation (L Pagani and P J Scott)
- On the Classification into Random and Systematic Effects (F Pavese)
- Measurement Models (A Possolo)
- Metrology and Mathematics — Survey on a Dual Pair (K H Ruhm)
- Fundaments of Measurement for Computationally-Intensive Metrology (P J Scott)
- Study of Gear Surface Texture Using Mallat's Scattering Transform (W Sun, S Chrétien, R Hornby, P Cooper, R Frazer and J Zhang)
- The Evaluation of the Uncertainty of Measurements from an Autocorrelated Process (N F Zhang)
- Dynamic Measurement Errors Correction in Sliding Mode Based on a Sensor Model (M N Bizyaev and A S Volosnikov)
- and other papers
Readership: Researchers, graduate students, academics and professionals in metrology.
Key Features:- Description of state of the art techniques for modeling measurement systems and analyzing measurement data
- Written by researchers active in institutions developing world-leading measurement capabilities
- Provides a multi-disciplinary approach to addressing measurement challenges in a wide range of applications
