9783642209888-3642209882-Measurement Uncertainties: Physical Parameters and Calibration of Instruments

Measurement Uncertainties: Physical Parameters and Calibration of Instruments

ISBN-13: 9783642209888
ISBN-10: 3642209882
Edition: 2012
Author: S. V. Gupta
Publication date: 2012
Publisher: Springer
Format: Hardcover 344 pages
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Book details

ISBN-13: 9783642209888
ISBN-10: 3642209882
Edition: 2012
Author: S. V. Gupta
Publication date: 2012
Publisher: Springer
Format: Hardcover 344 pages

Summary

Measurement Uncertainties: Physical Parameters and Calibration of Instruments (ISBN-13: 9783642209888 and ISBN-10: 3642209882), written by authors S. V. Gupta, was published by Springer in 2012. With an overall rating of 4.0 stars, it's a notable title among other Industrial, Manufacturing & Operational Systems (Engineering) books. You can easily purchase or rent Measurement Uncertainties: Physical Parameters and Calibration of Instruments (Hardcover) from BooksRun, along with many other new and used Industrial, Manufacturing & Operational Systems books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This book fulfills the global need to evaluate measurement results along with the associated uncertainty. In the book, together with the details of uncertainty calculations for many physical parameters, probability distributions and their properties are discussed. Definitions of various terms are given and will help the practicing metrologists to grasp the subject. The book helps to establish international standards for the evaluation of the quality of raw data obtained from various laboratories for interpreting the results of various national metrology institutes in an international inter-comparisons. For the routine calibration of instruments, a new idea for the use of pooled variance is introduced. The uncertainty calculations are explained for (i) independent linear inputs, (ii) non-linear inputs and (iii) correlated inputs. The merits and limitations of the Guide to the Expression of Uncertainty in Measurement (GUM) are discussed. Monte Carlo methods for the derivation of the output distribution from the input distributions are introduced. The Bayesian alternative for calculation of expanded uncertainty is included. A large number of numerical examples is included.

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