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  5. Improving of the type A uncertainty evaluation by refining the collected data from periodical and non-periodical influences

Improving of the type A uncertainty evaluation by refining the collected data from periodical and non-periodical influences

Z.L. Warsza, M.J. Korczynski
Системи обробки інформації. — 2008. — № 4(71). – С. 19-26.
УДК 6.91
Мова статті: англійська
Анотації на мовах:

A new approach to improving the type A uncertainty evaluation by cleaning of the collected data from unwanted influences which appears as non-periodical and periodical components identified in the data is presented in the paper. The approach refers to regularly in time sampled data. The non-periodical components are equivalent to trends while the periodical components are a type of disturbances of unknown a priori period. The cleaning process comply with the main stream of ISO GUM recommendation and can be recognized as good practice in uncertainty evaluation as the elimination of the influence like identified drift and periodic components are resulting in better approximation of the type A uncertainty. The proposed approach is discussed in the paper and the numerical result is presented as well
Ключові слова: the measurement process, the type A uncertainty ,the systematic component
Інформація про авторів публікації:
Reference:
Warsza, Z.L. and Korczynski, M.J. (2008), Improving of the type A uncertainty evaluation by refining the collected data from periodical and non-periodical influences, Information Processing Systems, Vol. 4(71), pp. 19-26.