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ETDs @PUC-Rio
Estatística
Título: COMPARISON OF DIFFERENT APPROACHES FOR DETECTION AND TREATMENT OF OUTLIERS IN METER FACTORS DETERMINATION
Autor: ANDERSON LUIZ DOS SANTOS FERREIRA
Colaborador(es): ELCIO CRUZ DE OLIVEIRA - Orientador
Catalogação: 20/FEV/2018 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=33040&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=33040&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.33040
Resumo:
The objective of the dissertation is to analyze the behavior of the different methodologies used for the detection and treatment of outliers in the determination of meter proving factors of turbine type meters. The motivation of this work is to avoid mistaken decision-making as a result of inadequate treatment of outliers, compromising reliability in measurement and consequently its billing. A meter proving factor can be considered as a calibration parameter, by expressing the ratio the reference volume and the gross volume of liquid passed through a meter. The international guideline recommends Dixon s test for outliers to a meter proving factor set. However, the literature is explicit regarding the evaluation of data behavior, a priori. The methodology evaluates if the behavior of the meter proving factor set is Gaussian, then different parametric and nonparametric approaches for detection and treating outliers applied to turbine meter proving factors for custody transfer of liquefied petroleum gas are compared. Afterwards, this effect is evaluated in relation to the number of outliers and how this handling affects the variable range criteria for expanded uncertainty in average meter proving factor. The results show that different average meter factors can be reached for each nonparametric and parametric test; anyway, it is concluded that no statistically significant difference between them is noticed.
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