@inproceedings{de3eb27dc5974945ab8ac56c7a704283,
title = "CLASSIFICATION OF SENSOR MEASUREMENTS FROM NON-NEWTOWNIAN FLUIDS USING BATCH AND ONLINE ANALYSIS OF DATA",
abstract = "With recent technological advancements most industrial processes collect an abundance of process data from sensors. Sensible utilization and interpretation of collected data is increasingly important. A primary objective of this work is to evaluate the potential of using only differential pressure measurements to classify operating flow rates of non-Newtonian fluids for single phase and multiphase flow conditions using both batch and online methods of data analysis. This was accomplished by using statistical tests and charts to monitor changes in the process mean and variance. For batch analysis, the two-sample t-test and the F-test for equality of variance provided classification accuracies of 100%, despite the presence of measurement noise, while advanced statistical hypothesis testing techniques, namely the generalized and exponential likelihood ratio charts, performed well for online analysis.",
keywords = "Data classification, flow analysis, generalized likelihood ratio (GLR), statistical hypothesis testing",
author = "Sheriff, {M. Ziyan} and Nounou, {Mohamed N.} and Rahman, {Mohammad A.} and Ibrahim Hassan and Nounou, {Hazem N.}",
note = "Publisher Copyright: Copyright {\textcopyright} 2023 by ASME.; ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2023 ; Conference date: 11-06-2023 Through 16-06-2023",
year = "2023",
doi = "10.1115/OMAE2023-108094",
language = "English",
series = "Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "Offshore Geotechnics; Petroleum Technology",
address = "United States",
}