Premium
z ‐Transform and adaptive signal processing in analysis of tracer data
Author(s) -
Furman Leszek
Publication year - 2002
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.5450800316
Subject(s) - tracer , a priori and a posteriori , residence time distribution , computer science , flow (mathematics) , interpretation (philosophy) , transfer function , time domain , signal processing , field (mathematics) , data processing , residence time (fluid dynamics) , algorithm , data mining , mathematics , mechanics , engineering , physics , digital signal processing , electrical engineering , geotechnical engineering , epistemology , pure mathematics , nuclear physics , computer hardware , computer vision , programming language , operating system , philosophy
Abstract In the field of data processing, the common practice is to interpret tracer‐determined residence time distributions (RTDs) of particles through different arrangements of elementary flow models. However, such analysis needs an a priori chosen arrangement of these models, and some information carried by the RTD curve may be lost. This paper presents a competitive method based on adaptive filtering in a z ‐transform domain, and it may give better insight into flow patterns in a steady‐state flow system. A physical interpretation of the transfer function was developed. The application of this modelling to the interpretation of radiotracer data from recent studies in different industry sectors is presented.