Process Failure Detection via Recurrence Quantification Analysis in a Slot-Rectangular Spouted Bed
Author(s) -
Steven Rowan,
Ronald W. Breault,
Justin Weber,
Nari Soundarrajan
Publication year - 2020
Publication title -
journal of energy resources technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.615
H-Index - 48
eISSN - 1528-8994
pISSN - 0195-0738
DOI - 10.1115/1.4046457
Subject(s) - recurrence quantification analysis , mechanics , economies of agglomeration , leak , pressure drop , materials science , flow (mathematics) , process (computing) , simulation , nonlinear system , computer science , engineering , thermodynamics , physics , chemical engineering , quantum mechanics , operating system
A study was conducted to explore the applicability of recurrence and recurrence quantification analysis (RQA) to the detection of process failures in spouted bed reactor systems. Three different potential failure modes were examined in a transparent, cold flow slot-rectangular spouted bed. These being, a simulated air leak from a side wall of the reactor, a simulated gas leak from the top wall of the reactor, and simulated agglomeration of solids via introduction of larger “klinker” particles. Bed pressure drop time history data were collected and analyzed via generation of recurrence plots (RPs) and RQA parameters. In general, the simulated agglomeration case was quite easily detected via ever RQA Parameter examined, whereas the simulated air leaks were detected by only a single RQA parameter.
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