A fuzzy inference system for two-phase flow regime identification from radiography images
Artikel i vetenskaplig tidskrift, 2010
Swiftly identifying the two-phase flow that occurs in coolant
channels is crucial for monitoring energy producing installations such as
boiling water reactors. In this piece of research, a Sugeno-type fuzzy inference
system is implemented for online, non-invasive flow regime identification. The
proposed system is predominantly efficient in its construction and operation: a
single directly computable input is employed and as many fuzzy inference
outputs and rules are used as there are flow regimes to be identified. Noninvasiveness
is accomplished through the utilisation of radiography images.
Compactness notwithstanding, the fuzzy inference system successfully and
reliably identifies the flow regime of sequences of frames from neutron
radiography videos.
energy producing installations
boiling water reactors
flow regime identification
online operation.online operation.online operation.on-line operation.
Sugeno-type
two-phase flow
non-invasiveness
monitoring
coolant channels
fuzzy inference system
neutron radiography images/videos