Keywords: flow regime identification, two-phase flow, energy producing installations, boiling water reactors, coolant channels, monitoring, neutron radiography images, neutron radiography videos, fuzzy inference systems, Sugeno-type, non-invasiveness, online operations
A fuzzy inference system for two-phase flow regime identification from radiography images
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. Non-invasiveness 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.