Flow regime identification using neural network based electrodynamic tomography system

• Main Authors: Rahmat, Mohd. fua’ad, Hakilo, Ahmed sabit
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2004
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/12798/1/MohdFuaadHjRahmat2004_FlowRegimeIdentificationUsingNeural.pdf; http://eprints.utm.my/id/eprint/12798/; http://www.jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/408/398

Process tomography is a low cost, efficient and non-invasive industrial process imaging technique. It is used in many industries for process imaging and measuring. Provided that appropriate sensing mechanism is used, process tomography can be used in processes involving solids, liquids, gases, and any of their mixtures. In this paper, the process to be imaged and measured involves solid particles flow in gravity drop system. Electrical charge tomography or electrodynamic tomography is a tomographic technique using electrodynamic sensors. This paper presents the flow regime identification using neural network.