Phase boundary estimation in electrical resistance tomography with weighted multi-layered neural networks and front point approach

Kim, J. H., Kang, B. C., Lee, S. H., Choi, B. Y., Kim, M. C., Kim, B. S., Ijaz, U. Z. , Kim, K. Y. and Kim, S. (2006) Phase boundary estimation in electrical resistance tomography with weighted multi-layered neural networks and front point approach. Measurement Science and Technology, 17(10), pp. 2731-2739. (doi: 10.1088/0957-0233/17/10/027)

Abstract

This work presents a boundary estimation approach in electrical impedance imaging for binary mixture fields based on weighted multi-layered neural network and front point approach. The interfacial boundary is expressed with front points and the unknown front points are estimated with the weighted multi-layered neural network. Numerical experiments show that the proposed electrical resistance imaging approach has a good possibility for the application in the visualization of a binary mixture boundary for real-time monitoring.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ijaz, Dr Umer
• Authors: Kim, J. H., Kang, B. C., Lee, S. H., Choi, B. Y., Kim, M. C., Kim, B. S., Ijaz, U. Z., Kim, K. Y., and Kim, S.
• College/School: College of Science and Engineering > School of Engineering > Infrastructure and Environment
• Journal Name: Measurement Science and Technology
• Publisher: Institute of Physics Publishing Ltd.
• ISSN: 0957-0233
• ISSN (Online): 1361-6501