Local gas holdup measurement of a bubble column using SONIA-ultrasonic non-invasive method

Muhammad R. Widyanto*, Marsudi B. Utomo, Kazuhiko Kawamoto, Benyamin Kusumoputro, Kaoru Hirota

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

12 引用 (Scopus)

摘要

A non-invasive technique for local gas holdup measurement of a bubble column using Self-Organized Network inspired by Immune Algorithm (SONIA) neural network and ultrasonic method is investigated. The energy attenuation and the transmission time difference of ultrasound are used as measurement parameters to obtain the local gas holdup in an air-water dispersion system using SONIA neural network reconstruction. Bubble size distributions in the bubble column are obtained by using a photographic method. The experimental results and simulations on three different mean bubble size condition show that the errors of SONIA neural network method is 1/9 times lower than those of the conventional back-propagation neural network. The results show a good agreement with measured data.

源语言英语
页(从-至)447-454
页数8
期刊Sensors and Actuators A: Physical
126
2
DOI
出版状态已出版 - 14 2月 2006
已对外发布

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