TY - GEN
T1 - Spectral Analysis of Line-Up Bubbles Flow Phenomena Using Electrical Impedance Signals in a Vertical Tube
AU - López, Alberto Soria
AU - Sierra, Juan Carlos Rodríguez
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - The technique of spectral analysis for multiphase phenomena identification is based on the transformed in frequency domain of the electrical impedance signal. A sensor of variable size electrodes were used to measure electrical impedance signals caused by bubble trains in still water. The experiments have been performed in a vertical transparent pipe system. The spectral power density was correlated with observed phenomena through video recording, in order to show that low and middle frequency peaks can be associated to dynamic phenomena, while high frequency peaks could not be clearly correlated to flow particularities. Five characteristic range frequencies were identified: low-frequency large-amplitude and rising-energy, low-frequency middling-amplitude and rising-energy fluctuations, middle-frequency small-amplitude and decreasing-energy fluctuations, high-frequency small-amplitude and decreasing-energy fluctuations, high-frequency small-amplitude and constant energy fluctuation. Each frequency range was associated with the time domain and the individual peaks interpretation of the simultaneously observed phenomena by a video recording could be assessed.
AB - The technique of spectral analysis for multiphase phenomena identification is based on the transformed in frequency domain of the electrical impedance signal. A sensor of variable size electrodes were used to measure electrical impedance signals caused by bubble trains in still water. The experiments have been performed in a vertical transparent pipe system. The spectral power density was correlated with observed phenomena through video recording, in order to show that low and middle frequency peaks can be associated to dynamic phenomena, while high frequency peaks could not be clearly correlated to flow particularities. Five characteristic range frequencies were identified: low-frequency large-amplitude and rising-energy, low-frequency middling-amplitude and rising-energy fluctuations, middle-frequency small-amplitude and decreasing-energy fluctuations, high-frequency small-amplitude and decreasing-energy fluctuations, high-frequency small-amplitude and constant energy fluctuation. Each frequency range was associated with the time domain and the individual peaks interpretation of the simultaneously observed phenomena by a video recording could be assessed.
KW - bubble column
KW - electrical impedance sensor
KW - spectral analysis
KW - two-phase flow
KW - void fraction
UR - http://www.scopus.com/inward/record.url?scp=84946110791&partnerID=8YFLogxK
U2 - 10.1109/ICMEAE.2014.37
DO - 10.1109/ICMEAE.2014.37
M3 - Contribución a la conferencia
AN - SCOPUS:84946110791
T3 - Proceedings - 2014 IEEE International Conference on Mechatronics, Electronics, and Automotive Engineering, ICMEAE 2014
SP - 163
EP - 167
BT - Proceedings - 2014 IEEE International Conference on Mechatronics, Electronics, and Automotive Engineering, ICMEAE 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Mechatronics, Electronics, and Automotive Engineering, ICMEAE 2014
Y2 - 18 November 2014 through 21 November 2014
ER -