TY - GEN
T1 - Reverse Polarity Scanning Method on 64-Channel Capacitive Sensor to Improve the Performance of ECVT System
AU - Yusuf, Arbai
AU - Santoso Tamsir, Agus
AU - Sudiana, Dodi
AU - Harry, Sudibyo S.
N1 - Funding Information:
ACKNOWLEDGMENT The author would like to thank all parties who kindly contribute to this research: Warsito P. Taruno, and Wahyu Widada from CTECH Labs Edwar Technology. This work is supported by a grant from Hibah PITTA DRPM Universitas Indonesia Grant Number: 2362/UN2.R3.1/HKP.05.00/2018.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/27
Y1 - 2018/11/27
N2 - This research proposes a scanning method on tomography namely electrical capacitance volume tomography (ECVT). This study discusses the new scanning method of reverse polarity scanning that is applied to 64-channel capacitive sensors. In tomography process, the data acquisition system measures the capacitance from capacitive sensors using scanning process by activating the electrode pairs. Generally, scanning process in ECVT uses conventional scanning by activating an electrode pair and measure the capacitance signal for the pair. This study proposes a new scanning process, by reversing the polarity of electrode in scanning method. The method is applied by changing the polarity of excitation electrode into detection electrode, and vice versa. Then, both of methods are compared to evaluate the performance of the acquisition system. Simulation and experiment are performed using 64-channel capacitive sensors with cylinder rods phantom filled with water. To evaluate the performance of the ECVT system, static objects were used to measure parameters such as Mean Absolute Error (MAE), Coefficient-Correlation (R), and image qualitative observation. From the simulation and experiment, the Coefficient-Correlation (R) value as 0.6 and Mean Absolute Error (MAE) value as 0.2, so that the proposed method can improve image quality of 3.2%.
AB - This research proposes a scanning method on tomography namely electrical capacitance volume tomography (ECVT). This study discusses the new scanning method of reverse polarity scanning that is applied to 64-channel capacitive sensors. In tomography process, the data acquisition system measures the capacitance from capacitive sensors using scanning process by activating the electrode pairs. Generally, scanning process in ECVT uses conventional scanning by activating an electrode pair and measure the capacitance signal for the pair. This study proposes a new scanning process, by reversing the polarity of electrode in scanning method. The method is applied by changing the polarity of excitation electrode into detection electrode, and vice versa. Then, both of methods are compared to evaluate the performance of the acquisition system. Simulation and experiment are performed using 64-channel capacitive sensors with cylinder rods phantom filled with water. To evaluate the performance of the ECVT system, static objects were used to measure parameters such as Mean Absolute Error (MAE), Coefficient-Correlation (R), and image qualitative observation. From the simulation and experiment, the Coefficient-Correlation (R) value as 0.6 and Mean Absolute Error (MAE) value as 0.2, so that the proposed method can improve image quality of 3.2%.
KW - ECVT
KW - capacitive sensor
KW - ill posed
KW - reverse polarity scanning
KW - stray capacitance
UR - http://www.scopus.com/inward/record.url?scp=85060043668&partnerID=8YFLogxK
U2 - 10.1109/ISEMANTIC.2018.8549720
DO - 10.1109/ISEMANTIC.2018.8549720
M3 - Conference contribution
AN - SCOPUS:85060043668
T3 - Proceedings - 2018 International Seminar on Application for Technology of Information and Communication: Creative Technology for Human Life, iSemantic 2018
SP - 159
EP - 165
BT - Proceedings - 2018 International Seminar on Application for Technology of Information and Communication
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018
Y2 - 21 September 2018 through 22 September 2018
ER -