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Study on Dual-Frequency Imaging of Capacitively Coupled Electrical Impedance Tomography: Frequency Optimization | IEEE Journals & Magazine | IEEE Xplore

Study on Dual-Frequency Imaging of Capacitively Coupled Electrical Impedance Tomography: Frequency Optimization


Abstract:

In this work, a new dual-frequency imaging framework of capacitively coupled electrical impedance tomography (CCEIT) is presented. Unlike conventional single-frequency im...Show More

Abstract:

In this work, a new dual-frequency imaging framework of capacitively coupled electrical impedance tomography (CCEIT) is presented. Unlike conventional single-frequency imaging and recently emerged multifrequency imaging, the dual-frequency imaging adopts two different working frequencies to obtain the real part and the imaginary part of the impedance, respectively. With the real part image and the imaginary part image reconstructed at the two frequencies, the framework further introduces image fusion to obtain the fused image. To achieve the optimal selection of the two frequencies, data collection in a wide frequency range is carried out with a 12-electrode CCEIT sensor, an impedance analyzer, and a computer to obtain the real part and the imaginary part measurements. The multifrequency data are then analyzed in depth, and other two aspects, including the sensitivity distribution and the imaging quality at different frequencies, are also investigated. Research results show that a low working frequency is recommended for the real part, while a relatively high working frequency is recommended for the imaginary part. Within the investigated frequency range of 200 kHz–20 MHz, the working frequencies for the real part and the imaginary part are optimized under the investigated distribution setups. Results of verification experiment show that the proposed framework is effective. Compared with single-frequency CCEIT, dual-frequency CCEIT with the two optimized frequencies has much better imaging performance.
Article Sequence Number: 4505718
Date of Publication: 01 July 2022

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I. Introduction

With the advantages of low cost, high speed, simple structure, and no radiation, electrical impedance tomography (EIT), also called electrical resistance tomography (ERT) in process tomography, has become a widely accepted technique for distribution reconstruction of conductive medium, which is applicable in both industrial processes and biomedical cases [1]–[5]. However, there still exist some issues limiting its practical applications. One problem of traditional EIT is its contact measurement principle. The contact between the electrodes and the measured medium has some unfavorable effects, such as electrochemical erosion, polarization effect, and electrode contamination, which are more prominent in practical industrial applications [2], [6]–[8], and contact impedance, which is notable in biomedical applications [9], [10]. To avoid the problems resulted from contact measurement, Wang et al. [11], [12] proposed the capacitively coupled electrical resistance tomography (CCERT) in 2013, which refers to the contactless measurement idea of capacitively coupled contactless conductivity detection () technique [13], [14]. Although the sensor structure of CCERT is similar to that of electrical capacitance tomography (ECT), which is basically for imaging dielectric or low-conductive materials, CCERT is regarded as a new kind of ERT that focuses on the imaging of conductive materials. The “CC” in CCERT comes from , indicating the keywords of the contactless measurement idea.

Cites in Papers - |

Cites in Papers - IEEE (5)

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1.
Yimin Wu, Yandan Jiang, Haifeng Ji, Baoliang Wang, Manuchehr Soleimani, "Image Reconstruction of Capacitively Coupled Electrical Resistance Tomography Based on An Improved Kalman Filter Model", IEEE Transactions on Instrumentation and Measurement, vol.74, pp.1-14, 2025.
2.
Shiyuan Zhu, Kun Li, Shihong Yue, Liping Liu, "Clustering-Based Reconstruction Algorithm for Electrical Impedance Tomography", IEEE Transactions on Instrumentation and Measurement, vol.73, pp.1-11, 2024.
3.
Yuxi Guo, Liying Zhu, Minmin Wang, Yandan Jiang, Manuchehr Soleimani, Maomao Zhang, "Capacitively Coupled Electrical Impedance Tomography in Lung Imaging", IEEE Sensors Journal, vol.24, no.20, pp.33072-33082, 2024.
4.
Yimin Wu, Yandan Jiang, Haifeng Ji, Baoliang Wang, Zhiyao Huang, "A Joint Image Reconstruction Method for Capacitively Coupled Electrical Impedance Tomography", IEEE Transactions on Instrumentation and Measurement, vol.73, pp.1-13, 2024.
5.
Bartłomiej Baran, Bartosz Przysucha, Tomasz Rymarczyk, Dariusz Wójcik, "Effect of Measurement Noise on Reconstruction using Machine Learning with Electrical Tomography in the Case of the Abdominal Cavity", 2023 International Interdisciplinary PhD Workshop (IIPhDW), pp.1-6, 2023.

Cites in Papers - Other Publishers (2)

1.
Heming Gao, Haoyang Pan, Zhongyu Liao, Yuguang Niu, "Research on capacitance-coupled electrical impedance imaging fusion algorithm based on wavelet transform", Review of Scientific Instruments, vol.95, no.10, 2024.
2.
Yimin Wu, Yandan Jiang, Haifeng Ji, Baoliang Wang, Zhiyao Huang, Manuchehr Soleimani, "A new image reconstruction strategy for capacitively coupled electrical impedance tomography", Measurement Science and Technology, vol.35, no.3, pp.035401, 2024.
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References

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