Contactless electrical impedance and ultrasonic tomography: correlation, comparison and complementarity study

Jiang, Yandan and Soleimani, Manuchehr and Wang, Baoliang (2019) Contactless electrical impedance and ultrasonic tomography: correlation, comparison and complementarity study. Measurement Science and Technology, 30 (11). p. 114001. ISSN 0957-0233

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Abstract

Electrical tomography (ET) and ultrasonic tomography (UT) techniques are effective and promising super-sensing tools with uses in many industrial process applications. They can create internal mapping images of both electrical and mechanical properties from measurements at the exterior boundaries of domains of interests. There are several different types of ET methods and different modes of UT imaging. Here we focus on contactless ET and contactless UT imaging for liquid masses, enabling fully non-intrusive, integrated mechanical and electrical imaging because direct contact to the process material is often a major limiting factor. ET is sensitive to the distribution of dielectric parameters inside the region of interest, and the highest sensitivity often lies near the outer surface of the boundary. UT has very good responses to the intersections of different phases of materials and has the highest resolution in the central area. Capacitively coupled electrical impedance tomography (CCEIT) is proposed as a contactless ET technique. This work investigates CCEIT based on phase measurements of the electrical impedance between transmitting and receiving electrodes, and UT based on the transmission mode, measuring the time-of-flight between the transmitted signal and the first received signals. A combined sensor which comprises a 16-electrode CCEIT array and a 16-transducer UT array is developed. Experimental results show the performances of the two tomography systems and their dual modality combination. This work highlights various aspects of the correlation, comparison and complementarity between these two contactless imaging techniques. Inclusion material characterization and identification is demonstrated using this novel dual modality.

Item Type: Article
Subjects: Eurolib Press > Computer Science
Depositing User: Managing Editor
Date Deposited: 12 Jul 2023 03:39
Last Modified: 09 Oct 2023 06:00
URI: http://info.submit4journal.com/id/eprint/2237

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