Abstract
Electrical resistance tomography (ERT) is an imaging technique to recover the conductivity distribution with boundary measurements via attached electrodes. There are a wide range of applications using ERT for image reconstruction or parameter calculation due to high speed data collection, low cost, and the advantages of being non-invasive and portable. Although ERT is considered a high temporal resolution method, a temporally regularized method can greatly enhance such a temporal resolution compared to frame-by-frame reconstruction. In some of the cases, especially in the industrial applications, dynamic movement of an object is critical. In practice, it is desirable for monitoring and controlling the dynamic process. ERT can determine the spatial conductivity distribution based on previous work, and ERT potentially shows good performance in exploiting temporal information as well. Many ERT algorithms reconstruct images frame by frame, which is not optimal and would assume that the target is static during collection of each data frame, which is inconsistent with the real case. Although spatiotemporal-based algorithms can account for the temporal effect of dynamic movement and can generate better results, there is not that much work aimed at analyzing the performance in the time domain. In this paper, we discuss the performance of a novel spatiotemporal total variation (STTV) algorithm in both the spatial and temporal domain, and Temporal One-Step Tikhonov-based algorithms were also employed for comparison. The experimental results show that the STTV has a faster response time for temporal variation of the moving object. This robust time response can contribute to a much better control process which is the main aim of the new generation of process tomography systems.
Highlights
Electrical resistance tomography has been investigated for few decades since it was proposed in 1984 as an approach for vivo image reconstruction to obtain the spatial distribution of the resistivity of a tissue [1]
The hardware system used in this paper is known as the electrical impedance tomography (EIT) Swisstom Pioneer system [20] with 32 channels (Picture of Swisstom Pioneer system is showing in Figure 1(a)), which has the following main components:
Smart SensorBeltConnector integrated with Alternating Current (AC) current injection (1–7 mA, 50 KHz–250 KHz), voltage signal demodulating, high speed data collection
Summary
Electrical resistance tomography has been investigated for few decades since it was proposed in 1984 as an approach for vivo image reconstruction to obtain the spatial distribution of the resistivity of a tissue [1]. Many applications have benefited from the ERT technique due to its low cost, high speed and non-invasive advantages. The implementation of ERT requires a conductive domain where electrodes are required to be directly attached to its boundary. An electric field is generated from injecting the current via electrode patterns where an Alternating Current (AC) source would be required. Voltmeters would be applied to electrodes simultaneously. The measurement strategy could be selected from among the neighboring method, opposite method, adaptive method, etc. The measurement strategy could be selected from among the neighboring method, opposite method, adaptive method, etc. [2]
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