EIT Sparse Imaging Method Research

Electrical Impedance Tomography (EIT) technology is a general designation of the ERT and ECT. According to the different electrical properties of different media in the sensitive field, the impedance distribution in the sensitive field can be inferred by the surface electrical potential, which is collected by sensors. And then the image of media distribution of a cross section in the sensitive field can be made by means of relevant image reconstruction algorithms. Thanks to its high speed, low cost, non-invasive, non-destructive measurements, EIT technology is of great potential application prospects in medical diagnostics, geophysical exploration, pipeline industry, etc., which also leads to rapid development of the technology.The inverse problem of EIT technology is ill-conditioned. At present, the only way to gain much more information is to increase the number of sensors, which will lead to rapid growth in the amount of calculation. Compressed sensing theory proposed in recent years proved that when the signal itself has certain characteristics and sampling matrix meets certain conditions, the original signal can be similar or even completely recovered from the highly incomplete observation data. This will break through the traditional bottleneck of Shannon sampling theorem.Considering all of the above factors, this paper implements the design and fulfillment a system of EIT technology based on the embedded Cortex-A9 platform, which is good to extend the application scenarios EIT technology. The main work of this paper is as follows:1. The experimental environment is built, which includes both hardware part and software part. The hardware circuit section mainly includes instrumentation amplifier, RMS calculation, A/D converter, analog switch array and constant current source circuit and other components. As for the software part, the Lubuntu system base on Linux 3.0.36 kernel, which runs on ARM Cortex-A9 is need to be configured. And then the Python2.7 environment and its associated libraries are also need to be installed.2. Solutions of imaging system are given according to the characteristics of EIT technology and compressed sensing theory. Several data sparsifying transformation methods are presented.3. Complete sparse reconstruction experiment on the built experimental environment with the method of discrete wavelet transform. And then analysis the experiment results of objects with different shape, height or numbers.