| Autor: |
Jinxi Xiang, Yonggui Dong, Maomao Zhang, Yi Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 7, Pp 56733-56744 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2914377 |
| Popis: |
Magnetic induction tomography (MIT) is a non-intrusive and non-invasive method that can image the cross-sectional conductivity distribution inside the object without contact. Target applications are conductive fluid testing in biomedical or industrial processes. The gradiometer coil is used as the front-end sensor of the proposed MIT system. As demonstrated through theoretical analysis and numerical simulation, the phase sensitivity to the conductivity of the gradiometer is greatly enhanced by eliminating the primary voltage with differential coils. The sensitivity is tunable by the residual voltage. The experimental test illustrates that 2 °/(Sm-1) sensitivity can be achieved at 10 MHz. The eight-channel MIT system MIT hardware is based on a dual-channel data acquisition board PCI-5122 at 100-MS/S sample rate per channel and a waveform generator PCI-5412 as the 10-MHz excitation source. One frame of data contains 64 phase measurements, and each is calculated with the built-in fast Fourier transform (FFT) function on LabVIEW. With full-period sampling and averaging, the sensor array can achieve less than 5-m° phase noise. The system yields good long-term stability with a phase drift less than 20 m° over 4 h. We use a FEM model to solve the forward problem and then reconstruct the 2D images by a one-step Laplacian regularization algorithm. The experimental phantom tests show that the system is capable of imaging the conductivity distribution and also indicate that the images' quality becomes better by tuning an appropriate regularization coefficient. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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