Muttakin Imamul, Soleimani Manuchehr
Engineering Tomography Laboratory (ETL), Department of Electronic and Electrical Engineering, University of Bath, Claverton Down, Bath, BA2 7AY, UK.
Materials (Basel). 2020 Jun 9;13(11):2639. doi: 10.3390/ma13112639.
Magnetic induction tomography (MIT) is a powerful imaging system for monitoring the state of metallic materials. Tomographic methods enable automatic inspection of metallic samples making use of multi-sensor measurements and data processing of eddy current-based sensing from mutual inductances. This paper investigates a multi-frequency MIT using both amplitude and phase data. The image reconstruction algorithm is based on a novel spectrally-correlative total variation method allowing an efficient and all-in-one spectral reconstruction. Additionally, the paper shows the rate of change in spectral images with respect to the excitation frequencies. Using both spectral maps and their spectral derivative maps, one can derive key structural and functional information regarding the material under test. This includes their type, size, number, existence of voids and cracks. Spectral maps can also give functional information, such as mechanical strains and their thermal conditions and composition.
磁感应断层成像(MIT)是一种用于监测金属材料状态的强大成像系统。断层成像方法利用多传感器测量和基于互感的涡流传感数据处理,能够对金属样品进行自动检测。本文研究了一种同时使用幅度和相位数据的多频MIT。图像重建算法基于一种新颖的频谱相关全变差方法,可实现高效的一体化频谱重建。此外,本文还展示了频谱图像随激励频率的变化率。利用频谱图及其频谱导数图,可以得出有关被测材料的关键结构和功能信息。这包括材料的类型、尺寸、数量、是否存在空隙和裂纹。频谱图还可以提供功能信息,如机械应变及其热状态和成分。