Abstract

This paper presents a new development in the magnetic particle tracking (MPT) technology that measures the translational and rotational motions of a small particle. A main advantage of MPT is that it is able to track objects in an opaque environment without using radioactive material or X-rays. In addition, it can provide information about the orientation and rotation of the object, which is difficult to obtain using other technologies. However, the reconstruction process of MPT using standard optimization approaches is very time consuming and, therefore, limits its applications. In this work, two new MPT reconstruction algorithms are examined and the results are compared with the optimization approach. The extended Kalman filter (EKF) algorithm has the same accuracy as the optimization method but is orders of magnitude faster. The speed of the sequential importance sampling approach is between those of the above two methods. The accuracy of position obtained using EKF is about 0.6%, and the uncertainty of orientation is less than 1.5°. The MPT is applied to measure a dense granular shear flow to investigate the spatial distribution of a tracer particle.

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