Yoon-Do Chung

Current Pumping Performance of Linear-Type Magnetic Flux Pump With Use of Feedback Control Circuit System

It has already been investigated that current pumping of the linear-type magnetic flux pump (LTMFP) is controlled by frequency of 3-phase inverter. In this paper, based on these operating characteristics, a current compensator, which is composed of a LTMFP and a feedback control circuit system, has been introduced to compensate for the persistent current decay of the superconducting magnet. From the experiment, the current compensator has been demonstrated with the toroidal assembly of six Nb-Ti magnets 543 mH under the operating load current at 10 A

Performances of a linear type magnetic flux pump for compensating a little decremented persistent current of HTS magnets

This paper describes the characteristics of a linear type magnetic flux pump recently developed. The linear type flux pump has been fabricated to apply to compensate decremented persistent current of HTS applications such as NMR and MRI system. The linear type magnetic flux pump mainly consists of 3-phase AC armature coil, DC bias coil and superconducting Nb foil. In the preliminary experiment, the flux pump can charge the pumping-up current in the load coil of 1.3 mH during 1000 seconds under the DC bias current of 10 A and 3-phase AC of 8 A, 60 Hz. The magnitude of pumping current is 0.1 mA/s.

Nonlinear Characteristic Analysis of Charging Current for Linear Type Magnetic Flux Pump Using RBFNN

In this work, to theoretically analyze the nonlinear charging characteristic, a Radial Basis Function Neural Network (RBFNN) is adopted. Based on the RBFNN, an charging characteristic tendency of a Linear Type Magnetic Flux Pump (LTMFP) is analyzed. In the paper, we developed the LTMFP that generates stable and controllable charging current and also experimentally investigated its charging characteristic in the cryogenic system. From these experimental results, the charging current of the LTMFP was also found to be frequency dependent with nonlinear quality due to the nonlinear magnetic behaviour of superconducting Nb foil. On the whole, in the case of essentially cryogenic experiment, since cooling costs loomed large in the cryogenic environment, it is difficult to carry out various experiments. Consequentially, in this paper, we estimated the nonlinear characteristic of charging current as well as realized the intelligent model via the design of RBFNN based on the experimental data. In this paper, we view RBF neural networks as predominantly data driven constructs whose processing is based upon an effective usage of experimental data through a prudent process of Fuzzy C-Means clustering method. Also, the receptive fields of the proposed RBF neural network are formed by the FCM clustering.