Performance analysis of the 2DoF direct drive induction motor applying composite multilayer method

This study presents a composite multilayer method (CMM) to evaluate the performance of a two-degree-offreedom (2DoF) direct drive induction motor (2DoFDDIM) whose solid rotor is coated with a copper layer. It includes a rotary part and a linear part. Based on the traditional multilayer theory, a complete 2DoFDDIM CMM computer program importing propagation constants is built. Due to the complex magnetic field in a 2DoFDDIM, this study mainly analyses it from the perspective of a single DOF motor. An equivalent circuit for the rotary part of the 2DoFDDIM is then derived applying CMM and the 2D magnetic field distribution is obtained by solving Maxwell's equations in motor layers. The developed torques, power factors and stator currents of the rotary part with different slips and the latter two of the linear part at zero speed are calculated by CMM, which are then compared with results from the finite element method (FEM) and experimental results. The computation time of the CMM is far less than that of the FEM. The acceptable accuracy confirms the effectiveness of the CMM for analysis and performance calculations of the 2DoFDDIM

Mathematical model of two-degree-of-freedom direct drive induction motor considering coupling effect

The Two-degree-of-freedom direct drive induction motor, which is capable of linear, rotary and helical two, has a wide application in special industry such as industrial robot arms. It is inevitable that the linear motion and rotary motion generate coupling effect on each other on account of the high integration. The analysis of this effect has great significance in the research of two-degree-of-freedom motors, which is also crucial to realize precision control of them. The coupling factor considering the coupling effect is proposed and addressed by 3D finite element method. Then the corrected mathematical model is presented by importing the coupling factor. The results from it are verified by 3D finite element model and prototype test, which validates the corrected mathematical model

Multi-level Asymmetric Contrastive Learning for Volumetric Medical Image Segmentation Pre-training

Medical image segmentation is a fundamental yet challenging task due to the arduous process of acquiring large volumes of high-quality labeled data from experts. Contrastive learning offers a promising but still problematic solution to this dilemma. Because existing medical contrastive learning strategies focus on extracting image-level representation, which ignores abundant multi-level representations. And they underutilize the decoder either by random initialization or separate pre-training from the encoder, thereby neglecting the potential collaboration between the encoder and decoder. To address these issues, we propose a novel multi-level asymmetric contrastive learning framework named MACL for volumetric medical image segmentation pre-training. Specifically, we design an asymmetric contrastive learning structure to pre-train encoder and decoder simultaneously to provide better initialization for segmentation models. Moreover, we develop a multi-level contrastive learning strategy that integrates correspondences across feature-level, image-level, and pixel-level representations to ensure the encoder and decoder capture comprehensive details from representations of varying scales and granularities during the pre-training phase. Finally, experiments on 12 volumetric medical image datasets indicate our MACL framework outperforms existing 11 contrastive learning strategies. {\itshape i.e.} Our MACL achieves a superior performance with more precise predictions from visualization figures and 2.28\%, 1.32\%, 1.62\% and 1.60\% Average Dice higher than previous best results on CHD, MMWHS, CHAOS and AMOS, respectively. And our MACL also has a strong generalization ability among 5 variant U-Net backbones. Our code will be available at https://github.com/stevezs315/MACL

Static coupling effect of a two-degree-of-freedom direct drive induction motor

Two-degree-of-freedom motors are capable of producing linear, rotary, and helical motion, and thus have widespread applications in special industries. In this study, a new concept- static coupling effect is studied in the two-degree-of-freedom direct-drive induction motor (2DoFDDIM). The proposed approach is based on the image method and the three-dimensional (3D) finite-element method. The image method model is established to analyse its reasons and predict the main effects, which are then verified by the proposed 3D finite-element static coupling model and experiments. The induced voltages and currents are produced in the static part and induced torque or force is obtained, even though the static part is not energised. It is concluded that the static coupling effect increases with the supply frequency and is influenced by the stator winding configuration. Thus, the existence of the static coupling effect is confirmed, which must be taken into account in future optimisation and precise control of the 2DoFDDIM