Analysis and structure optimization of radial halbach permanent magnet couplings for deep sea robots

Permanent magnet couplings (PMCs) can convert the dynamic seal of transmission shaft into a static seal, which will significantly improve the transmission efficiency and reliability. Therefore, the radial Halbach PMC in this paper is suitable as the transmission mechanism of deep sea robots. A two-segment Halbach array is adopted in the radial PMC, and the segment arc coefficient can be adjustable. This paper presents the general analytical solutions of the distinctive Halbach PMCs based on scalar magnetic potential and Maxwell stress tensor. The analytical solutions of magnetic field are in good agreement with 2-D finite element analysis (FEA) results. In addition, an initial prototype of the radial Halbach PMC has been fabricated, and the analytical solutions of magnetic torque are compared with 3-D FEA and experiment results. This paper also establishes an optimization procedure for PMCs based on the combination of 3-D FEA, Back Propagation Neural Network (BPNN), and Genetic Algorithm (GA). 3-D FEA is performed to calculate the pull-out torque of the samples from Latin hypercube sampling, then BPNN is used to describe the relationship between the optimization variables and pull-out torque. Finally, GA is applied to solve the optimization problem, and the optimized scheme is proved to be more reasonable with the FEA method.