Using Taguchi grey relational analysis to optimize the dimensional parameters of a Coercivity detection probe

The dimensions and number of turns per coercivity detection probe coil can strongly affect measurement accuracy. To address this problem, Maxwell simulation software was used to build a finite element model of a coercivity probe based on electromagnetic coupling and extract the cloud chart of the magnetic induction intensity for different specimen dimensions. The effect of the specimen dimensions on the magnetic induction intensity in the specimen was analyzed. Thus, Taguchi grey relational analysis was used to optimize the dimensional parameters of a coercivity detection probe. A five-factor four-level orthogonal test was designed based on the measurement principle of a closed magnetic circuit to perform a simulation analysis of the magnetization effect for specimens with various thicknesses using 16 orthogonal protocols. Taguchi grey relational analysis was performed on the simulation results to calculate the signal-to-noise ratios (SNRs) of evaluation indicators for the magnetization effect (the measured coercivity, leakage magnetic field and to magnetization depth) determine how changing the dimensional parameters of the detection probe affected magnetization. Finally, Taguchi grey relational analysis was used to determine the optimal combination of probe dimensional parameters.