Optimal design of electromagnetic metamaterial electronic device sensor with specific performance based on multivariate big data fusion

Abstract

As the basic unit structure of electromagnetic metamaterial, the structure size of open resonant ring directly determines the constitutive parameters of SRR (dielectric constant ε and permeability μ). In order to improve the energy exchange efficiency of the electromagnetic acoustic transducer, the coil backplane of the electromagnetic ultrasonic shear wave sensor was optimized. First, the influence of the thickness of the coil backplane on the ultrasonic signal is studied by the experimental method, and then, the magnetic field distribution of the coil backplane is simulated by the finite element simulation software. Finally, the SNR and lift distance of the shear wave sensor before and after the coil backplane optimization are compared by experiments. In this article, a multi-hypothesis data fusion method in distributed detection system is proposed, which extends the multi-sensor data fusion rules to more general cases. The results show that the optimum thickness of the coil back plate in the electromagnetic ultrasonic transverse wave sensor is 1.5–2.0 mm. Using iron powder with the same length and width as the working area of the coil as the coil backplane can significantly increase the magnetic field strength in the working area of the sensor. Compared with the coil backplane made of non-magnetic materials, the optimized backplane can increase the signal-to-noise ratio of the sensor by about one time and the lift-off distance by about 1 mm.