## 1 Introduction  
Materials are an important support for industrial development; metallic materials are particularly important. The consistency of metallic materials seriously affects the development of high-end industries. In order to test the consistency of metallic materials, titrimetric [1] and spectroscopic methods [2] are usually presented to detect the elemental composition of samples and thus determine the material properties. However, these methods are complex in operation process, destructive, costly in instrument and inconvenient for applications in the material production site, which greatly constrains the rapid identification of metallic materials. The eddy current technique is one of the nondestructive testing methods that is widely applied in metal material inspection, such as material integrity testing and material characterization [3; 4; 5; 6; 7; 8]. The single-frequency eddy current technique is suitable for classifying metals because different metals are made of materials with different electrical conductivity and magnetic permeability; thus, their absorptions of eddy currents are different. Consequently, eddy current detection for metals can replace the expensive spectral scanning method, since it reduces the detection time and improves the detection efficiency [9]. However, compared with the pulsed eddy current technique, single-frequency eddy current signals cannot express frequency domain information. The pulsed eddy current technique has a wide frequency spectrum, and the time domain signal can be filtered for multiple estimation of the electromagnetic parameters of the material from different frequency characteristics during the measurement. [PERSON] et al. put forward the method of quantitative calculation of metal defects by using eddy current nondestructive testing to establish a finite element model, semi-analytical method, etc. [10; 11; 12; 13]; [PERSON] et al. developed a model of the time domain induced voltage and the electromagnetic parameters of the material based on the pulsed signal. They demonstrated the effectiveness of the multi-frequency method in detecting the electromagnetic parameters of the material [14; 15]. [PERSON] et al. investigated the phase log-based of conductivity measurements. The results showed that the relationship between the logarithm of the phase and the variation of the conductivity was linear [16]. [PERSON] et al. proposed a model to reconstruct the magnetic permeability, conductivity, and thickness of the sample. The reconstruction error was 5% [17]. When using the eddy current technique to detect the electromagnetic properties of metallic materials, lift-off is one of the important factors affecting the accuracy of the measurement [18; 19; 20]. As such, eliminating the effect of lift-off is of great importance for metallic material identification. By varying the relative spatial positions of the receiving and transmitting coils, [PERSON] et al. achieved accurate measurements of the sample conductivity within a few millimeters, with a maximum error of 2.68% [21]. [PERSON] et al. proposed a stochastic inversion method with multi-frequency excitation to simultaneously determine the magnitude of lift-off as well as the conductivity and permeability of the sample; the inversion of these data resulted in a significant reduction in the a priori uncertainty of all model parameters [22]. [PERSON] et al. found that the dual-frequency signal was linearly related to lift-off. By applying different frequencies through the calculation, it was possible to reconstruct the variation of the lift-off of the signal and to reconstruct the electromagnetic properties of the material with an error of 1.4% within 12 mm [23]. In addition, the signal processing method also determines the accuracy of the eddy current method to identify material properties. [PERSON] et al. presented the wavelet transform method to process the eddy current signal of ferromagnetic metal.