## 3 Experiment and Results
### Discrete Wavelet Transform--Based Metal Material Analysis Model
The average values of the main peak area feature corresponding with iron element proportions are 803, 770 and 730, respectively; these have an opposite monotonicity compared to iron element proportions. It seems that the features of time of decay and main peak area are highly related with the iron element proportions and have high sensitivity to small content changes in ferroalloys. Figure 5: Signal characteristic distribution of Fe-K162, Fe-K163 and Fe-K240. Similar experiments have been applied to Cu, Fe, Al and St, as shown in Figure 6. It can be seen that the features of peak frequency and peak time are meaningless for metal recognition combined with the results of Figure 4. Different from Figure 4, the feature of amplitude of attenuation has contribution in Cu, Fe, Al and St identification. It should be noticed that Cu and Al are easily distinguished by the zero crossing time feature; Fe and St are also easily distinguished by the zero crossing time feature. However, the results in the time of decay feature are the opposite; the feature value is far less distinguishable than the feature of zero crossing time. However, the feature of main peak area is perfect for metal classification: there is no need to make a joint judgment with other features. That is because the four metals differ greatly in electrical and magnetic permeability. Figure 6: Signal characteristic distribution of air, Cu, Fe, Al and St.  
A fast logistic regression analysis was performed using 50 independent data samples to calculate feature correlations and significance to verify the accuracy of eddy current feature parameter selection. A binary regression analysis of eddy current signal feature correlation was established to validate the data samples using 50 groups of Fe-K162 gray cast iron metal samples against 50 groups of non-Fe-K162 metal samples, and the results of the regression analysis are shown in Figure 7.  
The classification map and the Hosmer-Lemeshaw goodness of fit were performed according to the six features mentioned previously. The number of iterations was set to 20; the predicted value probability, group membership, influence factor and leverage values were turned on; and the residuals of the criteria are analyzed. Then, the Statistical Product Service Solutions (SPSS) correlation and significance of metal signal characteristics can be analyzed. This paper adopts the binary logistic regression model of the IBM SPSS software and takes the characteristic data of Fe-K162 eddy current signal as an example to identify the correlation and significance of the characteristic parameters of the above samples. According to the significance analysis setting, if the significant \(p\) value of variable X shows significance, it means that X has an influential relationship on Y. If it is not significant, the variable should be excluded. From the results of the grouped experimental data, it can be seen that there are four explanatory variables in the model with significance analysis \(p\)-values less than 0.001 for Fe-K162 recognition rate, indicating that all X factors have a significant influence relationship on Y.  
Figure 3:0 IBM Statistical Product Service Solutions Software statistics binary logistic regression analysis results. The impact of the correlation of X-Y was compared based on the regression analysis scores. From the regression analysis scores, the four explanatory variables in the model, such as zero crossing time, main peak area, amplitude of attenuation and time of decay, had scores of 88.101, 47.304, 96.037 and 89.974, respectively, indicating that all variables showed significant positive influence relationships on the Fe-K162 recognition rate. In summary, combining the feature screening results and correlation verification conclusions, it is determined that the main feature parameters such as main peak area, time of decay and zero crossing time are selected. The amplitude of attenuation is selected as an auxiliary feature parameter to establish a functional mapping relationship with the metal eddy current signal.