## 3 Results
### Methods Reliability Evaluation  
Multiple SPMs have been created and applied for signal analysis of Lamb waves. Two-dimensional Fast Fourier Transform (2D-FFT), Short-Time Fourier Transform (STFT), Wavelets Transform (WT) and its variations, Wigner-Ville Distribution (WVD) and its variations, etc. [49, 58, 62] have been used for dispersion evaluation of Lamb waves. In many cases, the reliability of the method is not conducted and presented. It is a significant disadvantage for the application of Lamb waves, which makes it difficult to choose a suitable method for solving different problems. The accuracy assessment according to the requirements of ISO 17025 should be applied for the verification of the SPMs used to analyse the signals of Lamb waves because it is a necessary condition for setting reliable testing, inspecting, and monitoring standards for WTBs certification. The reliability evaluation of the SPMs for the dispersion estimation and reconstruction of the dispersion curves of the Lamb waves can be used as an example. Based on the presented methodology [63], three main steps should be taken in order to evaluate the main characteristics of the proposed SPMs used for the reconstruction of the dispersion curves. First, the mathematical verification of the proposed SPMs is used for the estimation of the Lamb wave dispersion. For that purpose, the dispersion curves using mathematical simulation and results obtained by analytical methods are compared. The techniques based on analytical and semianalytical finite element methods should be used as a reference method. Furthermore, the errors of the phase or group velocities at the informative points of the obtained dispersion curves and the average error can be calculated. The standard deviation of the velocity errors can be evaluated according to this parameter, as the uncertainty of the measurement model \(\sigma_{\Delta_{cant}}\) can be included in the budget of the combined standard uncertainty:  
\[\sigma_{\Delta_{cant}}=\sqrt{\frac{\sum_{i=1}^{N}\bigl{(}(\Delta c_{mat,i})- \overline{\Delta}c_{mat}\bigr{)}^{2}}{(N-1)}}, \tag{1}\]  
where \(N\) is the number of points in a segment of the mathematical reconstructed dispersion curve, \(i\)th is the point of the segment, \(\Delta c_{mat,i}\) are the errors of velocities of the reconstructed dispersion curve from the simulated signals, \(\overline{\Delta}_{cant}\) is the average of errors of velocities. The absolute error and the average of absolute errors can be calculated as follows:  
\[\Delta c_{mat,i}=c_{mat,i}(f)-c_{ref,i}(f), \tag{2}\]  
\[\overline{\Delta}c_{mat}=\frac{1}{N}\sum_{i=1}^{N}\Delta c_{mat,i}, \tag{3}\]  
where \(c_{mat,i}(f)\) are the velocities of the reconstructed dispersion curve from the simulated signals, \(c_{ref,i}(f)\) are the velocities obtained according to the reference dispersion curve. Second, a comparison of the analytical and experimental results of the proposed SPMs [64; 65]. The same characteristics as in the first step can be obtained. The systematic errors at different points are calculated by comparing the segments of the dispersion curves reconstructed in both experimental and analytical ways in the same frequency range. The average error of the velocity \(\overline{\Delta}_{c}\) is one of the main characteristics of the dispersion curves reconstruction. The systematic error and the average of the errors can be calculated accordingly:  
\[\Delta c_{n}=c_{ex,n}(f)-c_{ref,n}(f), \tag{4}\]  
\[\overline{\Delta}c=\frac{1}{K}\sum_{i=1}^{K}\Delta c_{n}, \tag{5}\]  
where \(K\) is the number of points in a segment of experimentally reconstructed dispersion curve, \(n\)th point of the segment is given by \(n=1,\ldots,K\), \(c_{ex,n}(f)\) are the velocities of the reconstructed dispersion curve from the experimental signals, \(c_{ref,n}(f)\) are the velocities obtained according to the reference dispersion curve.