The paper proposes a method for processing acoustic emission signals for calculating informative signal parameters characterizing the stages of plastic deformation and fractures in a loaded titanium alloy. The proposed method has a complex structure that includes digital signal processing algorithms and multivariate data analysis methods. The acoustic emission signals are processed using the mathematical apparatus of the multilevel discrete wavelet transform to obtain the approximation coefficients of the 10-level decomposition. These coefficients characterize the low-frequency features of acoustic emission at various stages of samples loading. The approximation coefficients are further used as informative parameters of acoustic emission signals. Principal components analysis is used to investigate the informative parameters and establish their quantitative relationship with the stages of plastic deformation of titanium by clustering the processed results. Differences in the informative parameters at different stages of plastic deformation of the material are revealed by the following analysis of the clustered results. The obtained results can be used to develop a new generation of diagnostic devices for acoustic emission measurements.