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Abstract. The article contains information about acoustic emission signals analysing using autocorrelation function. Operation factors were analysed, such as shape of signal, the origins time and carrier frequency. The purpose of work is estimating the validity of correlations methods analysing signals. Acoustic emission signal consist of different types of waves, which propagate on different trajectories in object of control. Acoustic emission signal is amplitude-, phase-and frequency-modeling signal. It was described by carrier frequency at a given point of time. Period of signal make up 12.5 microseconds and carrier frequency make up 80 kHz for analysing signal. Usage autocorrelation function like indicator the origin time of acoustic emission signal raises validity localization of emitters.

Currently, there is a clear trend towards updating technical regulations and improving control technologies in the field of maintenance and repair of car assemblies and parts. Therefore, there is a need for software and hardware that will provide updated information to specialists of car repair shops in a timely manner. This study is aimed at creating a computer-based network training system that will increase the effectiveness of training and reliability of results. The paper describes methods for verifying and identifying training results based on an analysis of user's behavioral parameters. As a result of the research, the authors have developed a system that can verify training results with a probability of more than 95%.