The possibilities of using characteristics of special-correlation analysis as informative parameters for the acoustic-emission (AE) inspection of pig launchers-receivers (PLRs) of oil main pipelines (OMPs) are considered. The acoustic emission caused by wind and atmospheric precipitation that act on a pipe and, thus, generate noise are studied. It can be concluded from the preliminary analysis that the effective width and median frequency of a spectrum can be used to identify the AE inspection processes of PLRs of OMPs.The specific character of an object selected for AE inspection is determined by placing a pig launcherreceiver (PLR) of an oil main pipeline (OMPs) in open air, thus exposing it to the action of natural phenomena (precipitation, wind), which can disguise a genuine AE signal with noise. Consequently, to ensure that the aforementioned noise is identified, the problem of AE inspection involves selection of an informative parameter of the AE signal. Let us consider the usefulness of spectral-correlation analysis as it relates to this purpose.It is mentioned in [1] that the study of the signal spectrum of acoustic emission can be important both theoretically (to estimate the duration of action of the AE sources, to analyze their precise time structure) and practically (to separate the contributions of strain and fracture in an acoustic emission, to separate useful signals from extraneous signals).The most important factor for spectral-data analysis is the relationship between effective extension F ef of the spectral density of a mechanical-stress pulse, that is, the spectral density's limiting frequency and the duration (lifetime) of this pulse τ [1]:This fact was pointed out first for acoustic emission by Stephens and Pollock, who had taken the shape of the pulse to be Gaussian. The effective width of the correlation function of the AE pulse is determined also by τ [2].The autocorrelation function is a time characteristic of a signal that represents the rate of signal variation in time and the signal duration without expanding the signal into harmonic components. Microdeformation and microfracture have discrete time kinetics as a result of their joint action. Any joint action that causes damage to a material (avalanching of dislocations, merging of cracks with one other or with a macrocrack, etc.) is accompanied by a primary elastic pulse, whose radiation process is an AE act itself [3]. The duration of this pulse can be obtained from the autocorrelation function by considering the calculated autocorrelation interval. Thus, it can be assumed that the durations of a real AE act and noises differ and the former can be taken as the classification parameter.The most comprehensive data on AE spectra were obtained by Hatano [4], who used narrowband detection with five resonance transducers characterized by frequencies of 0.1, 0.4, 1, 2, and 4 MHz. His studies were performed on industrial-grade polycrystalline aluminum and are summarized as follows. The spectrum is enriched with high-frequency components as d...