Pipelines are structural elements of many systems. For example, they are used in water supply and heat supply systems, in chemical production facilities, aircraft manufacturing, and in the oil and gas industry. Accidents in piping systems result in significant economic damage. An important factor for ensuring the reliability of energy transportation systems is the assessment of real technical conditions of pipelines. Methods for assessing the state of pipeline systems by their vibro-acoustic parameters are widely used today. Traditionally, the Fourier transform is used to process vibration signals. However, as a rule, the oscillations of the pipe-liquid system are non-linear and non-stationary. This reduces the reliability of devices based on the implementation of classical methods of analysis. The authors used neural network methods for the analysis of vibro-signals, which made it possible to increase the reliability of diagnosing pipeline systems. The present work considers a method of neural network analysis of amplitude-frequency measurements in pipelines to identify the presence of a defect and further clarify its variety.

The problem of detecting the location of hidden pipelines laid in the ground is currently being addressed by the devices based on the method of electromagnetic location. However, this method does not provide a high accuracy and selectivity in determination of pipeline location. Furthermore, using this method it is impossible to search for non-metallic objects. The low-frequency vibroacoustic method of determination of location of the hidden channels and pipelines is suggested. The measuring and diagnostic complex with the unified application program package is developed for approbation of the suggested method

Currently, acoustic methods are widely used as a way to detect pipeline leaks. This is due to the fact that the acoustic signal has sufficiently capacious information about the state of the pipeline. The effectiveness of acoustic monitoring depends on the correct extraction of this information from the diagnostic signal. Currently, there is a search for new, more effective methods for analyzing acoustic signals. The article proposes to apply the theory of fractals to determine pipeline leaks. One of the most accurate methods for determining the fractal dimension of time series is R/S analysis using the Hurst exponent. An experimental stand has been developed and created, which includes a steel pipeline with water circulating in it. Water leakage from the pipeline was simulated by installing discs with holes of different diameters. The discs were placed in a special fitting on the surface of the pipeline. Acoustic signals recorded from the pipeline surface at different leakages and water pressure were analyzed. A relationship has been established between the size of the leak and the Hurst exponent of acoustic signals. The proposed method is compared with spectral analysis. Empirical experience has proven that R/S analysis can be used to determine pipeline leaks, as well as their classification by size.

In this paper, the possibility of using monofractal and multifractal analysis of acoustic signals of pipelines to detect leaks is considered. An experimental stand has been created to study the fractal characteristics of acoustic signals of pipelines with “slit” type defects. During the experiments, defects of the “slit” type pipeline with dimensions of 2 mm, 8 mm, and 20 mm were modeled. Detrended fluctuation analysis (DFA) and the multifractal detrended fluctuation analysis (MF-DFA) were used. As a result of the experimental studies, it was found that the occurrence of leakage leads to the occurrence of anticorrelated vibrations in a pipeline with multifractal properties. The analyses of acoustic signals by DFA and MF-DFA methods make it possible to reliably determine the leakage. The Hurst exponent and the width of the multifractal spectrum can serve as indicators of the occurrence of leaks in pipelines.

In this paper discusses the issues related to the development of the acoustic method of free oscillations in relation to the diagnosis of cylindrical products. The results of numerical experiment to determine the oscillation frequencies of rods with defects such as "crack".

The article offers statistical criteria for comparison of vibration spectra for detecting the unbalance of rotor equipment. The method of rejection is described. Experimental studies were carried out on an axial fan.