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 work is devoted to improving the efficiency of the system of thermal energy transportation. The results of determining the thermophysical properties, such as the coefficient of thermal conductivity, water absorption, vapor permeability, the percentage of structural changes in the fibers during heating and exposure to vibration, basalt super thin fiber and other thermal insulation materials are presented. The results of thermal imaging testing control of basalt super-thin fiber mats are presented. The effect of the degree of thermal insulation aging on the increase in the heat flow density is shown.

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Problems of increasing the reliability and efficiency of heating networks operation are closely related to the reduction of costs for the repair and restoration activities. The high cost of installation and emergency restoration work in the conditions of a shortage of funds dictates the need to develop and implement new methods of maintenance. Diagnostics of heat networks allows to determine their technical condition, to identify the most decrepit sections of pipelines for the purpose of repair work.