IDENTIFYING THE MAIN FAULTS OF CENTRIFUGAL PUMPING UNITS USING A COLORIMETRIC AMPLITUDE INDICATOR BASED ON WAVELET PATTERN MODELING
Authors:   Ufa State Petroleum Technological University, Zakirnichnaya Marina M. , Palladina Yana A. ,   Ufa State Petroleum Technological University
Published: November 2024

Relevance Advanced production technologies do not stand still and include both modernization of equipment and updating of software necessary for the implementation of technological processes. Information and measurement systems are actively developing, the objects of which often have a very complex structure and multifaceted processes and phenomena can occur in them. Therefore, individual measuring devices that perceive only one parameter of a complex process usually cannot provide sufficient information, especially when it is necessary to simultaneously know a number of object parameters. Recently, artificial intelligence systems have been used to create information and measurement systems. The digital transformation of the oil refining and petrochemical industries is taking place especially dynamically. Thus, artificial intelligence systems and machine learning based on databases have found wide application in monitoring the technical condition of equipment, as well as for subsequent predictive assessment. Rotary-type machines are an integral part of technological processes, so preventing their emergency failure is the most important task. Such problems are solved using vibroacoustic diagnostics. One of the most common classical methods of vibration signal processing used by vibration diagnostic services of technical supervision departments of oil refining and petrochemical industry enterprises is Fourier spectral analysis. However, as a result of this type of analysis, there is a high probability of ambiguous recognition of different types of faults due to the similarity of their spectra. In addition, the loss of information about the time factor distorts the idea of the dynamics of changes in the spectral composition of the signal, as a result of which there is no possibility of carrying out a comprehensive analysis of it. It has been proven that wavelet analysis of vibration signals allows one to identify faults and defects that do not appear during the Fourier spectral transform. At the same time, to accurately diagnose centrifugal pumping units, additional quantitative assessment of wavelet patterns is required. Based on this, there is a need to develop additional approaches to the analysis of wavelet patterns of vibration signals to assess the technical condition of the centrifugal pump unit. Aim of research Improving the capabilities of vibration diagnostics by developing an additional criterion for analyzing wavelet patterns of vibration signals to assess the technical condition of centrifugal pumping units. Research methods To practically solve the problems, methods and algorithms for digital processing of vibration signals based on the wavelet transform were used. Results An algorithm has been developed to assess the technical condition of centrifugal pumping units using a colorimetric amplitude indicator, which allows one to assess the degree of development of the main malfunctions of centrifugal pumping units, such as imbalance, misalignment and loss of rigidity of supports.