Modern trends in technical condition monitoring systems of hydraulic drives in agricultural machinery
DOI:
https://doi.org/10.31548/dopovidi2(102).2023.018Keywords:
agricultural machinery, hydraulic system, information technology, technical condition, diagnostics, artificial neural networksAbstract
Increasing technical complexity of hydraulic systems in modern agricultural machines causes a low level of their maintainability in the domestic agro-industrial complex. In order to avoid unforeseen financial costs associated with equipment downtime due to emergency failures of their hydraulic drives, there is a need to identify the prerequisites for their efficiency loss in advance by using effective methods and means of monitoring the technical condition of machines in operation. The aim of the article is to analyse the applicability of methods for monitoring the technical condition of hydraulic drives in agricultural machinery and to substantiate the prospects for their improvement, in accordance with the level of modern information technology development and the conditions of the material and technical base of the domestic agro-industrial complex. To achieve this goal, a structural, logical, and comparative analysis of materials from periodicals and electronic information sources on the relevant topics was conducted. The article considers the known methods for diagnosing hydraulic drives and trends in improving the means of monitoring the technical condition through information technology. The study showed that the methods of the non-destructive testing group are the most applicable in conditions of weak material and technical base. Among the existing methods aimed at improving the process of monitoring the technical condition of agricultural machinery are remote diagnostic systems that combine the diagnostic parameters reading and their remote processing on electronic computers. Currently, artificial neural networks are being actively developed, which are finding their way into the monitoring hydraulic drive technical condition and can significantly improve the overall level of the planned preventive maintenance system.
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