Modern technologies of service life diagnostics and monitoring of technical condition of agricultural machinery

Abstract

The existing methods and technologies for diagnosing the technical condition of agricultural machinery and the main directions for their further improvement are discussed. The research targets are the modern methods and tools for diagnosing and monitoring the service life of agricultural machinery and equipment components. The research goal is to analyze scientific and practical developments in the field of diagnostics and control of the technical condition of machinery by using artificial intelligence technologies. The research materials included publications in the field of development and application of various modern technologies and tools for service life diagnostics and monitoring of the technical condition of machines online. Modern means of mechanization of agricultural production are expensive and complex in terms of their designs. Ensuring their operational status requires the use of a new generation of diagnostics, maintenance and repair tools to effectively solve the problem of reducing the cost of unforeseen downtime to eliminate the consequences of failures. The use of online condition diagnostics technologies will increase machine performance and reduce operating costs. Recently, artificial intelligence tools have been introduced quite intensively in diagnostic technology. These digital technologies make it possible to create systems based, among other things, on the use of neural networks that are able to independently learn from the analysis of large amounts of data and, in addition, predict possible malfunctions using accumulated databases. Such systems may significantly reduce maintenance and repair costs.