Применение цифровых технологий при диагностировании двигателей энергонасыщенной сельскохозяйственной техники

Abstract

The development of digital technologies aimed at improving the diagnostic process, increasing the reliability of determining the functional characteristics of agricultural machinery in real time is important and relevant in the technical support of energy-saturated machines. To develop an intelligent system for remote diagnostics of the engines of energy-saturated agricultural machinery, the authors tested a neural network constructor with the ability to use up to ten input and output parameters. An algorithm for a digital system for remote diagnostics, a scheme for predicting failures in online monitoring, and a digital platform for diagnosing energy-saturated agricultural machinery have been developed. The developed platform makes it possible to obtain ICE diagnostic parameters (fuel consumption, engine temperature, and engine shaft speed), which are remotely transmitted in the form of encrypted data to the server using a GPS modem and digitized in the data bank. Then the received data are structured and analyzed using the developed artificial neural network models. The decrypted diagnostic parameters of the internal combustion engine are sent to the operator, who sees graphs of the parameters of the technical condition of agricultural machinery and reports on predicting possible failures of internal combustion engine parts. The article presents a method for collecting and storing diagnostic information obtained as a result of monitoring the technical condition of agricultural machinery. These data are processed using a mathematical model of a neural network. The use of digital technologies in diagnosing equipment with the help of artificial intelligence can significantly reduce the complexity of the operations performed, evaluate the efficiency of the machine as a whole and predict the onset of failures of its mechanisms, perform timely maintenance and repair of machines, and reduce unplanned downtime of energy-saturated agricultural machinery.