Management of the Technical Condition of Agricultural Machinery Using Digital Technologies

The studies were performed to substantiate the development of devices and software for managing the technical condition of agricultural machinery using elements of artificial intelligence. Artificial intelligence enables us to implement strategy C₃ for predictive equipment maintenance and repair. This is an integrated approach to determine the condition of a machine in operation and to estimate when maintenance should be performed. To do this, it is necessary to develop electronic diagnostic devices and sensors that can be combined into a single intelligent information complex, which enables quick collection and processing of large amounts of data on the parameters of the technical condition of agricultural machinery using artificial intelligence. The study object was represented by the hydromechanical gearbox of a Kirovets tractor. Data-collection devices, software, and methods for assessing the technical condition of machines were elaborated in 2022–2024 using artificial intelligence and neural network algorithms, and manufactured digital diagnostic devices were described. The introduced concept of technical condition is specified by the example of analyzing the operating parameters of the hydromechanical gearbox of the Kirovets tractor. It consists in calculating the Y_n parameter using a neural network. The parameter characterizes the nominal, permissible, limiting, or emergency technical condition and determines the type of possible work and service. Monitoring and analyses of the operating parameters of the gearbox using artificial intelligence and continuous updating of the technical condition result in timely technical maintenance and repair, which ensures technical condition management, increases the reliability of agricultural machinery, and minimizes failures and related equipment downtime.