Software Package for Remote Diagnostics of Agricultural Machinery Condition

Abstract

Artificial intelligence is stated to be more and more widely used in agriculture, as well as for the diagnostics of the agricultural machinery condition. It was noted that in besides software, new computing devices are developed that enable processing and storing large amounts of data. (Research purpose) To create a neural network-based software package for remote diagnostics of the limit state of machinery individual components and assemblies. (Materials and methods) Foreign studies within the problem area were analysed. It was found out that for data collection for artificial intelligence there exist STM32 and Arduino microcontroller-based devices, and the Nvidia CUDA (Compute Unified Device Architecture) hardware and software platform is used. For the software was developed in the C / C ++ programming language, and the MS SQL Server database were used as a repository. The general software is emphasized to be able to run on all major operating systems such as Windows, Mac OS, Linux. The role of neural network is argued to be important since it integrated all program blocks and provides its own analysis. (Results and discussion) The information from the diagnostics devices is accumulated in a database. The neural network created on the basis of this database is constantly learning and simultaneously analyzing incoming data in real time, automatically issuing its recommendations. It was found that the neural network created by the employees of the Federal Scientific Agroengineering Center VIM has more functional options, for example, it is able to work directly with devices and conduct a more detailed technical analysis. (Conclusions) A neural network for equipment condition diagnostics was created, which increases the efficiency of decision-making in case of repair, and improves forecast and predictability. The criteria for equipment operation were proposed.