Technology for Adjusting Working Tools of a Rotary Harvester Based on Fuzzy Modelling

Introduction. The need to increase productivity of grain harvesting equipment and minimize crop losses has given rise to the increasing use of axial-flow combines (rotary harvester). The efficiency of harvesting operations depends on correct setting of the adjustable harvester parameters allowing full use of its design capabilities. For this reason, it is relevant to study the problems of optimal adjusting the working tools of a harvester operating in various environmental conditions.Aim of the Study. The study was aimed at developing an approach to the choice of optimal values for the adjustable parameters of the rotor type grain harvesters.Materials and Methods. Harvesting quality indices, adjustable parameters, and environmental factors are interdependent, so there has been used a linguistic approach to the description of the subject domain. Information about environmental conditions, the harvester technical state, interrelations between parameters and harvesting indicators is fuzzy that has led to the application of the theory of fuzzy sets to solve the problem of optimal choice of the adjustable parameters. The procedure of fuzzy logic inference has been performed in Fuzzy Logic Toolbox (MatLab) package.Results. There are presented the results of the developed approach to the problem of operational presetting adjustable parameters of a rotary harvester when harvesting various grain crops under different environmental conditions. The problem solution concept has been developed on the basis of the fuzzy logic formalism. A linguistic description of the problem has been given. Models of the considered features in the form of membership functions are proposed, which adequately take into account the external conditions in which the harvester operates. Basic and extended term sets have been identified. The optimal models have been selected on the basis of the consistency analysis of fuzzy expert knowledge using the indicators of general and pair consistency of the models. The results of the solutions obtained have been illustrated. On the basis of collected and analyzed expert information there has been created a base of fuzzy expert knowledge including the fuzzy production rules for 12 adjustable parameters of TORUM harvester. Different combinations of the values of environmental factors have been considered, for which there has been given an inference about specific values of the adjustable parameters. Discussion and Conclusion. The practical significance of the research carried out lies inthe creation of a basis for an intelligent information system to help a rotary harvesteroperator in making decisions on choosing adjustable parameter values when harvestingvarious grain crops. The use of such a system in field conditions in combination with sensors for continuous monitoring of harvesting conditions and an automated image analysis system will allow for a prompt response to changing conditions, significantly increase work efficiency and reduce decision-making time. The implementation of such systems will significantly reduce the information load on the operator, as well as use operators with little practical experience during harvesting. The development of such information systems creates the preconditions for increasing the level of automation of intelligent control of a grain harvester and is an important stage in the implementation of the approach to unmanned control of a harvester.