Method for Determining the Initial Values of the Adjustable Parameters of the Combine Harvester Cutting Unit

Abstract

Introduction. The article presents the solution of the problem of identifying the subject area “Preliminary adjustment of the working elements of the combine harvester cutting unitˮ. The correct choice of parameter values of the cutting unit as the most important element of a combine harvester is one of the main conditions for providing high quality harvesting. It is the fact that defined the object of the present study. The aim of the study is to develop a method for adjusting the values of parameters of a combine harvester cutting unit for the harvested crop and harvesting conditions. Materials and Methods. Decisions on the values of technological parameters of the harvester, which is a complex hierarchical system, are made on the basis of information about the external environment and the machine technical state. The incoming data are quantitative, qualitative and evaluative in nature. Taking into account the heterogeneity and vagueness of the information, the decisions are made through using intelligent information systems, which are based on the fuzzy logic programming and use a linguistic approach to describe the subject area. This approach is used because of the complexity and ambiguity of the relationships between regulated parameters and external factors. Results. The subject area “Preliminary adjustment of the combine harvester cutting unit parametersˮ has been investigated. The formal-logical scheme for selecting the values of adjustable parameters of the combine harvester cutting unit is described in detail. The main factors influencing the values of the combine harvester cutting unit adjustable parameters are defined, their linguistic description is given, the corresponding input and output linguistic variables are introduced, and the membership functions are built on the basis of expert information. The agreement analysis of the presented information has been carried out and optimal models have been selected. A fuzzy knowledge base is created, on which the deductive inference of decisions is based. Discussion and Conclusion. The proposed approach and created fuzzy knowledge base can be used as the basis for an intelligent decision-making system for adjusting combine parameters. Using this system in the field in combination with sensors for continuous monitoring of harvesting conditions and an automated image analysis system will allow responding quickly to changing conditions, will significantly improve operational efficiency and reduce decision-making time.