Research On Knowledge Base System Of Small Sugarcane Harvester In Soil Cutting

It is an effective method to improve the quality of sugarcane harvest and reduce the breaking rate by cutting soil.The research group has explored the influence of soil cutting factors and the cutting load pressure through investigations and experiments.However,However,the knowledge and experience of soil cutting are not well generalized and reused,which makes the sharing and reusability of soil cutting knowledge poor.In this article,the previous research results has been summarized in combination with the actual agriculture.Study the knowledge of small sugarcane harvester in soil cutting and develop a knowledge base system to improve the knowledge utilization rate of soil cutting,which has great guiding significance for the development of sugarcane harvester with automatic control of soil cutting depth.The knowledge about the soil characteristics,sugarcane characteristics and sugarcane harvester working conditions in different sugarcane fields have been collected widely,this paper analyzes the factors at different cutting conditions which influence on the cutting load pressure,the characteristics of cutting knowledge were analyzed and classified,which can provide support for the system building by constructing overall framework about knowledge base system of sugarcane harvester in soil cutting.On the basis of analyzing the knowledge characteristics of different working conditions of sugarcane harvester,the knowledge acquisition method of sugarcane harvester has been studied,and the knowledge acquisition of sugarcane harvester based on data-driven has been established and achieved case knowledge acquisition.According to the knowledge characteristics of sugarcane harvester,production rules and object-oriented knowledge representation methods were proposed to realize the knowledge representation of sugarcane harvester.The reasoning mechanism of sugarcane harvester cutting into soil is analyzed to realize the forward reasoning of cutting knowledge,and to solve the problem of knowledge transfer related to load pressure of cutting into soil.For regular knowledge acquisition,the data dimension is reduced by KPCA analysis method firstly,and the principal components affecting the load pressure of cutting in soil are obtained.Based on MATLAB,BP neural network algorithm is applied to predict the load pressure of cutting tool.The improved LM-BP neural network algorithm is used to reduce the error of load pressure prediction of cutting tool.Finally,the knowledge acquisition mechanism of load pressure rules is realized,which provide the support for the control system.Based on the development platform of Visual Studio 2010,C#programming language is adopted to develop the knowledge base system of small sugarcane harvester for soil cutting.SQL Server 2008 software is used as the background database to complete the storage and management of soil cutting knowledge data,knowledge acquisition,knowledge query,knowledge modification and knowledge management were realized.Finally,the feasibility of cutting load pressure acquiring knowledge of rules was verified by physical tests.