Agricultural Machinery Maintenance Service Decisionmaking Methond Research And System Implement Based On Knowledge Mining

According to the development of agricultural mechanization, demand for agricultural machinery and equipment is increasing. At the same time, demand for operation and maintenance services of agricultural machinery and equipment is also increasing. The main course of maintenance service currently is based on the way of breakdown maintenance and call-center model. This model includes many defects such as repair passive, low maintenance efficiency and lack of ability to respond to emergencies. Therefore it has great significance to research how to using historical maintenance data in knowledge mining and apply this knowledge to the operation and maintenance services decision making.In this paper, on the purpose of intelligence of agricultural machinery and equipment maintenance service, the key issues of long maintenance service time consumed and serious waste of resources were studies. Those research are studied for agricultural cooperatives, large-scale farms to solve the demand of maintenance service. The rute of research is using the historical maintenance data as the resurce of data and mining and search the useful advice of guide agricultural machinery remote maintence. Firstly the related domestic and international literature about industrial maintenance field knowledge mining, association rules mining and its industrial applications and bayesian networks and industrial applications. According to the characteristics of agricultural methinery equipment maintenance services, proposed the use of knowledge mining association rules and bayesian network association rules research line expression hand maintenance service decisions. In the knowledge mining process, we use k- near algorithm, correlation calculations, and methods of the Chinese word participle to pretreat the raw data. And the use apriori algorithm mining association rules, and has been a series of examples based on association rules. We use a Bayesian network for tissue expression of the existing association rules, proposed independence simplify network inference algorithm algorithm and based on the conditions to build the adjacent table, cross linked based network. Finally, the study on the basis of this paper, the development of agricultural equipment complete operation and maintenance services of data mining applications.This study implements farm machinery and equipment manufacturing enterprises for the effective use of historical maintenance data, complete knowledge discovery from model building to the operation and maintenance of the entire decision-making process, and the system implementation, in order to solve precision of operation and maintenance services to provide technical support improve the company’s operation and maintenance capabilities and competitiveness.