A Study On The Nuclear Power Station Intermittent Demand Spare Parts Classification Model Based On SVM Theory

Accompanied with the development of the economy and the improvement of the life quality of people, the electricity industry is developing rapidly. The nuclear power industry is playing a more and more important role in the electricity industry, with the attribute of economy, safety and cleanness. It is predicted that by the year 2020, the percentage of nuclear power industry will raise to 4% of the whole electricity industry. During the operation of the nuclear power station, reliability of machines is the key point. As a backup of the machines, the spare parts play an important role in maintenance jobs.First of all, the paper analyzes the problems existing in the current inventory classification, the incomprehensive coverage of indicators, the great subjectivity, the need of a large training data set etc. After that, the basic theory of support vector machine (SVM) and the advantages of SVM are introduced, such as simple structure, faster classification speed, better generalization ability and global optimized etc.Secondly, two kinds of spare parts, the frequently used spare parts and the intermittent demand spare parts, are introduced. A system of indicators in classification of nuclear power station spare parts is established, based on the attributes of the intermittent demand spare parts, such as high price, long lead-time and short lifetime.Thirdly, the classification model based on multi-class SVM theory is established, base on the study on the methods of multi-classification.Lastly, the paper offers a whole example of nuclear power station spare parts classification, which verifies the rightness and the effectiveness of the model.