An Application of Decision Tree Method for Fault Diagnosis of Induction Motors

  • Tran, Van Tung (Mechanical Engineering Department, Ho Chi Min City University of Technology) ;
  • Yang, Bo-Suk (School of Mechanical Engineering, Pukyong national University) ;
  • Oh, Myung-Suck (School of Mechanical Engineering, Pukyong national University)
  • Published : 2006.11.16

Abstract

Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for these data.