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International Journal of Rotating Machinery
Volume 6, Issue 1, Pages 19-27

An Efficient Method of Vibration Diagnostics For Rotating Machinery Using a Decision Tree

1School of Mechanical & Automotive Engineering, Pukyong National University, Pusan, Korea
2Research & Development Center, Korea Heavy Industries & Construction Co., Changwon, Korea

Received 15 May 1998; Revised 17 July 1998

Copyright © 2000 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper describes an efficient method to automatize vibration diagnosis for rotating machinery using a decision tree, which is applicable to vibration diagnosis expert system. Decision tree is a widely known formalism for expressing classification knowledge and has been used successfully in many diverse areas such as character recognition, medical diagnosis, and expert systems, etc. In order to build a decision tree for vibration diagnosis, we have to define classes and attributes. A set of cases based on past experiences is also needed. This training set is inducted using a result-cause matrix newly developed in the present work instead of using a conventionally implemented cause-result matrix. This method was applied to diagnostics for various cases taken from published work. It is found that the present method predicts causes of the abnormal vibration for test cases with high reliability.