Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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A Study on Machine Fault Diagnosis using Decision Tree

  • Published : 2007.12.31
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Abstract

The paper describes a way to diagnose machine condition based on the expert system. In this paper, an expert system-decision tree is built and experimented to diagnose and to detect machine defects. The main objective of this study is to provide a simple way to monitor machine status by synthesizing the knowledge and experiences on the diagnostic case histories of the rotating machinery. A traditional decision tree has been constructed using vibration-based inputs. Some case studies are provided to illustrate the application and advantages of the decision tree system for machine fault diagnosis.

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References

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Cited by

  1. A dual sensor signal fusion approach for detection of faults in rotating machines 2018, https://doi.org/10.1177/1077546316689644
  2. System availability enhancement using computational intelligence–based decision tree predictive model vol.229, pp.6, 2015, https://doi.org/10.1177/1748006X15595875