Bearing Fault Diagnosis Based on Multiscale Permutation Entropy and Support Vector Machine

@article{Wu2012BearingFD,
  title={Bearing Fault Diagnosis Based on Multiscale Permutation Entropy and Support Vector Machine},
  author={Shuen-De Wu and Po-Hung Wu and Chiu-Wen Wu and Jian-Jiun Ding and Chun-Chieh Wang},
  journal={Entropy},
  year={2012},
  volume={14},
  pages={1343-1356}
}
Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, multiscale permutation entropy (MPE) was introduced for feature extraction from faulty bearing vibration signals. After extracting feature vectors by MPE, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. Simulation results… CONTINUE READING
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