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Simple_PD_Classification

Computationally Efficient Detection Method for Acoustic Partial Discharge Signals

Please compile the MATLAB code "PDClassification_PDF.m" to generate the CSV file "PDClassification_PDF.csv" that includes the feature vectors. WEKA tool can be then used to examine the effectiveness of the selected features using RANDOM FOREST classifier.

  • Do not forget to include the PD data in the MATLAB directory first.
  • Please include the MATLAB vector "time_Acoustic" in the MATLAB directory too.

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This Repository includes the codes and discussions that are related to the conference paper entitled "Computationally Efficient Detection Method for Acoustic Partial Discharge Signals".

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