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Working in the field of predictive modelling to detect and classify various types of faults in induction motors by deploying various ML algorithms over the vibration and current signals data.

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Aficionado45/IM-Fault-Detection

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IM-Fault-Detection

Working in the field of predictive modelling to detect and classify various types of faults in induction motors using differnt ML classifier models over IM vibration and current signals data.

In this project study we considered Random forest ML classifier model under Scikit Learn library in contrast to original Multi-SVM model to test out the accuracy for predictive modelling in fault detection of induction motors. Following defects have been take in consideration for training and testing the model:

  • Bearing Fault
  • Bowed Row Fault
  • Rotor Misalignment
  • Unbalanced Rotor

Libraires Used:

  • Scikit Learn
  • Numpy
  • Pandas

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Working in the field of predictive modelling to detect and classify various types of faults in induction motors by deploying various ML algorithms over the vibration and current signals data.

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