Broken Rotor Bar Fault Detection and Severity Analysis using Machine Learning Techniques

 This is our project demo video

After training, validating and testing the models available in the Classification Learner app, the LSTM model, and the NPR tool model, it was seen that the Cubic Support Vector Machine provided the best test accuracy of 99.8% for 100% load.   The table below shows the accuracies obtained for each of the models for 12.5% of the load. Model Test Accuracy Train Accuracy ROC (AUC) LSTM     93.04%        92.69%        -    SDNN     96.9%        96.6%        -    Quadratic SVM     96.7%        98.5%        Class 1 – 0.9995        Class 2 – 0.9999        Class 3 – 0.9993        Class 4 – 0.9994        Class 5 – 0.9994    Cubic SVM     96.6%        98.7%        Class 1 – 0.9993        Class 2 – 0.9998        Class 3 – 0.9986        Class 4 – 0.9992        Class 5 – 0.9995