Induction machines are one of the crucial elements of many industrial processes nowadays (IM). These machines are prone to rotor, stator, or bearing failure due to diverse operating circumstances. All of these IM flaws have the potential to impair output, harm neighboring equipment, or, in the worst case, lead to the system’s complete failure[1]–[3]. Induction machines have been in use since the early 1800s. The operators or the equipment close to the working zones may be at danger from this motor’s strong starting torque and high operating speeds. Broken rotor bar defects are one of the frequent causes of motor failure, which may also be brought on by an unfavorable operating environment or artificial mis-operation during the manufacturing process. The rotor bar will first fracture locally, and the surrounding area will experience increased stress. As the defect worsens, the rotor bar entirely breaks, along with any adjacent bars, and finally the whole motor collapses. The early detec
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
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