Gear Fault Diagnosis Using SVM Based on Empirical Mode Decomposition

Vibration analysis is one of the major techniques in the condition monitoring of mechanical components. In vibration analysis, the vibration data were taken from earlier conducted experiments for healthy conditions using vibration sensors positioned at various locations. These datasets were imported to MATLAB for feature extraction and analysis. The gear fault-related features in the vibration signals are extracted by Empirical Mode Decomposition (EMD). Further, features like RMS, kurtosis, and skewness were extracted. The extracted features were classified in MATLAB classification algorithms like SVM. The confusion matrix plot will be used to distinguish between the classifiers. The confusion matrix uses both trained data and raw data for comparison and the accuracy of these algorithms was compared.