Fault Detection & Diagnostics of ElectroMechanical Devices is a project based on Sinfonia conveyor belts used in airports. Outliers detection, classification & prediction were the main tasks involved.
Various statistical tests like Grubbs test, Modified Thompson Tau test were used to find the outliers in the given datasets using Python and JavaScript programming languages. Finding outliers separately in the different features of the dataset itself is fault detection and classification. Further a prediction was made using algorithms like SVM, Decision trees to know the next series of data whether faulty or not. If faulty over a run was found then suitable diagnosis was applied to make the machine run smooth.