Fault classification using SVM

Analog circuits are abundantly used in today´s world. Unexpected failures might result in grave repercussions which is why their fault diagnosis is of utmost importance. We put forward an innovative fault classifier technique using Support Vector Machines (SVM) to identify whether the circuit is functioning properly and to identify the fault. We first train the SVM with sample voltages of a simple RLC circuit obtained by simulating this circuit on MATLAB. Fault classification can then be done accurately and precisely by the SVM. Simulations are done on MATLAB to calculate the accuracy and precision of this system.