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.
|Title of host publication
|Proceeding - 2015 IEEE International Circuits and Systems Symposium, ICSyS 2015
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 27-01-2016
|IEEE International Circuits and Systems Symposium, ICSyS 2015 - Langkawi, Malaysia
Duration: 02-09-2015 → 04-09-2015
|IEEE International Circuits and Systems Symposium, ICSyS 2015
|02-09-15 → 04-09-15
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering