Interharmonic Detection Based on Support Vector Machine

Support vector machine (SVM) based on the principle of structure risk minimization provides a new perspective in machine learning, and has been successfully applied to many areas in the last years, especially for pattern recognition and function fitting. In this paper, because of the adjustable resolution of the SVM algorithm, a new way to measure interharmonic is put forward, namely using wide analytical domain of frequency with low resolution at first and then using narrow analytical domain of frequency with high resolution to obtain the frequency spectrum of the signal. And based on this new method, the interharmonic detection system is designed and implemented with the prevailing and powerful software platform of LabVIEW with graphical nature