International audienceThis paper deals with a smart algorithm allowing short-circuit faults detection and diagnosis of PV generators. The proposed algorithm is based on the hybridization of a support vector machines (SVM) technique optimized by a k-NN tool for the classification of observations on the classifier itself or located in its margin. To test the proposed algorithm performance, a PV generator database containing observations distributed over classes is used for simulation purposes
