This paper created a new research space in the faults modeling and detection area of the industrial systems, especially photovoltaic generators. It reserved for modeling and detection the hybrid defects, like the presence of cells open- and short-circuit within the same photovoltaic cells group. For a small investment, the new algorithm created a new platform. It exposed a display screen of the database, which presented the power of the PV module production in each period. The display screen allows real-time monitoring of the PV module production throughout the year, and detecting its anomalies.

This article proposed a new smart diagnosis algorithm of the open-circuit fault in a PV generator. For the faults conventional diagnosis, it used the analysis of the actual operation parameters of the PV generator. For the faults smart diagnosis, it based on the optimization of SVM technique by the neural network for the classification of observations located on its margin. The resulting algorithm can ensure a better monitoring function of the open-circuit fault within the PV generator, with a high classification rate and a low error rate.