Stiffened composite structures are very appealing in aeronautic applications due to their unique stiffness to mass ratio. However, they are also prone to various and complex damage scenario (stiffener debonding, impact damage...) and to complex wave propagation phenomena due to the presence of the stiffener. Consequently, autonomous monitoring of such structure is still a real issue. The process of monitoring in real-time a structure is referred to structural health monitoring (SHM) and consists of several steps: damage detection, localization, classification, and quantification. The focus is put here on the damage detection step of SHM. To detect damages, stiffened composite structures are equipped with piezoelectric elements that act both as sensors and actuators. A database at the unknown (and possibly damaged state) is then compared to a healthy reference database. Several damage indexes (DIs) designed for detection are extracted from this comparison. The SHM process classically relies on four sequential steps: damage detection, localization, classification, and quantification. The most critical step of such process is the damage detection step since it is the first one and because performances of the following steps depend on it. A common method to design such a detector consists in relying on a statistical characterization of the damage indexes available in the healthy behavior of the structure. On the basis of this information, a decision threshold can then be computed in order to achieve a desired probability of false alarm (PFA). In this paper, the performances of these DIs with respect to damage detection in a stiffened composite plate are studied. Results show that DIs based on energy consideration perform better than the ones based on cross-correlation. Furthermore Fourier-transform based DIs appear to be insensitive to the presence of damage in such structure.