Robust switching detection and active mode recognition are addressed for switched nonlinear systems that may switch among non linear modes taken from a finite set. The proposed method uses only a partial knowledge of system parameters and is robust toward local model parameters uncertainties. A possible application of our method is fault detection and isolation, where faulty situations are represented as faulty modes. The nonlinear modes are represented by Takagi-Sugeno models. The proposed switching detection technique and the active mode recognition method use indicator signals that are generated using a data-driven projection technique. The main advantage of this method is that it does not need the knowledge of local model parameters values. Only input-output data and the weighting functions of the TS model are used to generate these indicator signals. A numerical example is provided to illustrate the proposed approach.