Multiple fault diagnosis by signature recognition of time-varying residuals
A Fault Detection and Diagnosis scheme able to deal with concurrent, incipient, sensor and actuator faults is presented. The architecture allows the diagnosis whenever the system's outputs are less than the number of faults. Residual generation is achieved by taking advantage from observer-based design, whereas the classification is performed by extending the concept of directional residual towards a time-varying setting. The scheme is designed to leverage the power from both model-based and data-driven approaches while mitigating their inherent drawbacks. The performances of the proposed strategy are evaluated by employing real data coming from the TEKOB1 Thermal Plant of Kostolac, Serbia.
Channel estimation is an essential component, in which channel state information playing very important role in wireless communications. But acquiring CSI in practice is a challenging issue for massive MIMO systems. To reduce the over burden for obtaining channel impulse response of huge Multi input multi output system channel reciprocity in TDD domain is suggested, because the forward link channel data can be derived from the reverse link signal without any feedback involvement. Because of mismatches at uplink, downlink channels maintaining reciprocity in TDD systems is impractical. We study the impact of multiplicative reciprocity error for precoders (Zero forcing, MMSE and MRT) performance along with channel estimation error. In this paper effect of RF mismatches impact on linear precoders is analyzed and simulated in terms of SINR versus SNR under additive white Gaussian noise.