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Riccardo M.G. Ferrari
Researcher at Delft University of Technology
Publications - 77
Citations - 1223
Riccardo M.G. Ferrari is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Fault detection and isolation & Fault (power engineering). The author has an hindex of 15, co-authored 60 publications receiving 925 citations. Previous affiliations of Riccardo M.G. Ferrari include Bosch & University of Trieste.
Papers
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Journal ArticleDOI
Distributed Fault Detection and Isolation of Large-Scale Discrete-Time Nonlinear Systems: An Adaptive Approximation Approach
TL;DR: The use of a specially-designed consensus-based estimator is proposed in order to improve the detectability and isolability of faults affecting variables shared among overlapping subsystems and simulation results are reported showing the effectiveness of the proposed methodology.
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A Distributed Networked Approach for Fault Detection of Large-Scale Systems
Francesca Boem,Riccardo M.G. Ferrari,Christodoulos Keliris,Thomas Parisini,Marios M. Polycarpou +4 more
TL;DR: This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems that incorporates a synchronization methodology with a filtering approach in order to reduce the effect of measurement noise and time delays on the fault detection performance.
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Distributed Fault Diagnosis With Overlapping Decompositions: An Adaptive Approximation Approach
TL;DR: The use of a specially-designed consensus-based estimator is proposed in order to improve the detectability of faults affecting variables shared among different subsystems, and results provide an evidence of the effectiveness of the proposed distributed fault detection scheme.
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Fault Detection and Isolation of the Wind Turbine Benchmark: an Estimation-based Approach
Xiaodong Zhang,Qi Zhang,Songling Zhao,Riccardo M.G. Ferrari,Marios M. Polycarpou,Thomas Parisini +5 more
TL;DR: In this paper, a fault detection and isolation (FDI) method is developed for wind turbines based on a benchmark system model, where a fault detector is used for fault detection, and a bank of fault isolation estimators are employed to determine the particular fault type/location.
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Distributed Fault Detection and Isolation of Continuous-Time Non-Linear Systems
TL;DR: A consensus-based estimator is designed to improve the detectability and isolability of faults affecting variables shared among different subsystems, andoretical results are provided to characterize the detection and isolation capabilities of the proposed distributed scheme.