This paper develops a filtering approach for distributed fault detection of a class of interconnected input-output nonlinear systems with modeling uncertainties, disturbances and measurement noise. A distributed fault detection filtering scheme and the corresponding adaptive thresholds are designed based on filtering certain signals so that the effect of the measurement noise and disturbances is attenuated, which facilitates less conservative thresholds and enhanced robustness. Further analysis leads to a quantitative characterization of the class of detectable faults and simulation results are used to illustrate the proposed distributed fault diagnosis filtering approach.
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