首页|Application of constrained unscented Kalman filter (CUKF) for system identification of coupled hysteresis under bidirectional excitation
Application of constrained unscented Kalman filter (CUKF) for system identification of coupled hysteresis under bidirectional excitation
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NETL
NSTL
Wiley
System identification is primarily studied for unidirectional excitation usingthe Bouc-Wen model, neglecting the torsional coupling, even though realstructure experiences multidirectional seismic excitation. Moreover, the highdamping rubber bearings exhibit bidirectional effects, thereby requiringcoupled biaxial Bouc-Wen (BBW) model and demand the estimation of modelparameters for structural health monitoring. The current work presents threenumerical case studies followed by experimental validation to demonstrate theapplicability and efficacy of Bayesian filters named constraint unscentedKalman filter (CUKF) in identifying model parameters for the nondeterioratingsystem as well as deteriorating systems. With limited measurementsand increased states, a two-stage framework of the CUKF is used toenhance the performance in identifying the hysteresis parameters and systemdynamics of the nondeteriorating systems. For the deteriorating system, theParis-Erdogan law is coupled with the stiffness in the BBW model to introducedegradation as per the acceleration fatigue crack growth. The degradationparameters and deteriorating stiffness is captured through CUKF accurately.The application of CUKF to the experimental responses proves the robustnessof the algorithm for coupled biaxial hysteresis system. Additionally, a unifiedstructural health monitoring (SHM) framework is proposed for condition monitoringduring extreme events and long-term periodic maintenance throughambient vibrations. Overall, the result concludes that CUKF is a reliableBayesian estimator for coupled biaxial hysteresis systems and demonstratespromising potential in identifying fatigue-induced deterioration.
NETL
NSTL
Wiley
