From nonlinear system identification to structural health monitoring
The process of implementing a damage monitoring strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM) and implies a sensor network that monitors the behavior of the structure on-line. A SHM process potentially allows for an optimal use of the monitored structure, a minimized downtime, and the avoidance of catastrophic failures. The SHM process classically relies on four sequential steps that are damage detection, localization, classification, and quantification. The key idea underlying this seminary is that structural damages may result in nonlinear dynamical signatures that are not yet used in SHM despite the fact that they can significantly enhance their monitoring. We thus propose to monitor these structural damages by identifying their nonlinear signature on the basis of a cascade of Hammerstein models representation of the structure. This model is here estimated at very low computational cost by means of the Exponential Sine Sweep Method. It will be shown that on the basis of this richer dynamical representation of the structure, SHM algorithms dedicated to damage detection, classification and quantification can be derived. This will be illustrated in the aeronautic and civil engineering contexts and using experimental as well as numerical data.
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BARTHES, Clément; MECHBAL, Nazih; MOSALAM, Khalid; REBILLAT, Marc (2017)The ability to monitor the health of complex structures such as aeronautic or civil engineering structures in real time is becoming increasingly important. This process is referred to as structural health monitoring (SHM) ...
BAKIR, Myriam; REBILLAT, Marc; MECHBAL, Nazih (IFAC, 2015)Structural damages result in nonlinear dynamical signatures that significantly help for their monitoring. A damage type classification approach is proposed here that is based on a parallel Hammerstein models ...
Comparison of least squares and exponential sine sweep methods for Parallel Hammerstein Models estimation REBILLAT, Marc; SCHOUKENS, Maarten (Elsevier, 2017)Linearity is a common assumption for many real-life systems, but in many cases the nonlinear behavior of systems cannot be ignored and must be modeled and estimated. Among the various existing classes of nonlinear models, ...
FENDZI, Claude; REBILLAT, Marc; MECHBAL, Nazih; GUSKOV, Mikhail; COFFIGNAL, Gérard (SAGE Journals, 2016)This paper presents a temperature compensation method for Lamb wave structural health monitoring. The proposed approach considers a representation of the piezo-sensor signal through its Hilbert transform that allows one ...
GHRIB, Meriem; BERTHE, Laurent; MECHBAL, Nazih; REBILLAT, Marc; GUSKOV, Mikhail; ECAULT, Romain; BEDREDDINE, Nas (Elsevier, 2017)Structural Health Monitoring (SHM) is defined as the process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructures. SHM can be organized into five main steps: ...