A spatio-temporal nonlinear semi-analytical framework describing longitudinal waves propagation in damaged structures based on Green–Volterra formalism
Article dans une revue avec comité de lecture
Date
2023-01Journal
Mechanical Systems and Signal ProcessingAbstract
Structural Health Monitoring (SHM) of aeronautic structures by means of Lamb waves opens promising perspectives in terms of maintenance costs reduction and safety increases. Lamb waves interactions with damages are known to be nonlinear, a property still largely underexploited in SHM. Difficulties in this context are (i) to be able to distinguish between nonlinearities due to the waves spatial propagation (i.e. material or geometrical nonlinearities) and those located at the damage position, (ii) to handle computational complexity associated with spatio-temporal nonlinear models, and (iii) to be able to physically link recorded signals with actual damage state. This work proposes to rely on the Green–Volterra formalism to build up a semi-analytical spatio-temporal framework describing longitudinal waves propagation and damage interaction able to physically represent both types of nonlinearities, and computationally simple enough to be tractable in real-time for SHM purposes. This approach is detailed here for longitudinal waves, which corresponds in the low frequency thickness range to the Lamb wave mode propagating in a damaged beam. A spatio-temporal semi-analytical model of the nonlinear longitudinal waves propagation is first derived, where the damage is represented by a polynomial stiffness characteristic acting via boundary conditions at a given position in the beam. This model is then used to derive the Green–Volterra series describing the nonlinear input–output relationship of the system. A modal decomposition of the Green–Volterra series is also provided to ease implementation and reduce computational cost. The proposed spatio-temporal semi-analytical approach is then successfully compared to state-of-the-art nonlinear Lamb waves simulation methods based on finite-element models. It is finally shown on a simulated example and discussed in detail how such a nonlinear framework could potentially be relevant for SHM purposes.
Files in this item
- Name:
- PIMM_MSSP_2023_BOUVIER.pdf
- Size:
- 3.252Mb
- Format:
- Description:
- A spatio-temporal nonlinear ...
- Embargoed until:
- 2023-07-04
Related items
Showing items related by title, author, creator and subject.
-
Communication avec acteStructural Health Monitoring of aeronautic composite structures through Lamb waves can advantageously exploit the fact that Lamb wave damage interaction is nonlinear. However, one di culty in this context is to be able to ...
-
Article dans une revue avec comité de lecturePOSTORINO, Hadrien; REBILLAT, Marc; MECHBAL, Nazih; MONTEIRO, Eric (University of Liege library ( Belgium), 2023-04)In Lamb Waves based Structural Health Monitoring (LWSHM) of composite aeronautic structures, Deep Learning (DL) methods have proven to be promising to monitor damage using the signals collected by piezoelectric sensors ...
-
Communication sans acteThe deployment of Deep Learning (DL) strategies is particularly advantageous in Structural Health Monitoring (SHM) based of lamb Wave (LW) propagation due to the high quantity of data collected by the network of piezoelectric ...
-
BrevetSystems and methods for controlling an implantable pump are provided. For example, the exemplary controller for controlling the implantable pump may only rely on the actuator's current measurement. The controller is robust ...
-
Communication avec actePOSTORINO, Hadrien; REBILLAT, Marc; MECHBAL, Nazih; MONTEIRO, Eric (Springer International Publishing, 2022-06)Structural Health Monitoring (SHM) based on Lamb wave propagation is a promising technology to optimize maintenance costs, enlarge service life and improve safety of aircrafts. A large quantity of data is collected during ...