Mikhail Guskov

A general Bayesian framework for ellipse-based and hyperbola-based damage localization in anisotropic composite plates

This article focuses on Bayesian Lamb wave-based damage localization in structural health monitoring of anisotropic composite materials. A Bayesian framework is applied to take account of uncertainties from experimental time-of-flight measurements and angle-dependent group velocity within the composite material. An original parametric analytical expression of the direction dependence of group velocity is proposed and validated numerically and experimentally for anisotropic composite and sandwich plates. This expression is incorporated into time-of-arrival (ellipse-based) and time-difference-of-arrival (hyperbola-based) Bayesian damage localization algorithms. This way, the damage location and the group velocity profile are estimated jointly and a priori information is taken into consideration. The proposed algorithm is general as it allows us to take into account uncertainties within a Bayesian framework, and to model effects of anisotropy on group velocity. Numerical and experimental results obtained with different damage sizes or locations and for different degrees of anisotropy validate the ability of the proposed algorithm to estimate both the damage location and the group velocity profile as well as the associated confidence intervals. Results highlight the need to consider for anisotropy in order to increase localization accuracy, and to use Bayesian analysis to quantify uncertainties in damage localization.

A data-driven temperature compensation approach for Structural Health Monitoring using Lamb waves

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 to extract the amplitude factor and the phase shift in signals caused by temperature changes. An ordinary least square (OLS) algorithm is used to estimate these unknown parameters. After estimating these parameters at each temperature in the operating range, linear functional relationships between the temperature and the estimated parameters are derived using the least squares method. A temperature compensation model is developed based on this linear relationship that allows one to reconstruct sensor signals at any arbitrary temperature. The proposed approach is validated numerically and experimentally for an anisotropic composite plate at different temperatures ranging from 16 ° C to 85 ° C . A close match is found between the measured signals and the reconstructed ones. This approach is interesting as it needs only a limited set of piezo-sensor signals at different temperatures for model training and temperature compensation at any arbitrary temperature. Damage localization results after temperature compensation demonstrate its robustness and effectiveness.

Simultaneous Influence of Static Load and Temperature on the Electromechanical Signature of Piezoelectric Elements Bonded to Composite Aeronautic Structures

Electromechanical (EM) signature techniques have raised a huge interest in the structural health-monitoring community. These methods aim at assessing structural damages and sensors degradation by analyzing the EM responses of piezoelectric components bonded to aeronautic structures. These structures are subjected simultaneously to static loads and temperature variations that affect the metrics commonly used for damage detection and sensor diagnostics. However, the effects of load and temperature on these metrics have mostly been addressed separately. This paper presents experimentations conducted to investigate the simultaneous influence of static load and temperature on these metrics for two kinds of piezoelectric elements (lead zirconate titanate (PZT) and macrofiber composite (MFC)) bonded on sandwich composite materials, for the full range of real-life conditions encountered in aeronautics. Results obtained indicate that both factors affect the metrics in a coupled manner in particular due to the variations of the mechanical properties of the bonding layer when crossing its glass transition temperature. Furthermore, both piezoelectric elements globally behave similarly when subjected to temperature variations and static loads. Simultaneous accounting of both temperature and static load is thus needed in practice in order to design reliable structural health-monitoring systems based on these metrics.

Simulation of a finishing operation : milling of a turbine blade and influence of damping

Milling is used to create very complex geometries and thin parts, such as turbine blades. Irreversible geometric defects may appear during finishing operations when a high surface quality is expected. Relative vibrations between the tool and the workpiece must be as small as possible, while tool/workpiece interactions can be highly non-linear. A general virtual machining approach is presented and illustrated. It takes into account the relative motion and vibrations of the tool and the workpiece. Both deformations of the tool and the workpiece are taken into account. This allows predictive simulations in the time domain. As an example the effect of damping on the behavior during machining of one of the 56 blades of a turbine disk is analysed in order to illustrate the approach potential.© 2012 ASME