Joseph Morlier

Virtual Vibration Measurement Using KLT Motion Tracking Algorithm

This paper presents a practical framework and its applications of motion tracking algorithms applied to structural dynamics. Tracking points (“features”) across multiple images is a fundamental operation in many computer vision applications. The aim of this work is to show the capability of computer vision (CV) for estimating the dynamic characteristics of two mechanical systems using a non contact, marker less and simultaneous Single Input Multiple Output (SIMO) analysis. KLT (Kanade-Lucas-Tomasi) trackers are used as virtual sensors on mechanical systems video from high speed camera. First we introduce the paradigm of virtual sensors in the field of modal analysis using video processing. To validate our method, a simple experiment is proposed: an Oberst beam test with harmonic excitation (mode 1). Then with the example of helicopter blade, Frequency Response Functions (FRFs) reconstruction is carried out by introducing several signal processing enhancements (filtering, smoothing). The CV experimental results (frequencies, mode shapes) are compared with classical modal approach and FEM model showing high correlation. The main interest of this method is that displacements are simply measured using only video at FPS (Frame Per Second) respecting the Nyquist frequency.

New Image Processing Tools for Structural Dynamic Monitoring

This paper presents an introduction to structural damage assessment using image processing on real data (non ideal conditions). Our contribution is much more a groundwork than a classical experimental validation. After measuring the bridge dynamic parameter on a small resolution video, we conjointly present advantages and limitations of our method. Finally we introduce several “computer vision” based rules and focus on the technical ability to detect damage using camera and video motion estimation.

Correlating low energy impact damage with changes in modal parameters: diagnosis tools and FE validation

This article presents a basic experimental technique and simplified finite element (FE)-based models for the detection, localization, and quantification of impact damage in composite beams around the barely visible impact damage level. Detection of damage is carried out by shift in modal parameters. Localization of damage is done by a topology optimization tool, which showed that correct damage locations can be found rather efficiently for low-level damage. The novelty of this article is that we develop an all in one package dedicated to impact identification by modal analysis. The damaged zones in the FE models are updated by reducing the most sensitive material property, in order to improve the experimental/ numerical correlation of the frequency response functions. These approximate damage models (in terms of equivalent rigidity) give us a simple degradation factor that can serve as a warning regarding the safety of the structure.

An Improved Approach for Estimating the Hyperparameters of the Kriging Model for High-Dimensional Problems through the Partial Least Squares Method

During the last years, kriging has become one of the most popular methods in computer simulation and machine learning. Kriging models have been successfully used in many engineering applications, to approximate expensive simulation models. When many input variables are used, kriging is inefficient mainly due to an exorbitant computational time required during its construction. To handle high-dimensional problems (100+), one method is recently proposed that combines kriging with the Partial Least Squares technique, the so-called KPLS model. This method has shown interesting results in terms of saving CPU time required to build model while maintaining sufficient accuracy, on both academic and industrial problems. However, KPLS has provided a poor accuracy compared to conventional kriging on multimodal functions. To handle this issue, this paper proposes adding a new step during the construction of KPLS to improve its accuracy for multimodal functions. When the exponential covariance functions are used, this step is based on simple identification between the covariance function of KPLS and kriging. The developed method is validated especially by using a multimodal academic function, known as Griewank function in the literature, and we show the gain in terms of accuracy and computer time by comparing with KPLS and kriging.

Improvement of efficient global optimization with application to aircraft wing design

For decades, numerical tool improvements enabled the optimization of complex processes occurring during the conceptual phase. Nowadays simulators can determine numerous coupled physical effects with high accuracy and allow cheap and fast virtual testing. However, high fidelity tools require long computation times (several days of computation using High Performance Computing solutions) and thus optimization based on these high fidelity tools is often done at higher computational cost (gradient based). This work aims at optimizing a complex design using costly simulation codes given a fixed computational budget. In aeronautical engineering these codes can be coupled in space (such as Fluid Structure Interaction) and/or in time (for transient analysis). The fixed budget implies the use of surrogate-based method with adaptive sampling in order to promote a trade-off between exploration and exploitation. The proposed optimization is based on a sequential enrichment approach (typically Efficient Global Optimization), using an adaptive mixture of kriging-based models. The strategy relies on an improvement of the kriging model that enables the handling of a large number of design variables whilst maintaining rapidity and accuracy. A key feature is the use of mixture of experts technique to combine local surrogate models to approximate both the objective function and the constraints. Our strategy will be introduced through mathematical methods and detailed algorithms presentation. Finally, we produce several validations on analytical test cases (supervised) and two exten- sions such as the well-known MOPTA test case from automobile industry and aircraft wing structural optimization. The experiments confirm that the proposed global optimization approach minimizes the number of black box evaluations and in this sense it is well suited for high-dimensional problems with a large number of constraints.

An adaptive optimization strategy based on mixture of experts for wing aerodynamic design optimization

In the field of aircraft design, the last few decades have focused on the iterative improve- ment of conventional tube-and-wing designs to reduce cost, noise, and emission. Never- theless, the growing expectation in terms of environment impact for the next generation of aircraft pushes for more radical changes in the design. For unconventional aircraft configurations, the need to integrate more accurate data coming from higher fidelity analysis earlier in the design process becomes more and more necessary. However, high-fidelity tools require long computation times and usually are associated with high-dimensional problems, both in terms of design variables and constraints. Therefore, these optimizations are often done at higher computational cost (gradient-based algorithms) in order to decrease the number of necessary function evaluations. In addition, the use of the adjoint method is often implemented to accurately and efficiently compute derivatives for large numbers of design variables. At the same time, new methods have been investigated to obtain opti- mized configurations at a reasonable computational cost. The work presented in this paper focuses on SEGOMOE algorithm, a solution to tackle this kind of optimization process of complex design problem through the use of an enrichment strategy approach based on mixture of experts surrogate models. Two aerodynamic shape optimization test cases, derived from cases developed by the Aerodynamic Design and Optimization Discussion Group (ADODG) are addressed: one with a single global minimum, and another one with several local minima. Both problems are nonlinearly constrained problems that involve a large number of design variables. Results are compared to gradient-based optimizers. A hybrid approach combining the advantages of both SEGOMOE and gradient-based optimization is proposed and evaluated to reduce the number of function evaluations and to ensure the convergence to the global optimum.

Damage localization map using electromechanical impedance spectrums and inverse distance weighting interpolation: Experimental validation on thin composite structures

Piezoelectric sensors are widely used for structure health monitoring technique. In particular, electromechanical impedance techniques give simple and low-cost solutions for detecting damage in composite structures. The purpose of the method proposed in this article is to generate a damage localization map based on both indicators computed from electromechanical impedance spectrums and inverse distance weighting interpolation. The weights for the interpolation have a physical sense and are computed according to an exponential law of the measured attenuation of acoustic waves. One of the main advantages of the method, so-called data-driven method, is that only experimental data are used as inputs for our algorithm. It does not rely on any model. The proposed method has been validated on both one-dimensional and two-dimensional composite structures.

Fabrication and Mechanical Testing of a New Sandwich Structure with Carbon Fiber Network Core

The aim is the fabrication and mechanical testing of sandwich structures including a new core material known as fiber network sandwich materials. As fabrication norms for such a material do not exist as such, the primary goal is to reproduce successfully fiber network sandwich specimens. Enhanced vibration testing diagnoses the quality of the fabrication process. These sandwich materials possess low structural strength as proved by the static tests (compression, bending), but the vibration test results give high damping values, making the material suitable for vibro-acoustic applications where structural strength is of secondary importance e.g., internal paneling of a helicopter.

Significance of low energy impact damage on modal parameters of composite beams by design of experiments

This paper presents an experimental study on the effects of multi-site damage on the vibration response of composite beams damaged by low energy impacts around the barely visible impact damage limit (BVID). The variation of the modal parameters with different levels of impact energy and density of damage is studied. Vibration tests have been carried out with both burst random and classical sine dwell excitations in order to compare that which of the methods among Polymax and Half Bandwidth Method is more suitable for damping estimation in the presence of damage. Results show that damping ratio is a more sensitive parameter for damage detection than the natural frequency. Design of experiments also highlighted energy of impact as the factor having a more significant effect on the modal parameters. Half Bandwidth Method is found to be unsuitable for damping estimation in the presence of damage.

Benchmark of Damage Localisation Algorithms Using Mode Shape Data

This paper presents a comparative study of three enhanced signal processing methods to locate damage on mode shape data. The first method called curvature mode shape is used as a reference. The second tool uses wavelet transform and singularity detection theory to locate damage. Finally we introduce the windowed fractal dimension of a signal as a tool to easily measure the local complexity of a signal. Our benchmark aims at comparing the crack detection using optimal spatial sampling under different severity, beam boundary conditions (BCs) and added noise measurements.