Nazih Mechbal

A novel inflatable robot with constant and continuous volume

Inflatable structures are already used in robotics to build stiff and light inflatable links. Moreover, those links are compliant and they can be safely used in robots interacting with critical installations. Nevertheless, until now, linkages with an inflatable structure have always been composed of independent inflatable links separated by joints. But the joints are heavier, less stiff, or less safe than the inflatable links. So in this paper, we present a new design of inflatable robots with joints having similar mechanical characteristics as the links. A first prototype, a model of the joints and some experimental validation will also be presented.

A combined sensitivity analysis and kriging surrogate modeling for early validation of health indicators

Abstract To increase the dependability of complex systems, one solution is to assess their state of health continuously through the monitoring of variables sensitive to potential degradation modes. When computed in an operating environment, these variables, known as health indicators, are subject to many uncertainties. Hence, the stochastic nature of health assessment combined with the lack of data in design stages makes it difficult to evaluate the efficiency of a health indicator before the system enters into service. This paper introduces a method for early validation of health indicators during the design stages of a system development process. This method uses physics-based modeling and uncertainties propagation to create simulated stochastic data. However, because of the large number of parameters defining the model and its computation duration, the necessary runtime for uncertainties propagation is prohibitive. Thus, kriging is used to obtain low computation time estimations of the model outputs. Moreover, sensitivity analysis techniques are performed upstream to determine the hierarchization of the model parameters and to reduce the dimension of the input space. The validation is based on three types of numerical key performance indicators corresponding to the detection, identification and prognostic processes. After having introduced and formalized the framework of uncertain systems modeling and the different performance metrics, the issues of sensitivity analysis and surrogate modeling are addressed. The method is subsequently applied to the validation of a set of health indicators for the monitoring of an aircraft engine’s pumping unit.

Tactile objects based on an amplitude disturbed diffraction pattern method

Tactile sensing is becoming widely used in human-computer interfaces. Recent advances in acoustic approaches demonstrated the possibilities to transform ordinary solid objects into interactive interfaces. This letter proposes a static finger contact localization process using an amplitude disturbed diffraction pattern method. The localization method is based on the following physical phenomenon: a finger contact modifies the energy distribution of acoustic wave in a solid; these variations depend on the wave frequency and the contact position. The presented method first consists of exciting the object with an acoustic signal with plural frequency components. In a second step, a measured acoustic signal is compared with prerecorded values to deduce the contact position. This position is then used for human-machine interaction (e.g., finger tracking on computer screen). The selection of excitation signals is discussed and a frequency choice criterion based on contrast value is proposed. Tests on a sandwich plate (liquid crystal display screen) prove the simplicity and easiness to apply the process in various solids.

Design of a Novel Long-Range Inflatable Robotic Arm: Manufacturing and Numerical Evaluation of the Joints and Actuation

The aim of this paper is to present the design of a new long-range robotic arm based on an inflatable structure. Inflatable robotics has potential for improved large payload-to-weight ratios, safe collision, and inspection in areas inaccessible to human beings as in nuclear plants. The robot presented here is intended to operate inspection or maintenance missions in critical installation taking care to not collide with its environment. It is made with innovative inflatable joints and an original actuation system. Prototypes of this inflatable manipulator were constructed using two different manufacturing procedures. Using LS-DYNA nonlinear dynamic finite element modeling we have numerically analyzed the specific geometry and dynamical behavior of the resulting joints. The simulations have given insight into understanding the joint bending process and have revealed guidance for optimizing the conception.

Principal Component Analysis and Perturbation Theory Based Robust Damage Detection of Multifunctional Aircraft Structure

A fundamental problem in structural damage detection is to define an efficient feature to calculate a damage index. Furthermore, due to perturbations from various sources, we also need to define a rigorous threshold whose overtaking indicates the presence of damages. In this article, we develop a robust damage detection methodology based on principal component analysis. We first present an original damage index based on projection of the separation matrix, and then, we drive a novel adaptive threshold that does not rely on statistical assumptions. This threshold is analytic, and it is based on matrix perturbation theory. The efficiency of the method is illustrated using simulations of a composite smart structure and experimental results performed on a conformal load-bearing antenna structure laboratory test.

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.

Active damage detection and localization applied to a composite structure using piezoceramic patches

This paper describes the application of an active structural health monitoring technique for a composite plate bonded with a distributed piezoceramic patches array. To maximize the performance of a structural health monitoring (SHM) system, an optimal placement of these patches has been proposed using grammians of controllability and observability and the Hœ modal norm. The proposed approach was established via finite element modelization (FE) of the composite structure. With this optimal placement, an active structural health monitoring scheme has been accomplished. Therefore, using spatial information given by the distributed sensors, we have proposed two damage indices (DI). These indices are able to detect and localize damages. The first DI is based upon non-parametric frequency response function estimates; the damage is detectable when changes in the estimates exceed their normal statistical bounds. The second DI uses change in the energy signal sensor to localize damage existing in the composite structure. The efficiency of the proposed approach is demonstrated through experimental tests.

An approach to the health monitoring of the fuel system of a turbofan

This paper focuses on the monitoring of the fuel system of a turbofan which is the core organ of an aircraft engine control system. The paper provides a method for real time onboard monitoring and on-ground diagnosis of one of its subsystems: the hydromechanical actuation loop. First, a system analysis is performed to highlight the main degradation modes and potential failures. Then, an approach for a real-time extraction of salient features named indicators is addressed. On-ground diagnosis is performed through a learning algorithm and a classification method. Parameterization of the on-ground part needs a reference healthy state of the indicators and the signatures of the degradations. The healthy distribution of the indicators is measured on datas whereas a physical model of the system is utilized to simulate degradations, quantify indicators sensibility and construct the signatures. Eventually, algorithms are deployed and statistical validation is performed by the computation of key performance indicators (KPI).

Numerical evaluation of a new robotic manipulator based on inflatable joints

This paper deals with a finite element evaluation of new kind of robotic arm based on a complete inflatable structure. Soft robotics and particularly inflatable robotics are now considered as a credible alternative to classical structures for a wide field of robotics. As they are made of textile materials, inflatable robots allow compact packaging and easier robot deployment. Moreover, they could be used in hostile and hard-to-reach spaces such as the inspection of nuclear plants. The main difficulty for the development of this technology is the design of efficient joints. Based on spacesuit-like-joints a new prototype of inflatable manipulator was constructed and tested. Here thanks to finite elements modeling its numerical evaluation is presented by comparing its mechanical performances to an existing solution. This analysis of the complete dynamical behavior has come up also with some new results and guidance for designing inflatable joints.

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.