SMART solutions for composite structures

In this paper, an improvement of the elliptical triangulation method for damage detection using Lamb waves is presented. The damage is the main cause of structural failure and often occurs on structures. In order to avoid sudden failure, a special attention was given in the past decades to the damage detection in structures. In order to obtain efficient damage detection techniques, the structural health monitoring has been the main research topic of many scientists worldwide. The elliptical triangulation method, proposed in this paper, is a non-destructive method based on measurement of Lamb waves. This method, through the calculation of the time of flight of the signals and the actuator-sensor positioning, allows to identify position and dimension of the damage. The application of the method to the metallic structures and to the composite material structures is presented in this paper. The complexity connected with the uncertainty of the waves’ propagation speed due to the anisotropy of the composite materials has been explored through an iterative approach. The initialization of the wave propagation speed at first tentative iteration is the key issue for the convergence of the method. Seven different conditions were used to validate the method on both metallic and composite structures combining two damage shapes, two damage dimensions (effective damaged area), and three different positions. Upon evaluating the effectiveness, the method has been applied at two composite panels in order to detect by test the post-impact damages. Tests results have been compared with the numerical ones. The feasibility of the elliptical triangulation method to detect the damage (evaluating the damage position and area) has been proved using the ultrasonic C-Scan.

This thesis is devoted to present some novel techniques in Structural Health Monitoring (SHM). SHM is a developing field that tries to monitor structures to make sure that they remain in their desired condition to avoid any catastrophe. SHM includes different levels from damage detection area to prognosis field. This work is dedicated to the first level, which might be considered the main and most important level. New techniques presented in this work are based on different statistical and signal processing methods such as Principal Component Analysis and its robust counterpart, Wavelet Transform, Fuzzy similarity, Andrew plots, etc. These techniques are applied on the propagated waves that are activated and captured in the structure using appropriate transducers. Piezoceramic (PZT) devices are chosen in this work to capture the signals due to their special characteristics such as high performance, low energy consumption and reasonable price. To guarantee the efficiency of the suggested techniques, they are tested on different laboratory and real scale test benchmarks, such as aluminum and composite plates, fuselage, wing skeleton, tube, etc. Because of the variety of tested benchmarks, this thesis is called damage detection in smart structures. This variety may promise the ability and capability of the proposed methods on different fields such as aerospace and gas/oil industry. In addition to the normal laboratory conditions, it is shown in this work that environmental changes can affect the performance of the damage detection and wave propagation significantly. As such, there is a vital need to consider their effect. In this work, temperature change is chosen as it is one of the main environmental fluctuation factors. To scrutinize its effect on damage detection, first, the effect of temperature is considered on wave propagation and then all the proposed methods are tested to check whether they are sensitive to temperature change or not. Finally, a temperature compensation method is applied to ensure that the proposed methods are stable and robust even when structures are subjected to variant environmental conditions. La presente tesis doctoral se dedica a la exploración y presentación de técnicas novedosas para la Monitorización y detección de defectos en estructuras (Structural Health Monitoring -SHM-) SHM es un campo actualmente en desarrollo que pretende asegurarse que las estructuras permanecen en su condición deseada para evitar cualquier catástrofe. En SHM se presentan diferentes niveles de diagnóstico, Este trabajo se concentra en el primer nivel, que se considera el más importante, la detección de los defectos. Las nuevas técnicas presentadas en esta tesis se basan en diferentes métodos estadísticos y de procesamiento de señales tales como el Análisis de Componentes Princpales (PCA) y sus variaciones robustas, Transformada wavelets, lógica difusa, gráficas de Andrew, etc. Estas técnicas de aplican sobre las ondas de vibración que se generan y se miden en la estructura utilizando trasductores apropiados. Dispositivos piezocerámicos (PZT's) se han escogido para este trabajo ya que presentan características especiales tales como: alto rendimiento, bajo consumo de energia y bajo costo. Para garantizar la eficacia de la metodología propuesta,se ha validado en diferentes laboratorios y estructuras a escala real: placas de aluminio y de material compuesto, fuselage de un avión, revestimiento del ala de un avóin, tubería, etc. Debido a la gran variedad de estructuras utilizadas, su aplicación en la industria aeroespacial y/o petrolera es prometedora. Por otra parte, los cambios ambientales pueden afectar al rendimiento de la detección de daños y propagación de la onda significativamente . En este trabajo , se estudia el efecto de las variaciones de temperatura ya que es uno de los principales factores de fluctuación del medio ambiente . Para examinar su efecto en la detección de daños, en primer lugar, todos los métodos propuestos se prueban para comprobar si son sensibles a los cambios de temperatura o no. Finalmente , se aplica un método de compensación de temperatura para garantizar que los métodos propuestos son estables y robustos incluso cuando las estructuras se someten a condiciones ambientales variantes

In civil engineering, health monitoring of structure have been treated as an important subject. Health monitoring by using experimental measurements such as strain, acceleration, velocity, displacement, rotation and other parameters has been used for detecting changes, which may indicate damage or degradation. In recent, the applications of health monitoring of large structure have been facilitated by the developments in measurement, communications and computational technology gradually. Especially, large civil structures as bridges are damaged by fatigue loads or unexpected load such as earthquakes and finally reach to failure. Thus, a structural health monitoring and damage detection methods have been developed and attracted a great deal of public attention in recent decades. Actually many research efforts have been conducted to develop a health monitoring and damage detection techniques of existing civil structures. However, these methods are needed to improve to apply to a real civil structure. The purpose of this study is to develop a practical instrument to identify dynamic parameters of real civil structural systems.

As newer and more reliable ways of construction were developed, civilization began to spread out further and retain functional infrastructure for longer periods of time.[...]

Structural health monitoring (SHM) is the process of implementing a damage identification strategy which can be utilized in several applications including aerospace, civil and mechanical engineering infrastructure. Damage is defined as changes to the material and/or geometric properties of these systems. These changes adversely affect the current or future performance of the system. In order to identify damage in a suitable and meaningful manner, the damaged state is compared with other usually undamaged states. This study focuses on a structural health monitoring (SHM) system based on detecting shifts in natural frequencies of the structure. This structural health monitoring system incorporates a low power wireless transmitter that sends a warning signal when damage is detected in a structure. The damage detection technique is implemented on composite structures which are widely used in many applications including aeronautical and aerospace. An automated damage detection system capable of providing information of damage locations based on the finite element analysis and able to compare damage events to other historical data is also proposed in this paper and initially implemented using a microcontroller chip. Moreover, a control methodology using piezoelectric fiber composites, such as active fiber composites (AFCs) and microfiber composites (MFCs), is included as part of the system for vibration suppression purposes. The advantages of using piezoelectric fiber composite actuators are their high performance, flexibility, and durability when compared with the traditional piezoceramic (PZT) actuators. The proposed system may be implemented in many structural components such as aircraft frames and bridges. This SHM technology may help replace the current time-based maintenance scheme with a condition-based one. The condition-based maintenance scheme relies on the ability to monitor the condition of the system and supply information of damage detection to allow a corrective action to be taken.

Many composite materials and structures are susceptible to defects, which can significantly reduce the strength of structures and may grow to failure. To avoid the catastrophic failure of structures, development of a reliable method of structural health monitoring is one of the most important keys in maintaining the integrity and safety of structures. Dynamic response-based damage detection offers a simple procedure as an alternative to the conventional nondestructive evaluation techniques. However, this technique depends on the quality of measured data for its identification accuracy. In this article, experimental aspects of dynamic response-based damage detection technique on carbon/ epoxy composites are addressed. Smart piezoelectric materials are used as sensors or actuators to acquire the curvature modes of structures. These materials are surface-bonded to the beams. An impulse hammer is used as an actuating source as well. Four types of damage detection algorithms are evaluated for several possible damage configurations with two different excitation sources. The quality of damage identification with the four different detection algorithms is discussed. These experimental damage identification techniques using curvature modes and piezoelectric materials can be effectively used in damage detection and health monitoring of composite structures.

Woven fabric composite structures are applied in a wide range of industrial applications. Composite structures are vulnerable to damage from working in complex conditions and environments, which threatens the safety of the in-service structure. Damage detection based on Lamb waves is one of the most promising structural health monitoring (SHM) techniques for composite materials. In this paper, based on guided Lamb waves, a lightweight deep-learning approach is proposed for identifying damaged regions in woven fabric composite structures. The designed deep neural networks are built using group convolution and depthwise separated convolution, which can reduce the parameters considerably. The input of this model is a multi-channel matrix transformed by a one-dimensional guided wave signal. In addition, channel shuffling is introduced to increase the interaction between features, and a multi-head self-attention module is designed to increase the model’s global modeling capabilities. The relevant experimental results show that the proposed SHM approach can achieve a recognition accuracy of 100% after only eight epochs of training, and the proposed LCANet has only 4.10% of the parameters of contrastive SHM methods, which further validates the effectiveness and reliability of the proposed method.

A hybrid structural health monitoring (SHM) system, consisting of a piezoelectric transducer and fiber optic sensors (FOS) for generating and monitoring Lamb waves, was investigated to determine their potential for damage detection and localization in composite aerospace structures. As part of this study, the proposed hybrid SHM system, together with an in-house developed algorithm, was evaluated to detect and localize two types of damage: a through thickness damage (hole of 2 mm in diameter) and a surface damage (2 mm diameter bore hole with a depth of 0.65 mm) located on the backside of the plate. The experiments were performed using an aircraft representative composite plate skin, manufactured from carbon fiber reinforced polymer (CFRP).

Industrialized countries have huge investments in civil infrastructure there is need for the proper structural audits for this Infrastructures. Structural health monitoring approach has come into action which is performed using Smart Sensors, Piezoelectric sensors and accelerometers are used for the environmental and some parameters of Structures, which results into detection of damages in structures. Data acquisition algorithms are used for transmission of data and calculate the overall statistics from the network, it requires less computational power. By this approach damage detection observation can be done from remote places. The parameters are measure vibration, temperature and moisture. It also identifies the stress, strain, pressure and load of a wall. This approach is mainly done using wireless sensor network. The network is simulated for the processing of data. The actual data is measure by the sensor which is calibrated in units. At the end structural heath monitoring will be useful in detecting all the necessary damage detection, to calculate the life of building and to go for efficient algorithms.

Carbon fiber composite laminates, consisting of highly anisotropic ply layers, are widely used in aerospace structures due to their good strength to weight ratio. However, due to poor interlaminar strength, composite components are prone to barely visible impact damage during aircraft operation. Sparse array guided wave imaging, using a network of distributed sensors, is an important Structural Health Monitoring (SHM) tool for the detection and localization of in-service damage in composite structures. However, the anisotropy of composite laminates influences guided wave scattering, impacting imaging performance. Defect characterization can be improved by considering the scattering characteristics of various damage types for the sparse array signal processing. Guided wave scattering (A0 Lamb wave mode) was investigated around an artificial insert delamination in a quasi-isotropic carbon fiber reinforced polymer (CFRP) panel. Permanent magnets, mounted on an undamaged region of the plate, were also used as scattering targets and compared to the delamination case. Full 3D Finite Element (FE) simulations were performed for both the delamination and magnet cases and compared to wavefield data obtained from non-contact laser measurements. Good agreement was found between the experimental measurements and simulations. Scattered guided wave amplitudes around each damage type show strong directional dependency with energy focusing along the fiber directions of the outer ply layers of the laminate. Distinct scattering behavior was observed for each damage type. A forward scattered wave was observed for the delamination, whereas the magnet blocked forward wave transmission. Implications of anisotropy and angular scattering on sparse array SHM of different defect types are discussed.

In this paper, we discuss the dynamics of beams with multiple delaminations. The objective of the study is to use the dynamic response of the delaminated beams in health monitoring of composite structures. As a first step, we present experimental results on the vibrations of a cantilever beam with multiple delaminations. These experiments are conducted by exciting the beam with piezoelectric actuators. The response is detected by using a high-speed video camera to study the existence of delamination opening modes in a beam with multiple delaminations. Then, an analysis of natural frequencies and mode shapes, for a delaminated beam, is presented by using analytical techniques. The measured dynamic responses of the beam with multiple delaminations are also presented. The experimentally detected nonlinear response is discussed. Introduction Delaminations or interlayer cracks and impact damages are typical defects observed in composite structures. The presence of these defects changes the dynamic characteristics of the structure . Some of the specific changes in the observed dynamic characteristics include changes in natural frequencies, changes in the mode shapes and changes in damping ratios. These changes can be used to identify the existence, location and magnitude of a delamination or an impact damage, before they can grow to their critical sizes. Studies, to date, are concerned with the dynamics of beams and plates with a single delamination. In this paper, we specifically discuss the structural dynamics of a beam with multiple delaminations. This information can be used to develop health-monitoring techniques for composite beams with multiple delaminations. In an earlier paper, Luo and Hanagud studied the effects of defects, like saw-cuts, impact damage and delamination, on the structural dynamic characteristics of composite beams. They have shown that perturbations in natural frequencies and modes of a beam, due to defects, can be used for health monitoring of structures. In particular, it has been shown that an integral equation that considers perturbations in curvature modes and natural frequencies can be very effectively used to detect local defects. To distinguish delaminations from other types of monitored (identified) defects Luo and Hanagud have discussed nonlinear effects like superharmonic response in the dynamic response of a harmonically excited delaminated beam. They considered only a single delamination. In this paper we study beams with multiple delaminations. More specifically, we discuss dynamic response and the changes in natural frequencies, mode shapes due to multiple delaminations in a composite beam. One of the earliest models for vibration analysis of composite beams with delaminations was proposed by Ramkumar et al. This model simply used four Timoshenko beams connected at the delamination edges to model a composite beam with one throughwidth delamination. The predicted frequencies, based on this model, were consistently lower than the results of experimental measurements. Wang et al. improved the analytical solution by including coupling between flexural and axial vibrations of the delaminated sublaminates. Using an isotropic beam with splits and the classical beam model, they found that the calculated natural frequencies were closer to experimental results. With similar considerations, Nagesh Gummadi and Hanagud formulated a finite element solution for arbitrary composite beams. In the finite element models, they considered a classical composite beam model as well as the beam model with high order shear deformations. Mujumdar and Suryanarayan have proposed a model which imposed a constraint between the delaminated sublaminates to force them to have the same flexural displacement. This model was unable to * Ph.D. Student, School of Aerospace Engineering † Professor, School of Aerospace Engineering, AIAA Member Copyright © 1999 The American Institute of Aeronautics and Astronautics Inc. All rights reserved

Fiber reinforced composite plate‐like structures have been used to achieve substantial reductions in the structural weight of both military and commercial aircrafts. For large area and layered structures, damage detection using any conventional testing methods is time consuming. Structural Health Monitoring (SHM) of such structures is seen as a new paradigm that will reduce maintenance costs and increase safety. The aim of the technology is to provide an early indication of physical damage. The early warning provided by an SHM system can then be used to define remedial strategies before the structural damage leads to failure. This paper describes the development and successful demonstration of a SHM system using Smart Flexible Sensor Patch (FSP) that has a built‐in network of Piezoelectric Wafer Active Sensors (PWAS) embedded on a thin film of dielectric material. These PWAS are arranged such that conventional cross‐hole tomography (CHT) as well as modified cross‐hole tomography (MCHT) can be carried out using Lamb waves. Using MCHT, the lateral extent of the damage for barely visible low‐velocity impact damages (BVID) on Composite structures like wing and aileron are were imaged. The conventional CHT was deployed in a region of large aspect‐ratio such as stiffeners. It was observed that disbonds of stiffener in Eleven and other structures may be effectively monitored by this method.

In this paper, the assessments of structural health monitoring (SHM) for metallic structures are presented. Tests were conducted on three specimens for fatigue crack testing and damage index measurements. In each specimen, a transducer array of six Stanford Multiactuator-Receiver Transduction (SMART) Layers, each of which contains a piezoelectric transducer, was mounted near the fatigue crack. The Lamb wave was driven by one SMART Layer and received by another. The transducer array generated nine forward and nine backward propagating paths. The damage index defined in the first arrival window (FAW) was obtained for each path. In this work, we propose an averaging process to obtain average damage index from the transducer array. The Lamb waves with various driving frequencies were tested to conduct the performance of the damage monitoring. The results show that the plot of the average damage index versus the actual crack length reveals a narrow band, indicating a small standard deviation of the measurement data. The data of numerous crack lengths and Lamb wave paths are processed statistically to determine the probability of detection (POD) of this damage detection method. It was found that the Lamb wave with the driving frequency of f=450 kHz performed best in the crack monitoring. By using an threshold damage index DIth=0.01, the detectable crack sizes a50/50, a90/50, and a90/95 for the case of f=450 kHz are 4.83, 5.79, and 5.92 mm, respectively. Based on the proposed approach, the relations between the damage index and actual crack length and the POD curves can be applicable to a real structure with the same geometry.

Flexible and composite structures often develop hidden damages, e.g. cracks or delamination between laminae or phases. Such events could be sensed through embedded structural health monitoring (SHM) systems, but past experimental studies in the literature proved that embedding sensors for SHM purposes may decrease the reliability of the structure, as the sensor acts as an inclusion. In former studies, the authors proposed to adopt a surface-mounted SHM approach based on inertial MEMS (micro electro-mechanical systems) sensors, which has two advantages: it is low cost and also it avoids the afore-mentioned detrimental effects on the endurance limit state of the structure. However, the low accuracy of the MEMS sensors and the type of response that they can measure may hinder an effective monitoring of the structural state; this can be overcome through redundancy and an efficient sensor placement. In this article, an automated approach is discussed for obtaining the optimal topology of a sparse MEMS sensor network. In this regard, the scenarios are assumed unknown in terms of extent and location of stiffness degradation due to damage. The optimal sensor locations are obtained via maximization of the global sensitivity of the measurements to damage. The method can be also implemented in a multi-scale framework, to efficiently handle (micro) sensors, (meso) damaged regions and (macro) structural components of (by far) different sizes. Data related to composite specimens and panels are discussed, with the aim of assessing the identifiability of damage through self-adapting theoretical/numerical (digital) twins of the monitored structures.

Structural health monitoring (SHM) and damage detection have attracted great interest in recent decades, in meeting the challenges of assessing the safety condition of large-scale civil structures. By wiring remote sensors directly to a centralized data acquisition system, traditional structural health monitoring systems are usually costly and the installation is time-consuming. Recent advances in wireless sensing technology have made it feasible for structural health monitoring; furthermore, the computational core in a wireless sensing unit offers onboard data interrogation. In addition to wireless sensing, the authors have recently developed a mobile sensing system for providing high spatial resolution and flexible sensor deployment in structural health monitoring. In this study, transmissibility function analysis is embedded in the mobile sensing node to perform onboard and in-network structural damage detection. The system implementation is validated using a laboratory 2D steel portal frame. Simulated damage is applied to the frame structure, and the damage is successfully identified by two mobile sensing nodes that autonomously navigate through the structure.