Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Comparación de sensores PZT y FBG para la detección de despegues en vigas de hormigón armado reforzadas externamente con bandas de CFRP y sometidas a cargas de flexión

The development of monitoring technologies particularly suitable to be used with novel CFRP strengthening techniques has gained great attention in recent years. However, in spite of the high performance of these advanced composite materials in the strengthening and repairing of structures in service, they are usually associated with brittle and sudden failure mainly caused by debonding phenomena, originated either at the CFRP-plate end or at the intermediate areas in the vicinity of flexural cracks in the RC beam. Thus, it is highly recommended for these structures to be monitored in order to ensure their integrity while in service. Specifically, the feasibility of smart sensing technologies such as Fiber Bragg Grating (FBG) sensors and piezo-impedance transducers (PZT) has been studied. To the knowledge of the authors, none serious study has been carried out until now concerned to the topic of damage detection due to debonding in rehabilitated structures with CFRP composites.El desarrollo de tecnologías de monitorización aplicables junto con las novedosas técnicas de refuerzo basadas en materiales CFRP ha recibido una atención creciente los últimos años. Sin embargo, a pesar del alto rendimiento de estos avanzados materiales compuestos en la reparación y refuerzo de estructuras en servicio, están habitualmente asociados a fallos frágiles y repentinos causados principalmente por fenómenos de despegue, originados bien en los extremos del refuerzo, bien en áreas intermedias en las proximidades de grietas de flexión existentes en la viga. Por tanto, es altamente recomendable monitorizar estas soluciones estructurales de cara a garantizar su integridad en servicio. Específicamente, se ha estudiado la viabilidad de sensores inteligentes tales como los sensores Fiber Bragg Grating (FBG) o los transductores piezoeléctricos (PZT). Hasta donde los autores saben, no se han realizado estudios serios hasta la fecha abordando la detección de daño debido al despegue en estructuras reforzadas con compuestos CFRP

Novel Structural Health Monitoring and Damage Detection Approaches for Composite and Metallic Structures

Mechanical durability of the structures should be continuously monitored during their operation. Structural health monitoring (SHM) techniques are typically used for gathering the information which can be used for evaluating the current condition of a structure regarding the existence, location, and severity of the damage. Damage can occur in a structure after long-term operating under service loads or due to incidents. By detection of these defects at the early stages of their growth and nucleation, it would be possible to not only improve the safety of the structure but also reduce the operating costs. The main goal of this dissertation is to develop a reliable and cost-effective SHM system for inspection of composite and metallic structures. The Surface Response to Excitation (SuRE) method is one of the SHM approaches that was developed at the FIU mechatronics lab as an alternative for the electromechanical impedance method to reduce the cost and size of the equipment. In this study, firstly, the performance of the SuRE method was evaluated when the conventional piezoelectric elements and scanning laser vibrometer were used as the contact and non-contact sensors, respectively, for monitoring the presence of loads on the surface. Then, the application of the SuRE method for the characterization vii of the milling operation for identical aluminum plates was investigated. Also, in order to eliminate the need for a priori knowledge of the characteristics of the structure, some advanced signal processing techniques were introduced. In the next step, the heterodyne method was proposed, as a nonlinear baseline free, SHM approach for identification of the debonded region and evaluation of the strength of composite bonds. Finally, the experimental results for both methods were validated via a finite element software. The experimental results for both SuRE and heterodyning method showed that these methods can be considered as promising linear and nonlinear SHM approaches for monitoring the health of composite and metallic structures. In addition, by validating the experimental results using FEM, the path for further improvement of these methods in future researches was paved

The Working Principles of a Multifunctional Bondline with Disbond Stopping and Health Monitoring Features for Composite Structures

In comparison to bolted joints, structural bonds are the desirable joining method for light-weight composite structures. To achieve a broad implementation of this technology in safety critical structures, the issues of structural bonds due to their complex and often unpredictable failure mechanisms have to be overcome. The proposed multifunctional bondline approach aims at solving this by adding two safety mechanisms to structural bondlines. These are a design feature for limiting damages to a certain size and a structural health monitoring system for damage detection. The key question is whether or not the implementation of both safety features without deteriorating the strength in comparison to a healthy conventional bondline is possible. In previous studies on the hybrid bondline, a design feature for damage limitations in bondlines by means of disbond stopping features was already developed. Thus, the approach to evolve the hybrid bondline to a multifunctional one is followed. A thorough analysis of the shear stress and tensile strain distribution within the hybrid bondline demonstrates the feasibility to access the status of the bondline by monitoring either of these quantities. Moreover, the results indicate that it is sufficient to place sensors within the disbond stopping feature only and not throughout the entire bondline. Based on these findings, the three main working principles of the multifunctional are stated. Finally, two initial concepts for a novel multifunctional disbond arrest feature are derived for testing the fundamental hypothesis that the integration of micro sensors into the disbond stopping feature only enables the crack arrest and the health monitoring functions, while reaching the mechanical strength of a conventional healthy epoxy bondline. This work therefore provides the fundamentals for future investigations in the scope of the multifunctional bondline

The durability and functionality assessment of SHM systems in multifunctional composites

The next-generation of composite structures, known as Multifunctional (MF) composites, involves combining various functions, such as structural and electrical, through multiple subsystems blended within a structural housing. The performance of MF composites can be affected by the degradation of any of these subsystems. Structural Health Monitoring Systems (SHMS) have emerged as a feasible method with which to improve the reliability of MF structures. However, the reliability of an SHMS can be affected by erroneous information from its sub-components such as transducers. Improving reliability requires a new capability to delineate failures associated with transducers and the transducer network from actual damage in the structure being monitored

Analysis and Structural Health Monitoring of Composite Plates with Piezoelectric Sensors and Actuators

Structural vibration suppression and health-monitoring have been the focus of intense research over the past decade, and piezoelectric actuators and sensors are particularly well suited to serve in this application. The first part is an analytical investigation into the cylindrical bending vibrations of piezoelectric composite plates. The second part is a fully experimental investigation into various vibration based structural health-monitoring techniques for bolted composites. The analytical solution consists of Fourier basis functions that satisfy the equations of motion and charge equation. The accuracy of the mechanical displacements, electric potential, and stresses are dependent on the number of terms in the series solution. The solution is validated by comparing the natural frequencies with published results for a simply supported piezoelectric plate. Studies were conducted to establish the convergence of the analytical solution. The analytical natural frequencies, electric potential, displacements and stresses compared well with the finite element method for cantilever piezoelectric composite plates. The bolted joint is one of the most common mechanical components in engineering structures. A common mode of failure for bolted joints is self-loosening. The objective of the second part of the thesis is to investigate different vibration based structural health monitoring schemes to actively interrogate a square composite plate to detect loose bolts in composite structures. The plate was excited using a piezoelectric actuator and piezoelectric shear accelerometers and dynamic strain sensors were used to characterize the system dynamics. The investigation began with the sensitivity of the fundamental frequency to changes in the bolt clamping force around the perimeter of the plate. Attempts were also made to quantify damage from changes in the transfer functions. The method of transmittance functions was employed extensively, and it was successful in detecting damage but proved to be unreliable in determining the damage location

Electromechanical Actuators Affected by Multiple Failures: Prognostic Method based on Wavelet Analysis Techniques

Incipient failures of electromechanical actuators (EMA) of primary flight command, especially if related to progressive evolutions, can be identified with the employment of several different approaches. A strong interest is expected by the development of prognostic algorithms capable of identifying precursors of EMA progressive failures: indeed, if the degradation pattern is properly identified, it is possible to trig an early alert, leading to proper maintenance and servomechanism replacement. Given that these algorithms are strictly technology-oriented, they may show great effectiveness for some specific applications, while they could fail for other applications and technologies: therefore, it is necessary to conceive the prognostic method as a function of the considered failures. This work proposes a new prognostic strategy, based on artificial neural networks, able to perform the fault detection and identification of two EMA motor faults (i.e. coil short circuit and rotor static eccentricity). In order to identify a suitable data set able to guarantee an affordable ANN classification, the said failures precursors are properly pre-processed by means of Discrete Wavelet Transform extracting several features: in fact, these wavelets result very effective to detect fault condition, both in time domain and frequency domain, by means of the change in amplitude and shape of its coefficients. A simulation test bench has been developed for the purpose, demonstrating that the method is robust and is able to early identify incoming failures, reducing the possibility of false alarms or non-predicted problems