Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Review on Strain Monitoring of Aircraft Using Optical Fibre Sensor

Structural health monitoring of aircraft assures safety, integrity and reduces cost-related concerns by reducing the number of times maintenance is required. Under aerodynamic loading, aircraft is subjected to strain, in turn causing damage and breakdown. This paper presents a review of experimental works, which focuses on monitoring strain of various parts of aircraft using optical fibre sensors. In addition, this paper presents a discussion and review on different types of optical fibre sensors used for structural health monitoring (SHM) of aircraft. However, the focus of this paper is on fibre bragg gratings (FBGs) for strain monitoring.  Here, FBGs are discussed in detail because they have proved to be most viable and assuring technology in this field. In most cases of strain monitoring, load conditioning and management employs finite element method (FEM). However, more effort is still required in finding the accurate positions in real time where the sensors can be placed in the structure and responds under complex deformation

Use of fibre-optic (FBG) sensors in the structural health monitoring of a battlefield helicopter rotor blade

As the use of fibre composite materials and components become more widely accepted, so does the inherent risks of sudden and possibly catastrophic failure. This creates a distinct need for sound, structural health monitoring (SHM) methods to be employed to both warn of, and prevent impending failure. For aviation related fibre composite components this is of paramount importance; however, a secondary but equally important consideration is that of service life. Any extension of a components service life is of great financial and operational benefit to both civil and military operators of aviation assets. This is particularly true of military helicopters which use fibre reinforced composite rotor blades, such as the Boeing CH-47 Chinook. Experience has shown that these highly exposed components are frequently damaged during combat operations and rapidly come into short supply as a result of often minor damage. This minor damage may necessitate blade replacement prior to the aircraft being authorised for further flight. This project seeks to use finite element analysis (FEA) methods and physical blade testing via the use of optical fibre Bragg grating (FBG) sensors to evaluate typical battlefield, ballistic penetration damage by small arms fire projectiles to a composite Boeing CH-47 Chinook rotor blade test section. Abaqus FEA software was used to create both a flat plate simulation and a Boeing-Vertol VR-7 Aerofoil assembly model. Physical testing was conducted on a blade by applying incremental load increases as well as incremental levels of simulated damage. Both FBG and strain gauge systems were used to assess the micro-strain levels at predetermined, critical locations. The data response from these systems was then validated as far as possible by FEA methods, with correlations able to be drawn between the strain systems and the FEA results. This research demonstrated that the use of FBG sensors on the surface of a complex composite component is an appropriate method for determining strains in the vicinity of damage, which was validated in specific areas by FEA methods. It also concluded that FEA methods alone are very difficult to use in a practical sense when assessing the significant size, type and random nature of ballistic damage to a complex composite structure. With further future development the possibility of the embedding FBG sensor systems at manufacture into a composite rotor blade for real time SHM or lifing assessment exists. This may in turn lead to enhanced service life management of such components by moving to an on-condition based lifing approach

Life cycle monitoring of composite aircraft components with structural health monitoring technologies

Life cycle monitoring could considerably improve the economy and sustainability of composite aircraft components. Knowledge about the quality of a component and its structural health allows thorough exploitation of it’s useful life and offers opportunity for optimization. Current life cycle monitoring efforts can be split in two main fields 1) process monitoring and 2) structural health monitoring with little overlap between them. This work aims to propose an integral monitoring approach, enabling entire life monitoring with the same sensor. First, the state of the art of both composite manufacturing as well as structural health monitoring technologies is presented. Piezoelectric sensors have been ruled out for further investigation due their brittleness. Fiber optical sensors and electrical property-based methods are further investigated. Distributed fiber optic sensors have been successfully used in composite manufacturing trials. Two processes were demonstrated: vacuum assisted resin transfer molding and resin infusion under flexible tooling. Due to their flexibility, optical fibers can survive the loads occurring during manufacturing and deliver valuable insights. It is shown for the first time numerically and experimentally, that fiber bed compaction levels and volume fractions can be calculated from the optical frequency shift measured by the optical fiber sensors. The same sensor was used for subsequent structural health monitoring. This proves that the gap between process monitoring and structural health monitoring can be closed with mutual benefits in both areas. The final chapter presents a novel electrical property-based sensing technique. The sensors are highly flexible and manufactured with a robot-based 3D-printing method. They are shown to reliably work as strain sensors and crack detectors. This work presents a thorough investigation of available and novel sensing technologies for process monitoring and structural health monitoring settings. The results obtained could pave the way to more efficient aircraft structures.Open Acces

Fiber Bragg Grating Based Sensors and Systems

This book is a collection of papers that originated as a Special Issue, focused on some recent advances related to fiber Bragg grating-based sensors and systems. Conventionally, this book can be divided into three parts: intelligent systems, new types of sensors, and original interrogators. The intelligent systems presented include evaluation of strain transition properties between cast-in FBGs and cast aluminum during uniaxial straining, multi-point strain measurements on a containment vessel, damage detection methods based on long-gauge FBG for highway bridges, evaluation of a coupled sequential approach for rotorcraft landing simulation, wearable hand modules and real-time tracking algorithms for measuring finger joint angles of different hand sizes, and glaze icing detection of 110 kV composite insulators. New types of sensors are reflected in multi-addressed fiber Bragg structures for microwave–photonic sensor systems, its applications in load-sensing wheel hub bearings, and more complex influence in problems of generation of vortex optical beams based on chiral fiber-optic periodic structures. Original interrogators include research in optical designs with curved detectors for FBG interrogation monitors; demonstration of a filterless, multi-point, and temperature-independent FBG dynamical demodulator using pulse-width modulation; and dual wavelength differential detection of FBG sensors with a pulsed DFB laser

Fiber Optic Sensor Fused Additive Manufacturing

This dissertation research establishes the foundation for converging disciplines to fiber optic sensors and additive manufacturing for smart part fabrication for energy system applications. Through innovation in numerical designs, thorough studies of layer-by-layer additive manufacturing procedures, and innovation in high-temperature fiber optic sensor development, this dissertation presents fiber optic sensor embedding in metals for smart component manufacturing. In this dissertation, standard telecom-grade single-mode optical fibers were metalized by nickel sulfamate electroplating method. Through electroplating process optimization, residual strain of fiber coating induced on optical fiber were controlled to ensure metal integrity of fiber sensors. Using Laser Engineered Net Shaping (LENS) process, metalized fiber sensors were embedded into objects with flat surfaces and curved surfaces to fabricate smart components. Using Rayleigh optical frequency domain reflectometry technology, the embedded fiber optic sensors were used to perform accurate and distributed temperature and strain sensing with 5 mm spatial resolution. Finite element analyses were performed to study additive manufacturing process. Plastic and elastic residual strain distributed incurred by the process were calculated and compared with measurement results obtained by embedded sensors. Both temperature and strain measured by fiber sensors are in excellent agreement with numerical simulations. Using embedded fiber sensor measurement results are cue, various laser processes were applied to further temper properties of metal components. This dissertation explores potentials on using adaptive optical technology to perform rapid and high precision laser shock peening to mitigate residual strain induced by additive manufacturing. Using embedded fiber sensors, laser shock peening induced strain modifications were measured with high spatial resolution to improve properties and accuracy of 3D manufactured metal components against corrosion. Research discussed in this dissertation has advanced both fiber optic sensing technology and additive manufacturing. By incorporating advanced optical sensing technology directly into the component’s design and additive manufacturing processes, this research results in new manufacturing techniques to produce a wide array of smart parts for advanced energy systems. The seamless incorporation of multi-functional fiber optic devices into components and parts common to advanced energy system will enable and facilitate condition-based monitoring of key components and systems of fossil, renewable and nuclear power systems to improve safety and efficiency of fossil-fuel energy power generation

Characterisation of Low Impact Energy Induced Damage in Composite Plates with Embedded Optical Sensors

Fibre reinforced materials are increasingly employed in aerospace, naval and civil structures because of their low weight and high specific strength and stiffness. A major concern is the inherent susceptibility of composite laminates to barely visible damage induced by low velocity impacts. Non-destructive, in-situ inspection techniques are required to continuously control the integrity of such structures. Traditional non-destructive testing methods, like ultrasonic scanning, are time-consuming and require the withdraw from service of the tested part. Vibration-based structural health monitoring methods are reported to be a promising tool to check the structural integrity. In fact, damage leads to a local decrease of the structural stiffness and alters the wave propagation in a laminate. The stiffness modification results in a change of the modal characteristics of the structure. Numerous studies have shown that eigenfrequencies, damping ratios and curvature mode shapes of a laminated composite structure are sensitive to impact induced damage. Inverse numerical-experimental techniques based on modal characteristics have already demonstrated their applicability for the identification of mechanical properties of intact composite laminates. By using an adequate damage model, a similar method may be used for the identification of damage parameters. In this work, a damage identification method based on signals obtained by an integrated sensing system is proposed. Fibre Bragg gratings (FBG), a recent sensor technology, are optical sensors allowing to measure internal strains in composite laminates. This type of sensor can be perfectly integrated in a structure, is maintenance-free and may last for the entire lifetime of a structure. A high rate FBG interrogation system based on intensity modulation is enhanced so that calibrated low-noise strain measurements can be performed with acquisition rates of up to 250 kHz. In this study, the FBG sensors are embedded in carbon fibre reinforced cross-ply plates made of 28 unidirectional plies. The sensors are used to capture the dynamic response of the plate to an impact event and to carry out experimental modal analysis. Moreover, acoustic waves originating from impacts are sensed with a high sensitivity and an acquisition rate of 1 GHz. The experimental results using several instrumented plates demonstrate the efficiency and accuracy of the interrogation system. Monitoring of the structural integrity of the composite plate consists of two stages, first impact localisation and second damage identification. The appearance of an eventual impact is detected by surveying the dynamic response of the FBG sensors and its location is predicted based on waves propagating from the impact to the sensors. The prediction is made via interpolation of a previously determined reference data set produced by non-destructive hammer impacts. The interpolation-based localisation method does neither require the knowledge of the wave propagation velocity nor the exact position of the sensors within the laminate. The prediction accuracy of the localisation method is evaluated with several numerical and experimental validation tests and is shown to be in the order of a few millimetres. The different potential error sources are identified and they are found to be mainly independent on the plate size. Upon the detection and localisation of an impact, an eventual damage is identified using an inverse numerical-experimental optimisation method. A finite element model of the damaged plate is built based on three-dimensional characterisation of the damage pattern using high resolution X-ray computed tomography. The identification method utilises a homogenised damage model with an approximated damage shape and reduced transverse shear moduli. The damage surface and position are identified by minimising the discrepancy between the numerically calculated and experimentally determined eigenfrequency changes using a hybrid iterative and global search algorithm. The initial guess of the damage position required for the optimisation procedure needs to be sufficiently precise. Within this work, it consists of the predicted impact location obtained from the localisation method. The robustness of the algorithm to different initial guesses of the parameters is tested by numerical and experimental examples. The impact localisation and damage identification method is summarised and demonstrated by a comprehensive experiment. Four FBG sensors are employed to detect and localise the impact and to determine the plate's eigenfrequencies. The damage surface is in general underestimated by approximately 20% by the numerical-experimental optimisation algorithm and the distance between the identified and exact damage position corresponds to less than 10% of the damage size

Structural Performance Evaluation of Bridges: Characterizing and Integrating Thermal Response

Bridge monitoring studies indicate that the quasi-static response of a bridge, while dependent on various input forces, is affected predominantly by variations in temperature. In many structures, the quasi-static response can even be approximated as equal to its thermal response. Consequently, interpretation of measurements from quasi-static monitoring requires accounting for the thermal response in measurements. Developing solutions to this challenge, which is critical to relate measurements to decision-making and thereby realize the full potential of SHM for bridge management, is the main focus of this research. This research proposes a data-driven approach referred to as temperature-based measurement interpretation (TB-MI) approach for structural performance evaluation of bridges based on continuous bridge monitoring. The approach characterizes and predicts thermal response of structures by exploiting the relationship between temperature distributions across a bridge and measured bridge response. The TB-MI approach has two components - (i) a regression-based thermal response prediction (RBTRP) methodology and (ii) an anomaly detection methodology. The RBTRP methodology generates models to predict real-time structural response from distributed temperature measurements. The anomaly detection methodology analyses prediction error signals, which are the differences between predicted and real-time response to detect the onset of anomaly events. In order to generate realistic data-sets for evaluating the proposed TB-MI approach, this research has built a small-scale truss structure in the laboratory as a test-bed. The truss is subject to accelerated diurnal temperature cycles using a system of heating lamps. Various damage scenarios are also simulated on this structure. This research further investigates if the underlying concept of using distributed temperature measurements to predict thermal response can be implemented using physics-based models. The case study of Cleddau Bridge is considered. This research also extends the general concept of predicting bridge response from knowledge of input loads to predict structural response due to traffic loads. Starting from the TB-MI approach, it creates an integrated approach for analyzing measured response due to both thermal and vehicular loads. The proposed approaches are evaluated on measurement time-histories from a number of case studies including numerical models, laboratory-scale truss and full-scale bridges. Results illustrate that the approaches accurately predicts thermal response, and that anomaly events are detectable using signal processing techniques such as signal subtraction method and cointegration. The study demonstrates that the proposed TB-MI approach is applicable for interpreting measurements from full-scale bridges, and can be integrated within a measurement interpretation platform for continuous bridge monitoring