Health Monitoring Of Aerospace Structures Research Articles

Additive Manufacturing of Flexible Strain Sensors Based on Smart Composites for Structural Health Monitoring with High Accuracy and Fidelity

This research introduces a novel flexible spherical carbon nanoparticle‐based polyurethane conductive ink, which is employed to fabricate strain sensors by a lab‐developed direct ink writing/3D printing system. Rheological tests are performed, and sensors are pasted on glass fiber‐reinforced plastic specimens to study strain gauge behaviors under quasistatic loading. The gauge factor in tensile loading is found to be layer width dependent as decreasing the strain gauge's layer width increases the sensitivity of the strain sensor. A maximum gauge factor of 34 is achieved using a layer width of 0.2 mm, 17 times greater than commercially available metal foil strain gauges. The four‐point bend tests are performed under tension/compression to assess the sensor's strain‐sensing and damage‐monitoring ability. Fractographic analysis is coupled with strain monitoring using the developed sensor, which confirms that the failure progresses from intralaminar failure modes such as ply splitting in tension. At the same time, delamination leads to kink band formation under compression and the eventual failure of load‐bearing fibers. The developed sensor exhibits repeatable performance with low hysteresis and integrated nonlinearity errors for up to 1000 cycles. The developed sensors could be effectively employed for online in situ structural health monitoring of aerospace structures under static and dynamic loading.

Cosmic time calibrator for wireless sensor network

Time synchronization of sensor nodes is critical for optimal operation of wireless sensor networks (WSNs). Since clocks incorporated into each node tend to drift, recurrent corrections are required. Most of these correction schemes involve clients periodically receive RF timing signals from a time server. However, an RF-based scheme is prone to glitches or failure unless operating in a region with almost entirely unobstructed space; hence it only operates well in a limited range of environments. For example, GPS requires open-sky environments. Moreover, the precision of land-based RF schemes is limited to a few micro seconds. In this work, we report on a more versatile and new type of recurrent clock resynchronization scheme called cosmic time calibrator (CTC) and its development and testing. CTC utilizes cosmic-ray muon signals instead of RF signals. Muons are penetrative and continuously precipitating onto the Earth’s surface, and they tend to travel linearly through encountered matter at approximately the speed of light in vacuum. Therefore, muons themselves can periodically transfer the precise timing information from node to node; hence, the performance of the inter-nodal communication device such as Wi-Fi or Bluetooth is minimized/unnecessary for an online/offline WSN analysis. The experimental results have indicated that a resynchronization frequency and precision of 60 Hz and ± 4.3 ns (S.D.) can be achieved. Modelling work of the WSN-based structural health monitoring of aerospace structures has shown that CTC can contribute to the development of new critical and useful applications of WSN in a wider range of environments.

In-situ integration and performance verification of large-scale PZT network for composite aerospace structure

Piezoelectric transducer (PZT) based structural health monitoring (SHM) technology has been proved to be effective in increasing safety and reliability of composite aircraft structures. However, the attachment of PZT network to the host structure is considered as a weak link when facing the long term durability requirement of aerospace SHM, which should be overcome for aerospace SHM. In this paper, a surface-mounted co-curing method is creatively proposed to realize in-situ integration of large-scale PZT network and composite structure. By jointly controlling curing temperature and pressure, the proposed method can realize integration of large-scale PZT network and structural surface with high reliability and performance consistency. Compared with the conventional integration methods, the proposed method does not affect the manufacturing process or reduce the mechanical property of structure, and can be easily implemented whenever the host structure is available. To evaluate the effectiveness of the proposed integration method, a large-scale PZT network with an overall dimension of 1100 mm × 600 mm is integrated with a carbon fiber composite panel of wing box. The integration caused influence on functional integrity is first assessed by performing electro-mechanical impedance based theoretical analysis and experimental investigation. Then guided wave signals of the integrated large-scale PZT network are also acquired and analyzed, which proves the good signal repeatability and consistency of the network. At last, the SHM performance of the network is verified by conducting impact damages on the composite panel and performing damage monitoring, experimental results show that accurate monitoring is realized.

Fatigue Performance of Type I and Type II Fibre Bragg Gratings Fabricated by Femtosecond Laser Inscription through the Coating.

Strain sensing technology using fibre Bragg grating (FBG) sensors is an attractive capability for aerospace structural health monitoring (SHM) and assessment because they offer resistance to harsh environments, low maintenance, and potential for high density and high strain sensing. The development of FBG inscription techniques through the fibre polymer coating using infrared (IR) lasers has overcome the mechanical weaknesses introduced by removal of the fibre coating, which is typically required for conventional UV laser inscription of FBGs. Type I and Type II femtosecond gratings are fabricated using through-coating inscription techniques, but the higher laser energy used for Type II gratings damages the glass fibre core, impacting mechanical performance. This paper investigates the fatigue performance of Type I and Type II through-coating FBG sensors with different fibre geometries and photosensitisation approaches to evaluate their overall reliability and durability, with a view to assess their performance for potential use in civil and defence SHM applications. The fatigue performance of FBG sensors was assessed under high-strain and high-frequency mechanical loading conditions by using a custom-designed electro-dynamically actuated loading assembly. In addition, pre- and post-fatigue microscopic analyses and high-resolution reflection spectrum characterisation were conducted to investigate the failure regions of the fibres and the effect of fatigue loading on reflection spectrum features. As expected, Type I gratings had a significantly higher fatigue life compared to Type II gratings. However, Type II gratings performed significantly better than conventional UV laser-inscribed FBGs and electrical foil strain gauges. Type II gratings withstand higher temperatures, and are therefore more suitable for application in harsh environments.

Health Monitoring of Aerospace Structures Utilizing Novel Health Indicators Extracted from Complex Strain and Acoustic Emission Data.

The development of health indicators (HI) of diagnostic and prognostic potential from generally uninformative raw sensor data is both a challenge and an essential feature for data-driven diagnostics and prognostics of composite structures. In this study, new damage-sensitive features, developed from strains acquired with Fiber Bragg Grating (FBG) and acoustic emission (AE) data, were investigated for their suitability as HIs. Two original fatigue test campaigns (constant and variable amplitude) were conducted on single-stringer composite panels using appropriate sensors. After an initial damage introduction in the form of either impact damage or artificial disbond, the panels were subjected to constant and variable amplitude compression–compression fatigue tests. Strain sensing using FBGs and AE was employed to monitor the damage growth, which was further verified by phased array ultrasound. Several FBGs were incorporated in special SMARTapesTM, which were bonded along the stiffener’s feet to measure the strain field, whereas the AE sensors were strategically placed on the panels’ skin to record the acoustic emission activity. HIs were developed from FBG and AE raw data with promising behaviors for health monitoring of composite structures during service. A correlation with actual damage was attempted by leveraging the measurements from a phased array camera at several time instances throughout the experiments. The developed HIs displayed highly monotonic behaviors while damage accumulated on the composite panel, with moderate prognosability.

Need for Aerospace Structural Health Monitoring

Aircraft accidents involving catastrophic fatigue failure have the potential for significant loss of life. The aim of this research was to investigate trends in aircraft fatigue failure accidents to inform aerospace Structural Health Monitoring (SHM) system Research and Development (R&D). The research involved collecting 139 aircraft fatigue failure accident reports from the Aviation Safety Network database, which were coded using a directed content analysis. The trends and features of the categorical data were then explored using an ex-post facto study. The results showed that fatigue failure accidents have increased at a rate of (3.4 ± 0.6)×10-2 per year since the 1920’s. Over the period of the study there were 2098 fatalities in 57 fatal accidents, giving (15.1 ± 1.6) fatalities per accident and a fatal accident percentage of (45 ± 10)%. The data indicates that engine failures combined with smaller aircraft and operators should be the focus of SHM R&D. While there is a desire to further improve safety for large transport category aircraft, results indicate that smaller aircraft and operators have seen a relative increase in fatigue failure accidents, and hence are also in need of SHM systems. Engine and undercarriage systems have the greatest number of fatigue failure accidents associated with them, suggesting these should be the focus of SHM R&D.

Accurate self‐damage detection by electrically conductive epoxy/graphene nanocomposite film

AbstractDetecting and locating accurately structure damages at an early stage is essential to minimization of catastrophic disasters, prevention of fatalities and provision of cost‐effective maintenance. We herein report a facile approach to detect structure damages and to accurately identify their locations by using an electrically conductive epoxy/graphene nanocomposite film. A percolation threshold of electrical conductivity was observed at 0.58 vol% of graphene platelets (GnPs, ~3 nm in thickness and ~15 μm in length); electrical conductivity of 3.3 S/cm was obtained at 9.00 vol% of GnPs. The epoxy/GnP composite film containing 9.00 vol% of GnPs was employed as an array of electrically conductive paths in horizontal and vertical directions to detect and locate structure's damages. Thermal stability and temperature coefficient of the composite film were studied. Relative resistance change due to temperature effect was fitted into an exponential function, which showed strong correlation with the temperature change. This implies that an algorithm can be developed to compensate drift errors in resistance measurement due to temperature variation. With the help of Internet of Things, our self‐sensing epoxy/graphene nanocomposite films have great potential for smart aerospace structural health monitoring.

Porosity Modulated High-Performance Piezoelectric Nanogenerator Based on Organic/Inorganic Nanomaterials for Self-Powered Structural Health Monitoring.

In the modern era, structural health monitoring (SHM) is critically important and indispensable in the aerospace industry as an effective measure to enhance the safety and consistency of aircraft structures by deploying a reliable sensor network. The deployment of built-in sensor networks enables uninterrupted structural integrity monitoring of an aircraft, providing crucial information on operation condition, deformation, and potential damage to the structure. Sustainable and durable piezoelectric nanogenerators (PENGs) with good flexibility, high performance, and superior reliability are promising candidates for powering wireless sensor networks, particularly for aerospace SHM applications. This research demonstrates a self-powered wireless sensing system based on a porous polyvinylidene fluoride (PVDF)-based PENG, which is prominently anticipated for developing auto-operated sensor networks. Our reported porous PVDF film is made from a flexible piezoelectric polymer (PVDF) and inorganic zinc oxide (ZnO) nanoparticles. The fabricated porous PVDF-based PENG demonstrates ∼11 times and ∼8 times enhancement of output current and voltage, respectively, compared to a pure PVDF-based PENG. The porous PVDF-based PENG can produce a peak-to-peak short-circuit current of 22 μA, a peak-to-peak open-circuit voltage of 84.5 V, a peak output power of 0.46 mW , and a peak output power density of 41.02 μW/cm2 (P/A). By harnessing energy from minute vibrations, the fabricated porous PVDF-based PENG device (area of A = 11.33 cm2) can generate sufficient electrical energy to power up a customized wireless sensing and communication unit and transfer sensor data every ∼4 min. The PENG can generate sufficient electrical energy from an automobile car vibration, which reflects the scenario of potential real-life SHM systems. We anticipate that this high-performance porous PVDF-based PENG can act as a reliable power source for the sensor networks in aircraft, which minimizes potential safety risks.

The investigation on structural health monitoring of aerospace structures via piezoelectric aeroelastic energy harvesting

From the past few decades, the aerospace industry is using composite materials having low weight to strength ratio, and the aerospace vehicles are subjected to adverse and harsh conditions, during the operational time. Furthermore, they require a continuous power supply to operate the wireless sensors. So, in the aerospace industry, energy harvesting and structural health monitoring (SHM) are the critical tasks. Piezoelectric (PZT) materials can play a vital role in the field of energy harvesting and structural health monitoring of the structures at the same time, which makes them more convenient to use in aerospace applications. In this research paper, the fluid-structure interaction (FSI) based system is analyzed, the PZT harvester is subjected to the axial airflow for energy harvesting. The campaign is carried out to predict the energy harvesting capability of the aeroelastic harvester via PZT transduction. The parameters influencing the energy harvesting mechanism i.e., airflow and external resistance are analyzed. The numerical bifurcation diagram is also constructed to understand the plunge amplitude of the harvester at the different values of airflow. Moreover, the SHM of the host structure (aeroelastic harvester) is also analyzed via the admittance method at the same time. The results showed that the magnitude of energy harvesting and quality of SHM for the harvester attached with the rectangular PZT patch is better than with the circular PZT patch.

The Industry Internet of Things (IIoT) as a Methodology for Autonomous Diagnostics in Aerospace Structural Health Monitoring

Structural Health Monitoring (SHM), defined as the process that involves sensing, computing, and decision making to assess the integrity of infrastructure, has been plagued by data management challenges. The Industrial Internet of Things (IIoT), a subset of Internet of Things (IoT), provides a way to decisively address SHM’s big data problem and provide a framework for autonomous processing. The key focus of IIoT is operational efficiency and cost optimization. The purpose, therefore, of the IIoT approach in this investigation is to develop a framework that connects nondestructive evaluation sensor data with real-time processing algorithms on an IoT hardware/software system to provide diagnostic capabilities for efficient data processing related to SHM. Specifically, the proposed IIoT approach is comprised of three components: the Cloud, the Fog, and the Edge. The Cloud is used to store historical data as well as to perform demanding computations such as off-line machine learning. The Fog is the hardware that performs real-time diagnostics using information received both from sensing and the Cloud. The Edge is the bottom level hardware that records data at the sensor level. In this investigation, an application of this approach to evaluate the state of health of an aerospace grade composite material at laboratory conditions is presented. The key link that limits human intervention in data processing is the implemented database management approach which is the particular focus of this manuscript. Specifically, a NoSQL database is implemented to provide live data transfer from the Edge to both the Fog and Cloud. Through this database, the algorithms used are capable to execute filtering by classification at the Fog level, as live data is recorded. The processed data is automatically sent to the Cloud for further operations such as visualization. The system integration with three layers provides an opportunity to create a paradigm for intelligent real-time data quality management.

Composite wing box deformed-shape reconstruction based on measured strains: Optimization and comparison of existing approaches

The reconstruction of the displacement field of a structure (shape sensing) has become crucial for the Structural Health Monitoring of aerospace structures and for the progress of the recently developing morphing structures. As a consequence, shape sensing techniques based on discrete surface strains measurements have seen a consistent expansion in the last few years. In this paper, the three main shape sensing methods, the Modal Method, the Ko's displacements theory and the inverse Finite Element Method, are presented. The most recent and also novel improvements are discussed and added to the methods' formulations. Then, the three methods are numerically applied to a complex aerospace structure such as that of a composite wing box experiencing bending and twisting deformations. For the first time, a detailed investigation on the optimal strain sensors configuration is performed for all the three techniques simultaneously. Finally, the methods' performances, in terms of accuracy of the reconstruction and of number of required sensors, are compared. The three methods show different characteristics that make them suitable for different applications, depending on the level of accuracy and the number of strain information required. The iFEM is proven to be the more accurate but the more demanding in terms of required sensors; the Ko's displacement theory is capable of giving a rough estimation of the displacement field, but requires a small amount of sensors; the Modal Method represents a trade-off between the other two in terms of accuracy and number of sensors required.

Design and development of a heatsink for thermo-electric power harvesting in aerospace applications

In recent years, the growing interest of aerospace companies in wireless structural health monitoring (SHM) systems has led to the research of new energy efficient sources and power harvesting solutions. Among available environmental power sources, temperature gradients originated at different locations of the aircraft can be used by thermo-electric generators (TEGs) to create electrical voltage. TEGs are lightweight, provide high-energy conversion and do not contain movable parts. Thermal diffusion systems, commonly known as heatsinks, can be combined with TEGs to enhance their performance by increasing heat dissipation from a high temperature surface to the ambient air. This paper focused on the enhancement of TEG performance by developing an air-cooled heatsink for low-power wireless SHM applications. The design, manufacturing and testing of the proposed thermal diffusion system was investigated by evaluating the increase of the temperature gradient between the opposite surfaces of a commercial TEG element. The thermal performance of the heatsink was assessed with numerical finite element thermal simulations and validated with experimental tests. Experimental results revealed that the proposed thermal diffusion system provided higher temperature differences and, therefore, higher output power in comparison with traditional cylindrical pin-fin heatsinks. A hybrid heat diffusion system composed by copper heatsinks and highly oriented pyrolytic graphite layers was also here proposed in order to allow TEG reaching wireless SHM operative power requirements of tens of mW and, at the same time, adapt the assembly to the complexity of aerospace SHM arrangements. Experimental results revealed that the proposed heatsink-TEG arrangement was able to generate an output power over 25 mW.

Temperature Effects on Electromechanical Response of Deposited Piezoelectric Sensors Used in Structural Health Monitoring of Aerospace Structures

Turbomachine components used in aerospace and power plant applications preferably require continuous structural health monitoring at various temperatures. The structural health of pristine and damaged superalloy compressor blades of a gas turbine engine was monitored using real electro-mechanical impedance of deposited thick film piezoelectric transducers at 20 and 200 °C. IVIUM impedance analyzer was implemented in laboratory conditions for damage detection in superalloy blades, while a custom-architected frequency-domain transceiver circuit was used for semi-field circumstances. Recorded electromechanical impedance signals at 20 and 200 °C acquired from two piezoelectric wafer active sensors bonded to an aluminum plate, near and far from the damage, were initially utilized for accuracy and reliability verification of the transceiver at temperatures >20 °C. Damage formation in both the aluminum plate and blades showed a peak shift in the swept frequency along with an increase in the amplitude and number of impedance peaks. The thermal energy at 200 °C, on the other hand, enforces a further subsequent peak shift in the impedance signal to pristine and damaged parts such that the anti-resonance frequency keeps reducing as the temperature increases. The results obtained from the impedance signals of both piezoelectric wafers and piezo-films, revealed that increasing the temperature somewhat decreased the real impedance amplitude and the number of anti-resonance peaks, which is due to an increase in permittivity and capacitance of piezo-sensors. A trend is also presented for artificial intelligence training purposes to distinguish the effect of the temperature versus damage formation in sample turbine compressor blades. Implementation of such a monitoring system provides a distinct advantage to enhance the safety and functionality of critical aerospace components working at high temperatures subjected to crack, wear, hot-corrosion and erosion.

Impact Localization and Severity Estimation on Composite Structure Using Fiber Bragg Grating Sensors by Least Square Support Vector Regression

Low-velocity impact (LVI) events in carbon fiber reinforced plastic (CFRP) structures are a major concern as they result in barely visible impact damage which can reduce the strength and stiffness of impacted structure. Detection of such impact events in terms of location and severity will be a significant milestone for aerospace structural health monitoring applications. This can result in well-targeted inspection programs thereby reducing the time and cost of periodic inspections. One of the easy and efficient ways of getting the impact response of a structure is through strain measurement. LVI event monitoring using fiber Bragg grating sensors has evolved as an attractive choice in recent years along with various soft computing algorithms and advanced signal processing techniques. Machine learning techniques such as artificial neural networks and support vector machine are widely used to localize impact events. Getting information regarding the ensuing damage due to LVI event from the strain response is not straight forward as it could involve estimation of intermediate parameters like energy/force of impact, which are further related with probable damage size. This paper demonstrates least square support vector regression-based algorithm to localize impact event in terms of $X$ - and $Y$ -coordinates and its energy on a CFRP plate-like structure and its comparison with other algorithms cited in the literature.

Response of piezoelectric materials on thermomechanical shocking and electrical shocking for aerospace applications

Piezoelectric materials are widely used as smart structure in various aerospace applications as they can generate voltage, store charge and drive microelectronics directly because of its ability to sense, actuate and harvest energy. It is a well known phenomenon in terms of the linear electromechanical interaction between mechanical and electrical state. It is actively used in aerospace structural health monitoring, due to the high stiffness and drive capacity depending on the voltage, widespread mechanical properties and their interactions. In this research work Barium Titanate ( $$BaTiO_3$$ ) is shocked by variable mechanical loading under different thermal and electrical shocking conditions for behavior analysis. A test rig is constructed on the basis of equivalent circuit method to perform experimentation. The relationship between electrical shocking in terms of frequency and peak to peak voltage at variable thermo-mechanical shocking conditions has been developed and analyzed. The variable frequency shocking represented one of the most important parameter to characterize and design the piezoelectric material, especially when it relates to design of intelligent structures for aerospace industry. Effect of thermo mechanical loading, frequency and resistance to peak to peak voltage is predicted experimentally and numerically. Abaqus is used for numerical simulations. Numerical model constructed for $$BaTiO_3$$ in this research predicts the actual behavior for voltage generation with accuracy of 10%.

Industrial Age non-destructive evaluation to Information Age structural health monitoring

This article was originally presented as a keynote address at the Ninth International Workshop on Structural Health Monitoring with the intent of provoking discussions relating to the transformation of aircraft maintenance practices by exploiting opportunities and benefits offered by Information Age technology and techniques. The US Air Force currently manages its aircraft using a schedule-based maintenance philosophy. This schedule-based approach works well for ensuring aircraft integrity; however, it is very costly, labor-intensive, and reduces aircraft availability. Structural health monitoring systems have the potential to analyze near-real-time and historical weapon systems data to provide a predictive maintenance capability. However, much aerospace structural health monitoring research has focused on in situ structural inspection techniques instead of structural monitoring. Structural inspections typically entail examining key locations of an airframe for material degradation or flaws. These examinations usually occur at predefined time intervals. As such, each inspection is considered an independent evaluation. Conversely, structural monitoring involves continuous condition surveillance of an airframe over an extended period of time. Structural monitoring uses past conditions and expected future conditions for producing a comprehensive understanding of the current health state. A new architecture, Cognitive Architecture for State Exploitation, is introduced as a monitoring technique that combines diagnostic or state (i.e. health) assessments, prognostic assessments, and mission objectives into a common framework to enable goal-based decision making. Results from a laboratory experiment are utilized to demonstrate the application of Cognitive Architecture for State Exploitation and to illustrate the potential to improve effectiveness and efficiency metrics compared to those of the current US Air Force maintenance procedures.

Echelle Diffractive Grating Based Wavelength Interrogator for Potential Aerospace Applications

Operational load monitoring and impact damage detection are the two critical aspects of aerospace structural health monitoring (SHM). Fiber Bragg grating (FBG) sensors have demonstrated great potential in both. But the currently available interrogation systems can only handle one of the two types of SHM capabilities offered by FBG sensors. In addition, the practical implementation of FBG sensor systems in aerospace vehicles requires the interrogator to be small size, light weight, and low-power consuming. In this paper, we present an Echelle diffractive grating (EDG) based interrogation system for FBG sensors, which possesses two operation modes, i.e., the sweeping mode for operational load monitoring and the parked mode for impact damage detection. Experimental results show that this interrogator offers better than 1-pm measurement resolution and 10-pm repeatability. In addition, the interrogation system is very compact and weighs less than 60 g (excluding the electronic controller). It also has the potential to achieve a measurement speed of 300 kHz and be powered by a battery.

Energy Harvesting for Aerospace Structural Health Monitoring Systems

Recent research into damage detection methodologies, embedded sensors, wireless data transmission and energy harvesting in aerospace environments has meant that autonomous structural health monitoring (SHM) systems are becoming a real possibility. The most promising system would utilise wireless sensor nodes that are able to make decisions on damage and communicate this wirelessly to a central base station. Although such a system shows great potential and both passive and active monitoring techniques exist for detecting damage in structures, powering such wireless sensors nodes poses a problem. Two such energy sources that could be harvested in abundance on an aircraft are vibration and thermal gradients. Piezoelectric transducers mounted to the surface of a structure can be utilised to generate power from a dynamic strain whilst thermoelectric generators (TEG) can be used to generate power from thermal gradients. This paper reports on the viability of these two energy sources for powering a wireless SHM system from vibrations ranging from 20 to 400Hz and thermal gradients up to 50°C. Investigations showed that using a single vibrational energy harvester raw power levels of up to 1mW could be generated. Further numerical modelling demonstrated that by optimising the position and orientation of the vibrational harvester greater levels of power could be achieved. However using commercial TEGs average power levels over a flight period between 5 to 30mW could be generated. Both of these energy harvesting techniques show a great potential in powering current wireless SHM systems where depending on the complexity the power requirements range from 1 to 180mW.

Intelligent health monitoring of aerospace composite structures based on dynamic strain measurements

This work presents a study on an intelligent system for structural health monitoring of aerospace structures based on dynamic strain measurements, in order to identify in an exhaustive way the structural state condition. Four fiber Bragg grating (FBG) optical sensors were used for collecting strain data, representing the dynamic response of the structure and the expert system that was developed was based on the collected response data. Multi-sensor data fusion in a feature-level approach was followed. Advanced signal processing and pattern recognition techniques such as discrete wavelet transform (DWT) and support vector machines (SVM) were used in the system. For the current analysis, independent component analysis (ICA) was additionally used for the reduction of feature space. The results showed that SVMs using non-linear kernel is a powerful and promising pattern recognition scheme for damage diagnosis.The system was developed and experimentally validated on a flat stiffened composite panel, representing a section of a typical aeronautical structure. Within the frame of the present work the flat stiffened panel was manufactured using carbon fiber pre-pregs. Damage was simulated by slightly varying the mass of the panel in different zones of the structure by adding lumped masses. The analysis of operational dynamic responses was employed to identify both the damage and its position. Numerical simulation with finite element analysis (FEA) was also used as a support tool.

A strain amplitude-based algorithm for impact localization on composite laminates

Automated detection of damage due to low energy impacts in composite structures is very important for aerospace structural health monitoring applications. Low-velocity impact creates subsurface damage that can significantly reduce the stiffness of a component, yet show barely visible damage. This article proposes a novel methodology for impact localization based on the maximum strain amplitude measured by fiber Bragg grating (FBG) sensors during an impact event. The approach correlates the strain amplitude of each sensor pair to find the location of highest strain corresponding to the impact location. This approach requires minimal knowledge of the structure and fewer number of sensors as opposed to current localization methods. Both simulation and experimental data are used as proof of concept. Since FBG sensors measure strain in only one direction, the effect of sensor orientation on the performance of the algorithm is also studied. The algorithm is tested on graphite/epoxy composite plates and shows good localization results in all impact cases considered.