Literatura académica sobre el tema "Impact localization,structural health monitoring (SHM)"
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Artículos de revistas sobre el tema "Impact localization,structural health monitoring (SHM)"
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Bouzid, Omar Mabrok, Gui Yun Tian, Kanapathippillai Cumanan, and David Moore. "Structural Health Monitoring of Wind Turbine Blades: Acoustic Source Localization Using Wireless Sensor Networks." Journal of Sensors 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/139695.
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Structural health monitoring (SHM) is important for reducing the maintenance and operation cost of safety-critical components and systems in offshore wind turbines. This paper proposes anin situwireless SHM system based on an acoustic emission (AE) technique. By using this technique a number of challenges are introduced due to high sampling rate requirements, limitations in the communication bandwidth, memory space, and power resources. To overcome these challenges, this paper focused on two elements: (1) the use of anin situwireless SHM technique in conjunction with the utilization of low sampling rates; (2) localization of acoustic sources which could emulate impact damage or audible cracks caused by different objects, such as tools, bird strikes, or strong hail, all of which represent abrupt AE events and could affect the structural health of a monitored wind turbine blade. The localization process is performed using features extracted from aliased AE signals based on a developed constraint localization model. To validate the performance of these elements, the proposed system was tested by testing the localization of the emulated AE sources acquired in the field.
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Pang, Zhuo, Mei Yuan, Hao Song, and Zongxia Jiao. "Impact Localization Method for Composite Plate Based on Low Sampling Rate Embedded Fiber Bragg Grating Sensors." Mathematical Problems in Engineering 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/7083295.
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Fiber Bragg Grating (FBG) sensors have been increasingly used in the field of Structural Health Monitoring (SHM) in recent years. In this paper, we proposed an impact localization algorithm based on the Empirical Mode Decomposition (EMD) and Particle Swarm Optimization-Support Vector Machine (PSO-SVM) to achieve better localization accuracy for the FBG-embedded plate. In our method, EMD is used to extract the features of FBG signals, and PSO-SVM is then applied to automatically train a classification model for the impact localization. Meanwhile, an impact monitoring system for the FBG-embedded composites has been established to actually validate our algorithm. Moreover, the relationship between the localization accuracy and the distance from impact to the nearest sensor has also been studied. Results suggest that the localization accuracy keeps increasing and is satisfactory, ranging from 93.89% to 97.14%, on our experimental conditions with the decrease of the distance. This article reports an effective and easy-implementing method for FBG signal processing on SHM systems of the composites.
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Capineri, Lorenzo, and Andrea Bulletti. "Ultrasonic Guided-Waves Sensors and Integrated Structural Health Monitoring Systems for Impact Detection and Localization: A Review." Sensors 21, no. 9 (2021): 2929. http://dx.doi.org/10.3390/s21092929.
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This review article is focused on the analysis of the state of the art of sensors for guided ultrasonic waves for the detection and localization of impacts for structural health monitoring (SHM). The recent developments in sensor technologies are then reported and discussed through the many references in recent scientific literature. The physical phenomena that are related to impact event and the related main physical quantities are then introduced to discuss their importance in the development of the hardware and software components for SHM systems. An important aspect of the article is the description of the different ultrasonic sensor technologies that are currently present in the literature and what advantages and disadvantages they could bring in relation to the various phenomena investigated. In this context, the analysis of the front-end electronics is deepened, the type of data transmission both in terms of wired and wireless technology and of online and offline signal processing. The integration aspects of sensors for the creation of networks with autonomous nodes with the possibility of powering through energy harvesting devices and the embedded processing capacity is also studied. Finally, the emerging sector of processing techniques using deep learning and artificial intelligence concludes the review by indicating the potential for the detection and autonomous characterization of the impacts.
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Qiu, Lei, Shen Fang Yuan, and Tian Xiang Huang. "A Time Reversal Imaging Method without Relying on Transfer Function for Impact and Damage Monitoring of Composite Structures." Applied Mechanics and Materials 330 (June 2013): 542–48. http://dx.doi.org/10.4028/www.scientific.net/amm.330.542.
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Composite structures adopted in aerospace structures have attracted much interest to structural health monitoring (SHM) for localization of impact and damage positions due to their poor impact resistance properties. Propagation mechanism and frequency dispersion characteristics of Lamb wave signals on composite structures are more complicated than that on simple aluminum plates. Recently, much attention has been paid to the research of time reversal focusing method because this method shows a promising advantage to give a focusing image of the structural damage, improve the signal-to-noise ratio and compensate the dispersion of Lamb wave signals. In this paper, aiming at developing a practical method for on-line localization of impact and damage on aircraft composite structures which can take advantage of time reversal focusing and does not rely on the transfer function, a new phase synthesis based time reversal focusing method is proposed. Impact and damage images are given out directly through time reversal focusing based on phase synthesis process of the signals. A SHM demonstration system is built on a composite panel of an aircraft wing box with many bolt holes and stiffeners using the phase synthesis based time reversal focusing method. The demonstration results show that this method can estimate the positions of impact and damage efficiently with a low sensitivity of velocity errors.
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Faisal Haider, Mohammad, Asaad Migot, Md Bhuiyan, and Victor Giurgiutiu. "Experimental Investigation of Impact Localization in Composite Plate Using Newly Developed Imaging Method." Inventions 3, no. 3 (2018): 59. http://dx.doi.org/10.3390/inventions3030059.
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This paper focuses on impact localization of composite structures, which possess more complexity in the guided wave propagation due to the anisotropic behavior of composite materials. In this work, a composite plate was manufactured by using a compression molding process with proper pressure and temperature cycle. Eight layers of woven composite prepreg were used to manufacture the composite plate. A structural health monitoring (SHM) technique was implemented with piezoelectric wafer active sensors (PWAS) to detect and localize the impact on the plate. There were two types of impact event that were considered in this paper (a) low energy impact event (b) high energy impact event. Two clusters of sensors recorded the guided acoustic waves generated from the impact. The acoustic signals were then analyzed using a wavelet transform based time-frequency analysis. The proposed SHM technique successfully detected and localized the impact event on the plate. The experimentally measured impact locations were compared with the actual impact locations. An immersion ultrasonic scanning method was used to visualize the composite plate before and after the impact event. A high frequency 10 MHz 1-inch focused transducer was used to scan the plate in the immersion tank. Scanning results showed that there was no visible manufacturing damage in the composite plate. However, clear impact damage was observed after the high-energy impact event.
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Gao, Qiang, Jun Young Jeon, Gyuhae Park, Yeseul Kong, Yunde Shen, and Jiawei Xiang. "Beamforming using non-equidistant linear array for acoustic source localization." Journal of Intelligent Material Systems and Structures 33, no. 8 (2021): 1028–45. http://dx.doi.org/10.1177/1045389x211039558.
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Beamforming is widely used in structural health monitoring (SHM) systems for impact or damage localization. Beamforming directionality is achieved by the constructive interference of sensor wavefronts, which results in a significant amplification of the measured signal in a particular direction. For beamforming applications, the cost per sensor is typically significant, because of the sensor itself, and the associated electronics. Therefore, in order to minimize the cost of SHM in practice, it is highly desirable to reduce the number of sensors. Beamforming with an array of sensors requires an advanced signal processing technique to detect the direction-of-arrival (DOA). In addition, by deploying more sensors, better detection accuracy can be achieved. In this paper, the non-equidistant linear sensor array is proposed, to obtain lower costs while guaranteeing reasonable detection accuracy. In addition, the proposed sensor deployment scheme is able to reduce the effects of “spatial aliasing,” which phenomenon is typically encountered in the equidistant linear sensor array layout. To validate the performance of the proposed non-equidistant linear array technique in SHM applications, several finite element models (FEM) simulation and experimental investigations are carried out. Different sensor array layouts are also compared to optimize the performance of the non-equidistant linear array.
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Marino-Merlo, Eugenio, Andrea Bulletti, Pietro Giannelli, Marco Calzolai, and Lorenzo Capineri. "Analysis of Errors in the Estimation of Impact Positions in Plate-Like Structure through the Triangulation Formula by Piezoelectric Sensors Monitoring." Sensors 18, no. 10 (2018): 3426. http://dx.doi.org/10.3390/s18103426.
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The structural health monitoring (SHM) of critical structures is a complex task that involves the use of different sensors that are also aimed at the identification of the location of the impact point using ultrasonic sensors. For the evaluation of the impact position, reference is often made to the well-known triangulation method. This method requires the estimation of the differential time of arrival (DToA) and the group velocity of the Lamb waves propagating into a plate-like structure: the uncertainty of these two parameters is taken into consideration as main cause of localization error. The work proposes a simple laboratory procedure based on a set-up with a pair of sensors that are symmetrically placed with respect to the impact point, to estimate the uncertainty of the DToA and the propagation velocity estimates. According to a theoretical analysis of the error for the impact position, the experimental uncertainties of DToA and the propagation velocity are used to estimate the overall limit of the SHM system for the impact positioning. Because the error for the DToA estimate depends also on the adopted signal processing, three common methods are selected and compared: the threshold, the correlation method, and a likelihood algorithm. Finally, the analysis of the positioning error using multisensory configuration is reported as useful for the design of the SHM system.
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Azuara, Guillermo, and Eduardo Barrera. "Influence and Compensation of Temperature Effects for Damage Detection and Localization in Aerospace Composites." Sensors 20, no. 15 (2020): 4153. http://dx.doi.org/10.3390/s20154153.
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Structural Health Monitoring (SHM) of Carbon Fiber Reinforced Polymers (CFRP) has become, recently, in a promising methodology for the field of Non-Destructive Inspection (NDI), specially based on Ultrasonic Guided Waves (UGW), particularly Lamb waves using Piezoelectric Transducers (PZT). However, the Environmental and Operational Conditions (EOC) perform an important role on the physical characteristics of the waves, mainly the temperature. Some of these effects are phase shifting, amplitude changes and time of flight (ToF) variations. In this paper, a compensation method for evaluating and compensating the effects of the temperature is carried out, performing a data-driven methodology to calculate the features from a dataset of typical temperature values obtained from a thermoset matrix pristine plate, with a transducer network attached. In addition, the methodology is tested on the same sample after an impact damage is carried out on it, using RAPID (Reconstruction Algorithm for Probabilistic Inspection of Damage) and its geometrical variant (RAPID-G) to calculate the location of the damage.
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Katsidimas, Ioannis, Vassilis Kostopoulos, Thanasis Kotzakolios, Sotiris E. Nikoletseas, Stefanos H. Panagiotou, and Constantinos Tsakonas. "An Impact Localization Solution Using Embedded Intelligence—Methodology and Experimental Verification via a Resource-Constrained IoT Device." Sensors 23, no. 2 (2023): 896. http://dx.doi.org/10.3390/s23020896.
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Recent advances both in hardware and software have facilitated the embedded intelligence (EI) research field, and enabled machine learning and decision-making integration in resource-scarce IoT devices and systems, realizing “conscious” and self-explanatory objects (smart objects). In the context of the broad use of WSNs in advanced IoT applications, this is the first work to provide an extreme-edge system, to address structural health monitoring (SHM) on polymethyl methacrylate (PPMA) thin-plate. To the best of our knowledge, state-of-the-art solutions primarily utilize impact positioning methods based on the time of arrival of the stress wave, while in the last decade machine learning data analysis has been performed, by more expensive and resource-abundant equipment than general/development purpose IoT devices, both for the collection and the inference stages of the monitoring system. In contrast to the existing systems, we propose a methodology and a system, implemented by a low-cost device, with the benefit of performing an online and on-device impact localization service from an agnostic perspective, regarding the material and the sensors’ location (as none of those attributes are used). Thus, a design of experiments and the corresponding methodology to build an experimental time-series dataset for impact detection and localization is proposed, using ceramic piezoelectric transducers (PZTs). The system is excited with a steel ball, varying the height from which it is released. Based on TinyML technology for embedding intelligence in low-power devices, we implement and validate random forest and shallow neural network models to localize in real-time (less than 400 ms latency) any occurring impacts on the structure, achieving higher than 90% accuracy.
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Capineri, Lorenzo, Andrea Bulletti, and Eugenio Marino Merlo. "Multichannel Real-Time Electronics Platform for the Estimation of the Error in Impact Localization with Different Piezoelectric Sensor Densities." Applied Sciences 11, no. 9 (2021): 4027. http://dx.doi.org/10.3390/app11094027.
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The work presents a structural health monitoring (SHM) electronic system with real-time acquisition and processing for the determination of impact location in laminate. The novelty of this work is the quantitative evaluation of impact location errors using the Lamb wave guided mode S0, captured and processed in real-time by up to eight piezoelectric sensors. The differential time of arrival is used to minimize an error function for the position estimation. The impact energy is correlated to the amplitudes of the antisymmetric (A0) mode and the electronic design is described to avoid saturation for signal acquisition. The same electronic system is designed to acquire symmetric (S0) low level signals by adequate gain, bandwidth, and signal-to-noise ratio. Such signals propagate into a 1.4 mm thick aluminum laminate at the group velocity of 5150 m/s with frequency components above 270 kHz, and can be discriminated from the A0 mode to calculate accurately the differential arrival time. The results show that the localization error stabilizes at a value comparable with the wavelength of the S0 mode by increasing the number of sensors up to six, and then remains constant at up to eight sensors. This suggests that a compromise can be found between sensor density and localization error.
Tesis sobre el tema "Impact localization,structural health monitoring (SHM)"
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Ciampa, Francesco. "Structural health monitoring systems for impacted isotropic and anisotropic structures." Thesis, University of Bath, 2012. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558884.
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This thesis investigates the development of ultrasonic Structural Health Monitoring (SHM) systems, based on guided waves propagation, for the localization of low-velocity impacts and the detection of damage mechanisms in isotropic and anisotropic structures. For the identi- cation of the impact point, two main passive techniques were developed, an algorithm-based and an imaging-based method. The former approach is based on the dierences of the stress waves measured by a network of piezoelectric transducers surface bonded on plate-like structures. In particular, four piezoelectric sensors were used to measure the antisymmetrical A0 Lamb mode in isotropic materials, whilst six acoustic emission sensors were employed to record the wave packets in composite laminates. A joint time-frequency analysis based on the magnitude of the Continuous Wavelet Transform was used to determine the time of arrivals of the wave packets. Then, a combination of unconstrained optimization technique associated to a local Newton's iterative method was employed to solve a system of non linear equations, in order to assess the impact location coordinates and the wave group speeds. The main advantages of the proposed algorithms are that they do not require an a-priori estimation of the group velocity and the mechanical properties of the isotropic and anisotropic structures. Moreover, these algorithms proved to be very robust since they were able to converge from almost any guess point and required little computational time. In addition, this research provided a comparison between the theoretical and experimental results, showing that the impact source location and the wave velocity were predicted with reasonable accuracy. The passive imaging-based method was developed to detect in realtime the impact source in reverberant complex composite structures using only one passive sensor. This technique is based on the re- ciprocal time reversal approach, applied to a number of waveforms stored in a database containing the impulse responses of the structure. The proposed method allows achieving the optimal focalization of the acoustic emission source (impact event) as it overcomes the limitations of other ultrasonic impact localization techniques. Compared to a simple time reversal process, the robustness of this approach is experimentally demonstrated on a stiened composite plate. This thesis also extended active ultrasonic guided wave methods to the specic case of dissipative structures showing non-classical nonlinear behaviour. Indeed, an imaging method of the nonlinear signature due to impact damage in a reverberant complex anisotropic medium was developed. A novel technique called phase symmetry analysis, together with frequency modulated excitation signals, was used to characterize the third order nonlinearity of the structure by exploiting its invariant properties with the phase angle of the input waveforms. Then, a \virtual" reciprocal time reversal imaging process was employed to focus the elastic waves on the defect, by taking advantage of multiple linear scattering. Finally, the main characteristics of this technique were experimentally validated.
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Carrara, Matteo. "Fourier-based design of acoustic transducers." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54925.
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The work presented in this thesis investigates novel transducer implementations that take advantage of directional sensing and generation of acoustic waves. These transducers are conceived by exploiting a Fourier-based design methodology. The proposed devices find application in the broad field of Structural Health Monitoring (SHM), which is a very active research area devoted to the assessment of the structural integrity of critical components in aerospace, civil and mechanical systems. Among SHM schemes, Guided Waves (GWs) testing has emerged as a prominent option for inspection of plate-like structures using permanently attached piezoelectric transducers.
GWs-based methods rely on the generation and sensing of elastic waves to evaluate structural integrity. They offer an effective method to estimate location, severity and type of damage. It is widely acknowledged among the GWs-SHM community that effective monitoring of structural health is facilitated by sensors and actuators designed with ad hoc engineered capabilities. The objective of this research is to design innovative piezoelectric transducers by specifying their electrode patterns in the Fourier domain. Taking advantage of the Fourier framework, transducer design procedures are outlined and tailored to relevant SHM applications, such as (i) directional actuation and sensing of GWs, (ii) simultaneous sensing of multiple strain components with a single device, and (iii) estimation of the location of impact sites on structural components. The proposed devices enable significant reductions in cost, hardware, and power requirements for advanced SHM schemes when compared to current technologies.
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MERLO, Eugenio MARINO. "Metodi di analisi passiva mediante sensori piezoelettrici in sistemi di monitoraggio strutturale e sviluppo di algoritmi per la localizzazione di impatti. (Passive analysis methods using piezoelectric sensors in structural monitoring systems and development of algorithms for the localization of impacts.)." Doctoral thesis, 2019. http://hdl.handle.net/2158/1153042.
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Technique for Impact Localization on Carbon Fiber Laminate Sheets: il problema affrontato è stato quello della localizzazione di un impatto a bassa energia (simulati con sfere in caduta libera) su strutture planari in materiale polimerico rinforzato con fibra di carbonio (CFRP) per mezzo della formula di triangolazione di Tobias sviluppando un nuovo algoritmo “di verosimiglianza” per l’estrazione del tempo di arrivo differenziale (DToA) da una coppia di sensori piezoelettrici flessibili incollati alla superficie del materiale. In particolare, è stata fatta la caratterizzazione della lastra in CFRP in termini di diagramma delle velocità di propagazione delle onde di Lamb. L’algoritmo ha reso indipendente la valutazione del DToA dal tipo di trasduttore utilizzato, ha migliorato la stima l’accuratezza delle coordinate di impatto. I parametri da inserire nel sistema di elaborazione sono minimi e sono stati migliorati i tempi di elaborazione. Sono state sviluppate nuove geometrie per i sensori in PVDF. Infine, è stato popolato un data base con i segnali acquisiti ed estratti dati statistici con i quali è stato possibile valutare l’algoritmo e confrontarlo con il metodo classico a soglia fissa per lastre in CFRP.
Analysis of the errors in the estimation of impact positions in plate-like structure through the triangulation formula: l’attività di ricerca si è svolta concentrandosi sullo studio di una sperimentazione che diminuisse i parametri di incertezza. È stata condotta quindi un’analisi degli errori nella stima della posizione di impatto su alluminio attraverso la formula di triangolazione. Inizialmente, al fine di ridurre l’incertezza sulla generazione degli impatti con sfere in caduta libera, è stato realizzato un sistema meccanico, completo di elettronica di pilotaggio, per la generazione di impatti controllati e ripetibili. Il lavoro si è concentrato su una semplice procedura di laboratorio basata su un set-up con una coppia di sensori posizionati simmetricamente rispetto al punto di impatto, per stimare l'incertezza del DToA e la velocità di propagazione. Successivamente dallo studio del modello matematico di triangolazione sono stati individuati ed indagati, in modo simulato, i due fattori che ne influiscono sulla stima: il tempo differenziale di arrivo (DToA) ad ogni coppia di sensori dell’array e l’incertezza sulla stima della velocità di gruppo delle onde guidate di Lamb. Le prove sperimentali per la misura della velocità delle onde di Lamb e per la stima del DToA, sono state fatte su di una lastra di alluminio di spessore 1.4 mm con sensori piezoelettrici commerciali. Poiché l'errore per la stima DToA dipende anche dal tipo di elaborazione del segnale adottato, tra i molti metodi
riportati in letteratura per la stima del DToA, abbiamo analizzato e confrontato tre metodi: l'attraversamento di una soglia predeterminata, il metodo di correlazione e l’algoritmo di “verosimiglianza” sviluppato in [A1]. Per il rilevamento dell'incertezza della velocità di propagazione, sono state calcolate le curve di dispersione della piastra di alluminio ed i risultati sono stati poi confrontati con le misurazioni sperimentali. Inoltre, un'analisi teorica ha mostrato come gli errori che influenzano il DToA e la velocità di propagazione agiscano sulla stima del punto di impatto nella formula di triangolazione. L'analisi dell'errore di posizionamento, nell’ottica di un utilizzo di configurazione multisensoriale, è considerata utile per la progettazione di un sistema di monitoraggio strutturale (SHM).
Capítulos de libros sobre el tema "Impact localization,structural health monitoring (SHM)"
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Pant, Shashank, Zahra Sharif Khodaei, and Mohamad Ghazi Droubi. "Monitoring Tasks in Aerospace." In Structural Health Monitoring Damage Detection Systems for Aerospace. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72192-3_2.
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AbstractApproximately up to one-fifth of the direct operating cost of a commercial civilian fixed-wing aircraft is projected to be due to inspection and maintenance alone. Managing aircraft health with minimal human intervention and technologies that can perform continuous or on-demand monitoring/evaluation of aircraft components without having to take the aircraft out of service can have a significant impact on increasing availability while reducing maintenance cost. The ambition of these monitoring technologies is to shift aircraft maintenance practice from planned maintenance (PM), where the aircraft is taken out of service for scheduled inspection/maintenance, to condition-based maintenance (CBM), where aircraft is taken out of service only when maintenance is required, while maintaining the required levels of safety. Structural health monitoring (SHM) techniques can play a vital role in progressing towards CBM practice. Therefore, this chapter aims to provide the reader with a brief overview of the different SHM techniques and their use, as well as, challenges in implementing them for aircraft applications.
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Sause, Markus G. R., Elena Jasiūnienė, and Rhys Pullin. "Introduction." In Structural Health Monitoring Damage Detection Systems for Aerospace. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72192-3_1.
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AbstractThe aerospace industry is aiming for a cleaner means of transport. One way to achieve this is by making transportation lighter, thus directly improving fuel efficiency and reducing environmental impact. A further aim, of the industry, is to reduce maintenance time to lessen operating costs, which can result in a reduction of air transport costs, benefitting both passenger and freight services. Current developments to support these aims include using advanced materials, with the current generation of aerospace structures being 50% composite materials. These materials offer a weight reduction whilst maintaining adequate stiffness; however, their damage mechanics are very complex and less deterministic than those of metals. This results in an overall reduced benefit. Structures are manufactured thicker using additional material to accommodate unknown or unpredictable failure modes, which cannot be easily detected during maintenance. A way to overcome these issues is the adoption of a structural health monitoring (SHM) inspection system.
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Giurgiutiu, Victor. "Impact and Acoustic Emission Monitoring for Aerospace Composites SHM." In Structural Health Monitoring of Aerospace Composites. Elsevier, 2016. http://dx.doi.org/10.1016/b978-0-12-409605-9.00009-x.
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Xu, Qingsong. "Structure Impact Localization Using Emerging Artificial Intelligence Algorithms." In Emerging Design Solutions in Structural Health Monitoring Systems. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8490-4.ch006.
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Extreme learning machine (ELM) is a learning algorithm for single-hidden layer feedforward neural networks. In theory, this algorithm is able to provide good generalization capability at extremely fast learning speed. Comparative studies of benchmark function approximation problems revealed that ELM can learn thousands of times faster than conventional neural network (NN) and can produce good generalization performance in most cases. Unfortunately, the research on damage localization using ELM is limited in the literature. In this chapter, the ELM is extended to the domain of damage localization of plate structures. Its effectiveness in comparison with typical neural networks such as back-propagation neural network (BPNN) and least squares support vector machine (LSSVM) is illustrated through experimental studies. Comparative investigations in terms of learning time and localization accuracy are carried out in detail. It is shown that ELM paves a new way in the domain of plate structure health monitoring. Both advantages and disadvantages of using ELM are discussed.
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Prokopenko, Mikhail, Geoff Poulton, and Don Price. "Self-Organising Impact Sensing Networks in Robust Aerospace Vehicles." In Computational Intelligence and its Applications. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-827-7.ch007.
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An approach to the structural health management (SHM) of future aerospace vehicles is presented. Such systems will need to operate robustly and intelligently in very adverse environments, and be capable of self-monitoring (and ultimately, self-repair). Networks of embedded sensors, active elements, and intelligence have been selected to form a prototypical “smart skin” for the aerospace structure, and a methodology based on multi-agent networks developed for the system to implement aspects of SHM by processes of self-organisation. Problems are broken down with the aid of a “response matrix” into one of three different scenarios: critical, sub-critical, and minor damage. From these scenarios, three components are selected, these being: (a) the formation of “impact boundaries” around damage sites, (b) self-assembling “impact networks”, and (c) shape replication. A genetic algorithm exploiting phase transitions in systems dynamics has been developed to evolve localised algorithms for impact boundary formation, addressing component (a). An ant colony optimisation (ACO) algorithm, extended by way of an adaptive dead reckoning scheme (ADRS) and which incorporates a “pause” heuristic, has been developed to address (b). Both impact boundary formation and ACO-ADRS algorithms have been successfully implemented on a “concept demonstrator”, while shape replication algorithms addressing component (c) have been successfully simulated.
Actas de conferencias sobre el tema "Impact localization,structural health monitoring (SHM)"
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Hinderdael, Michaël F., Dieter De Baere, Wim Devesse, Maria Strantza, and Patrick Guillaume. "Negative Pressure Waves Analysis for Crack Localization and Crack Size Estimation for 3D Printed SHM System." In ASME 2015 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/smasis2015-8845.
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A new Structural Health Monitoring system was developed to allow a faster introduction of 3D printed components into safety critical applications. Additive manufacturing techniques are used to embed capillaries in a 3D printed structure that are then pressurized. Continuous monitoring of the capillary pressure allows the system to indicate the existence of a crack when the pressure deviates from the initial pressure level. A specifically developed experimental set-up enables the study of the impact of different parameters on the leak flow behavior and the occurring Negative Pressure Waves. Negative Pressure Waves are analyzed to demonstrate the crack localization and crack size estimation feasibility. It will first be theoretically proven that the size and location of the crack can be derived from the Negative Pressure Waves. Secondly, measurements will validate the crack localization and size estimation feasibility of the new Structural Health Monitoring system.
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Pierdicca, Alessio, Francesco Clementi, Diletta Maracci, Daniela Isidori, and Stefano Lenci. "Vibration-Based SHM of Ordinary Buildings: Detection and Quantification of Structural Damage." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46763.
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One of the most important issues in civil and in mechanical engineering is the detection of structural damages, which are defined as changes of material properties, of boundary conditions and of system connectivity, which adversely affect the system’s performances. The damage identification process generally requires establishing existence, localization, type and intensity of the damage. During its service life, a structure, besides his natural aging, can be subjected to earthquakes. These events may have a deep impact on building safety and a continuous monitoring of the structure health conditions, through Structural Health Monitoring (SHM) techniques, is necessary in many cases. Within this a background, the purpose of this work is to propose an integrated novel approach for the diagnosis of structures after a seismic event. The proposed monitoring system is based on recording the accelerations of the real structure during a seismic input, and the reintroduction of them into a numerical model, suitably tuned, in order to outline a possible post-earthquake scenario. This approach provides an estimation of the health of the building and of its residual life, and to detect and quantify the damage, some of the crucial aspects of SHM. Actually, we also get both online and self-diagnosis of the structural health. The technique is applied to a real structure, an industrial building liable of some seismic vulnerabilities. It it did not undergo an earthquake, so we have not recordered accelerations, and get them from a different numerical models subjected to the ground acceleration of a realistic earthquake.
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Vizzini, Anthony J., Yingtao Liu, and Aditi Chattopadhyay. "Damage Localization in a Stiffened Composite Panel Using a Lamb Wave Based Tomography Approach." In ASME 2011 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2011. http://dx.doi.org/10.1115/smasis2011-5101.
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In structural health monitoring (SHM) of aerospace components, such as stiffened panels, detection and localization of damage is an important issue. This paper presents a methodology for determining the existence and location of low velocity impact damage in a stiffened composite panel. Using a matching pursuit decomposition algorithm, converted modes due to damage were extracted in the time-frequency domain. The energy of the converted mode was then used in conjunction with a probabilistic tomography approach that was able to localize the damage with a high level of accuracy. The results obtained confirm the ability of this approach to detect and localize damage in complex composite structures.
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Hervin, Flora, and Paul Fromme. "Directionally Dependent Guided Wave Scattering for the Monitoring of Anisotropic Composite Structures." In 2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/qnde2022-98367.
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Abstract 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.
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ZHOU, PEIYUAN, and OTIS KOPSAFTOPOULOS. "DAMAGE LOCALIZATION AND MAGNITUDE ESTIMATION ON A COMPOSITE UAV WING VIA STOCHASTIC FUNCTIONALLY POOLED MODELS." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36240.
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A vibration-based active-sensing global SHM method is proposed and evaluated for its damage localization and quantification accuracy on complex wing structure. In the process, the wing structure is actuated by a white noise vibration and the response signals are collected by a distributed sensor network. The proposed SHM method first utilize auto-regressive exogenous (ARX) model [1] for representing the time-domain response at each sensor location under various damage conditions, where stochasticity contained in structural response is minimized and identified. ARX models are then mapped to damage parameter space via vector-dependent functionally pooled (VFP) method [2]. Then, a damage estimation algorithm based on minimizing VFP-ARX model prediction error is developed. Finally, the damage estimation results are evaluated as the possibility of leveraging multiple senor signal in SHM process is implicated.
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HANSEN, J. B., M. K. HOVGAARD, P. OLSEN, A. SKAFTE, and R. BRINCKER. "Study of Vibration Based SHM Technologies, Part IV: Localization Using Physical-based Methods." In Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/171.
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HOVGAARD, M. K., J. B. HANSEN, A. SKAFTE, P. OLSEN, and R. BRINCKER. "Study of Vibration Based SHM Technologies, Part III: Localization Using Statistical Learning Theory." In Structural Health Monitoring 2015. Destech Publications, 2015. http://dx.doi.org/10.12783/shm2015/305.
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STEINWEG, DOMINIK, and MIRKO HORNUNG. "COST AND BENEFIT OF SHM IN COMMERCIAL AVIATION." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36239.
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An integrated techno-economic cost-benefit analysis is presented to analyze the impact of damage detection-based SHM on an Airbus A320-based reference aircraft, instrumented with ultrasonic and fiber-optic sensors. The operational performance of aircraft with and without SHM is compared in terms of inspection effort, dispatch reliability, payload capacity, service limit, SHM equipment weight and performance, as well as total operating cost. Finally, the net present value of SHM is calculated. While SHM can be profitable for airlines, the achievable benefit depends on the SHM system performance and the economic environment of the airline.
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Hervin, Flora, and Paul Fromme. "Anisotropy Influence on Guided Wave Propagation and Steering in Unidirectional CFRP." In 2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/qnde2022-98375.
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Abstract Carbon fiber reinforced composite laminates (CFRP) are often selected for aerospace structures due to their low weight and high strength compared to their metallic counterparts. They consist of very stiff and highly anisotropic fiber matrix ply layers, resulting in high in-plane strength. However, composite laminates are prone to barely visible impact damage when subjected to low velocity impacts during service. Undetected impact damage can cause significant strength reduction of the laminate. Effective structural health monitoring (SHM) of composite panels is therefore required to prevent component failure, which can be achieved using guided waves propagating along the structure. A number of guided wave propagation effects occur in composite laminates due to the high material anisotropy of the ply layers, such as directionality of phase and group velocity and wave steering effects. If unaccounted for, these anisotropic effects could lead to inaccurate localization of damage, and potential regions of the structure where guided waves do not provide sufficient defect detection sensitivity. Propagation of the A0 Lamb mode was investigated for multiple incident wave directions in an undamaged unidirectional CFRP panel. Full 3D Finite Element (FE) models were developed using homogenized anisotropic material properties to investigate the directional dependency of velocity. Non-contact guided wave velocity measurements were obtained using a laser vibrometer to validate the FE model. Both a point and line source were modelled to investigate the influence of the excitation source on the guided wave evaluation and signal processing. Significant wave skewing behavior was predicted from the numerical simulations for several wave propagation directions, with good agreement with theoretical values.
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BÜCHTER,, KAI-DANIEL, and LILY KOOPS. "RETROFITTING POTENTIALS IN AIRCRAFT STRUCTURAL HEALTH MONITORING—A VALUE OF INFORMATION ANALYSIS." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36238.
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Structural Health Monitoring (SHM) systems promise to improve cost efficiency in aircraft maintenance. Beyond the cost of developing and procuring SHM systems, however, a potentially adverse impact on aircraft performance may negatively affect operational cost. With this in mind, we use an SHM sensor-network model to derive optimal SHM configurations, considering instrumentation and fuel costs as well as saved inspection time, on individual structural component level. Based on Net Present Value theory, we find that retrofitting provides a 20-% benefit on fleet level over factory-only instrumentation, considering the increasing maintenance effort throughout aircraft life as well as variations in individual aircraft usage. We also show that a Value of Information analysis supports more gainful decisions regarding the optimal set of instrumented parts as well as retrofitting times, considering individual aircraft usage.