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Bouzid, Omar Mabrok, Gui Yun Tian, Kanapathippillai Cumanan y 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 y 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 y Andrea Bulletti. "Ultrasonic Guided-Waves Sensors and Integrated Structural Health Monitoring Systems for Impact Detection and Localization: A Review". Sensors 21, n.º 9 (22 de abril de 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 y 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 (junio de 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 y Victor Giurgiutiu. "Experimental Investigation of Impact Localization in Composite Plate Using Newly Developed Imaging Method". Inventions 3, n.º 3 (27 de agosto de 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 y Jiawei Xiang. "Beamforming using non-equidistant linear array for acoustic source localization". Journal of Intelligent Material Systems and Structures 33, n.º 8 (8 de octubre de 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 y 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, n.º 10 (12 de octubre de 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 y Eduardo Barrera. "Influence and Compensation of Temperature Effects for Damage Detection and Localization in Aerospace Composites". Sensors 20, n.º 15 (26 de julio de 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 y Constantinos Tsakonas. "An Impact Localization Solution Using Embedded Intelligence—Methodology and Experimental Verification via a Resource-Constrained IoT Device". Sensors 23, n.º 2 (12 de enero de 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 y 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, n.º 9 (28 de abril de 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.
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Dziendzikowski, Michal, Mateusz Heesch, Jakub Gorski, Krzysztof Dragan y Ziemowit Dworakowski. "Application of PZT Ceramic Sensors for Composite Structure Monitoring Using Harmonic Excitation Signals and Bayesian Classification Approach". Materials 14, n.º 19 (22 de septiembre de 2021): 5468. http://dx.doi.org/10.3390/ma14195468.
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The capabilities of ceramic PZT transducers, allowing for elastic wave excitation in a broad frequency spectrum, made them particularly suitable for the Structural Health Monitoring field. In this paper, the approach to detecting impact damage in composite structures based on harmonic excitation of PZT sensor in the so-called pitch–catch PZT network setup is studied. In particular, the repeatability of damage indication for similar configuration of two independent PZT networks is analyzed, and the possibility of damage indication for different localization of sensing paths between pairs of PZT sensors with respect to damage locations is investigated. The approach allowed for differentiation between paths sensitive to the transmission mode of elastic wave interaction and sensitive reflection mode. In addition, a new universal Bayesian approach to SHM data classification is provided in the paper. The defined Bayesian classifier is based on asymptotic properties of Maximum Likelihood estimators and Principal Component Analysis for orthogonal data transformation. Properties of the defined algorithm are compared to the standard nearest-neighbor classifier based on the acquired experimental data. It was shown in the paper that the proposed approach is characterized by lower false-positive indications in comparison with the nearest-neighbor algorithm.
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Lee, Jung Ryul, Chen Ciang Chia, Hye Jin Shin, Jong Heon Kim y Chan Yik Park. "Aircraft Wing Inspection Based on Anomalous Wave Propagation Imaging". Advanced Materials Research 123-125 (agosto de 2010): 879–82. http://dx.doi.org/10.4028/www.scientific.net/amr.123-125.879.
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Non-destructive evaluation (NDE) and structural health management (SHM) with the ability to evaluate the severity of a damage are important to ensure the reliability of a structure. We propose a local non-destructive evaluation (NDE) system based on Anomalous Wave Propagation Imaging (AWPI) method. When possible damage is flagged during the lifecycle of the structure, the proposed system will be launched for automatic damage evaluation. This technology was demonstrated on a CFRP skin-spar-stringers wingbox integrated with an AE sensor. 17 mm diameter impact damage was made between the stringers using hammer strike from outer surface of the skin. Based on the impact location determined by other global structural health monitoring system, the AWPI automatically inspects an area 400×400 mm2 with the impacted location enclosed. Anomalous Wave Propagation Movie (AWPM) was generated as inspection result. As contrast to its predecessor, the AWPM shows only the damage induced ultrasonic wave (anomalous wave), making the damage detection an intuitive decision making process. Precise damage localization was performed by identifying the location of area with anomalous wave propagation in the AWPM. Besides, the size of the area with anomalous wave agreed well with the size of impact damage, which demonstrated that damage size quantification is possible using the proposed system. Being sensitive only to anomalous wave, it is expected that this NDE system is exceptionally suitable not only for aircraft structures such as wingbox with stiffeners, but also for other complex engineering structures.
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Manawadu, Ayumi y Pizhong Qiao. "Impact identification on concrete panels using a surface-bonded smart piezoelectric module system". Smart Materials and Structures 31, n.º 1 (13 de diciembre de 2021): 015044. http://dx.doi.org/10.1088/1361-665x/ac3c03.
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Abstract Timely identification of collision damage, especially in aging bridges, is critical for the safety of commuters. However, there is no efficient, cost-effective, in-situ technique to serve this purpose. Wave propagation-based structural health monitoring (SHM) using piezoelectric material is a promising alternative for remote sensing. To that end, this study aims to develop a wave propagation-based monitoring technique using surface-bonded smart piezoelectric modules (SPM) to determine the impact force, location, and projectile properties of low-velocity impacts on concrete panels. An impact source localization algorithm used in composite structures is adapted and simplified for concrete structures. This technique is validated using a combined experimental and numerical investigation, which shows good agreement with the actual impact source location. The impact force, projectile mass, and velocity are determined using a semi-theoretical-experimental technique based on Reed contact model. A special contact-SPM is fabricated and calibrated to determine the contact force at the impact location. The relationship between contact-SPM response and distributed-SPM response is determined using a drop-weight test with steel sphere. The peak contact force and contact duration are in good agreement with Reed contact model, although the latter overpredicts the given parameters. A simplified formula based on Reed contact model is used to inversely estimate the projectile velocity of a known mass and vice versa. Then, using the pre-calibrated data, the impact force, projectile properties, and impact force-time distribution are determined using the response of distributed-SPM system. The technique is validated using an arbitrary steel sphere mass. As demonstrated in the combined experimental, theoretical, and numerical study, the proposed surface-bonded SPM system is capable of effectively identifying low-velocity impact incidents on concrete structures, which could potentially facilitate inexpensive, in-situ, real-time condition assessment.
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Kelkel, Benjamin, Philipp Argus y Martin Gurka. "Scalable Monitoring System for the Localization of Damaging Events in Thin-Walled CFRP Structures Based on Acoustic Emission Analysis and Neural Networks". Key Engineering Materials 809 (junio de 2019): 401–6. http://dx.doi.org/10.4028/www.scientific.net/kem.809.401.
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A constant challenge for the design and operation of CFRP primary structures is their sensitivity towards impact loading. This can lead to the formation of externally invisible delaminations which endanger the structural integrity. In practice, this circumstance is encountered with elaborate inspections or conservative design. Structural Heath Monitoring (SHM) systems offer the potential for permanent monitoring and represent an alternative approach that has drawn more attention in the last decade. The biggest barriers to market entry for this technology are system costs and reliability. This study is dedicated to these two points with the development of a low-cost system with which representative acoustic emission sources can be located reliably in a complex CFRP structure. The implementation is carried out using acoustic emission analysis, which represents a promising solution for the integral monitoring of primary structures. It is based on the detection of acoustic waves that are released during crack initiation and growth and propagate over large areas in thin-walled structures as Lamb waves. The challenges of source localization in thin-walled CFRP structures lie in the consideration of wave dispersion, anisotropic material properties, variable component geometry and interfaces. In this thesis, this complexity is captured by training a neural network. For this purpose, artificial sources are used which imitate acoustic emissions of typical damaging events in the material in frequency and mode content. The demonstrating component is an omega profile equipped with a network of piezoelectric sensors that is designed for reliable localization within a defined window. Signal processing takes place on a single-board computer which, together with a digital oscilloscope, completes the measurement chain. The system represents a modular, low-cost approach that can be transferred to other applications by adapting the hardware and training.
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Akiba, Tatsuya, Nobukazu Lee y Akira Mita. "Sensor Agent Robot with Servo-Accelerometer for Structural Health Monitoring". Key Engineering Materials 558 (junio de 2013): 289–96. http://dx.doi.org/10.4028/www.scientific.net/kem.558.289.
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SHM systems are becoming feasible with the growth of computer and sensor technologies during the last decade. However, high implantation cost prevents SHM from becoming common in general buildings. The reason of this high cost is partially due to many accelerometers. In this research, we propose a mobile sensor agent robot with accelerometers and a laser range finder (LRF). If this robot can properly measure accurate acceleration data, the cost of SHM would be cut down and the SHM systems would become common. Our goal is to develop a platform for SHM using the sensor agent robot. We designed the prototype robot to detect the floor vibrations and acquire the micro tremor information correctly. When the sensor agent robot is set in the mode of acquiring the data, the dynamics of the robot should be tuned not to be affected by its flexibility. To achieve this purpose the robot frame was modified to move down to the floor and to provide enough rigidity to obtain good data. In addition to this mechanism, we tested an algorithm to know the location of the robot and the map of the floor correctly to be used in the SHM system using the LRF and Simultaneously Localization and Mapping (SLAM).
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Guo, Ziyi, Tianxiang Huang y Kai-Uwe Schröder. "Development of a Piezoelectric Transducer-Based Integrated Structural Health Monitoring System for Impact Monitoring and Impedance Measurement". Applied Sciences 10, n.º 6 (18 de marzo de 2020): 2062. http://dx.doi.org/10.3390/app10062062.
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Structural health monitoring (SHM) techniques, which are also considered as online nondestructive testing methods, are significant in modern structural engineering due to their ability to guarantee structure safety while reducing maintenance cost. It is often necessary to combine different SHM methods to achieve a more reliable damage detection result. However, the hardware of the SHM systems is usually expensive, bulky, and heavy when they are designed separately. Therefore, this paper proposes a three-layer architecture for designing an integrated multi-function SHM system to achieve a small, lightweight, and low power consumption SHM system. Based on the architecture, an integrated SHM system with impact monitoring and electromechanical impedance measurement is developed. In addition, a scheduling module is developed to manage the two functions of the system. Furthermore, an integrated interface is developed to transfer the data and the command. Then, an integrated printed circuit board is designed and manufactured to achieve the aforementioned functions. The designed system is applied for impact monitoring and damage detection for a supporting structure of a sailplane.
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Liu, Tao, Yu Lei y Yibing Mao. "Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement". Advances in Civil Engineering 2022 (30 de junio de 2022): 1–11. http://dx.doi.org/10.1155/2022/5444101.
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In conventional structural health monitoring (SHM), the installation of sensors and data acquisition devices will affect the regular operation of structures to a certain extent and is also expensive. In order to overcome these shortcomings, the computer vision- (CV-) based method has been introduced into SHM, and its practical applications are increasing. In this paper, CV-based SHM methods such as template matching and Hough circle transform are described. In order to improve the accuracy of pixel localization, the subpixel localization refinement method is introduced. The displacement monitoring experiment of an aluminum alloy cantilever with three targets is conducted by using the two CV-based SHM methods and the laser displacement sensors simultaneously. The displacement monitoring results of CV-based methods agree well with those measured by the laser transducer system in the time domain. After that, the first two modes of the cantilever are identified from the monitoring results. In addition, the experimental modes identified from the monitoring data and those calculated from the finite element model are also consistent. Therefore, the developed CV-based methods can obtain accurate displacement results in both time and frequency domains, which could be applied to complex structures with more monitoring targets.
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Büchter, Kai-Daniel, Carlos Sebastia Saez y Dominik Steinweg. "Modeling of an aircraft structural health monitoring sensor network for operational impact assessment". Structural Health Monitoring 21, n.º 1 (10 de diciembre de 2021): 208–24. http://dx.doi.org/10.1177/14759217211048149.
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Structural health monitoring (SHM) of aircraft components can improve maintenance operations, potentially reducing costs for inspections, unscheduled maintenance events, and unexpected delays. On the other hand, aircraft safety and net present value can be adversely influenced by false alarms, missed detections, system costs, and weight and power requirements of the SHM system. In order to gain a better understanding into the latter, we present a weight and power model for a sensor network, comprising sensors, interrogators, data collectors, and wiring. We assess the net benefit of using SHM in terms of reduced expenditure as function of network coverage, considering a corresponding potential in reducing the inspection effort.
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Balasubramaniam, Krishnan, B. V. Soma Sekhar, J. Vishnu Vardan y C. V. Krishnamurthy. "Structural Health Monitoring of Composite Structures Using Guided Lamb Waves". Key Engineering Materials 321-323 (octubre de 2006): 759–64. http://dx.doi.org/10.4028/www.scientific.net/kem.321-323.759.
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Structural Health Monitoring (SHM) of aircrafts is of great relevance in the present age aircraft industry. The present study demonstrates three techniques that have the potential for the SHM of multi-layered composite structures. The first technique is based on multi-transmitter-multireceiver (MTMR) technique with tomographic methods used for data reconstruction. In the MTMR, the possibility of SHM using algebraic reconstruction techniques (ART) for tomographic imaging with Lamb wave data measured in realistic materials is examined. Defects (through holes and low velocity impact delaminations) were synthetic and have been chosen to simulate impact damage in composite plates. The second technique is a single-transmitter-multi-receiver (STMR) technique that is more compact and uses reconstruction techniques that are analogous to synthetic aperture techniques. The reconstruction algorithm uses summation of the phase shifted signals to image the location of defects, portions of the plate edges, and any reflectors from inherent structural features of the component. The third technique involves a linear array of sensors across a stiffener for the detection of disbanded regions.
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Ursu, Ioan, Daniela Enciu y Adrian Toader. "Towards structural health monitoring of space vehicles". Aircraft Engineering and Aerospace Technology 89, n.º 6 (2 de octubre de 2017): 920–27. http://dx.doi.org/10.1108/aeat-07-2015-0173.
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Purpose The purpose of this paper is to report the results of a recent project of complex tests on the survival of structural health monitoring (SHM) technology with piezo wafer active sensors (PWAS) and electromechanical impedance spectroscopy (EMIS) at simulating the concomitant action of harsh conditions of outer space: extreme temperatures, radiations, vacuum. Design/methodology/approach The tests were conducted on PWAS, consists in adhesive and aluminium discs as structural specimens, with PWAS bonded on them. The substantiating of PWAS-EMIS-based SHM technique consists the fact that real part of the PWAS electromechanical impedance spectrum follows with fidelity the resonance behaviour of the structure vibrating under the PWAS excitation. This EMIS signature is very sensitive to any structural changes and, on this basis, can be monitored the onset and progress of structural damages such as fatigue, cracks, corrosion, etc. Findings The conclusion of the tests is that the cumulative impact of severe conditions of temperature, radiation and vacuum has not generated decommissioning of sensors or adhesive, which would have meant the compromise of the methodology. A second important outcome is linked to the capability of this methodology to distinguish between the damages of mechanical origin and the false ones, caused by environmental conditions, which are, basically, harmless. Originality/value The question of transfer of PWAS-EMIS-based SHM technology to space vehicles and applications received, as a novelty, a first and encouraging response.
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Barazanchy, Darun, Marcias Martinez, Bruno Rocha y Marko Yanishevsky. "A Hybrid Structural Health Monitoring System for the Detection and Localization of Damage in Composite Structures". Journal of Sensors 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/109403.
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A hybrid structural health monitoring (SHM) system, consisting of a piezoelectric transducer and fiber optic sensors (FOS) for generating and monitoring Lamb waves, was investigated to determine their potential for damage detection and localization in composite aerospace structures. As part of this study, the proposed hybrid SHM system, together with an in-house developed algorithm, was evaluated to detect and localize two types of damage: a through thickness damage (hole of 2 mm in diameter) and a surface damage (2 mm diameter bore hole with a depth of 0.65 mm) located on the backside of the plate. The experiments were performed using an aircraft representative composite plate skin, manufactured from carbon fiber reinforced polymer (CFRP).
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Momeni, Hamed y Arvin Ebrahimkhanlou. "High-dimensional data analytics in structural health monitoring and non-destructive evaluation: a review paper". Smart Materials and Structures 31, n.º 4 (1 de marzo de 2022): 043001. http://dx.doi.org/10.1088/1361-665x/ac50f4.
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Abstract This paper aims to review high-dimensional data analytic (HDDA) methods for structural health monitoring (SHM) and non-destructive evaluation (NDE) applications. High-dimensional data is a type of data in which the number of features for each observation is much larger than the number of all observations. High-dimensional data may violate assumptions of the classic methods for statistical modeling and data analysis. Then, classic statistical modeling will no longer be applicable. HDDA methods were developed to overcome this challenge and analyze these types of data. In the field of SHM/NDE, there are several sources of high-dimensionality. Examples include a large number of data points in continuous waves/signals or high-resolution images/videos. HDDA methods are used as a dimension-reduction tool to preprocess data for further analysis, or they are directly implemented for damage detection and localization. This paper reviews six HDDA methods as well as existing and potential applications in SHM/NDE. Particularly, this paper discusses the vast range of implemented SHM/NDE applications from crack detection to missing data imputation. Furthermore, experimental and simulated datasets have been used to show the application of HDDA methods as hands-on examples. It is shown that the potential of HDDA for SHM/NDE studies is significantly more than the existing studies in the literature, and these methods can be used as a powerful tool that provides vast opportunities in SHM/NDE.
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Bayoumi, Ahmed, Tobias Minten y Inka Mueller. "Determination of Detection Probability and Localization Accuracy for a Guided Wave-Based Structural Health Monitoring System on a Composite Structure". Applied Mechanics 2, n.º 4 (2 de diciembre de 2021): 996–1008. http://dx.doi.org/10.3390/applmech2040058.
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The capabilities of detection and localization of damage in a structure, using a guided wave-based structural health monitoring (GWSHM) system, depend on the damage location and the chosen sensor array setup. This paper presents a novel approach to assess the reliability of an SHM system enabling to quantify localization accuracy. A two-step technique is developed to combine multiple paths to generate one probability of detection (POD) curve that provides information regarding the detection capability of an SHM system at a defined damage position. Moreover, a new method is presented to analyze localization accuracy. Established probability-based diagnostic imaging using a signal correlation algorithm is used to determine the damage location. The resultant output of the localization accuracy analysis is the smallest damage size at which a defined accuracy level can be reached at a determined location. The proposed methods for determination of detection probability and localization accuracy are applied to a plate-like CFRP structure with an omega stringer with artificial damage of different sizes at different locations. The results show that the location of the damage influences the sensitivity of detection and localization accuracy for the used detection and localization methods. Localization accuracy is enhanced as it becomes closer to the array’s center, but its detection sensitivity deteriorates.
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Mustapha, Samir, Ye Lu, Ching-Tai Ng y Pawel Malinowski. "Sensor Networks for Structures Health Monitoring: Placement, Implementations, and Challenges—A Review". Vibration 4, n.º 3 (10 de julio de 2021): 551–84. http://dx.doi.org/10.3390/vibration4030033.
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The development of structural health monitoring (SHM) systems and their integration in actual structures has become a necessity as it can provide a robust and low-cost solution for monitoring the structural integrity of and the ability to predict the remaining life of structures. In this review, we aim at focusing on one of the important issues of SHM, the design, and implementation of sensor networks. Location and number of sensors, in any SHM system, are of high importance as they impact the system integration, system performance, and accuracy of assessment, as well as the total cost. Hence we are interested in shedding the light on the sensor networks as an essential component of SHM systems. The review discusses several important parameters including design and optimization of sensor networks, development of academic and commercial solutions, powering of sensors, data communication, data transmission, and analytics. Finally, we presented some successful case studies including the challenges and limitations associated with the sensor networks.
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Jacot, Maurine, Victor Champaney, Francisco Chinesta y Julien Cortial. "Parametric Damage Mechanics Empowering Structural Health Monitoring of 3D Woven Composites". Sensors 23, n.º 4 (9 de febrero de 2023): 1946. http://dx.doi.org/10.3390/s23041946.
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This paper presents a data-driven structural health monitoring (SHM) method by the use of so-called reduced-order models relying on an offline training/online use for unidirectional fiber and matrix failure detection in a 3D woven composite plate. During the offline phase (or learning) a dataset of possible damage localization, fiber and matrix failure ratios is generated through high-fidelity simulations (ABAQUS software). Then, a reduced model in a lower-dimensional approximation subspace based on the so-called sparse proper generalized decomposition (sPGD) is constructed. The parametrized approach of the sPGD method reduces the computational burden associated with a high-fidelity solver and allows a faster evaluation of all possible failure configurations. However, during the testing phase, it turns out that classical sPGD fails to capture the influence of the damage localization on the solution. To alleviate the just-referred difficulties, the present work proposes an adaptive sPGD. First, a change of variable is carried out to place all the damage areas on the same reference region, where an adapted interpolation can be done. During the online use, an optimization algorithm is employed with numerical experiments to evaluate the damage localization and damage ratio which allow us to define the health state of the structure.
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Sun, Ya Jie, Yong Hong Zhang y Cheng Shan Qian. "Implement of Lamb Wave Using PZT Phased Arrays for Structural Health Monitoring". Applied Mechanics and Materials 347-350 (agosto de 2013): 36–39. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.36.
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Phased array theory is analyzed. The PZT phased array is applied in SHM for the Al plate to identify the hole in the structure. The Lamb wave beam steering is controlled by adding the time delay to the signals. The structure can be scanned in half plane by using the phased array theory to control the Lamb wave beam steering. The damage in the structure can be recognized and localized by the phased array method. The identification result is shown on mapped image. The phased array damage localization method is verified by the experiment and the result shows that the method is effective to recognize the hole damage in the structure.
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Jayawardhana, Madhuka, Xin Qun Zhu, Ranjith Liyanapathirana y Upul Gunawardana. "Compressive Sensing for Structural Damage Detection of Reinforced Concrete Structures". Key Engineering Materials 569-570 (julio de 2013): 742–50. http://dx.doi.org/10.4028/www.scientific.net/kem.569-570.742.
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High energy consumption, excessive data storage and transfer requirements are prevailing issues associated with structural health monitoring (SHM) systems, especially with those employing wireless sensors. Data compression is one of the techniques being explored to mitigate the effects of these issues. Compressive sensing (CS) introduces a means of reproducing a signal with a much less number of samples than the Nyquist's rate, reducing the energy consumption, data storage and transfer cost. This paper explores the applicability of CS for SHM, in particular for damage detection and localization. CS is implemented in a simulated environment to compress SHM data. The reconstructed signal is verified for accuracy using structural response data obtained from a series of tests carried out on a reinforced concrete (RC) slab. Results show that the reconstruction was close, but not exact as a consequence of the noise associated with the responses. However, further analysis using the reconstructed signal provided successful damage detection and localization results, showing that although the reconstruction using CS is not exact, it is sufficient to provide the crucial information of the existence and location of damage.
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Braunfelds, Janis, Ugis Senkans, Peteris Skels, Rims Janeliukstis, Toms Salgals, Dmitrii Redka, Ilya Lyashuk et al. "FBG-Based Sensing for Structural Health Monitoring of Road Infrastructure". Journal of Sensors 2021 (8 de enero de 2021): 1–11. http://dx.doi.org/10.1155/2021/8850368.
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Public road infrastructure is developed all around the world. To save resources, ensure public safety, and provide longer-lasting road infrastructure, structural health monitoring (SHM) applications for roads have to be researched and developed. Asphalt is one of the largest used surface materials for the road building industry. This material also provides relatively easy fiber optical sensor technology installment, which can be effectively used for SHM applications—road infrastructure monitoring as well as for resource optimization when road building or their repairs are planned. This article focuses on the research of the fiber Bragg grating (FBG) optical temperature and strain sensor applications in road SHM, which is part of the greater interdisciplinary research project started at the Riga Technical University in the year 2017. Experimental work described in this article was realized in one of the largest Latvian road sites where the FBG strain and temperature sensors were installed into asphalt pavement, and experiments were carried out in two main scenarios. Firstly, in a controlled environment with a calibrated falling weight deflectometer (FWD) to test the installed FBG sensors. Secondly, by evaluating the real-time traffic impact on the measured strain and temperature, where different types of vehicles passed the asphalt span in which the sensors were embedded. The findings in this research illustrate that by gathering and combining data from calibrated FWD measurements, measurements from embedded FBG optical sensors which were providing the essential information of how the pavement structure could sustain the load and information about the traffic intensity on the specific road section, and the structural life of the pavement can be evaluated and predicted. Thus, it enables the optimal pavement future design for necessary requirements and constraints as well as efficient use, maintenance, and timely repairs of the public roads, directly contributing to the overall safety of our transportation system.
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Braunfelds, Janis, Ugis Senkans, Peteris Skels, Rims Janeliukstis, Toms Salgals, Dmitrii Redka, Ilya Lyashuk et al. "FBG-Based Sensing for Structural Health Monitoring of Road Infrastructure". Journal of Sensors 2021 (8 de enero de 2021): 1–11. http://dx.doi.org/10.1155/2021/8850368.
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Public road infrastructure is developed all around the world. To save resources, ensure public safety, and provide longer-lasting road infrastructure, structural health monitoring (SHM) applications for roads have to be researched and developed. Asphalt is one of the largest used surface materials for the road building industry. This material also provides relatively easy fiber optical sensor technology installment, which can be effectively used for SHM applications—road infrastructure monitoring as well as for resource optimization when road building or their repairs are planned. This article focuses on the research of the fiber Bragg grating (FBG) optical temperature and strain sensor applications in road SHM, which is part of the greater interdisciplinary research project started at the Riga Technical University in the year 2017. Experimental work described in this article was realized in one of the largest Latvian road sites where the FBG strain and temperature sensors were installed into asphalt pavement, and experiments were carried out in two main scenarios. Firstly, in a controlled environment with a calibrated falling weight deflectometer (FWD) to test the installed FBG sensors. Secondly, by evaluating the real-time traffic impact on the measured strain and temperature, where different types of vehicles passed the asphalt span in which the sensors were embedded. The findings in this research illustrate that by gathering and combining data from calibrated FWD measurements, measurements from embedded FBG optical sensors which were providing the essential information of how the pavement structure could sustain the load and information about the traffic intensity on the specific road section, and the structural life of the pavement can be evaluated and predicted. Thus, it enables the optimal pavement future design for necessary requirements and constraints as well as efficient use, maintenance, and timely repairs of the public roads, directly contributing to the overall safety of our transportation system.
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Hoschke, Nigel, Don C. Price, D. Andrew Scott y W. Lance Richards. "Structural Health Monitoring of Space Vehicle Thermal Protection Systems". Key Engineering Materials 558 (junio de 2013): 268–80. http://dx.doi.org/10.4028/www.scientific.net/kem.558.268.
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The thermal protection systems of spacecraft are vulnerable to damage from impacts by foreign objects moving at high velocities. This paper describes a proposed novel structural health monitoring system that will detect, locate and evaluate the damage resulting from such impacts. This system consists of a network of intelligent local agents, each of which controls a network of piezoelectric acoustic emission sensors to detect and locate an impact, and a network of optical fibre Bragg grating sensors to evaluate the effect of the impact damage by means of a thermographic technique. The paper concentrates on two issues that are critical to the successful implementation of the proposed SHM system: measurement of the elastic properties of the thermal protection material, knowledge of which is essential to the design and operation of the acoustic emission sensor network; and investigation of the practical feasibility of a switched network of optical fibre sensors.
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Baran, Marta, Dominik Nowakowski, Janusz Lisiecki y Sylwester Kłysz. "Mechanical Tests Applied to Structural Health Monitoring: An Overview of Previous Experience". Fatigue of Aircraft Structures 2020, n.º 12 (1 de diciembre de 2020): 123–35. http://dx.doi.org/10.2478/fas-2020-0012.
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Abstract Laboratory for Materials Strength Testing (LMST) has been conducting accredited mechanical research for aviation from 2003. Among accredited procedures are e.g. low and high cycle fatigue tests, fracture toughness tests and fatigue crack growth rate tests. The main goal of them is obtaining materials constants and characteristics. However knowledge how to conduct these tests could be used also in other applications, for instance in the work on development of Structural Health Monitoring systems (SHM). When cracks propagate in a controlled way in laboratory conditions, it allows verifying the operation of a single sensor or a network of sensors. In this paper, an overview of mechanical tests carried out at the Laboratory for Materials Strength Testing within Air Force Institute of Technology (AFIT) work on research and development of SHM systems is presented. Specimens prepared from materials such as aluminum alloys (among other withdrawn PZL-130 Orlik TC-II aircraft) and CFRP composite were tested under different mechanical loads, i.e., cycle and impact loads. In the presented research, both constant amplitude and spectrum loads were applied.
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Azizi, Aydin y Ali Ashkzari. "Health Monitoring in Petrochemical Vessels". Advanced Materials Research 1030-1032 (septiembre de 2014): 983–86. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.983.
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Industrial structures deteriorate generally in an uncontrollable rate. To assess the short-term impact due to hazards and the long-term deterioration process due to physical aging and routine operation, structural health monitoring (SHM) is proposed. In this paper as a model of vessel a simply supported beam under constant distributed force is investigated. The objective is to estimate the severity of damage in a known location with sensing devices. As no actuation is consider the problem is solved statically. Finite element method by using MATLAB software to calculate the global stiffness matrix of the smart beam has been applied. It is expected the results show that higher severity of damage causes higher deflection and higher sensor of voltage.
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Lambinet, Florian, Zahra Sharif Khodaei y M. H. Ferri Aliabadi. "Structural Health Monitoring of Bonded Patch Repaired Composite". Key Engineering Materials 713 (septiembre de 2016): 135–38. http://dx.doi.org/10.4028/www.scientific.net/kem.713.135.
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Bonded repair of composite structures still remains a crucial concern for the airworthiness authorities because of the uncertainty about the repair quality. This works, investigates the applicability of Structural Health Monitoring (SHM) techniques for monitoring of bonded repair. Active sensing method has been applied to two case studies: a sensorised panel impacted to cause barely visible impact damage (BVID) and repaired afterwards, the tensile and fatigue testing of a composite strap repair. In the first case, the previous sensors have been used to detect an artificially introduced damage. In the second case the failure of the adhesive during the tensile testing is used as basis of the load levels in the tensile-tensile fatigue test. In both cases PZT transducers have been used to monitor the bonded patch. An electromechanical impedance (EMI) and Lamb wave analysis have been carried out to check the overall integrity of the repair patch between. In both cases the state of the repaired composite was monitored successfully and reported.
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Torzoni, Matteo, Luca Rosafalco y Andrea Manzoni. "A Combined Model-Order Reduction and Deep Learning Approach for Structural Health Monitoring under Varying Operational and Environmental Conditions". Engineering Proceedings 2, n.º 1 (30 de diciembre de 2020): 94. http://dx.doi.org/10.3390/ecsa-7-08258.
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Nowadays, the aging, deterioration, and failure of civil structures are challenges of paramount importance, increasingly motivating the search of advanced Structural Health Monitoring (SHM) tools. In this work, we propose a SHM strategy for online structural damage detection and localization, combining Deep Learning (DL) and Model-Order Reduction (MOR). The developed data-based procedure is driven by the analysis of vibration and temperature recordings, shaped as multivariate time series and collected on the fly through pervasive sensor networks. Damage detection and localization are treated as a supervised classification task considering a finite number of predefined damage scenarios. During a preliminary offline phase, for each damage scenario, a collection of synthetic structural responses and temperature distributions, is numerically generated through a physics-based model. Several loading and thermal conditions are considered, thanks to a suitable parametrization of the problem, which controls the dependency of the model on operational and environmental conditions. Because of the huge amount of model evaluations, MOR techniques are employed in order to relieve the computational burden that is associated to the dataset construction. Finally, a deep neural network, featuring a stack of convolutional layers, is trained by assimilating both vibrational and thermal data. During the online phase, the trained DL network processes new incoming recordings in order to classify the actual state of the structure, thus providing information regarding the presence and localization of the damage, if any. Numerical performances of the proposed approach are assessed on the monitoring of a two-storey frame under low intensity seismic excitation.
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Das, Swagato y Purnachandra Saha. "Performance of Ant Lion Optimization and Artificial Bee Colony Algorithm for Structural Health Monitoring of ASCE Benchmark Structure". Proceedings of the 12th Structural Engineering Convention, SEC 2022: Themes 1-2 1, n.º 1 (19 de diciembre de 2022): 1423–28. http://dx.doi.org/10.38208/acp.v1.672.
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Structural health Monitoring (SHM) has been a fast-moving tread for monitoring the health status of civil engineering structures. The SHM strategy involves application of different techniques involving the use of modal parameters, such as natural frequencies and mode shapes, to detect and localize the damage. Though localization of damage in structure plays an important role, damage quantification, which helps in performing repair works, is also essential. However, very few algorithms have been developed which calculates the amount of damage in structure. In view to this situation, the swarm-based optimization algorithms have been developed which can detect the damage severity in a structure. Some of the algorithms developed so far are Grey Wolf Algorithm (GWO), Artificial Bee Colony (ABC) algorithm, Firefly algorithm, Ant Lion Optimization (ALO) algorithm and others. Out of these algorithms, ALO and ABC have been used in limited number of cases for performing SHM. No real-life structures, considering the effect of noise, has been analysed using ALO and ABC. In this paper, the ALO and ABC optimization algorithm has been studied for damage analysis using an objective function based on the eigen value problem. The structure chosen for analysis is the ASCE Benchmark building which is a quarter scale model of an original building which give the real-life sense of SHM. Damage considered in the structure is of less severity occurring at multiple locations under an external noise, which is also a real-life challenge for damage analysis. The experimental results show that both ABC and ALO algorithms are able to quantify both major and minor damages in the presence of moderate amount of noise, proving the robustness of these algorithms.
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Yang, Chaochao y John Newhook. "Developing a structural-health-monitoring model to monitor cracking in steel-free concrete deck slabs". Canadian Journal of Civil Engineering 34, n.º 3 (1 de marzo de 2007): 378–88. http://dx.doi.org/10.1139/l06-141.
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The ISIS Canada Networks of Centres of Excellence (NCE) program has focused on two main themes to improve civil engineering infrastructure, namely innovative construction technologies, and structural health monitoring (SHM). The former began with the construction of the first field application of the innovative steel-free concrete bridge deck slab technology at the Salmon River bridge, Nova Scotia, in 1995. Although this bridge has continued to function safely under heavy traffic loads, it has developed characteristic longitudinal cracking of the concrete between adjacent girders due to fatigue. This paper describes the recent research to develop an SHM model for monitoring the impact and stability of this cracking. Theoretical and experimental models were used to examine the change in response as cracking develops. A global load distribution matrix was proposed, and the variation in load distribution values with cracking was used to develop a cracking index that can be employed in monitoring the field structure.Key words: structural health monitoring, bridges, concrete, deck slabs, cracking, load distribution.
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Li, Peng, Liuwei Huang y Jiachao Peng. "Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition". Sensors 18, n.º 12 (4 de diciembre de 2018): 4264. http://dx.doi.org/10.3390/s18124264.
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Optimal sensor placement is a significant task for structural health monitoring (SHM). In this paper, an SHM system is designed which can recognize the different impact location and impact degree in the composite plate. Firstly, the finite element method is used to simulate the impact, extracting numerical signals of the structure, and the wavelet decomposition is used to extract the band energy. Meanwhile, principal component analysis (PCA) is used to reduce the dimensions of the vibration signal. Following this, the non-dominated sorting genetic algorithm (NSGA-II) is used to optimize the placement of sensors. Finally, the experimental system is established, and the Product-based Neural Network is used to recognize different impact categories. Three sets of experiments are carried out to verify the optimal results. When three sensors are applied, the average accuracy of the impact recognition is 59.14%; when the number of sensors is four, the average accuracy of impact recognition is 76.95%.
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Nyikayaramba, Gift y Boris Murmann. "S-Parameter-Based Defect Localization for Ultrasonic Guided Wave SHM". Aerospace 7, n.º 3 (20 de marzo de 2020): 33. http://dx.doi.org/10.3390/aerospace7030033.
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In this work, an approach for enabling miniaturized, low-voltage hardware for active structural health monitoring (SHM) based on ultrasonic guided waves is investigated. The proposed technique relies on S-parameter measurements instead of time-domain pulsing and thereby trades off longer measurement times with lower actuation voltages for improved compatibility with dense complementary metal-oxide-semiconductor (CMOS) chip integration. To demonstrate the feasibility of this method, we present results showing the successful localization of defects in aluminum and carbon-fiber-reinforced polymer (CFRP) test structures using S-parameter measurements. The S-parameter measurements were made on benchtop vector network analyzers that actuate the piezoelectric transducers at output voltage amplitudes as low as 1.264 Vpp.
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Sawicki, Bartłomiej, Antoine Bassil, Eugen Brühwiler, Xavier Chapeleau y Dominique Leduc. "Detection and Measurement of Matrix Discontinuities in UHPFRC by Means of Distributed Fiber Optics Sensing". Sensors 20, n.º 14 (12 de julio de 2020): 3883. http://dx.doi.org/10.3390/s20143883.
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Following the significant improvement in their properties during the last decade, Distributed Fiber Optics sensing (DFOs) techniques are nowadays implemented for industrial use in the context of Structural Health Monitoring (SHM). While these techniques have formed an undeniable asset for the health monitoring of concrete structures, their performance should be validated for novel structural materials including Ultra High Performance Fiber Reinforced Cementitious composites (UHPFRC). In this study, a full scale UHPFRC beam was instrumented with DFOs, Digital Image Correlation (DIC) and extensometers. The performances of these three measurement techniques in terms of strain measurement as well as crack detection and localization are compared. A method for the measurement of opening and closing of localized fictitious cracks in UHPFRC using the Optical Backscattering Reflectometry (OBR) technique is verified. Moreover, the use of correct combination of DFO sensors allows precise detection of microcracks as well as monitoring of fictitious cracks’ opening. The recommendations regarding use of various SHM methods for UHPFRC structures are given.
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Tan, Langxing, Osamu Saito, Fengming Yu, Yoji Okabe, Taku Kondoh, Shota Tezuka y Akihiro Chiba. "Impact Damage Detection Using Chirp Ultrasonic Guided Waves for Development of Health Monitoring System for CFRP Mobility Structures". Sensors 22, n.º 3 (20 de enero de 2022): 789. http://dx.doi.org/10.3390/s22030789.
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When impact damage occurs in carbon fiber-reinforced plastic (CFRP) structures, it is barely visible but may cause significant degradation in the mechanical properties of the structure. Hence, a structural health monitoring (SHM) system that can be installed in CFRP mobility structures and is sensitive to impact damage is needed. In this study, we attempted to establish an SHM system based on ultrasonic guided waves, which are generated by inputting a broadband chirp signal into a film-like piezoelectric actuator. The relationship between impact damage size and maximum time-of-flight (ToF) delay was investigated for three types of CFRP plates: woven, non-woven, and hybrid laminates. As a result, it was found that the maximum ToF delay increased linearly with an increase in the damage size for all CFRP laminates. Moreover, the amplitude of the A0 mode was found to be significantly affected by the damage length in the wave propagation direction. Thus, this SHM method using chirp ultrasonic waves can quantitatively evaluate the size and extent of the impact damage in CFRP laminates.
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Zhao, Jian Hua y Ling Zhang. "Structural Damage Localization Using D-S Evidence Theory". Applied Mechanics and Materials 105-107 (septiembre de 2011): 999–1003. http://dx.doi.org/10.4028/www.scientific.net/amm.105-107.999.
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Damage localization is a key issue in the Structural Health Monitoring (SHM). In order to enhance the accuracy of damage localization, an approach based on D-S evidence theory is studied in this paper. First, damage results obtained from the modal strain energy change ratio (MSECR) method and the multiple damage location assurance criterion (MDLAC) method are regarded as two independent information sources, respectively. And then, the D-S evidence theory-based information fusion technique is employed to integrate these two results and make a final decision. To compare the damage identification results under different methods, a practical damage evaluation indicator is presented. Numerical study on a cantilever beam is carried out to verify the proposed method. Results indicate that the damage evaluation indicators calculated by D-S evidence theory are superior to the single method. That is to say, structural damage identification method based on D-S evidence theory performs very well in determining the damage locations.
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Zhuang, Yizhou, Weimin Chen, Tao Jin, Bin Chen, He Zhang y Wen Zhang. "A Review of Computer Vision-Based Structural Deformation Monitoring in Field Environments". Sensors 22, n.º 10 (16 de mayo de 2022): 3789. http://dx.doi.org/10.3390/s22103789.
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Computer vision-based structural deformation monitoring techniques were studied in a large number of applications in the field of structural health monitoring (SHM). Numerous laboratory tests and short-term field applications contributed to the formation of the basic framework of computer vision deformation monitoring systems towards developing long-term stable monitoring in field environments. The major contribution of this paper was to analyze the influence mechanism of the measuring accuracy of computer vision deformation monitoring systems from two perspectives, the physical impact, and target tracking algorithm impact, and provide the existing solutions. Physical impact included the hardware impact and the environmental impact, while the target tracking algorithm impact included image preprocessing, measurement efficiency and accuracy. The applicability and limitations of computer vision monitoring algorithms were summarized.
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Yan, Shi, Hao Yan Ma, Xue Lei Jiang, Bao Hui Qi y Fu Xue Liu. "A Bridge Health Monitoring System Based on Wireless Smart Aggregates". Applied Mechanics and Materials 578-579 (julio de 2014): 1138–44. http://dx.doi.org/10.4028/www.scientific.net/amm.578-579.1138.
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Researches on health monitoring technology of concrete structures by using piezoelectric smart aggregates have achieved a great development. However, the technique is not widely used so far in practical engineering. Because when constructing large-scale structural health monitoring (SHM) system using wire-based sensors, it requires a lot of cables to form a monitoring network, resulting in huge cost of abundant material of wires and labor for wire placement, and the relatively heavy maintenance work in case of failure of the SHM system. A kind of wireless sensor network based on the protocol for Zigbee802.15.4 and the passive piezoelectric smart health monitoring technology is developed in the paper. Through internal load monitoring tests of a concrete bridge model under impact loading, the developed wireless smart aggregate (WSA) health monitoring system is experimentally validated. The finite element method (FEM) is used to simulate the process as the same as the bridge model test, and the numerical results are consistent with those of the experiment. The experimental results show that the developed wireless system is stable and reliable, and can be applied in concrete bridge structure health monitoring under impact loading.
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Zacchei, Enrico, Pedro H. C. Lyra, Gabriel E. Lage, Epaminondas Antonine, Airton B. Soares, Natalia C. Caruso y Cassia S. de Assis. "Structural Health Monitoring of a Brazilian Concrete Bridge for Estimating Specific Dynamic Responses". Buildings 12, n.º 6 (8 de junio de 2022): 785. http://dx.doi.org/10.3390/buildings12060785.
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A 3D coupled model to simulate vehicle–bridge interactions (VBI) to estimate its structural responses and impact factors (IMs) was developed in this study. By structural health monitoring (SHM) of a real concrete bridge, several data were collected to calibrate the bridge model by the finite element method (FEM). These models provide the bridge response in terms of vertical displacements and accelerations. VBI models provide reliable outputs without significantly altering the dynamic properties of the bridge. Modified recent analytical equations, which account for the effects of the asymmetric two-axle vehicles, were developed numerically. These equations, plus some proposed solutions, also quantified the vehicle response in terms of accelerations to estimate a more conservative driving comfort. The goal consisted in fitting the SHM with numerical and analytical models to find a more appropriate response for safety purposes and maintenance. From the codes and the literature, it was shown that a unique IM factor was not found. Moreover, most approaches underestimate the phenomena; in fact, results show that a monitored IM factor is 2.5 greater than IM from codes. Proposed equations for vehicle accelerations provided more conservative values up to about three times the standard comfort value.
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Sharif-Khodaei, Z., M. Ghajari, M. H. Aliabadi y A. Apicella. "SMART Platform for Structural Health Monitoring of Sensorised Stiffened Composite Panels". Key Engineering Materials 525-526 (noviembre de 2012): 581–84. http://dx.doi.org/10.4028/www.scientific.net/kem.525-526.581.
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A SMART Platform is developed based on sensor readings for Structural Health Monitoring of a stiffened composite panel. The platforms main function is divided into three categories: Passive sensing, Active sensing and Optimal sensor positioning. The platform has self-diagnostic capabilities, i.e. prior to its application the health of the sensors and their connection will be checked to avoid any false alarm. Passive sensing results in impact location and force magnitude detection. Active sensing is performed for damage detection. It results in detecting the damage location and severity. Finally the optimal sensor location can be provided given the number of sensors and probability of detection value. This platform is the first step in applying the developed SHM methodologies to real size structures in service load conditions.
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Thiene, Marco, Zahra Sharif Khodaei y M. H. Aliabadi. "Statistical Analysis of SHM Passive Sensing Systems". Key Engineering Materials 665 (septiembre de 2015): 241–44. http://dx.doi.org/10.4028/www.scientific.net/kem.665.241.
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Structural Health Monitoring (SHM) techniques have gained an increased interest to be utilised alongside NDI techniques for aircraft maintenance. However, to take the SHM methodologies from the laboratory conditions to actual structures under real load conditions requires them to be assessed in terms of reliability and robustness. In this work, a statistical analysis is carried out for a passive SHM system capable of impact detection and identification. The sensitivity of the platform to parameters such as noise, sensor failure and in-service load conditions has been investigated and reported.
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Stawiarski, Adam y Aleksander Muc. "On Transducers Localization in Damage Detection by Wave Propagation Method". Sensors 19, n.º 8 (25 de abril de 2019): 1937. http://dx.doi.org/10.3390/s19081937.
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In this paper, the elastic wave propagation method was used in damage detection in thin structures. The effectiveness and accuracy of the system based on the wave propagation phenomenon depend on the number and localization of the sensors. The utilization of the piezoelectric (PZT) transducers makes possible to build a low-cost damage detection system that can be used in structural health monitoring (SHM) of the metallic and composite structures. The different number and localization of transducers were considered in the numerical and experimental analysis of the wave propagation phenomenon. The relation of the sensors configuration and the damage detection capability was demonstrated. The main assumptions and requirements of SHM systems of different levels were discussed with reference to the damage detection expectations. The importance of the damage detection system constituents (sensors number, localization, or damage index) in different levels of analysis was verified and discussed to emphasize that in many practical applications introducing complicated procedures and sophisticated data processing techniques does not lead to improving the damage detection efficiency. Finally, the necessity of the appropriate formulation of SHM system requirements and expectations was underlined to improve the effectiveness of the detection methods in particular levels of analysis and thus to improve the safety of the monitored structures.
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Dragan, Krzysztof, Michał Dziendzikowski, Artur Kurnyta, Michal Salacinski, Sylwester Klysz y Andrzej Leski. "Composite Aerospace Structure Monitoring with use of Integrated Sensors". Fatigue of Aircraft Structures 2015, n.º 7 (1 de diciembre de 2015): 12–17. http://dx.doi.org/10.1515/fas-2015-0002.
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Abstract One major challenge confronting the aerospace industry today is to develop a reliable and universal Structural Health Monitoring (SHM) system allowing for direct aircraft inspections and maintenance costs reduction. SHM based on guided Lamb waves is an approach capable of addressing this issue and satisfying all the associated requirements. This paper presents an approach to monitoring damage growth in composite aerospace structures and early damage detection. The main component of the system is a piezoelectric transducers (PZT) network integrated with composites. This work describes sensors’ integration with the structure. In particular, some issues concerning the mathematical algorithms giving information about damage from the impact damage presence and its growth are discussed.
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Giordano, Pier Francesco, Said Quqa y Maria Pina Limongelli. "Statistical Approach for Vibration-Based Damage Localization in Civil Infrastructures Using Smart Sensor Networks". Infrastructures 6, n.º 2 (1 de febrero de 2021): 22. http://dx.doi.org/10.3390/infrastructures6020022.
Texto completoResumen
One of the most discussed aspects of vibration-based structural health monitoring (SHM) is how to link identified parameters with structural health conditions. To this aim, several damage indexes have been proposed in the relevant literature based on typical assumptions of the operational modal analysis (OMA), such as stationary excitation and unlimited vibration record. Wireless smart sensor networks based on low-power electronic components are becoming increasingly popular among SHM specialists. However, such solutions are not able to deal with long data series due to energy and computational constraints. The decentralization of processing tasks has been shown to mitigate these issues. Nevertheless, traditional damage indicators might not be suitable for onboard computations. In this paper, a robust damage index is proposed based on a damage sensitive feature computed in a decentralized fashion, suitable for smart wireless sensing solutions. The proposed method is tested on a numerical benchmark and on a real case study, namely the S101 bridge in Austria, a prestressed concrete bridge that has been artificially damaged for research purposes. The results obtained show the potential of the proposed method to monitor the conditions of civil infrastructures.
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Kohut, Piotr, Krzysztof Holak, Tadeusz Uhl, Jędrzej Mączak y Przemysław Szulim. "Application of Vision Based Damage Detection for Real Civil Engineering Structure". Key Engineering Materials 588 (octubre de 2013): 22–32. http://dx.doi.org/10.4028/www.scientific.net/kem.588.22.
Texto completoResumen
Structural Health Monitoring (SHM) is an emerging field of technology that involves the integration of sensors, data transmission, processing and analysis for detection, as well as localization and assessment of damage which can lead to its failure in the future [1,. In general, SHM methods can be divided into two groups: local and global ones. The second group can be applied if a global change in the geometry of a structure can be observed. In practice, the most commonly used methods of damage detection are based on the analysis of variations in various dynamic properties caused by damage [3,. However, the excitation of large structures can be costly and difficult. The acquisition of static deflection requires much less effort, which makes the damage detection methods based on changes in deflection curves more attractive for practical use [5-1. Damage detection and localization methods require a densely sampled deflection curve.