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A novel time–frequency transform for broadband Lamb waves dispersion characteristics analysis Struct. Health Monit. (IF 4.87) Pub Date : 2021-01-14 Zhi Luo; Liang Zeng; Jing Lin
Owing to carrying rich information about structure flaws, broadband Lamb waves are considered as a promising tool for non-destructive testing. However, since every Lamb wave mode has its own dispersion characteristics, the feature extraction among broadband multimodal Lamb wave is challenging. Time–frequency representation is significantly effective to analyze dispersive signals. In this article, taking
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Nonlinear modulation with low-power sensor networks using undersampling Struct. Health Monit. (IF 4.87) Pub Date : 2021-01-14 Peter Oppermann; Lennart Dorendorf; Marcus Rutner; Christian Renner
Nonlinear modulation is a promising technique for ultrasonic non-destructive damage identification. A wireless sensor network is ideally suited to monitor large structures using nonlinear modulation in a cost-efficient manner. However, existing approaches rely on high sampling rates and resource-demanding computations that are not feasible on low-cost and low-power sensor network devices. We present
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Laboratory investigation of a bridge scour monitoring method using decentralized modal analysis Struct. Health Monit. (IF 4.87) Pub Date : 2021-01-14 Muhammad Arslan Khan; Daniel P McCrum; Luke J Prendergast; Eugene J OBrien; Paul C Fitzgerald; Chul-Woo Kim
Scour is a significant issue for bridges worldwide that influences the global stiffness of bridge structures and hence alters the dynamic behaviour of these systems. For the first time, this article presents a new approach to detect bridge scour at shallow pad foundations, using a decentralized modal analysis approach through re-deployable accelerometers to extract modal information. A numerical model
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IWSHM 2019: Perturbation-based Bayesian damage identification using responses at vibration nodes Struct. Health Monit. (IF 4.87) Pub Date : 2021-01-14 Tianxiang Huang; Kai-Uwe Schröder
One important topic for structural health monitoring is to achieve accurate damage detection with a small number of noisy sensors and without the requirement of a high-fidelity finite element model. This article adopts the Bayesian probabilistic approach combined with a perturbation model using responses at a few vibration nodes for damage monitoring. First, the node displacement, or the response at
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Simultaneous pixel-level concrete defect detection and grouping using a fully convolutional model Struct. Health Monit. (IF 4.87) Pub Date : 2021-01-14 Chaobo Zhang; Chih-chen Chang; Maziar Jamshidi
Deep learning techniques have attracted significant attention in the field of visual inspection of civil infrastructure systems recently. Currently, most deep learning-based visual inspection techniques utilize a convolutional neural network to recognize surface defects either by detecting a bounding box of each defect or classifying all pixels on an image without distinguishing between different defect
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Effect of propagation distance on acoustic emission of carbon fiber/epoxy composites Struct. Health Monit. (IF 4.87) Pub Date : 2021-01-14 Doyun Jung; Byoung-Sun Lee; Woong-Ryeol Yu; Wonjin Na
This study examined the change in acoustic emission as a function of measurement position of fiber-reinforced composites. Single-edge-notched carbon fiber/epoxy composites were prepared and tested under cyclic loading, with sensors located at specific distances from the end of the notch. Although the Ib-value increased overall, the degree of increase significantly varied with position and acoustic
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Improved damage detection in Pelton turbines using optimized condition indicators and data-driven techniques Struct. Health Monit. (IF 4.87) Pub Date : 2021-01-07 Weiqiang Zhao; Mònica Egusquiza; Aida Estevez; Alexandre Presas; Carme Valero; David Valentín; Eduard Egusquiza
The health condition of hydraulic turbines is one of the most critical factors for the operation safety and financial benefits of a hydro power plant. After the massive entrance of intermittent renewable energies, hydropower units have to regulate their output much more frequently for the balancing of the power grid. Under these conditions, the components of the machine have to withstand harsher excitation
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Improved current injection pattern for the detection of delaminations in carbon fiber reinforced polymer plates using electrical impedance tomography Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 Mathias Haingartner; Sandra Gschoßmann; Max Cichocki; Martin Schagerl
In this article, we introduce a new current injection pattern for electrical impedance tomography. The pattern improves the quality of hole detection in carbon fiber reinforced polymer plates and allows the detection of delaminations. The new pattern is described in detail and compared to three widely used, classical injection patterns. The advantages of the new pattern are demonstrated by numerical
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Experimental investigation of fiber Bragg grating hoop strain sensor–based method for sudden leakage monitoring of gas pipeline Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 Tao Jiang; Liang Ren; Jia-jian Wang; Zi-guang Jia; Dong-sheng Li; Hong-nan Li
Pipeline, serving as one of the most important gas transportation methods, can cause serious consequences in the event of leakage, so leakage monitoring is particularly important. In our previous study, a fiber Bragg grating hoop strain sensor was developed to detect pipeline leakage by measuring circumferential strain, and this sensor was utilized in a liquid pipeline leakage test to verify its performance
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Crack damage detection of structures using spectral transfer matrix Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 P. Nandakumar; K. Shankar
A novel spectral transfer matrix for a cracked beam element is developed in this article and the same is used to identify the crack parameters on the beam structures. Spectral transfer matrix is developed from trigonometric functions based on the theory of fracture mechanics. This matrix determines the natural frequencies of a structure with crack with better accuracy than any other transfer matrices
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Research on early weak structural damage detection of aeroengine intershaft bearing based on acoustic emission technology Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 Zheming Liang; Anna Wang; Yang Yu; Ping Yang
Until now, there is no effective method to detect the early weak structural damage of the aero engine intershaft bearing. In this article, an online method based on acoustic emission technology is used to detect the early weak structural damage of aeroengine intershaft bearing. The combination of maximum correlated kurtosis deconvolution and bandpass filter is proposed to enhance and denoise fault
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Using a single sensor for bridge condition monitoring via moving embedded principal component analysis Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 Zhenhua Nie; Zhaofeng Shen; Jun Li; Hong Hao; Yizhou Lin; Hongwei Ma; Hui Jiang
This article presents a novel data-driven structural damage detection method named moving embedded principal component analysis to monitor the bridge condition and detect the damage occurrence using only one sensor. A fixed moving window is used to cut out the time series of the recorded data for the analysis. The data set inside the window is embedded to be a multidimensional state space using time
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Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 Kun Yu; Qiang Fu; Hui Ma; Tian Ran Lin; Xiang Li
In current research works, a number of intelligent fault diagnosis methods have been proposed with the assistance of domain adaptation approach, which attempt to distinguish the health modes for target domain data using the diagnostic knowledge learned from source domain data. An important assumption for these methods is that the label information for the source domain data should be known in advance
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Change detection using the generalized likelihood ratio method to improve the sensitivity of guided wave structural health monitoring systems Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 Stefano Mariani; Peter Cawley
The transition from one-off ultrasound–based non-destructive testing systems to permanently installed monitoring techniques has the potential to significantly improve the defect detection sensitivity, since frequent measurements can be obtained and tracked with time. However, the measurements must be compensated for changing environmental and operational conditions, such as temperature, and careful
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Parameter identification of crack-like notches in aluminum plates based on strain gauge data Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-31 Ramdane Boukellif; Andreas Ricoeur; Matthias Oxe
The identification of crack parameters and stress intensity factors in aluminum plates under tensile loading is in the focus of the presented research. In this regard, data of strain gauges, distributed along the edges of the samples, are interpreted. In the experiments, slit-shaped notches take the role of cracks located in the interior of the specimens. Their positions, inclinations and lengths as
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Bayesian uncertainty quantification for guided-wave-based multidamage localization in plate-like structures using Gibbs sampling Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-24 Meijie Zhao; Yong Huang; Wensong Zhou; Hui Li
In this article, a new Bayesian approach for guided-wave-based multidamage localization by employing Gibbs sampling is proposed. By using the information of time-of-flight (ToF) embedded in guided wave signals, the posterior probability distributions of three parameter groups, that is, the horizontal and vertical coordinates of the multidamage locations (x, y) and wave velocity v, are characterized
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A review on diagnostic and prognostic approaches for gears Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-23 Pradeep Kundu; Ashish K Darpe; Makarand S Kulkarni
Prognostics and health management has become a significant part of component life-cycle in modern industries. The prognostics and health management framework is implemented in the industries to identify the fault type, assess fault severity, and predict the future state or remaining useful life to optimize the maintenance activities. Three significant aspects of a prognostics and health management
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A vibration analysis strategy for quantitative fracture healing assessment of an internally fixated femur with mass-loading effect of soft tissue Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-23 Benjamin Steven Vien; Wing Kong Chiu; Matthias Russ; Mark Fitzgerald
Vibration analysis methods have been studied to evaluate bone stiffness as a quantifiable mechanical parameter that associates with the degree of fracture healing. However, the effects of soft tissue on the bone frequency response still remain as significant challenges in successfully implementing vibration analysis-based methods as an effective clinical assessment tool. This study presents a computational
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Quality inspection of complex-shaped metal parts by vibrations and an integrated Mahalanobis classification system Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-23 Liangliang Cheng; Vahid Yaghoubi; Wim Van Paepegem; Mathias Kersemans
The Mahalanobis–Taguchi system is considered as a promising and powerful tool for handling binary classification cases. Though, the Mahalanobis–Taguchi system has several restrictions in screening useful features and determining the decision boundary in an optimal manner. In this article, an integrated Mahalanobis classification system is proposed which builds on the concept of Mahalanobis distance
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Nonlinear ultrasonic imaging of damage in composite materials using a higher harmonic and modulated multi-path reciprocal method Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-21 Salvatore Boccardi; Gian Piero Malfense Fierro; Michele Meo
Structural health monitoring has become an important factor in the assessment of defects/damage in material components. Ultrasonic methods generally incorporate a sparse array of sensors/transducers as they provide a low number of piezoelectric sensors per area, thus providing savings with regard to system costs and weight. Many structural health monitoring techniques rely on linear ultrasonic effects
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Anomaly detection of structural health monitoring data using the maximum likelihood estimation-based Bayesian dynamic linear model Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-20 Yi-Ming Zhang; Hao Wang; Hua-Ping Wan; Jian-Xiao Mao; Yi-Chao Xu
Enormous data are continuously collected by the structural health monitoring system of civil infrastructures. The structural health monitoring data inevitably involve anomalies caused by sensors, transmission errors, or abnormal structural behaviors. It is important to identify the anomalies and find their origin (e.g. sensor fault or structural damage) to make correct interventions. Moreover, online
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Noncontact laser vibrometry-based fence-like arrays with wavefield filtering-assisted adaptive imaging algorithms for detecting multiple pits in a compact cluster Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Zhenhua Tian; Zhaoyun Ma; Wenfeng Xiao; Lingyu Yu
Pitting corrosion presents challenges for ultrasonic nondestructive evaluation due to the small pit dimension. Few Lamb wave-based techniques have achieved the identification of individual pits as subwavelength wave scatterers that are densely packed in a small cluster. In this article, noncontact laser vibrometry-based fence-like arrays with wavefield filtering-assisted adaptive imaging algorithms
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Acoustic emission diagnostics of corrosion monitoring in prestressed concrete using hidden Markov and semi-Markov models Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Brennan Dubuc; Konstantinos Sitaropoulos; Arvin Ebrahimkhanlou; Salvatore Salamone
This article presents a framework based on hidden Markov modeling for monitoring corrosion damage in prestressed concrete structures through acoustic emission measurements. Both hidden Markov models and hidden semi-Markov models are investigated to determine the merits of each under typical challenges encountered in real-world monitoring scenarios: an unknown initial corrosion condition and an uncertain
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An acoustic-homologous transfer learning approach for acoustic emission–based rail condition evaluation Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Si-Xin Chen; Lu Zhou; Yi-Qing Ni; Xiao-Zhou Liu
This article presents a novel transfer learning approach for evaluating structural conditions of rail in a progressive manner, by using acoustic emission monitoring data and knowledge transferred from an acoustic-related database. Specifically, the low-level layers of a model pre-trained on large audio data are leveraged in our model for feature extraction. Compared with conventional transfer learning
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Augmented reality for enhanced visual inspection through knowledge-based deep learning Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Shaohan Wang; Sakib Ashraf Zargar; Fuh-Gwo Yuan
A two-stage knowledge-based deep learning algorithm is presented for enabling automated damage detection in real-time using the augmented reality smart glasses. The first stage of the algorithm entails the identification of damage prone zones within the region of interest. This requires domain knowledge about the damage as well as the structure being inspected. In the second stage, automated damage
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1D-TICapsNet: An audio signal processing algorithm for bolt early looseness detection Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Furui Wang; Gangbing Song
Recently, for bolt looseness detection, percussion-based methods have attracted more attention due to their advantages of eliminating contact sensors. The core issue of percussion-based methods is audio signal processing to characterize different bolt preloads, while current percussion-based methods all depend on machine learning–based techniques that require hand-crafted features and overlook bolt
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Enabling human–infrastructure interfaces for inspection using augmented reality Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 D Maharjan; M Agüero; D Mascarenas; R Fierro; F Moreu
Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied
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A new acoustic emission damage localization method using synchrosqueezed wavelet transforms picker and time-order method Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Jingkai Wang; Linsheng Huo; Chunguang Liu; Gangbing Song
Acoustic emission technique, as a passive structural health monitoring technique, has been widely applied to detecting and locating the structural damage. The time difference of arrival and the wave velocity are the key factors in most of the acoustic emission localization methods, and the accuracy of these two factors will affect the accuracy of damage localization. To improve the accuracy of damage
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Multidimensional data statistical processing of magnetic flow leakage signals from a Colombian gas pipeline Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Luis Eduardo Mujica; Magda Ruiz; Rodolfo Villamizar
The hydrocarbon industry in Colombia is one of the principal pillars for the Colombian economy, representing around 5% of its gross domestic product. Since petroleum reserves have decreased, gas becomes one main alternative for economical growth. However, current gas pipelines have been in service for over 30 years and some of them are buried and phenomena, such as metal losses, corrosion, mechanical
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Fault state recognition of wind turbine gearbox based on generalized multi-scale dynamic time warping Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-15 Bin Pang; Tian Tian; Gui-Ji Tang
Fault diagnosis of wind turbine gearbox is significant to ensure the operating efficiency and reduce the maintenance cost of wind farms. The key to achieve an accurate fault diagnosis is to extract the evidence of fault state identification effectively. Dynamic time warping has been widely used as a classifier for automatic pattern recognition as the dynamic time warping distance can indicate the similarity
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Predicting material properties of concrete from ground-penetrating radar attributes Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-07 Isabel M Morris; Vivek Kumar; Branko Glisic
We present here a laboratory-based experimental protocol that seeks to establish and characterize the relationship between ground-penetrating radar attributes and the mechanical properties (density, porosity, and compressive strength) of typical industry concrete mixes. The experimental data consist of ground-penetrating radar attributes from 900 MHz radargrams that correspond to simultaneously measured
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Analytical approach for crack identification of glass fiber reinforced polymer–sea sand concrete composite structures based on strain dissipations Struct. Health Monit. (IF 4.87) Pub Date : 2020-12-03 Dongsheng Xu; Qichao Liu; Yue Qin; Bo Chen
Glass fiber reinforced polymer bars have potential application in the seawater sea sand concrete. In this study, an analytical method was proposed to examine the internal crack development in glass fiber reinforced polymer–sea sand concrete composites. The method was derived by analyzing the strain dissipation and shear-lag behavior. Thus, the internal cracks can be quantitatively identified by the
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Fatigue damage diagnosis and prognosis of an aeronautical structure based on surrogate modelling and particle filter Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-28 Demetrio Cristiani; Claudio Sbarufatti; Francesco Cadini; Marco Giglio
A key issue affecting the performances of every human-conceived engineering system is its degradation, fatigue crack growth being one of the major structural deterioration phenomena. Fatigue crack growth is usually modelled as a stochastic process: uncertainty sources lie both in the item and in the physical degradation process variability. Fatigue crack growth deserves close attention, especially
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Time-domain Markov chain Monte Carlo–based Bayesian damage detection of ballasted tracks using nonlinear ballast stiffness model Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-27 Heung-Fai Lam; Mujib Olamide Adeagbo; Yeong-Bin Yang
This article reports the development of a methodology for detecting ballast damage under a sleeper based on measured sleeper vibration following the Bayesian statistical system identification framework. To ensure the methodology is applicable under large amplitude vibration of the sleeper (e.g. under trainload), the nonlinear stress–strain behavior of railway ballast is considered. This, on one hand
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An adaptive and efficient variational mode decomposition and its application for bearing fault diagnosis Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-25 Xingxing Jiang; Jun Wang; Changqing Shen; Juanjuan Shi; Weiguo Huang; Zhongkui Zhu; Qian Wang
Variational mode decomposition has been widely applied to machinery fault diagnosis during these years. However, it remains difficult to set proper hyperparameters for the variational mode decomposition, including number of decomposed modes, initial center frequencies, and balance parameter. Moreover, the low efficiency of the existing variational mode decomposition methods hinders their applications
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Machine learning paradigm for structural health monitoring Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-24 Yuequan Bao; Hui Li
Structural health diagnosis and prognosis is the goal of structural health monitoring. Vibration-based structural health monitoring methodology has been extensively investigated. However, the conventional vibration–based methods find it difficult to detect damages of actual structures because of a high incompleteness in the monitoring information (the number of sensors is much fewer with respect to
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A mechanical model to interpret distributed fiber optic strain measurement at displacement discontinuities Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-18 Shenghan Zhang; Han Liu; Jeffrey Cheng; Matthew J DeJong
Distributed fiber optic (strain) sensing, which provides the unique advantage of sensing damage (e.g. cracking) at locations that are not known a priori, has been increasingly used in civil engineering. Quantitative crack measurement requires the translation of a discontinuous displacement field at the crack to a continuous strain deformation in the fiber. The main purpose of this article is to develop
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On information modeling in structural integrity management Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-12 Kashif Ali; Jianjun Qin; Michael Havbro Faber
Value of information analyses in structural integrity management has gained significant interest over especially the last decade. The concept of value of information analysis provides a methodical framework facilitating for the optimization of strategies for information collection through inspections and structural health monitoring. The information, which is collected, represents indications of the
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A nonlinear dynamic vibration model of a defective bearing: the importance of modelling the angle of the leading and trailing edges of a defect Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-10 Francesco Larizza; Carl Q Howard; Steven Grainger; Wenyi Wang
Rolling element bearings eventually become worn and fail by developing surface defects, such as spalls, dents and pits. Previous researchers have tested bearings with defects that have sharp 90° rectangular edges that were used to develop analytical models of a defective bearing. These models have limitations that require smooth surfaces and constant curvature of the bearing components; as well as
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Monitoring internal corrosion in steel pipelines: a two-step helical guided wave approach for localization and quantification Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-10 Stylianos Livadiotis; Arvin Ebrahimkhanlou; Salvatore Salamone
This article presents a two-step approach for the assessment of internal corrosion in cylindrical structures using helical guided ultrasonic waves. The approach consists of two steps such as (1) localization and (2) estimation of the size of the corroded area. Localization is performed with the algebraic reconstruction technique where the energy ratio of the two fundamental Lamb modes S0 and A0 is
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Interrogating the health condition of rails using the narrowband Rayleigh waves emitted by an innovative design of non-contact laser transduction system Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-02 Faeez Masurkar; Kim Ming Ng; Peter W Tse; Nitesh P Yelve
The article reports an innovative optical system that is designed to interrogate the health condition of macroscopically intact rail specimens by measuring its inherent nonlinearity using the narrowband Rayleigh waves. A line-arrayed pattern is developed through the optical system that generates narrowband Rayleigh waves with high power on the surface of the rail. As a result of lattice-anharmonicity
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Vision-based automated crack detection using convolutional neural networks for condition assessment of infrastructure Struct. Health Monit. (IF 4.87) Pub Date : 2020-11-01 Aravinda S Rao; Tuan Nguyen; Marimuthu Palaniswami; Tuan Ngo
With the growing number of aging infrastructure across the world, there is a high demand for a more effective inspection method to assess its conditions. Routine assessment of structural conditions is a necessity to ensure the safety and operation of critical infrastructure. However, the current practice to detect structural damages, such as cracks, depends on human visual observation methods, which
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Fusion of structural damage identification results from different test scenarios and evaluation indices in structural health monitoring Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-28 XY Li; SJ Lin; SS Law; YZ Lin; JF Lin
There are many existing algorithms and damage indices that can effectively meet the engineering need in damage diagnosis. However, all of them (except those with an exact formulation) are based on certain assumptions with approximations, and their performances depend on the combination of test parameters, for example, type, number, and location of excitations and sensors; identification algorithm adopted;
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Health indicator construction for roller bearing based on an unsupervised deep belief network with a novel sigmoid zero local minimum point model Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-24 Fan Xu; Xin Shu; Xin Li; Ruoli Tang
Extracting bearing degradation curves with good smoothness and monotonicity as a health indicator lays a solid foundation for predicting the bearing’s remaining useful life. Traditional bearing health indicator construction methods generally have the following problems: (1) they require manual experience, such as manual labeling of data is burdensome when the amount of collected data is large, for
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Time reversibility of Lamb waves in thin plates with surface-bonded piezoelectric transducers is temperature invariant at the best reconstruction frequency Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-23 Bhabagrahi Natha Sharma; Santosh Kapuria; A Arockiarajan
The Lamb wave time-reversal method has been widely proposed as a baseline-free method for damage detection in thin-walled structures. Under varying thermal environments, it would require that the time reversibility of Lamb waves is temperature invariant. In this study, we examine the temperature dependence of Lamb waves and its time reversibility using experiments and finite element simulations on
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A hybrid learning strategy for structural damage detection Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-23 Lorena Andrade Nunes; Rafaelle Piazzaroli Finotti Amaral; Flávio de Souza Barbosa; Alexandre Abrahão Cury
Over the past decades, several methods for structural health monitoring have been developed and employed in various practical applications. Some of these techniques aimed to use raw dynamic measurements to detect damage or structural changes. Desirably, structural health monitoring systems should rely on computational tools capable of evaluating the information acquired from the structure continuously
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An fast Fourier transform–based correlation coefficient approach for structural damage diagnosis Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-20 Nhi K Ngo; Thanh Q Nguyen; Thu V Vu; H Nguyen-Xuan
We present a novel approach to evaluating mechanical features of structures using correlation coefficients and fast Fourier transform analysis. Although correlation coefficient is always a sensitive parameter to changes of mechanical properties of real structures, it is rarely used due to high complication in data collection. To overcome this drawback, we propose fast Fourier transform analysis to
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A comparison of machine learning algorithms for assessment of delamination in fiber-reinforced polymer composite beams Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-20 Mengyue He; Yishou Wang; Karthik Ram Ramakrishnan; Zhifang Zhang
Structural health monitoring techniques based on vibration parameters have been used to assess the internal delamination damage of fiber-reinforced polymer composites. Recently, machine learning algorithms have been adopted to solve the inverse problem of predicting delamination parameters of the delamination from natural frequency shifts. In this article, a delamination detection methodology is proposed
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Time history analysis-based nonlinear finite element model updating for a long-span cable-stayed bridge Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-16 Kaiqi Lin; You-Lin Xu; Xinzheng Lu; Zhongguo Guan; Jianzhong Li
Accurate finite element models play significant roles in the design, health monitoring and life-cycle maintenance of long-span bridges. However, due to uncertainties involved in finite element modelling, updating of the finite element model to best represent the real bridge is inevitable. This is particularly true after a long-span bridge experiences a moderate or severe earthquake and suffers some
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Improving sensitivity and coverage of structural health monitoring using bulk ultrasonic waves Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-16 Stefano Mariani; Yuan Liu; Peter Cawley
Practical ultrasonic structural health monitoring systems must be able to deal with temperature changes and some signal amplitude/phase drift over time; these issues have been investigated extensively with low-frequency-guided wave systems but much less work has been done on bulk wave systems operating in the megahertz frequency range. Temperature and signal drift compensation have been investigated
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Efficient storage and processing of large guided wave data sets with random projections Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-15 Sungwon Kim; Spencer Shiveley; Alexander CS Douglass; Yisong Zhang; Rajeev Sahay; Daniel O Adams; Joel B Harley
Over the last several decades, structural health monitoring systems have grown into increasingly diverse applications. Structural health monitoring excels with large data sets that can capture the typical variability, novel events, and undesired degradation over time. As a result, the efficient storage and processing of these large, guided wave data sets have become a key feature for successful application
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VoI-informed decision-making for SHM system arrangement Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-15 Wei-Heng Zhang; Jianjun Qin; Da-Gang Lu; Sebastian Thöns; Michael Havbro Faber
Structural health monitoring systems have been widely implemented to provide real-time continuous data support and to ensure structural safety in the context of structural integrity management. However, the quantification of the potential benefits of structural health monitoring systems has not yet attracted widespread attention. At the same time, there is an urgent need to develop strategies, such
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An effective health indicator for bearing using corrected conditional entropy through diversity-driven multi-parent evolutionary algorithm Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-12 Sumika Chauhan; Manmohan Singh; Ashwani Kumar Aggarwal
The bearing vibration signal possesses nonlinear and non-stationary characteristics; hence; it is difficult to diagnosis the faults in the bearing under different working conditions. In this article, a new scheme has been proposed based on complete ensemble empirical mode decomposition with adaptive noise and corrected conditional entropy to recognize the different class of faults in bearing. The mode
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Lost data reconstruction for structural health monitoring using deep convolutional generative adversarial networks Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-10 Xiaoming Lei; Limin Sun; Ye Xia
In the application of structural health monitoring, the measured data might be temporarily or permanently lost due to sensor fault or transmission failure. The measured data with a high data loss ratio undermine its ability for modal identifications and structural condition evaluations. To reconstruct the lost data in the field of structural health monitoring, this study proposes a deep convolutional
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Thermal integrity testing of cast in situ piles: An alternative interpretation approach Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-10 Qianchen Sun; Mohammed Elshafie; Chris Barker; Anthony Fisher; Jennifer Schooling; Yi Rui
Integrity testing of deep cast in situ concrete foundations is challenging due to the intrinsic nature of how these foundations are formed. Several integrity test methods have been developed and are well established, but each of these have strengths and weaknesses. A relatively recent integrity testing method is thermal integrity testing. The fundamental feature is the early age concrete release of
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Measurement of defects in a plate using dry-coupled interdigital transducer–based scanning laser Doppler vibrometer Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-08 To Kang; Seong-Jin Han; Seongin Moon; Soonwoo Han; Jun Young Jeon; Gyuhae Park
The interdigital transducer–based scanning laser Doppler vibrometer has recently been introduced to efficiently generate the symmetric mode for damage detection of shallow defects in thick plates. To measure shallow defects in a carbon steel plate, the excitation frequency is optimized based on the analysis of wavenumber sensitivity and degree of separation between modes. Even though the interdigital
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Visualization of hidden damage from scattered wavefield reconstructed using an integrated high-speed camera system Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-06 Huan-Yu Chang; Fuh-Gwo Yuan
In this article, a feasibility study for the visualization of hidden damage using an integrated high-speed camera system was carried out. A thin, planar, and low-modulus high-density polyethylene plate with surrogate damage was chosen to represent a damaged structure for the proof of concept, and two different damage scenarios (mimicked by attaching lightweight rectangular/circular masses to the back
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Using Bayesian networks for the assessment of underwater scour for road and railway bridges Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-06 Andrea Maroni; Enrico Tubaldi; Dimitri V Val; Hazel McDonald; Daniele Zonta
Flood-induced scour is among the most common external causes of bridge failures worldwide. In the United States, scour is the cause of 22 bridges fails every year, whereas in the UK, it contributed significantly to the 138 collapses of bridges in the last century. Scour assessments are currently based on visual inspections, which are time-consuming and expensive. Nowadays, sensor and communication
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An intelligent algorithm based on evolutionary strategy and clustering algorithm for Lamb wave defect location Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-06 Honglei Chen; Zenghua Liu; Bin Wu; Cunfu He
Imaging algorithms for visualization of defects play a significant role in Lamb wave–based research of nondestructive testing and structural health monitoring. In classical algorithms, the position or distribution of defects is located by mapping the amplitude or phase information of signals from the time domain to every discrete spatial grid of the structure. It is time-consuming. In this study, the
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Laser ultrasonic imaging of wavefield spatial gradients for damage detection Struct. Health Monit. (IF 4.87) Pub Date : 2020-10-02 Zihan Wu; See Yenn Chong; Michael D Todd
This article describes a new damage visualization method to investigate and analyze propagating guided Lamb waves using analyses of wavefield spatial gradients. A laser ultrasonic interrogation system was used to create full-field ultrasonic data measurements for ultrasonic wavefield imaging. The laser scanning process was performed based on both a raster scan and a circle scan. From the high-resolution
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