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Damage detection in beam-like structures using static shear energy redistribution

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 12,   Pages 1552-1564 doi: 10.1007/s11709-022-0903-4

Abstract: In this study, a static shear energy algorithm is presented for the damage assessment of beam-like structuresthe energy release principle, the strain energy of a damaged element suddenly changes when structural damageTherefore, the change in the static shear energy is employed to determine the damage locations in beam-likeis that only a few deflection data points of the beam structure are required during the process of damageAnother advantage of the proposed approach is that damage detection can be performed without establishing

Keywords： damage detection     beam structure     strain energy     static displacement variation     energy damage index    

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Multiple damage detection in complex bridges based on strain energy extracted from single point measurement

Alireza ARABHA NAJAFABADI, Farhad DANESHJOO, Hamid Reza AHMADI

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 3,   Pages 722-730 doi: 10.1007/s11709-020-0624-5

Abstract: Strain Energy of the structure can be changed with the damage at the damage location.The accurate detection of the damage location using this index in a force system is dependent on thedegree of accuracy in determining the structure deformation function before and after damage.Then two damage detection indicators were developed based on strain energy variations.Damage was simulated by decreasing stiffness at different sections of the deck.

Keywords： damage detection     strain energy     influence line     complex bridges     rotation displacement    

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An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 907-929 doi: 10.1007/s11709-020-0628-1

Abstract: In this study, the performance of an efficient two-stage methodology which is applied in a damage detectionIn the first stage, in order to locate the damage accurately, the performance of the modal strain energyIn the second stage, to estimate the damage extent, the sensitivity of most used modal properties dueto damage, such as natural frequency and flexibility matrix is compared with the mean normalized modalvector is evaluated using the group method of data handling (GMDH) network as a surrogate model during damage

Keywords： two-stage method     modal strain energy     surrogate model     GMDH     optimization damage detection    

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Static-based early-damage detection using symbolic data analysis and unsupervised learning methods

João Pedro SANTOS,Christian CREMONA,André D. ORCESI,Paulo SILVEIRA,Luis CALADO

Frontiers of Structural and Civil Engineering 2015, Volume 9, Issue 1,   Pages 1-16 doi: 10.1007/s11709-014-0277-3

Abstract: been recently performed by applying statistical and machine learning techniques for vibration-based damagedetection.number of modal properties issued from operational modal analysis may be not appropriate for early-damageThe present paper aims at detecting this type of damage by using static SHM data and by assuming thatearly-damage produces dead load redistribution.

Keywords： structural health monitoring     early-damage detection     principal component analysis     symbolic data     symbolicdissimilarity measures     cluster analysis     numerical model     damage simulations    

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A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 6,   Pages 1453-1479 doi: 10.1007/s11709-021-0767-z

Abstract: This paper proposes a new Deep Feed-forward Neural Network (DFNN) approach for damage detection in functionallythe proposed approach, the DFNN model is developed based on a data set containing 20 000 samples of damagetranslational nodal displacements of the structures, are utilized as input of the DFNN model while the damageObtained results indicate that the proposed DFNN model is able to give sufficiently accurate damage detection

Keywords： damage detection     deep feed-forward neural networks     functionally graded carbon nanotube-reinforced composite    

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Detection of oxidative stress and DNA damage in freshwater snail

Daoud Ali, Huma Ali, Saud Alifiri, Saad Alkahtani, Abdullah A Alkahtane, Shaik Althaf Huasain

Frontiers of Environmental Science & Engineering 2018, Volume 12, Issue 5, doi: 10.1007/s11783-018-1039-6

Abstract:

Freshwater snail (Lymnea luteola L.) is good bio indicator of water pollution.

Profenofos is tested for its molluscicidal activity against Lymnea luteola L. snail.

Deleterious effects on some oxidative stress were detected.

Profenofos has a genotoxic effect on Lymnea luteola L. snails.

Keywords： Acute toxicity     Profenofos     ROS     oxidative stress     DNA damage     Lymnea luteola    

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Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 8,   Pages 1281-1294 doi: 10.1007/s11709-023-0975-9

Abstract: Subsequently, various indices for the damage diagnosis of concrete structures based on the curvatureA damage assessment method for concrete structures is established using an artificial bee colony backpropagationThe proposed damage assessment method for dam concrete structures comprises various modal parameters,The results show that the damage assessment model can accurately evaluate the damage degree of concretestructures with a maximum error of less than 2%, which is within the required accuracy range of damage

Keywords： hydraulic structure     curvature mode     damage detection     artifical neural network     artificial bee colony    

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Detection of damage locations and damage steps in pile foundations using acoustic emissions with deep

Alipujiang JIERULA, Tae-Min OH, Shuhong WANG, Joon-Hyun LEE, Hyunwoo KIM, Jong-Won LEE

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 318-332 doi: 10.1007/s11709-021-0715-y

Abstract: The aim of this study is to propose a new detection method for determining the damage locations in pileFirst, the damage location is simulated using a back propagation neural network deep learning model withIn particular, the damage location is identified using two parameters: the pile location ( ) and theSecond, the damage step condition is determined using a classification model with an acoustic emissionFinally, a new damage detection and evaluation method for pile foundations is proposed.

Keywords： pile foundations     damage location     acoustic emission     deep learning     damage step    

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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 3,   Pages 393-410 doi: 10.1007/s11709-024-1060-8

Abstract: The paper introduces a novel approach for detecting structural damage in full-scale structures usingapproach involves training a single surrogate model that can quickly predict the location and severity of damageThis approach also shows potential for broader applications in structural damage detection.

Keywords： vibration-based damage detection     deep neural network     full-scale structures     finite element model updating    

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Uncertainty quantification of stability and damage detection parameters of coupled hydrodynamic-ground

Nazim Abdul NARIMAN, Tom LAHMER, Peyman KARAMPOUR

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 2,   Pages 303-323 doi: 10.1007/s11709-018-0462-x

Abstract: The non coupled models results determined overestimated predicted stability and damage detection in theThe XFEM approach has been used for damage detection in relation with both minimum and maximum values

Keywords： massed foundation     hydrodynamic pressure     Box-Behnken method     meta model     Sobol’s sensitivity indices    

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Development of temperature-robust damage factor based on sensor fusion for a wind turbine structure

Jong-Woong PARK,Sung-Han SIM,Jin-Hak YI,Hyung-Jo JUNG

Frontiers of Structural and Civil Engineering 2015, Volume 9, Issue 1,   Pages 42-47 doi: 10.1007/s11709-014-0285-3

Abstract: Vibration-based damage detection has widely been researched to identify damages on a structure baseddetection capability; mode shapes are less influenced by temperature variation and able to locate damageThis study proposes novelty of damage factor based on sensor fusion to exclude effect of temperatureThe combined use of an accelerometer and an inclinometer was considered and damage factor was definedof sensor, 2) robustness to change in temperature and signal noise and 3) ability to roughly locate damage

Keywords： sensor fusion     damage detection     structural health monitoring    

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Crack identification in concrete, using digital image correlation and neural network

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 4,   Pages 536-550 doi: 10.1007/s11709-024-1013-2

Abstract: Therefore, more comprehensive detection of concrete damage under different scenarios is of high value

Keywords： digital image correlation     convolutional neural network     back propagation neural neural network     damagedetection     concrete    

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Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target Research Article

Xiao YANG, Chun YIN, Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU,yinchun.86416@163.com,chunyin@uestc.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 571-586 doi: 10.1631/FITEE.2000695

Abstract: To detect spacecraft damage caused by hypervelocity impact, we propose an advanced spacecraft defectextraction algorithm based on infrared imaging detection.multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used for optimization to ensure damage

Keywords： Hypervelocity impact damage     Defect detection     Gaussian mixture model     Image segmentation    

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Corrosion damage assessment and monitoring of large steel space structures

Bo CHEN, You-Lin XU, Weilian QU,

Frontiers of Structural and Civil Engineering 2010, Volume 4, Issue 3,   Pages 354-369 doi: 10.1007/s11709-010-0088-0

Abstract: This paper proposes a framework for assessing the corrosion damage of large steel space structures subjectedreal large steel space structure built in the southern coastal area in China to assess its corrosion damage

Keywords： large steel space structure     atmospheric corrosion     stress corrosion cracking     corrosion damage     damage assessment    

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Windborne debris damage prediction analysis

Fangfang SONG, Jinping OU,

Frontiers of Structural and Civil Engineering 2010, Volume 4, Issue 3,   Pages 326-330 doi: 10.1007/s11709-010-0067-5

Abstract: Windborne debris is one of the most important causes of the envelop destruction according to the post-damageThe problem of windborne debris damage could be summarized as three parts, including windborne debrisBesides, the process of windborne debris damage analysis is described in detail.

Keywords： typhoon     windborne debris     structural envelopes     damage estimation    

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Title Author Date Type Operation

Damage detection in beam-like structures using static shear energy redistribution

Journal Article

Multiple damage detection in complex bridges based on strain energy extracted from single point measurement

Alireza ARABHA NAJAFABADI, Farhad DANESHJOO, Hamid Reza AHMADI

Journal Article

An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Journal Article

Static-based early-damage detection using symbolic data analysis and unsupervised learning methods

João Pedro SANTOS,Christian CREMONA,André D. ORCESI,Paulo SILVEIRA,Luis CALADO

Journal Article

A deep feed-forward neural network for damage detection in functionally graded carbon nanotube-reinforced

Journal Article

Detection of oxidative stress and DNA damage in freshwater snail

Daoud Ali, Huma Ali, Saud Alifiri, Saad Alkahtani, Abdullah A Alkahtane, Shaik Althaf Huasain

Journal Article

Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning

Journal Article

Detection of damage locations and damage steps in pile foundations using acoustic emissions with deep

Alipujiang JIERULA, Tae-Min OH, Shuhong WANG, Joon-Hyun LEE, Hyunwoo KIM, Jong-Won LEE

Journal Article

A deep neural network based surrogate model for damage identification in full-scale structures with incomplete

Journal Article

Uncertainty quantification of stability and damage detection parameters of coupled hydrodynamic-ground

Nazim Abdul NARIMAN, Tom LAHMER, Peyman KARAMPOUR

Journal Article

Development of temperature-robust damage factor based on sensor fusion for a wind turbine structure

Jong-Woong PARK,Sung-Han SIM,Jin-Hak YI,Hyung-Jo JUNG

Journal Article

Crack identification in concrete, using digital image correlation and neural network

Journal Article

Spacecraft damage infrared detection algorithm for hypervelocity impact based on double-layer multi-target

Xiao YANG, Chun YIN, Sara DADRAS, Guangyu LEI, Xutong TAN, Gen QIU,yinchun.86416@163.com,chunyin@uestc.edu.cn

Journal Article

Corrosion damage assessment and monitoring of large steel space structures

Bo CHEN, You-Lin XU, Weilian QU,

Journal Article

Windborne debris damage prediction analysis

Fangfang SONG, Jinping OU,

Journal Article