• Title/Summary/Keyword: Local damage detection

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Damage Detection in Bridges Using Modal Flexibility Matrices Under Temperature Variation (상시 온도변화 효과를 고려한 모드 유연도행렬 기반의 교량의 손상탐색기법)

  • Koo, Ki-Young;Lee, Jong-Jae;Yun, Chung-Bang
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.651-656
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    • 2007
  • Changes in measured structural responses induced by a damage could be significantly smaller than those by environmental effects such as temperature and temperature gradients. It is highly desirable to develop a methodology to distinguish the changes due to the structural damage from those by the environmental variations. In this study, a novel method to extract the damage-induced deflection under temperature variations is presented using the outlier analysis on the deflections obtained using the modal flexibility matrices. The main idea is that temperature change in a bridge would produce global increase or decrease in deflections over the whole bridge while structural damages may cause local variations in deflections near the damage locations. Hence, the correlation between the deflection measurements may show high abnormality near the damage locations. A series of laboratory tests were carried out on a bridge model with a steel box-girder for 14 days. It has been found that the damage existence assessment and localization can carried out for a case with relatively small damage under the temperature variations

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A decentralized approach to damage localization through smart wireless sensors

  • Jeong, Min-Joong;Koh, Bong-Hwan
    • Smart Structures and Systems
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    • v.5 no.1
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    • pp.43-54
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    • 2009
  • This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

Advances and challenges in impedance-based structural health monitoring

  • Huynh, Thanh-Canh;Dang, Ngoc-Loi;Kim, Jeong-Tae
    • Structural Monitoring and Maintenance
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    • v.4 no.4
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    • pp.301-329
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    • 2017
  • Impedance-based damage detection method has been known as an innovative tool with various successful implementations for structural health monitoring of civil structures. To monitor the local critical area of a structure, the impedance-based method utilizes the high-frequency impedance responses sensed by piezoelectric sensors as the local dynamic features. In this paper, current advances and future challenges of the impedance-based structural health monitoring are presented. Firstly, theoretical background of the impedance-based method is outlined. Next, an overview is given to recent advances in the wireless impedance sensor nodes, the interfacial impedance sensing devices, and the temperature-effect compensation algorithms. Various research works on these topics are reviewed to share up-to-date information on research activities and implementations of the impedance-based technique. Finally, future research challenges of the technique are discussed including the applicability of wireless sensing technology, the predetermination of effective frequency bands, the sensing region of impedance responses, the robust compensation of noise and temperature effects, the quantification of damage severity, and long-term durability of sensors.

Novel Islanding Detection Method using Frequency Drift for Grid-connected PV System (계통연계형 태양광발전 시스템의 주파수 변동에 의한 새로운 고립운전 검출기법)

  • Eun Suk-Jun;;;Lee Dong-Chun
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.54 no.6
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    • pp.294-302
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    • 2005
  • PV system's islanding occurs when the uitilty grid is removed but local sources continue to operate and provide power to local loads. Islanding is one of the serious problems in an electric power system connected with dispersed power sources. Also, this can present safety hazards and the possibility of damage to other electric equipments. If the real and reactive power of RLC load and PV system are closely matched, islanding detection by passive methods becomes difficult. This paper shows the simulation and comparision for the previous active methods and novel islanding detection method using frequency drift is proposed for grid-connected PV system.

Deep learning of sweep signal for damage detection on the surface of concrete

  • Gao Shanga;Jun Chen
    • Computers and Concrete
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    • v.32 no.5
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    • pp.475-486
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    • 2023
  • Nondestructive evaluation (NDE) is an important task of civil engineering structure monitoring and inspection, but minor damage such as small cracks in local structure is difficult to observe. If cracks continued expansion may cause partial or even overall damage to the structure. Therefore, monitoring and detecting the structure in the early stage of crack propagation is important. The crack detection technology based on machine vision has been widely studied, but there are still some problems such as bad recognition effect for small cracks. In this paper, we proposed a deep learning method based on sweep signals to evaluate concrete surface crack with a width less than 1 mm. Two convolutional neural networks (CNNs) are used to analyze the one-dimensional (1D) frequency sweep signal and the two-dimensional (2D) time-frequency image, respectively, and the probability value of average damage (ADPV) is proposed to evaluate the minor damage of structural. Finally, we use the standard deviation of energy ratio change (ERVSD) and infrared thermography (IRT) to compare with ADPV to verify the effectiveness of the method proposed in this paper. The experiment results show that the method proposed in this paper can effectively predict whether the concrete surface is damaged and the severity of damage.

A hybrid self-adaptive Firefly-Nelder-Mead algorithm for structural damage detection

  • Pan, Chu-Dong;Yu, Ling;Chen, Ze-Peng;Luo, Wen-Feng;Liu, Huan-Lin
    • Smart Structures and Systems
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    • v.17 no.6
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    • pp.957-980
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    • 2016
  • Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

Damage Detection in Shear Building Based on Genetic Algorithm Using Flexibility Matrix (유연도 행렬을 이용한 전단빌딩의 유전자 알고리즘 기반 손상추정)

  • Na, Chae-Kuk;Kim, Sun-Pil;Kwak, Hyo-Gyoung
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.21 no.1
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    • pp.1-11
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    • 2008
  • Stiffness estimation of a shear building due to local damages is usually achieved though structural analysis based on the assumed material properties and idealized numerical modeling of structure. Conventional numerical modeling, however, frequently causes an inevitable error in the structural response and this makes it difficult to exactly predict the damage state in structure. To solve this problem, this paper introduces a damage detection technique for shear building using genetic algorithm. The introduced algorithm evaluates the damage in structure using a flexibility matrix since the flexibility matrix can exactly be obtained from the field test in spite of using a few lower dynamic modes of structure. The introduced algorithm is expected to be more effectively used in damage detection of structures rather than conventional method using the stiffness matrix. Moreover, even in cases when an accurate measurement of structural stiffness cannot be expected, the proposed technique makes it possible to estimate the absolute change in stiffness of the structure on the basis of genetic algorithm. The validity of the proposed technique is demonstrated though numerical analysis using OPENSEES.

Fault Detections of Ring Structures using Vibration Modes (진동모드를 이용한 링 구조물의 결함 탐지)

  • Kim, Seock-Hyun;Jang, Ho-Sik
    • Journal of Industrial Technology
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    • v.22 no.A
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    • pp.29-36
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    • 2002
  • A damage detection algorithm using vibration modes is applied to the ring structures and the modal behaviors of the slightly asymmetric rings are examined. Mode shape change, MSER(modal strain energy ratio) and MCR(modal curvature ratio) are investigated to identify the locations of faults or damages The above fault detection parameters are calculated and compared by the finite element analysis on rings with designed local damages. Damages are modeled as a reduced stiffness in the analysis The results show that MSER and MCR can be proper parameters to detect local damages in the ring structures.

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Performance Improvement of Islanding Detection Technique in Photo-Voltaic System (계통 연계형 PV 시스템의 고립운전 검출기법의 성능개선)

  • Choi, Chul-Hoon;Choi, Jong-Woo
    • Proceedings of the KIPE Conference
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    • 2011.07a
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    • pp.378-379
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    • 2011
  • PV system's islanding occurs when the uitilty grid is removed but local sources continue to operate and provide power to local loads. Islanding is one of the serious problems in an electric power system connected with dispersed power sources. Also, this can present safety hazards and the possibility of damage to other electric equipments. If the real and reactive power of RLC load and PV system are closely matched, islanding detection by passive methods becomes difficult. Novel islanding detection method is proposed for grid-connected PV system.

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Novel Islanding Detection Method using Frequency Drift for Grid-connected PV System (계통연계형 PV 시스템의 주파수 변동에 의한 새로운 단독운전 검출기법)

  • Eun Seog-Jun;Choi Jong-Woo;Kim Heung-Geun
    • Proceedings of the KIPE Conference
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    • 2004.11a
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    • pp.133-137
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    • 2004
  • PV system's islanding occurs when the uitilty grid is removed but local sources continue to operate and provide power to local loads. Islanding is one of the serious problems m an electric power system connected with dispersed power sources. Also, this can present safety hazards and the possibility of damage to other electric equipments. If the real and reactive power of RLC load and PV system are closely matched, islanding detection by passive methods becomes difficult. Novel islanding detection method using frequency drift is proposed for grid-connected PV system.

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