• Title/Summary/Keyword: real-time damage detection

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ANN-based Real-Time Damage Detection Algorithm using Output-only Acceleration Signals (가속도를 이용한 인공신경망 기반 실시간 손상검색기법)

  • Kim, Jung-Tae;Park, Jae-Hyung;Do, Han-Sung
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.43-48
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    • 2007
  • In this study, an ANN-based damage detection algorithm using acceleration signals is developed for alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed for damage detection in real time. The cross-covariance of two acceleration signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained for potential loading patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.

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A statistical reference-free damage identification for real-time monitoring of truss bridges using wavelet-based log likelihood ratios

  • Lee, Soon Gie;Yun, Gun Jin
    • Smart Structures and Systems
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    • v.12 no.2
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    • pp.181-207
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    • 2013
  • In this paper, a statistical reference-free real-time damage detection methodology is proposed for detecting joint and member damage of truss bridge structures. For the statistical damage sensitive index (DSI), wavelet packet decomposition (WPD) in conjunction with the log likelihood ratio was suggested. A sensitivity test for selecting a wavelet packet that is most sensitive to damage level was conducted and determination of the level of decomposition was also described. Advantages of the proposed method for applications to real-time health monitoring systems were demonstrated by using the log likelihood ratios instead of likelihood ratios. A laboratory truss bridge structure instrumented with accelerometers and a shaker was used for experimental verification tests of the proposed methodology. The statistical reference-free real-time damage detection algorithm was successfully implemented and verified by detecting three damage types frequently observed in truss bridge structures - such as loss of bolts, loosening of bolts at multiple locations, sectional loss of members - without reference signals from pristine structure. The DSI based on WPD and the log likelihood ratio showed consistent and reliable results under different damage scenarios.

Real-time structural damage detection using wireless sensing and monitoring system

  • Lu, Kung-Chun;Loh, Chin-Hsiung;Yang, Yuan-Sen;Lynch, Jerome P.;Law, K.H.
    • Smart Structures and Systems
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    • v.4 no.6
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    • pp.759-777
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    • 2008
  • A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

Real-time Failure Detection of Composite Structures Using Optical Fiber Sensors (광섬유 센서를 이용한 복합재 구조물의 실시간 파손감지)

  • 방형준;강현규;류치영;김대현;강동훈;홍창선;김천곤
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2000.11a
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    • pp.128-133
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    • 2000
  • The objective of this research is to develop real-time failure detection techniques for damage assessment of composite materials using optical fiber sensors. Signals from matrix cracking or fiber fracture in composite laminates are treated by signal processing unit in real-time. This paper describes the implementation of time-frequency analysis such as the Short Time Fourier Transform(STFT) to determine the time of occurrence of failure. In order to verify the performance of the optical fiber sensor for stress wave detection, we performed pencil break test with EFPI sensor and compared it with that of PZT. The EFPI sensor was embedded in composite beam to sense the failure signals and a tensile test was performed. The signals of the fiber optic sensor when damage occurred were characterized using STFT and wavelet transform. Failure detection system detected the moment of failure accurately and showed good sensitivity with the infinitesimal failure signal.

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Acceleration-based neural networks algorithm for damage detection in structures

  • Kim, Jeong-Tae;Park, Jae-Hyung;Koo, Ki-Young;Lee, Jong-Jae
    • Smart Structures and Systems
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    • v.4 no.5
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    • pp.583-603
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    • 2008
  • In this study, a real-time damage detection method using output-only acceleration signals and artificial neural networks (ANN) is developed to monitor the occurrence of damage and the location of damage in structures. A theoretical approach of an ANN algorithm that uses acceleration signals to detect changes in structural parameters in real-time is newly designed. Cross-covariance functions of two acceleration responses measured before and after damage at two different sensor locations are selected as the features representing the structural conditions. By means of the acceleration features, multiple neural networks are trained for a series of potential loading patterns and damage scenarios of the target structure for which its actual loading history and structural conditions are unknown. The feasibility of the proposed method is evaluated using a numerical beam model under the effect of model uncertainty due to the variability of impulse excitation patterns used for training neural networks. The practicality of the method is also evaluated from laboratory-model tests on free-free beams for which acceleration responses were measured for several damage cases.

Infrared Thermography Quantitative Diagnosis in Vibration Mode of Rotational Mechanics

  • Seo, Jin-Ju;Choi, Nam-Ryoung;Kim, Won-Tae;Hong, Dong-Pyo
    • Journal of the Korean Society for Nondestructive Testing
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    • v.32 no.3
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    • pp.291-295
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    • 2012
  • In the industrial field, real-time monitoring system like a fault early detection is very important. For this, the infrared thermography technique as a new diagnosis method is proposed. This study is focused on the damage detection and temperature characteristic analysis of ball bearing using the non-destructive infrared thermography method. In this paper, thermal image and temperature data were measured by a Cedip Silver 450 M infrared camera. Based on the results, the temperature characteristics under the conditions of normal, loss lubrication, damage, dynamic loading, and damage under loading were analyzed. It was confirmed that the infrared technique is very useful for the detection of the bearing damage.

Comparison of FEA with Condition Monitoring for Real-Time Damage Detection of Bearing Using Infrared Thermography Techniques (적외선열화상을 이용한 베어링 실시간 손상검출 상태감시의 전산수치해석 비교)

  • Kim, Hojong;Kim, Wontae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.35 no.3
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    • pp.185-192
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    • 2015
  • Since real-time monitoring systems, such as early fault detection, have been very important, an infrared thermography technique was proposed as a new diagnosis method. This study focused on damage detection and temperature characteristic analysis of ball bearings using the non-destructive, infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with finite element analysis (FEA) results from ANSYS. In this investigation, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally, it was confirmed that the infrared thermography technique was useful for the real-time detection of damage to bearings.

ANN-Based Real-Time Damage Detection Technique Using Acceleration Signals in Beam-Type Structures (보 구조물의 가속도 신호를 이용한 인공신경망 기반 실시간 손상검색기법)

  • Park, Jae-Hyung;Lee, Yong-Hwan;Kim, Jeong-Tae
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.20 no.3
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    • pp.229-237
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    • 2007
  • In this study, an artificial neural network (ANN)-based damage detection algorithm using acceleration signals is developed for real-time alarming locations of damage in beam-type structures. A new ANN-algorithm using output-only acceleration responses is designed tot damage detection in real time. The cross-covariance of two acceleration-signals measured at two different locations is selected as the feature representing the structural condition. Neural networks are trained lot potential loading Patterns and damage scenarios of the target structure for which its actual loadings are unknown. The feasibility and practicality of the proposed method are evaluated from laboratory-model tests on free-free beams for which accelerations were measured before and after several damage cases.

Developing a smart structure using integrated DDA/ISMP and semi-active variable stiffness device

  • Karami, Kaveh;Nagarajaiah, Satish;Amini, Fereidoun
    • Smart Structures and Systems
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    • v.18 no.5
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    • pp.955-982
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    • 2016
  • Recent studies integrating vibration control and structural health monitoring (SHM) use control devices and control algorithms to enable system identification and damage detection. In this study real-time SHM is used to enhance structural vibration control and reduce damage. A newly proposed control algorithm, including integrated real-time SHM and semi-active control strategy, is presented to mitigate both damage and seismic response of the main structure under strong seismic ground motion. The semi-active independently variable stiffness (SAIVS) device is used as semi-active control device in this investigation. The proper stiffness of SAIVS device is obtained using a new developed semi-active control algorithm based on real-time damage tracking of structure by damage detection algorithm based on identified system Markov parameters (DDA/ISMP) method. A three bay five story steel braced frame structure, which is equipped with one SAIVS device at each story, is employed to illustrate the efficiency of the proposed algorithm. The obtained results show that the proposed control algorithm could significantly decrease damage in most parts of the structure. Also, the dynamic response of the structure is effectively reduced by using the proposed control algorithm during four strong earthquakes. In comparison to passive on and off cases, the results demonstrate that the performance of the proposed control algorithm in decreasing both damage and dynamic responses of structure is significantly enhanced than the passive cases. Furthermore, from the energy consumption point of view the maximum and the cumulative control force in the proposed control algorithm is less than the passive-on case, considerably.

A Study on Real-Time Fault Monitoring Detection Method of Bearing Using the Infrared Thermography (적외선 열화상을 이용한 베어링의 실시간 고장 모니터링 검출기법에 관한 연구)

  • Kim, Ho-Jong;Hong, Dong-Pyo;Kim, Won-Tae
    • Journal of the Korean Society for Nondestructive Testing
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    • v.33 no.4
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    • pp.330-335
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    • 2013
  • Since real-time monitoring system like a fault early detection has been very important, infrared thermography technique as a new diagnosis method was proposed. This study is focused on the damage detection and temperature characteristic analysis of ball bearing using the non-destructive infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with the frequency data of the existing. As results, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally it was confirmed that the infrared technique was useful for real-time detection of the bearing damages.