Papers by Keyword: Structural Health Monitoring (SHM)

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Authors: In Pil Kang, Mark J. Schulz, Jong Won Lee, Gyeong Rak Choi, Joo Yung Jung, Jae Boong Choi, Sung Ho Hwang
Abstract: This study introduces a nano smart material to develop a novel sensor for Structural Health Monitoring (SHM) of mechanical and civil systems. Mechanical, civil, and environmental systems need to become self-sensing and intelligent to preserve their integrity, optimize their performance, and provide continuous safety for the users and operators. Present smart materials and structures have fundamental limitations in their sensitivity, size, cost, ruggedness, and weight. Smart materials developed using nanotechnology have the potential to improve the way we generate and measure motion in devices from the nano to the macro scale in size. Among several possible smart nanoscale materials, Carbon Nanotubes (CNT) have aroused great interest in the research community because of their remarkable mechanical, electrochemical, piezoresistive, and other physical properties. To address the need for new intelligent sensing based on CNT, this study presents piezoresistivity and electrochemical properties and preliminary experiments that can be applied for SHM. This study is anticipated to develop a new multifunctional sensor which can simultaneously monitor strain, stress and corrosion on a structure with a simple electric circuit.
Authors: Shi Feng Huang, Jun Chang, Lei Qin, Xiao Ming Yang, Zong Jin Li, Xin Cheng
Abstract: A cement based piezoelectric composite sensor using 1-3 cement based piezoelectric composite as sensing element was fabricated. The basic properties of the sensor were mainly investigated. The results indicate that in the frequency range from 0.1 to 40 Hz, the output voltage amplitudes of the sensor increase nonlinearly with increasing frequency of input load under 10 Hz. When the frequency of input load is larger than about 10 Hz, the output voltage amplitudes of the sensor is nearly independent of frequency. There exists an obviously linear relationship between the output voltage amplitude of the sensor and input load amplitude. The output voltage of the sensor is correspond to the complex load very well. The phase difference between the output voltage of the sensor and input load is near zero. Therefore such sensors have a good potential to be used in civil engineering structural health monitoring.
Authors: Ekhi Zugasti, Ana Gomez Gonzalez, Javier Anduaga, Miguel Angel Arregui, Fernando Martínez
Abstract: In the present paper, we introduce an application of two damage detection methods to a laboratory structure. One of the methods is based on autoregressive modeling of the signals involved, whereas the second one is based on subspace identification. Both have been tested in a tower that simulates a wind turbine. The results obtained are correct for the damages simulated by loosening some bolts of the different joints. The results show that the second method is computationally more efficient whereas the results are more stable in the first one.
Authors: Hoon Sohn, Charles R. Farrar, Francois M. Hemez, Gyuhae Park, Amy N. Robertson, Todd O. Williams
Authors: Ling Ling Lu, Chen Guang Huang, Xi Wang
Abstract: A damage identification method based on differential gradient of normalized strain (DGNS) is presented to overcome the disadvantages of traditional static damage identification, such as the complicacy of measurement system and the limited measurement points etc. Two numerical simulations were conducted on a dog-bone specimen to verify the feasibility of the method. In the experiment, differential of strain contour density (DSCD), which has the same physical meaning with DGNS,significantly improves the smoothness and visualization of field information. Both the simulation and experiment results show that, DGNS (DSCD) is capable of describing the structural damage property meanwhile effectively isolates the damaged areas from regions with inhomogeneous deformation due to geometric inhomogeneity. Moreover, DGNS (DSCD) is a structural intrinsic parameter, and independent on external loads.
Authors: Yong Ming Fu, Ling Yu
Abstract: The development of a methodology for the accurate and reliable assessment of structural damages, as one crucial step in the structural health monitoring (SHM) field, is very important to ensure the safety, integrity and stability of structures. An improved adaptive differential evolution (IADE) algorithm is proposed for structural damage detection (SDD) based on DE algorithm and FE model-updating techniques. An objective function is defined as minimizing the discrepancies between the experimental and analytical modal parameters (namely, natural frequencies and mode shapes). It is set as a nonlinear least-squares problem with bound constraints. Unlike the commonly used line-search methods, the IADE approach, a heuristic method for the direct search of the optimal point of the given objective function, is employed to make the optimization process more robust and reliable. Some numerical simulations for single and multiple damage cases of a 25-bar space truss frame structure have been conducted for evaluation on the reliability and robustness of the proposed method. The illustrated results show that the IADE algorithm is very effective for SDD. It can not only locate the structural damages but also quantify the severity of damages. Regardless of slight damage or multiple damages, the identification accuracy is very high and noise immunity is better, which shows that the IADE algorithm is feasible and effective for SDD.
Authors: Yan Hui Zhang, Wen Yu Yang
Abstract: This paper researches a robust damage identification system considering the effects of the environmental and operational conditions based on distributed fiber Bragg grating system. Initially a well-verified method is used to identify damage, but the failure result is obtained. The environmental and operational variations causing the false-positive indication are analyzed, such as the temperature, the change of the excitation and the relaxation phenomenon of the sensors. The Hilbert-Huang Transform method is used to decompose the dynamic strain signal into several intrinsic mode function components, the physical meanings of which are discussed. Then the second level component is used as the damage-induced signal component. Lastly the damage index based on the autoregressive model and Mahalanobis distance is constructed to detect and locate damage.
Authors: Xing Hua Chen, Piotr Omenzetter
Abstract: Because of the critical role that bridges play in land transport networks and broader economy, the assessment of existing bridges is gradually becoming a global concern. Structural health monitoring (SHM) systems have been installed on many bridges to provide data for the evaluation of bridge performance and safety. The challenge for bridge engineers is now to make use of the data and convert them into usable information and knowledge. Integrating SHM data with reliability analysis procedures offers a useful and practical methodology for bridge assessment since reliability is an important performance index and reliability-based procedures have the capability of accommodating uncertainties in structural models, responses, loads and monitoring data. In this paper, an approach for integrating SHM data in a reliability assessment framework is proposed. The reliability of the bridge is quantified by incorporating SHM information in the resistance, load and structural models. Advanced modeling tools and techniques, such as finite element analysis, finite model updating and Bayesian updating, are used for the reliability computations. Data from the SHM system installed on the Newmarket Viaduct, a newly constructed, 12-span, post-tensioned box girder bridge erected by the balanced cantilever method in Auckland, New Zealand, are also presented in this paper and used to explain the proposed framework.
Authors: Chen Ning Cai, Gang Yan
Abstract: This paper presents a genetic algorithm (GA)-based approach for localizing damage in plate-like structure. Diagnostic Lamb wave is excited into structure before and after damage to obtain scattered wave that contain characteristic information of the damage. After the time-of-flight (ToF) of the scattered wave in each actuator-sensor path is measured by continuous wavelet transform (CWT), a GA optimization procedure is developed to adaptively identify the location of damage without knowing the material properties a priori. It is achieved by minimizing the difference between the measured and calculated ToF of the scattered Lamb wave. Experimental study for an aluminium plate is conducted to validate the proposed damage localization approach.
Authors: Yan Sheng Song, Zong Guang Sun, Nai Zhi Zhao
Abstract: This paper demonstrates a new abnormal index based on frequency change for structural health monitoring (SHM) which utilizes probability and statistics method. And it was introduced to analyze a steel frame. The results show it could indicate the abnormity of corresponding test cases clearly.
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