• Journal of the Korea institute for structural maintenance and inspection
• /
• v.18 no.1
• /
• pp.138-149
• /
• 2014

This study proposes an estimation method of strain distribution for multi-span steel beam structure under unspecific loading conditions. The estimation method in this paper employs the curve fitting using the least square method from measured strain data, not analytical method. To verify the proposed estimation method, a static loading test for multi-span steel beam on which distributed and concentrated loads act was conducted. The strain data for verification was measured by FBG sensors that have multiplexing technology. The analysis of the accuracy of strain estimation for distributed and concentrated loads and the errors by considering the number of measured points used in the estimation were conducted. In the maximum strain points, the strains could be estimated with the errors of 5.89% (loading step 1) and 6.26% (loading step 2). In case of decreasing the number of sensors, it was also confirmed that the errors increased (0.26~0.37%). Through the curve fitting method, it is possible to estimate the strain distribution (maximum strains and their locations) of multi-span beam for unspecific loads and go over the limit of the analytical estimation method which is suitable for specific distributed loads.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2010.04a
• /
• pp.704-707
• /
• 2010

구조 건전성 모니터링에 사용되는 기존 센서들의 문제점을 극복하고 높은 분해능과 동특성 모니터링에 대한 이점을 지닌 FBG센서는 구조물 모니터링에 있어 큰 이점을 지니고 있다. FBG 센서는 점 센서라는 한계 때문에 구조물의 전체적인 변형률 및 응력 평가에 어려움이 있을 수 있다. 본 연구에서는 FBG 센서로부터 계측한 변형률 값들로부터 임의의 하중조건에서 철골 보의 변형률 분포를 추정하는 기법을 제시하였다. 임의의 개별 하중조건에 대해 FBG 센서로 계측된 값을 통해 센서의 부착 위치와 최소 필요 개수를 결정하고 변형률 추정식을 유도함으로써 FBG 센서의 계측 기법에 대한 기준을 세웠다. 나아가 임의의 조합 하중이 작용하는 실제의 경우를 고려하여 철골 보의 변형률 분포를 추정하는 보다 일반화된 수학적 모델을 제시하였다. 그리고 예제를 통하여 본 연구에서 제시한 변형률 분포 추정 모델을 검증하였다.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.20 no.3
• /
• pp.18-24
• /
• 2016

This study presents a simple method which can estimate displacement using measured strain response of simply supported girder bridges. The basic concept of the present method is derived from a relation between displacement and strain, and is generalized by introducing analytical tool. Static and dynamic laboratory test are conducted on simply supported plate which is designed to respond dynamically similar to actual bridges to experimentally verify the present method, and displacement and strain are measured at the midpoint of specimen. Displacement estimated by using measured strain is well agreed with measured one. This study demonstrates that the present method is suitable for estimating displacement of real simply supported bridge, in which the installation of a displacement transducer at the fixed reference point is difficult.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.17 no.2
• /
• pp.10-20
• /
• 2013

To evaluate the safety of a beam structure, strains are measured as an indicator of structural states. However, unless strain sensors are installed exactly on where maximum or other representative strains occur, the techniques by which rational assessment through measured strains is accomplished are required. Thus, this study suggests a process to estimate strain distribution on the steel beam from discrete strains measured by sensors. In the presented technique, the targeted beam is regarded to be subjected to unknown loads so that applicability is enhanced. Final strain distribution is given as form of a function after regression analysis. To verify the performance of estimation, a bending test for steel beam on which distributed and concentrated loads simultaneously act is conducted. From the comparison between estimated and directly measured strains in the test, the curve of strain distribution and the strain at arbitrary location could be predicted within maximum relative error 3.32% and maximum absolute error of $2.32{\mu}{\varepsilon}$, respectively. Thus reliable and practical monitoring is expected to apply effectively for the steel beam structure.

• Journal of the Korean Society for Railway
• /
• v.19 no.6
• /
• pp.755-764
• /
• 2016

In this paper, to verify the field application of a displacement estimation technique based on the relationship between displacement and strain, static and dynamic field load test are performed on three-span continuous real bridge structures. The superstructure types of the test bridges are IPC girder highway bridge and steel box girder AGT bridge. LVDTs and strain gauges are attached to them; then, the responses due to test vehicle are measured. To obtain the displacement-strain relationship of the test bridges, the bridges are modeled as grillage system with 6 DOFs for the purpose of structural analyses. Static and dynamic displacements, which are estimated using both the calculated displacement-strain relationship and the measured strain signal, agree well with the values measured by LVDT. This study demonstrates that the displacement estimation technique using the strain signal can be effectively applied to the displacement measurement of bridge structures that cross rivers/roads/railways or have high clearance.

• Journal of the Korea Concrete Institute
• /
• v.21 no.2
• /
• pp.121-127
• /
• 2009

The failure behavior of RC structure was exceedingly affected by the size and the local strain distribution of the failure zone due to the strain localization behavior on the tension softening materials. However, it is very difficult to quantify and assess the local strain occurring in the failure zone by the conventional test method. In this study, image processing technology, which is available to measure the strain up to the complete failure of RC structures, was used to estimate the local strain distribution and the size of failure zone. In order to verify the reliability and validity for the image processing technology, the strain transition acquired by the image processing technology was compared with strain values measured by the concrete gauge on the uniaxial compressive specimens. Based on the verification of image processing technology for the uniaxial compressive specimens, the size and the local strain distribution of the failure zone of deep beam was measured using the image processing technology. With the results of test, the principal tensile/compressive strain contours were drawn. Using the strain contours, the size of the failure zone and the local strain distribution on the failure of the deep beam was evaluated. The results of strain contour showed that image processing technology is available to assess the failure behavior of deep beam and obtain the local strain values on the domain of the post-peak failure comparatively.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.18 no.2
• /
• pp.64-73
• /
• 2014

This study proposes a load identification for the safety monitoring of the steel structure based on measured strain data. Instead of parameterizing the stiffness of structure in the existing system identification researches, the loads on a structure and a matrix (the unit strain matrix) defined by the relationship between strain and load on structure are parameterized in this study. The error function is defined by the difference between measured strain and strain estimated by parameters. In order to minimize this error function, the genetic algorithm which is one of the optimization algorithm is applied and the parameters are found. The loads on the structure can be identified through the founded parameters and measured strain data. When the loads are changed, the unmeasured strains are estimated based on founded parameters and measured strains on changed state of structure. To verify the load identification algorithm in this paper, the static experimental test for 3 dimensional steel frame structure was implemented and the loads were exactly identified through the measured strain data. In case of loading changes, the unmeasured strains which are monitoring targets on the structure were estimated in acceptable error range (0.17~3.13%). It is expected that the identification method in this study is applied to the safety monitoring of steel structures more practically.

• Bulletin of the Society of Naval Architects of Korea
• /
• v.27 no.1
• /
• pp.17-23
• /
• 1990

When a thin walled member is subjected to compression in a condition such as collision, the energy is mainly absorbed by axial crumpling. In this case, dynamic crushing strength of the member is increased due to the effects of strain-rate compared with the static strength, even though the inertia effect is neglected. In this paper, the method of predicting the static crushing for tubular members is presented using the kinematic method of plasticity. Since, a predicted crushing load, taking account of the dynamic yield stress, usually overestimates the effects of strain-rate, the average plastic flow stress for the effects of strain-rate is used to obtain the dynamic crushing load for tubular members. The analytical results are compared with the experiments published in references, and a good correlation is observed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.5
• /
• pp.611-617
• /
• 2018

The application of health monitoring, including a fault detection technique, is needed to secure the structural safety of large structures. A 2-step crack identification method for detecting the crack location and size of the beam structure is presented. First, a crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape obtained from the distributed local strain data. The crack location and size were then identified based on the natural frequencies obtained from the acceleration data and the neural network technique for the pre-estimated crack occurrence region. The natural frequencies of a cracked beam were calculated based on an equivalent bending stiffness induced by the energy method, and used to generate the training patterns of the neural network. An experimental study was carried out on an aluminum cantilever beam to verify the present method for crack identification. Cracks were produced on the beam, and free vibration tests were performed. A crack occurrence region was estimated using the modified Laplacian operator for the strain mode shape, and the crack location and size were assessed using the natural frequencies and neural network technique. The identified crack occurrence region agrees well with the exact one, and the accuracy of the estimation results for the crack location and size could be enhanced considerably for 3 damage cases. The presented method could be applied effectively to the structural health monitoring of large structures.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.4A
• /
• pp.507-515
• /
• 2008

In this study, a method predicting the displacement response of structures from the measured dynamic strain signal is proposed by using mode decomposition technique. Evaluation of bridge stability is normally focused on the bridge completed. However, dynamic loadings including wind and seismic loadings could be exerted to the bridge under construction. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. As previous studies on the prediction of displacement response by using the FBG sensors, the static displacement has been mainly predicted. For predicting the dynamic displacement, it has been known that the measured strain signal includes higher modes and then the predicted dynamic displacement can be inherently contaminated by broad-band noises. To overcome such problem, a mode decomposition technique was used. Mode decomposition technique estimates the displacement response of each mode with mode shape estimated to use POD from strain signal and with the measured strain signal decomposed into mode by EMD. This is a method estimating the total displacement response combined with the each displacement response about the major mode of the structure. In order to examine the mode decomposition technique suggested in this study model experiment was performed.