• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1996년도 봄 학술발표회 논문집
• /
• pp.119-126
• /
• 1996

In this paper, a method of substructural identification is presented for the estimation of localized structural parameters. for this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for the substructure to process the measurement data impaired by noises. The sequential prediction error method is used fer the estimation of unknown localized parameters. Using the substructural method, the number of unknown parameters can be reduced and the convergence and accuracy of estimation can be improved. For some substructures, the effect of the input excitation is expressed in terms of the responses at the inferences with the main structure, and substructural identification may be carried out without measuring the actual input excitation to the whole structure. Example analysis is carried out for idealized structural models of a multistory building and a truss bridge. The results indicate that the present method is effective and efficient for local damage estimation of complex structures.

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2001년도 추계학술대회논문집 II
• /
• pp.1073-1077
• /
• 2001

The objective of this paper is to apply an experimental method based on the principle of reciprocity to measuring the structural intensity. Since only one accelerometer is used in this method it has the advantages of shortening measurement time. reducing accelerometer phase error. overcoming the limitation that the situation should be stationary during the experiment. It has been used to measure the vibration intensity of an infinite beam (beam with damped ends) and a semi-infinite beam (beam with simply supported and damped ends). Results showed that the experiment method based on the principle of reciprocity can be effectively used to measure the structural intensity.

• Structural Engineering and Mechanics
• /
• 제22권4호
• /
• pp.401-418
• /
• 2006

Solutions to the problems of structural parameter estimation from modal response using leastsquares minimization of force or displacement residuals are generally sensitive to noise in the response measurements. The sensitivity of the parameter estimates is governed by the physical characteristics of the structure and certain features of the noisy measurements. It has been shown that the regularization method can be used to reduce effects of the measurement noise on the estimation error through adding a regularization function to the parameter estimation objective function. In this paper, we adopt the regularization function as the Euclidean norm of the difference between the values of the currently estimated parameters and the a priori parameter estimates. The effect of the regularization function on the outcome of parameter estimation is determined by a regularization factor. Based on a singular value decomposition of the sensitivity matrix of the structural response, it is shown that the optimal regularization factor is obtained by using the maximum singular value of the sensitivity matrix. This selection exhibits the condition where the effect of the a priori estimates on the solutions to the parameter estimation problem is minimal. The performance of the proposed algorithm is investigated in comparison with certain algorithms selected from the literature by using a numerical example.

• 대한조선학회논문집
• /
• 제57권6호
• /
• pp.373-380
• /
• 2020

We have developed the hybrid prototype load cell structures. These developed load cell structures may increase the reliability of the load sensing by deriving the load values through the double sensing method through the vertical maximum deflection and bending stress of the simple beams. For this purpose, the structure design was performed so that the load value, the deflection and stress value could be output to the same value through the optimal structure design. The structurally designed dimensions reaffirmed the accuracy of the design through the structural analysis program and the matching of the load value and the deflection value. Based on the designed structural dimension, the prototype form was constructed through laser cutting and production using hot rolled steel materials. The developed prototype load cell structure can be used as good educational material in various subjects such as material mechanics, steel structure design, measurement engineering, and mechatronics engineering. It is also believed that the measurement system ideas can inform the occurrence of errors in the event of a problem, and if a major accident caused by a sensing error is predicted, it will show good utilization to prevent accidents.

• 한국구조물진단유지관리공학회 논문집
• /
• 제23권7호
• /
• pp.40-48
• /
• 2019

본 연구에서는 건설 현장에서 발생하는 미세먼지의 정확한 측정을 위한 새로운 개념의 알고리즘을 제안한고 검증한다. 기존 측정법의 한계를 보완하기 위하여 초음파 산란 기반 측정법을 제안하였으며, 유한 차분법을 통하여 알고리즘의 활용 및 그 정확성을 검증하고자 하였다. 미세먼지와 같은 다중 산란을 일으키는 현상에 대하여 수학적 모델링을 수행하였고 신호의 감쇠율, 평균 자유 거리, 산란 반경으로 미세먼지의 단위 밀도를 예측할 수 있는 알고리즘을 도출하였다. 2-D 시간 이력해석을 통하여 미세먼지 부피비에 따라 알고리즘을 검증하였으며 신호 해석을 위한 신호처리 기법을 나타내었다. 해석 결과, 알고리즘의 오차는 개수밀도 단위 최소 0.7, 최대 24.9를 보였다. 오차율을 줄이기 위해 미세먼지의 산란 반경을 주파수별로 도출하여야 하는 추후 연구가 필요함을 토의하였다.

• International Journal of Aeronautical and Space Sciences
• /
• 제16권3호
• /
• pp.380-393
• /
• 2015

This study presents how we can evaluate stereo camera systems for the structural deformation monitoring. A stereo camera system, consisting of a set of stereo cameras and reflective markers attached on the structure, is introduced for the measurement and the stereo pattern recognition (SPR) method is utilized for the full-field structural deformation estimation. Performance of this measurement system depends on many parameters including types and specifications of the cameras, locations and orientations of them, and sizes and positions of markers; it is difficult to experimentally identify the effects of each parameter on the measurement performance. In this study, a simulation framework for evaluating performance of the stereo camera systems with various parameters has been developed. The maximum normalized root-mean-square (RMS) error is defined as a representative index of stereo camera system performance. A plate structure is chosen for an introductory example. Its several modal harmonic vibrations are generated and estimated in the simulation framework. Two cases of simulations are conducted to see the effects of camera locations and the resolutions of the cameras. An experimental validation is carried out for a few selected cases from the simulations. Using the simultaneous laser displacement sensor (LDS) measurements as the reference, the measurement errors are obtained and compared with the simulations.

• 전기학회논문지
• /
• 제59권10호
• /
• pp.1874-1881
• /
• 2010

A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

• 한국공작기계학회논문집
• /
• 제13권2호
• /
• pp.75-80
• /
• 2004

Vehicle structures are composed of many substructure connected to one another by various types of mechanical joints. In vehicle engineering it is important to study these connected structures under various dynamic forces for the evaluations of fatigue life and stress concentration exactly. It is difficult to obtain the accurate load history of specified positions because of the errors such as modeling, measurement and etc. In the beginning of design exact load data are actually necessary for the fatigue strength and life analysis to minimize the cost and time of designing. In this paper, the procedure of practical dynamic force determination is developed by the combination of the principal stresses of F. E. Analysis and experiment. Least square pseudo inverse matrix is adopted to obtain in inverse matrix of analyzed stresses matrix. The error minimization method utilizes the inaccurate measured error and the shifting error that the whole data is stiffed over real data. The least square criterion is adopted to avoid these non. Finally, to verify the proposed procedure, a bus is analyzed. This measurement and prediction technology can be extended to the structural modification of any geometric shape in complex structure.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1995년도 봄 학술발표회 논문집
• /
• pp.136-143
• /
• 1995

The problem of the structural identification becomes important, particularly with relation to the rapid increase of the number of the damaged or deteriorated structures, such as highway bridges, buildings, and industrial facilities. This paper summarizes the recent studies related to those problems by the present authors. The system identfication methods are generally classified as the time domain and the frequency domain methods. As time doamin methods, the sequential algorithms such as the extended Kalman filter and the sequential prediction error method are studied. Several techniques for improving the convergences are incorporated. As frequency domain methods, a new frequency response function estimator is introduced. For damage estimation of existing structures, the modal perturbation and the sensitivity matrix methods are studied. From the example analysis, it has been found that the combined utilization of the measurement data for the static response and the dynamic (modal) properties are very effictive for the damage estimation.

• Smart Structures and Systems
• /
• 제15권2호
• /
• pp.489-503
• /
• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.