• Structural Engineering and Mechanics
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• v.31 no.3
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• pp.333-347
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• 2009

Due to structural complicacy, structural health monitoring for civil engineering needs more accurate and effectual methods of damage identification. This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve the validity of damage detection. Firstly, the essential theory and applied mathematic methods of MSIF are introduced. And then, the structural damage identification method based on multi-mode information fusion is put forward. Later, on the basis of a numerical simulation of a concrete continuous box beam bridge, it is obviously indicated that the improved modal strain energy method based on multi-mode information fusion has nicer sensitivity to structural initial damage and favorable robusticity to noise. Compared with the classical modal strain energy method, this damage identification method needs much less modal information to detect structural initial damage. When the noise intensity is less than or equal to 10%, this method can identify structural initial damage well and truly. In a word, this structural damage identification method based on multi-mode information fusion has better effects of structural damage identification and good practicability to actual structures.

• Structural Engineering and Mechanics
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• v.22 no.4
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• pp.469-481
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• 2006

A new method called fuzzy factor method for the stationary stochastic response analysis of fuzzy truss with global fuzzy structural parameters is presented in this paper. Considering the fuzziness of the structural physical parameters and geometric dimensions simultaneously, the fuzzy correlation function matrix of structural displacement response in time domain is derived by using the fuzzy factor method and the optimization method, the fuzzy mean square values of the structural displacement and stress response in the frequency domain are then developed with the fuzzy factor method. The influences of the fuzziness of structural parameters on the fuzziness of mean square values of the displacement and stress response are inspected via an example and some important conclusions are obtained. Finally, the example is simulated by Monte-Carlo method and the results of the two methods are close, which verified the feasibility of the method given in this paper.

• Structural Engineering and Mechanics
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• v.30 no.4
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• pp.445-466
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• 2008

This paper presents a novel structural damage detection method with a new damage index based on the statistical moments of dynamic responses of a structure under a random excitation. After a brief introduction to statistical moment theory, the principle of the new method is put forward in terms of a single-degree-of-freedom (SDOF) system. The sensitivity of statistical moment to structural damage is discussed for various types of structural responses and different orders of statistical moment. The formulae for statistical moment-based damage detection are derived. The effect of measurement noise on damage detection is ascertained. The new damage index and the proposed statistical moment-based damage detection method are then extended to multi-degree-of-freedom (MDOF) systems with resort to the leastsquares method. As numerical studies, the proposed method is applied to both single and multi-story shear buildings. Numerical results show that the fourth-order statistical moment of story drifts is a more sensitive indicator to structural stiffness reduction than the natural frequencies, the second order moment of story drift, and the fourth-order moments of velocity and acceleration responses of the shear building. The fourth-order statistical moment of story drifts can be used to accurately identify both location and severity of structural stiffness reduction of the shear building. Furthermore, a significant advantage of the proposed damage detection method lies in that it is insensitive to measurement noise.

• Journal of Power System Engineering
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• v.11 no.1
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• pp.92-97
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• 2007

It is important to compute the structural analysis of plate structures in structural design. In this paper, the author uses the finite element-transfer stiffness coefficient method (FE-TSCM) for the structural analysis of plate structures. The FE-TSCM is based on the concept of the successive transmission of the transfer stiffness coefficient method and the modeling technique of the finite element method (FEM). The algorithm for in-plane structural analysis of a rectangular plate structure is formulated by using the FE-TSCM. In order to confirm the validity of the FE-TSCM for structural analysis of plate structures, two numerical examples for the in-plane structural analysis of a plate with triangular elements and the bending structural analysis of a plate with rectangular elements are computed. The results of the FE-TSCM are compared with those of the FEM on a personal computer.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.12
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• pp.1984-1994
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• 1989

Techniques for approximating digitalcurves by polygonal lines are a valuable tool for image analysis and data compression. S. Shilien proposed a method for segmenting a digital curve into digital straight line segments digital straight line segments which are not satisfied with the structural properties, and have more than one break point by Shilien's method. Here, the structural representation of digital straight lines and digital staight line segments is described. And a method for segmenting a digital curve into digital straight line segments which are not satisfied with the structural properties, and have more than one break point by Shilien's method. Here, the structural representation of digital straight lines and digital staight line segments is described. And a method for segmenting a digital curve into digital straight line segments which may be not satisfied with the structural properties is proposed. The number of break points extracted by this method is less than that by S. Shilien's method from the digital curve which includes the digital straight line segments not satisfied with the structural properties.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1248-1259
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• 2016

Classification methods based on dual energy X-ray absorptiometry, ultrasonic waves, and quantitative computed tomography have been proposed. Also, a classification method based on machine learning with bone mineral density and structural indicators extracted from the CT images has been proposed. We propose a method which enhances the performance of existing classification method based on bone mineral density and structural indicators by extending structural indicators and using principal component analysis. Experimental result shows that the proposed method in this paper improves the correctness of osteoporosis classification 2.8% with extended structural indicators only and 4.8% with both extended structural indicators and principal component analysis. In addition, this paper proposes a method of automatic phantom analysis needed to convert the CT values to BMD values. While existing method requires manual operation to mark the bone region within the phantom, the proposed method detects the bone region automatically by detecting circles in the CT image. The proposed method and the existing method gave the same conversion formula for converting CT value to bone mineral density.

• Structural Engineering and Mechanics
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• v.29 no.5
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• pp.469-488
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• 2008

Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.298-299
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• 2014

As a governmental plan for real estate revitalization, remodeling vertical extension has been permitted. Thus, the Ministry of Land, Infrastructure and Transport preannounced proclaiming the revised Housing Act and establishing the remodeling basic plan, and it is anticipated that the remodeling market will be revitalized in earnest after the enforcement of remodeling vertical extension(April 25th. 2014). As vertical extension is applicable up to 3 stories, the safety of building for remodeling is becoming important, so most remodeling construction works use various methods for structural reinforcement. In this process, the selection of structural reinforcement method has depended on structural engineer's experience and knowledge and there has been a limitation in selecting the optimum structural reinforcement method which considers remodeling project characteristics. Therefore, this study analyzed the factors to determine the kinds of structural reinforcement method in a remodeling project and suggested a process to select the best structural reinforcement method of remodeling construction.

• Structural Engineering and Mechanics
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• v.62 no.2
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• pp.139-142
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• 2017

For the conventional computational methods for structural reliability analysis, the common limitations are long computational time, large number of iteration and low accuracy. Thus, a new novel method for structural reliability analysis has been proposed in this paper based on response surface method incorporated with an improved genetic algorithm. The genetic algorithm is first improved from the conventional genetic algorithm. Then, it is used to produce the response surface and the structural reliability is finally computed using the proposed method. The proposed method can be used to compute structural reliability easily whether the limit state function is explicit or implicit. It has been verified by two practical engineering cases that the algorithm is simple, robust, high accuracy and fast computation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.10a
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• pp.248-255
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• 1993

Recently, due to the increasing attention to the structural safety under uncertain environments, many researches on the structural reliability analysis have been peformed. Some useful methods are available to evaluate performance reliability of structures with explicit limit states. However, for large structures, in which structural behaviors can be analyzed with finite element models and the limit states are only expressed implicitly, Monte-Carlo simulation method has been mainly used. However, Monte-Carlo simulation method spends too much computational time on repetitive structural analysis. Many alternative methods are suggested to reduce the computational work required in Monte-Carlo simulation. Response surface method is widely used to improve the efficiency of structural reliability analysis. Response surface method is based on the concept of approximating simple polynomial function of basic random variables for the limit state which is not easily expressed in explicit forms of design random variables. The response surface method has simple algorithm. However, the accuracy of results highly depends on how properly the stochastic characteristics of the original limit state has been represented by approximated function, In this study, an improved response surface method is proposed in which the sampling points for creating response surface are modified to represent the failure surface more adequately and the combined use of a linear response surface function and Rackwitz-Fiessler method has been employed. The method is found to be more effective and efficient than previous response surface methods. In addition more consistent convergence is achieved, Accuracy of the proposed method has been investigated through example.