• Structural Engineering and Mechanics
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• v.43 no.1
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• pp.31-51
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• 2012

This paper presents a computational study that explores the design of rigid steel frames by considering construction related costs. More specifically, two different aspects are investigated in this study focusing on the effects of (a) reducing the number of labor intensive rigid connections within a frame of given geometric layout, and (b) reducing the number of different member section types used in the frame. A genetic algorithm based optimization framework searches design space for these objectives. Unlike some studies that express connection cost as a factor of the entire frame weight, here connections and their associated cost factors are explicitly represented at the member level to evaluate the cost of connections associated with each beam. In addition, because variety in member section types can drive up construction related costs, its effects are evaluated implicitly by generating curves that show the trade off between cost and different numbers of section types used within the frame. Our results show that designs in which all connections are considered to be rigid can be excessively conservative: rigid connections can often be eliminated without any appreciable increase in frame weight, resulting in a reduction in overall cost. Eliminating additional rigid connections leads to further reductions in cost, even as frame weight increases, up to a certain point. These complex relationships between overall cost, rigid connections, and member section types are presented for a representative five-story steel frame.

• Smart Structures and Systems
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• v.33 no.2
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• pp.119-131
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• 2024

Drift angle is a significant index for diagnosing post-event structures. A common way to estimate this drift response is by using modal parameters identified under natural excitations. Although the modal parameters of shear structures cannot be identified accurately in the real environment, the identification error has little impact on the estimation when measurements from several floors are used. However, the estimation accuracy falls dramatically when there is only one accelerometer. This paper describes the susceptibility of single sensor identification to modelling error and simulations that preliminarily verified this characteristic. To make a robust evaluation from measurements of one floor of shear structures based on imprecisely identified parameters, a novel scheme is devised to approximately correct the mode shapes with respect to fictitious frequencies generated with a genetic algorithm; in particular, the scheme uses constrained minimization to take both the mathematical aspect and the realistic aspect of the mode shapes into account. The algorithm was validated by using a full-scale shear building. The differences between single-sensor and multiple-sensor estimations were analyzed. It was found that, as the number of accelerometers decreases, the error rises due to insufficient data and becomes very high when there is only one sensor. Moreover, when measurements for only one floor are available, the proposed method yields more precise and appropriate mode shapes, leading to a better estimation on the drift angle of the lower floors compared with a method designed for multiple sensors. As well, it is shown that the reduction in space complexity is offset by increasing the computation complexity.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.181-192
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• 2022

Active vibration control system(AVCS) for helicopter enables to control the vibration generated from the main rotor and has the superb vibration reduction performance with low weight compared passive vibration reduction device. In this paper, FxLMS algorithm-based vibration control software of the light civil helicopter tansmits the control command calculated using the signals of the tachometer and accelerometers to the circular force generator(CFG) is developed and verified. According to the RTCA DO-178C/DO-331, the vibration control software is developed through the model based design technique, and real-time operation performance is evaluated in PILS(processor in-the loop simulation) and HILS(hardware in-the loop simulation) environments. In particular, the reliability of the software is improved through the LDRA-based verification coverage in the PIL environments. In order to AVCS to light civil helicopter(LCH), the dynamic response characteristic model is obtained through the ground/flight tests. AVCS configuration which exhibits the optimal performance is determined using system optimization analysis and flight test and obtain STC certification.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.4
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• pp.1-6
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• 2005

The ability to predict radar return from flying vehicles becomes a critical technology issue in the development of stealth configurations. Toward developing a CEM code based on Maxwell's equations for analysis of RCS reduction schemes, an explicit upwind scheme suitable for multidisciplinary design is presented. The DFFT algorithm is utilized to convert the time-domain field values to the frequency-domain. A Green's function based on near field-to-far field transformation is also employed to calculate the bistatic RCS. To verify the numerical calculation the two-dimensional field around a perfectly conducting cylinder is considered. Finally results are obtained for the scattering electromagnetic field around an airfoil in order to illustrate the feasibility of applying CFD based methods to CEM.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.4
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• pp.73-80
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• 2004

A dual purpose robot automation system is developed for both arc welding and spot welding by one robot within a cell. The need for automation of both arc welding and spot welding processes is urgent while the production volume is not so big as to accommodate separate station for the two processes. Also, space is too narrow for separate station to be settled down in the factory. A spot welding robot is chosen and the function for arc welding are implemented in-house at cost of advanced functions. For the spot welding, a single pole type gun is used and the robot has to push down the plate to be welded, which causes the robot positioning error. Therefore, position error compensation algorithm is developed. The basic functions for the arc welding processes are implemented using the digital I/O board of robot controller, PLC, and A/D conversion PCB. The weaving pattern is taught in meticulously by manual teach. A fixture unit is also developed for dual purpose. The main aspects of the system is presented in this paper especially in the design and implementation procedure. The signal diagrams and sequence logic diagrams are also included. The outcome of the dual purpose welding cell is the increased productivity and good production stability which is indispensable for production volume prediction. Also, it leads to reduction of manufacturing lead time.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.9-22
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• 2005

The allowed operation space for the mass damper in an active tuned mass damper (ATMD) system is limited for most civil structures. In this study, a restrained stroke active tuned mass damper (RS-ATMD) system with a end-spring and a holder that reduces the stroke of the mass damper with maintaining the control effect durably is proposed. This new control system functions as a conventional ATMD within the predetermined stroke limitation under small excitation and as an RS-ATMD beyond that limitation under large excitation. A new control algorithm considering such an operation principle of the RS-ATMD are also provided. Parameteric study for the various design factors of the RS-ATMD is conducted and the control effectiveness are investigated in comparison with the ATMD. Exposed to sinusoidal or impact load, the RS-ATMD system shows the considerable reduction of the maximum stroke of the mass damper with the slight diminution in the control effectiveness. Excited by random load, it also shows the considerable reduction of the maximum stroke of the mass damper not allowing the diminution in the control effectiveness.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.195-201
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• 2014

In this study, face recognition system was designed based on polynomial Radial Basis Function Neural Networks(pRBFNNs) pattern classifier using 2-directional 2-dimensional principal component analysis algorithm. Existing one dimensional PCA leads to the reduction of dimension of image expressed by the multiplication of rows and columns. However $(2D)^2PCA$(2-Directional 2-Dimensional Principal Components Analysis) is conducted to reduce dimension to each row and column of image. and then the proposed intelligent pattern classifier evaluates performance using reduced images. The proposed pRBFNNs consist of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with the aid of fuzzy c-means clustering. In the conclusion part of rules. the connection weight of RBFNNs is represented as the linear type of polynomial. The essential design parameters (including the number of inputs and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. Using Yale and AT&T dataset widely used in face recognition, the recognition rate is obtained and evaluated. Additionally IC&CI Lab dataset is experimented with for performance evaluation.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.790-793
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• 2008

Recently, Intelligent Excavating System(IES) for earthwork automation is on progress since the end of 2006 as a part of construction technology innovation projects in Ministry of Land, Transport and Maritime Affairs. Task Planning System(TPS), one of the detail core technologies of IES, is an optimal work planning system in conditions of effectiveness, safety and economic efficiency by analyzing the work environment data based on earthwork design and work environment recognition technology. For effective earthwork planning, the location of platform must be the most optimal spot for minimization of time, maximization of productivity and reduction of overlapped work spaces and unnecessariness. Besides, the decision of optimal platform location is to be based on the specifications and then is able to be converted with the local area calculation algorithm. This study explains the decision of optimal platform location on the basis of local area from the work space separate process and judges the effectiveness.