• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1605-1608
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• 2005

This study was carried out to analyze the effect of machinery house location on the stability of high efficiency gantry crane which can improve the productivity of the container transportation wok by reducing cycle time. The wind load was evaluated according to 'Load Criteria of Building Structures' enacted by the ministry of construction & transportation. The uplift forces of high efficiency gantry crane under this wind load were calculated by analyzing reaction forces at each supporting point. And variation of reaction forces at each supporting point was analyzed according to machinery house location.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2004년도 추계학술발표대회 논문집
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• pp.216-219
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• 2004

The stitching process has been widely utilized for the improvement of through-thickness property of the conventional laminated composites. This paper rep0l1s the effects of stitching on the flexural and interlaminar shear properties of multiaxial warp knitted composites in order to examine the performance improvements. Considered parameters are as follows: the stacking regularity of the multiaxial warp knits, the stitch spacings, the stitching types, the stitching location, and the location of compression fixture nose. These parameters have little effect on the flexural and interlaminar shear properties, except for the case of stitching location. Stitching on the $0^{\circ}$ fibers showed the lowest flexural strength and modulus ($12\%$reduction for both properties). The stitch spacing of 5mm resulted 8% reduction in interlaminar strength compared with 10mm spacing.

• Journal of Mechanical Science and Technology
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• 제16권4호
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• pp.454-467
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• 2002

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

• 한국정밀공학회지
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• 제22권2호
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• pp.148-155
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• 2005

This study was carried out to analyze the effect of direction of wind load and machinery house location on the stability of container crane loading/unloading a container on a vessel. The overturning moment of container crane under wind load at 50m/s velocity was estimated by analyzing reaction forces at each supporting point. And variations of reaction forces at each supporting point of a container crane were analyzed according to direction of wind load and machinery house location. The critical location of machinery house was also investigated to install a tie-down which has an anti-overturning function of container crane at the land side supporting point.

• 한국정밀공학회지
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• 제16권11호
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• pp.158-165
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• 1999

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses hybrid neuro-genetic technique. Feed-forward multilayer neural networks trained by back-propagation are used to learn the input)the location and dept of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this neural network and genetic algorithm, it is possible to formulate the inverse problem. Neural network training algorithm is the back propagation algorithm with the momentum method to attain stable convergence in the training process and with the adaptive learning rate method to speed up convergence. Finally, genetic algorithm is used to fine the minimum square error.

• 대한기계학회논문집A
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• 제24권1호
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• pp.190-195
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• 2000

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure. Nikolakopoulos et. al. used the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However the intersecting point of the superposed contours is not only difficult to find but also incorrect to calculate. A method is presented in this paper which uses optimization technique for the location and depth of the crack. The basic idea is to find parameters which use the structural eigenfrequencies on crack depth and location and optimization algorithm. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. Method of optimization is augmented lagrange multiplier method and search direction method is BFGS variable metric method and one dimensional search method is polynomial interpolation.

• 대한기계학회논문집A
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• 제25권12호
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• pp.2062-2069
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.182-188
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Journal of Electrical Engineering and Technology
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• 제6권1호
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• pp.1-7
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• 2011

This paper proposes an enhanced noise robust algorithm for fault location on double-circuit transmission line for the case of single line-to-ground (SLG) fault, which uses distributed parameter line model that also considers the mutual coupling effect. The proposed algorithm requires the voltages and currents from single-terminal data only and does not require adjacent circuit current data. The fault distance can be simply determined by solving a second-order polynomial equation, which is achieved directly through the analysis of the circuit. The algorithm, which employs the faulted phase network and zero-sequence network with source impedance involved, effectively eliminates the effect of load flow and fault resistance on the accuracy of fault location. The proposed algorithm is tested using MATLAB/Simulink under different fault locations and shows high accuracy. The uncertainty of source impedance and the measurement errors are also included in the simulation and shows that the algorithm has high robustness.

• Structural Monitoring and Maintenance
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• 제4권1호
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• pp.69-84
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• 2017

Delamination is the most common failure mode in layered composite materials. The author have found that the electrical potential change (EPC) technique using response surfaces method is very effective in assessment delamination in basalt fiber reinforced polymer (FRP) laminate composite pipe by using electrical capacitance sensor (ECS). In the present study, the effect of the electrodes number on the method is investigated using FEM analyses for delamination location/size detection by ANSYS and MATLAB, which are combined to simulate sensor characteristic. Three cases of electrodes number are analyzed here are eight, twelve and sixteen electrodes, afterwards, the delamination is introduced into between the three layers [$0^{\circ}/90^{\circ}/0^{\circ}$]s laminates pipe, split into eight, twelve and sixteen scenarios for cases of eight, twelve and sixteen electrodes respectively. Response surfaces are adopted as a tool for solving inverse problems to estimate delamination location/size from the measured EPC of all segments between electrodes. As a result, it was revealed that the estimation performances of delamination location/size depends on the electrodes number. For ECS, the high number of electrodes is required to obtain high estimation performances of delamination location/size. The illustrated results are in excellent agreement with solutions available in the literature, thus validating the accuracy and reliability of the proposed technique.