• Proceedings of the KSME Conference
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• 2001.11a
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• pp.527-532
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• 2001

In this paper, we will propose the new method that estimates the sensing ability of HH smart sensor. We have developed a new signal processing method that can distinguish among different materials relatively. The HH smart sensor was developed for recognition of materials. We made the HH smart sensor in our experiment. Then, we estimated the ability to recognize objects according to acceleration value. We estimated the sensing ability of HH smart sensor with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to acceleration value changing. Dynamic characteristics of HH smart sensor were evaluated relatively through a new $R_{SAI}$ method that uses the power spectrum density. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.304-310
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• 2001

Cracks at mechanical fastener holes usually nucleate as elliptical comer cracks at the faying surface of the mechanical joints and grow as elliptical arc through cracks after penetrating the opposite surface. In this study mode I, II and III stress intensity factors at two surface points of elliptical arc through cracks at mechanical fastener holes are analyzed by applying weight function method. The weight function method for two dimensional mixed-mode problem is extended to three dimensional one and it is verified.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.111-117
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• 2001

In this paper, we will propose the new method that estimates the sensing ability of smart sensor. A study is estimation method that evaluates the sensing ability about smart sensor respectively. According to acceleration(g) and displacement changing, we estimated the sensing ability of smart sensor using the SAI(Sensing Ability Index) method respectively. We made the smart sensors in our experiment. The types of smart sensor are three types(H1, H1, H3 smart sensor). The smart sensors were developed for recognition of materials. Experiments and analysis were executed to estimated the sensing abili-ty of smarty sensor. Dynamic characteristics of smart sensors(acceleration changing) were evaluated respectively through a new method(SAI) that uses the power spectrum density.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.23-26
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• 2000

This paper descrtbcs our prlmary study for a new mncthod of recogninng materials. which is need for precision work system. This IS a study of dynarnlc characteristics of sensor. new melhod ($R_{SAI}$) has thc sensing ability of distinguishing materials. Experiment and annlysis are executed for proper dynamic scnslng condition. First. we developed advanced smart sensor Second, we develop new methods that have a sensing ability of distinguish matarialsAccording to frequency changing. mtluence of smart sensor are evaluated through new recognition Index ($R_{SAI}$) that ratioof sensing ability index. Disungush of object is cxucuted wllh RsA, method relalivcly according to liequency changing. Wecan use the RsAl for finding materids. Applfciltionr of thls method are linding abnormal condition of obicct (automanufacturing).keling ofobject (medlcal product). tobolics, safety diagnosis of structure, etc

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2705-2712
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• 2000

In meshless methods some techniques to impose essential boundary conditions have been developed since the approximations do not satisfy Kronecker delta properties at nodal points. In this study, new scheme for imposing essential boundary conditions is developed. Weight functions are modified by multiplying with auxiliary weight functions and the resulting shape functions satisfy Kronecker delta property on the bound ary nodes. In addition, the resulting shape functions possess and interpolation features on the boundary segments where essential boundary conditions are prescribed. Therefore the essential boundary conditions can be exactly satisfied with the new method. More importantly, the impositions of essential boundary conditions using the present method is relatively easy as in finite element method. Numerical examples show that the method also retains high convergence rate comparable to Lagrange multiplier method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.318-322
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• 2001

This paper deals with sensing ability of smart sensor that has a sensing ability to distinguish materials according to surface types of smart sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. We made two types of smart sensors in our experiment. Then, we estimated the ability to recognize objects according to smart sensor type. We estimated the sensing ability of smart sensor with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to surface types of smart sensor. Sensing ability of smart sensors was evaluated relatively through a new $R_{SAI}$ method. Applications of smart sensors are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.etc.

• Journal of Ocean Engineering and Technology
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• v.23 no.1
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• pp.146-151
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• 2009

In this paper, a weight function theory for the calculation of the mode III stress intensity factor in a rectilinear anisotropic body is formulated. This formulation employs Lekhnitskii's formalism for two dimensional anisotropic materials. To illustrate the method used for the weight function theory, we calculated the mode III stress intensity factor in a single edge-notched configuration.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2344-2352
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• 2000

Mechanical joints such as bolted or riveted joints are widely used in mechanical components. The reliable determination of the stress intensity factors for cracks in bolted joints is needed to evaluate the safety and fatigue life of them. The weight function method is an efficient technique to calculate the stress intensity factors for various loading conditions because only the stress analysis of an uncracked model is required. In this paper the mixed-mode stress intensity factors for cracks in bolted joints are obtained by weight function method, in which the coefficients of weight function are determined by finite element analyses for reference loadings. Critical inclined angle that mode I stress intensity factor becomes maximum is determined and the effects of crack length and the magnitude of clearance on critical inclined angle are investigated.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.212-217
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• 2000

The reliable determination of the stress intensity factors for cracks in bolted Joints is needed to evaluate the safety and fatigue life of them widely used in mechanical components. The weight function method is an efficient technique to calculate the stress intensity factors for various loading conditions using the stresses of an uncracked model. In this paper the mixed-mode stress intensity factors for cracks in bolted joints are obtained by weight function method, in which the coefficients of weight function are determined by finite element analyses far reference loadings. The effects of the magnitude of clearance and factional coefficient on the stress intensity factors are investigated.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.22-27
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• 2004

A new method that estimates the sensing ability of HH smart sensor is proposed. The new signal processing method have been developed that can distinguish among different materials relatively. The HH smart sensor was developed far recognition of materials. The HH smart sensor was made for experiment. Then, it was estimated the ability to recognize objects according to acceleration value. The sensing ability of HH smart sensor has been estimated with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to acceleration value changing. Dynamic characteristics of HH smart sensor were evaluated relatively through a new $R_{SAI}$ method that uses the power spectrum density. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.