• International Journal of Precision Engineering and Manufacturing
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• 제7권1호
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• pp.47-50
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• 2006

An active contour model has been used to detect the edges in a still image. In order to apply the active contour model to edge detection, the energy function which consists of internal, external and image energies should be defined. After defining the energy function, the edge of an object is detected through minimization of the value of the energy function. In this paper, the modified internal energy function is proposed to improve the convergence of the energy function when the active contour model is applied to the tracking of deformable objects using the greedy algorithm. In order to show the performance of the proposed energy function, experiments were carried out for the still and animated images.

• 한국정밀공학회지
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• 제14권4호
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• pp.46-55
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• 1997

This paper presents the development of intelligent performance management of computer communication networks for larger-scale integrated systems and the demonstration of its efficacy using computer simula- tion. The innermost core of the performance management is based on fuzzy set theory. This fuzzy perfor- mance manager has learning ability by using principles of neuro-fuzzy model, neuralnetwork, genetic algo- rithm(GA). Two types of performance managers are described in this paper. One is the Neuro-Fuzzy Per- formance Manager(NFPM) of which learning ability is based on the conventional gradient method, and the other is GA-based Neuro-Fuzzy Performance Manager(GNFPM)with its learning ability based on a genetic algorithm. These performance managers have been evaluated via discrete event simulation of a computer network.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 춘계학술대회 논문집
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• pp.125-130
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• 1997

In this paper, it is presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C3x is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, andsuitable for implementation of robust control.

• 한국공작기계학회논문집
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• 제15권5호
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• pp.29-36
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• 2006

The hydraulic excavators are mainly applied for excavating, public works, quarrying, etc. In some of the construction site, however, they are used for crane works of relatively light materials, although the crane works by the hydraulic excavators are forbidden by law due to the safety reasons. The major construction equipment companies in forward countries have been developing the new systems, e.g. crane works by the hydraulic excavators, and they are working in the construction site. Therefore, the new system of crane works by the hydraulic excavators should be developed for the domestic construction site in order to prevent the accident. In this paper, the fundamental study and experiment are accomplished for the crane system application on the hydraulic excavators.

• International Journal of Precision Engineering and Manufacturing
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• 제1권1호
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• pp.146-151
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• 2000

The importance of shape reconstruction is increasing in many areas such as RPD(Rapid Product Development) and reverse engineering. Typical data in these areas are mainly classified as the shape data measured by a laser scanner and the data extracted from the CT image. The goal of this research is to realize three-dimensional shape construction by showing a possible way to analyze input image data and reconstruct the original shape. Two main steps of the reconstructing process are obtaining cross-section data from image processing and linking loops between one slice and the next. Objects reconstructed in this way are compared with other objects using a laser scanner and modelled by commercially available software. The technique is expected to be used in reverse engineering applications and the object modeling with automated process.

• 대한안전경영과학회지
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• 제10권3호
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• pp.81-87
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• 2008

The reliability prediction and evaluation for general electronic components are required to guarantee in quality and in efficiency. Although many methodologies for predicting the reliability of electronic components have been developed, their reliability might be subjective according to a particular set of circumstances, and therefore it is not easy to quantify their reliability. In this study reliability prediction of electronic components, that is the interface card, which is used in the CNC(Computerized Numerical Controller) of machine tools, was carried out using PRISM reliability prediction specification. Reliability performances such as MTBF(Mean Time Between Failure), failure rate and reliability were obtained, and the variation of failure rate for electronic components according to temperature change was predicted. The results obtained from this study are useful information to consider a counter plan for weak components before they are used.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.255-260
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.43-46
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• 1997

Reliability engineering is regarded as the major and important roll for all industry. And advanced manufacturing systems with high sped and intelligent have been developing for betterment of machining ability. In this study, we have systemized evaluation of reliability for machinery system. We proposed the reliability assessment and designed and manufactured reliability test-bed to evaluate reliability. In addition we acquired reliability data using test-bed system and made database to handle reliability data. And also we not only use reliability data by analyzing reliability, but also apply design review method using analyzing critical units of machinery system. Form this study, we will expect to guide and increase the reliability engineering in developing and processing phase of high quality product.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 추계학술대회 논문
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• Journal of Advanced Marine Engineering and Technology
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• 제28권5호
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• pp.811-817
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• 2004

Recently embedded systems are widely used in various industrial fields as supervisory controller because they have many merits. One of merits seems to be that operating environment of embedded system is the same as development environment using PC. That makes developing and manufacturing period shorten and also proper time to market Most of all machinery have sequential control system for their maneuvering which is composed of relays. contacts. timers. etc. In this paper. software sequential control system is proposed to be able to replace hardware sequential control system by using embedded system A lot of merits by the software sequential control system can be expected in the respect of economic reproduction, intelligent technologies and utilities, And porting of LINUX operating system to embedded system is carried out and device drivers and interface boards for LINUX 05 are designed for controlling air compressor by software Internet remote control and monitoring system of air compressor is implemented with Java script and CGI for these purposes. The experiment for operating air compressor system is taken through internet networks. The results show that developed system can be used for real plant.