• 한국기계가공학회지
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• 제1권1호
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• pp.123-132
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• 2002

In this study, the static and dynamic characteristics of endmilling process was modelled and the analytic realization of chatter mechanism was discussed. In this regard, We have discussed on the comparative assessment of recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental work were performed to show the malfunctional behaviors. For this purpose, new recursive least square method (RLSM) were adopted for the on-line system identification and monitoring of a machining process, we can apply these new algorithms in real process for detection of abnormal chatter. Also, The stability lobe of chatter was analysed by varying parameter of cutting dynamices in regenerative chatter mechanics.

• 통상정보연구
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• 제9권3호
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• pp.305-320
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• 2007

With expanded use of B2B(between enterprises), B2G(between enterprises and government) and EDI(Electronic Data Interchange), and increased amount of available network information and information protection threat, as it was judged that security can not be perfectly assured only with security technology such as electronic signature/authorization and access control, Bayesian networks have been developed for protection of information. Therefore, this study speculates Bayesian networks system, centering on ERP(Enterprise Resource Planning). The Bayesian networks system is one of the methods to resolve uncertainty in electronic data interchange and is applied to overcome uncertainty of abnormal invasion detection in ERP. Bayesian networks are applied to construct profiling for system call and network data, and simulate against abnormal invasion detection. The host-based abnormal invasion detection system in electronic trade analyses system call, applies Bayesian probability values, and constructs normal behavior profile to detect abnormal behaviors. This study assumes before and after of delivery behavior of the electronic document through Bayesian probability value and expresses before and after of the delivery behavior or events based on Bayesian networks. Therefore, profiling process using Bayesian networks can be applied for abnormal invasion detection based on host and network. In respect to transmission and reception of electronic documents, we need further studies on standards that classify abnormal invasion of various patterns in ERP and evaluate them by Bayesian probability values, and on classification of B2B invasion pattern genealogy to effectively detect deformed abnormal invasion patterns.

• 한국기계가공학회지
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• 제8권2호
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• pp.25-31
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• 2009

The image processing methods are widely used in many industrial fields to detect defections in inspection devices. In this study an image processing method was conducted for the detection of abnormal pixels in a OLED(Organic Light Emitting Diode) type panel which is used for small size displays. The display quality of an OLED device is dependent on the pixel formation quality. So, among the so many pixels, to find out the faulty pixels is very important task in manufacturing processing or inspection division. We used a line scanning type BW(Black & White) camera which has very high resolution characteristics to acquire an image of display pixel patterns. And the various faulty cases in pixel abnormal patterns are considered to detect abnormal pixels. From the results of the research, the normal BW pixel image could be restored to its original color pixel.

• 한국분말재료학회지
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• 제12권4호
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• pp.261-265
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• 2005

In order to fabricate complex-shaped polycrystalline ceramics by sintering, organic binders are usually pre-mixed with ceramic powders to enhance the formability during the shape forming process. These organic binders, however, must be eliminated before sintering so as to eliminate the possibilities of poor densification and unusual grain growth during sintering. The present work studies the effect of binder addition on grain growth behavior during sintering of $92(70Pb(Mg_{1/3}Nb_{2/3})O_3-30PbTiO_3))$-8PbO(mol%) piezoelectric ceramics. The microstructures of the sintered samples were examined for various heating profiles and debinding schedules of the binder removal process. Addition of Polyvinyl butyral(PVB) binder promoted abnormal grain growth especially in incompletely debinded regions. Residual carbon appears to change the grain shape from comer-rounded to faceted and enhance abnormal grain growth.

• 한국세라믹학회지
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• 제32권1호
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• pp.51-56
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• 1995

Variation of sintered density of BaTiO3 powder calcined at 120$0^{\circ}C$ and 135$0^{\circ}C$ was investigated with respect to the grain growth behavior. It was found that BaTiO3 powder, which was calcined at 120$0^{\circ}C$, showed abnormal grain growth behavior during sintering process. At initial stage of sintering process, the densification rate of specimen was accelerated with rapid grain growth caused by the abnormal grain growth. But with the increase of sintering time, abnormally grown grain met each other and the density of specimen decreased drastically due to coalescence of pores located in triple junction. On the contrary, BaTiO3 powder calcined at 135$0^{\circ}C$ showed normal grain growth behavior and gradually densified with the increase of sintering time.

• 한국기계가공학회지
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• 제3권3호
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• pp.11-16
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• 2004

In this study, the characteristics of signals such as acoustic emission, vibration amplitude and noise level which are derived from the abnormal condition of compressor are investigated. The normal condition, vane stick sound and roller defect condition are chosen to analyze the signal in each cases. From the feature extraction of each signals, the dominant parameters of each signals which can identify the abnormal condition are suggested.

• JSTS:Journal of Semiconductor Technology and Science
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• 제14권4호
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• pp.365-375
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• 2014

This paper proposes an abnormal V-shaped-error-free non-blind deconvolution technique featuring an adaptively segmented forward-problem based iterative deconvolution (ASDCN) process. Unlike the algebraic based inverse operations, this eliminates any operations of differential and division by zero to successfully circumvent the issue on the abnormal V-shaped error. This effectiveness has been demonstrated for the first time with applying to a real analysis for the effects of the Random Telegraph Noise (RTN) and/or Random Dopant Fluctuation (RDF) on the overall SRAM margin variations. It has been shown that the proposed ASDCN technique can reduce its relative errors of RTN deconvolution by $10^{13}$ to $10^{15}$ fold, which are good enough for avoiding the abnormal ringing errors in the RTN deconvolution process. This enables to suppress the cdf error of the convolution of the RTN with the RDF (i.e., fail-bit-count error) to $1/10^{10}$ error for the conventional algorithm.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.821-826
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• 2001

Out of all metal-cutting processes, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. Accordingly, this paper deals with Basic system and Online system. Basic system comprised of spindle rotational speed, feed rates, thrust, torque and flank wear measured tool microscope. Online system comprised of spindle rotational speed, feed rates, AE signal, flank wear area measured computer vision. On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• 한국생산제조학회지
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• 제8권3호
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• pp.42-51
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• 1999

An experimental modeling of cutting and structural dynamics and the on-line detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics of cutting process but also for the analytic realization of diagnostic systems. In this regard, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision round shape machining such as turning, drilling and boring in mold and die making. In this study, simulation and experimental work were performed to show the malfunctioned behaviors. For this purpose, two new recursive approach (REIVM, RLSM) were adopted fur the on-line system identification and monitoring of a machining process, we can apply these new algorithm in real process for the detection of abnormal machining behaviors such as chipping, chatter, wear and round shape lobe waviness.

• 한국정밀공학회지
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• 제12권4호
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• pp.100-110
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• 1995

This paper aims at reviewing the possibility of application over normal or abnormal, detection used by AE, and the characteristics of grinding processes. In this study, when WA-vitri-fied ' resinoid bond grinding wheels:36 kinds of grinding wheel and grinding depth were tuned at the surface grinding, the zone of AE signal generation is theoretically modelled and reviewed by grinding processes. The variation of grinding resistance( F$n^{9}$ $F_{t}$) and AE signal is detected in-process by the use of AE measuring system. The tests are carried out in accordance with grain size and grade of grinding wheels, and work-pieces-STD11 and STD61. According to the experiment's results, the following can be expected;as grinding time passes by, the relation of grinding depth and quantity of AE signal, observing on AE signal and grinding burn suggest the characteristics of grinding processes and evalution on the possibility of control of grinding machine, and monitoring abnormal conditions.e, and monitoring abnormal conditions.