• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1517-1518
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• 2015

The paper deals with the real time sensing of a chatter vibration in grinding machine line of automobile bearings using machine black box. The chatter vibration plays bad role in machining quality such as high roughness as well as tool life and machine failure. In this paper, the vibration signals of the automobile hub bearing in the grinding process are shown in the time domain and frequency domain. Through the vibrational signals, chatter vibration badness is detected using machine black box. Therefore, machine black box can be applied to the real time detection of the grinding process in engineering fields.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.947-951
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• 1997

Recently, the necessity of the detection of abnormal machining process is being emphasized in order to improve the machining accuracy and reduce the cost in unmanned operating system. The vibration by chatter generated in cutting processes within machine tools is a relative motion between tools and workpieces. So, if the chatter occurs, the surface roughness and accuracy of workpieces will be deteriorate and it leads to the rapid wear of tools. The author intended to use the I /sab/RMS (current of root mean square) of current sigals and the movimg C.V. (coefficient of variation) of each phase for the detection method of chatter.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.179-184
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• 2013

In this article, we introduce the study case of technology that can automatically compensate the errors of these factors of a machine during processing on the machine tool's CNC(Computerized Numerical Controller) in real time. The biggest factors that lower the machining accuracy are thermal deformation and chatter vibration. This study is related to the detection and compensation of thermal deformation and chatter vibration that can compensate for faster and produce processed goods with more precision by autonomous compensation. In addition, this study is related to the active control of vibration during machining, monitoring of cutting force and auto recognition of machining axes origin. Thus, we attempt to introduce the related contents of the development we have made in this article.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.5
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• pp.25-32
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• 1995

In highly automated milling process, in-process monitoring of the malfunction is indispensable to ensure efficient cutting operation. Among many malfunctions in milling process, chatter vibration deteriorates surface finish, tool life and productivity. In this study, the monitoring system of chatter vibration for face milling process is proposed and experimentally estimated. The monitoring system employs two types of sensor such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are extracted in time domain for the input patterns of neural network to reduce time delay in signal processing state. The resultes of experimental evaluation show that the system works well over a wide range of cutting conditions.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.367-372
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• 2012

The biggest factors that lower the machining accuracy are thermal deformation and chatter vibration. In this article, we introduce the study case of technology that can automatically compensate the errors of these factors of a machine during processing on the machine tool's CNC(Computerized Numerical Controller) in real time. This study is related to the detection and compensation of thermal deformation and chatter vibration that can compensate for faster and produce processed goods with more precision by autonomous compensation. In addition, this study is related to the active control of vibration during machining, monitoring of cutting force and auto recognition of machining axes origin. Thus, we attempt to introduce the related contents of the development we have made in this article.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.76-83
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• 2001

In this study, the static and dynamic characteristics of turning process was modelled and the analytic realization of regen-erative chatter mechanism was discussed. In this regard, we have discussed on the comparative assessment of recursive times series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision turning operation. In this study, simulation and experimental work were performed to show the malfunction behaviors. For this purpose, new Recursive Extended Instrument Variable Method(REIVM) was adopted for the on-line system identification and monitoring of a machining process. Also, we can apply REIVE algorithms in real process for the detection of chatter frequency and dynamic property and analyze the stability lobe of the system by changing a parameter of cutting dynamics in regenerative chatter mechanics, if it is stable or unstable, Also, The stability lobe of chatter was analysed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.971-974
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• 2001

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(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.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.101-108
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• 2001

In this study, the static and dynamic characteristics of endmilling process were modelled and the analytic realization of chatter mechanism was discussed. In this reward, We have discussed on the comparative assessment of recursive time series modeling algorithms that cal represent time machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental works were performed to show the malfunctional behaviors. For this purpose, new recursive algorithm(RLSM) was adopted for the oil-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 dynamics in regenerative chatter mechanics.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.20-27
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• 2000

A chatter vibration and a workpiece burn are the main phenomena to be monitored in modern grinding processes. This study describes a trouble diagnosis of the cylindrical plunge grinding process using the power and acoustic emission (AE) signals. The raw signals of the power and the AE occurred during the grinding operation were sampled and analyzed to determine the relationship between each fault and change of signals. A neural network that has a high success rate of the fault detection was used. Furthermore, an analysis on the influence of parameters to the chatter vibration and the grinding burn was conducted.