• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.129-134
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• 2002

In this study, the compliance measurement and cutting operation in tool - machine tool - workpiece system were carried out for the parameters identification of chatter vibration in turning.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.72-77
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• 2001

Monitoring of the chatter vibration is necessarily required to do automatic manufacturing system. Therefore, we constructed a sensing system using tool dynamometer in order to monitor of chatter vibration on cutting process. Furthemore, an application of neural network using behavior of principal cutting force signals Is attempted. With the error back propagation trining process, the neural network memorized and classified the feature of principal cutting force signals. From obtained result, it is shown that the chatter vibration can be monitored effectively by neural network.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.5
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• pp.49-54
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• 2004

In order to evaluate the stability of chatter vibration in turning precess, the micro-positioning cutting test with artificial tool vibration by piezoelectric actuation were carried out. In experiment, the phase lags between cutting forces and chip thickness variations were measured, and the dimensionless penetration-rate coefficient（$\overline{K^*}$） which is the most important parameter on the stability for chatter vibration was calculated. The results show that$\overline{K^*}$ can be applicable to the stability criterion for regenerative chatter vibration.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.85-90
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• 1996

In order to detect and suppress chatter in turning processes a stability control methodology was studied through manipulation of spindle speeds regarding to chatter frequencies. The chatter frequency was identified by monitoring and signal processing of sound pressure during turning on a lathe. The stability control methodology can select stable spindle speeds without knowing a prior knowledge of machine compliances and cutting dynamics. Teliability of the developed stability control methodology was verified through turning experiments on an engine lathe. Experimental results show that a microphone is an excellent sensor for chatter detection and control

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.219-224
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• 2004

There have been many researches on machine tool vibration and chatter to obtain assessment procedure and more productivity. In this paper chatter limit is predicted on a universal machining center which used a parallel mechanism. The prediction method uses the combination of structural dynamic characteristics and cutting dynamics. So the dynamic characieristics were obtained by vibration experiments. We showed the unstable cutting conditions, and from them we could plot the unstable borderlines.

• 한국기계연구소 소보
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• s.12
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• pp.93-103
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• 1984

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1618-1631
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• 1994

In this paper, in-process chatter detection methodology which utilizes nondimensional characteristic variables is introduced. To obtain nondimensional chatter detection indexes which are constant regardless of the cutting conditions during machining with the same tool and workpiece material, both the cutting forces and accelerations are measured and processed in time and frequency domain. The indexes are calculated from the present and past value of the acceleration and cutting force signals in time and frequency domain. The chatter is identified when these chatter detection indexes are bigger than the threshold which is decided by preliminary experiments. The experiment shows that these indexes works very well in-process chatter detection.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.745-750
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• 2014

The chatter vibration in the machining process plays bad role in machining quality such as high roughness as well as tool life and machine failure. And the grinding process under this risk in the fully automated factory is exposed to the unexpected mass machining quality problem. Studying the vibration signal of the hub bearing grinding process, the reason of chatter vibration was explained with the specific machining pattern of chatter. And this study suggests the chatter detecting method in the production line, which is monitoring the peak acceleration level around the natural frequencies of the specimen, and calculating kurtosis value by assuming the chatter is related to the resonance of the specimen. The suggested method was applied to the vehicle hub bearing grinding process and proved good to detecting the chatter induced machining quality problem.

• 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.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.6
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• pp.10-16
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• 2004

The detection and analysis of chatter behaviour in endmilling is very complex and difficult so it is necessary to detect and diagnose this chatter phenomenon clearly. This paper presents a new method for detecting the abnormal chatter in endmilling operation, based on the wavelet transform. Using AR spectrum the data that has chatter phenomenon was verified and the fundamental property of chatter and its characteristics in endmilling by using the wavelet transform is reviewed. This result obtained by wavelet transform proves the possibility and reliability of detecting the chatter in endmilling operation.