• 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.10 no.4
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• pp.1-7
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• 2011

The mode analysis of end-milling was introduced using recursive parametric modeling. Also, a numerical mode analysis of FRF in end-milling at different conditions was performed systematically. In this regard, a REIVM(recursive extended instrumental variable method) modeling algorithm was adopted and natural modes of real and imaginary part were discussed. This recursive approach can be used for the on-line system identification and monitoring of an end-milling for this purpose. For acquiring a cutting force, an experimental practice was performed. And these end-milling forces were used for the calculation of FRF(Frequency response function) and its mode analysis. Also, the FRF was analysed for the prediction of end-milling system. As a results, this algorithm was successful in each condition for the detection of natural modes of end-milling. After numerical analysis of the FRF, the tooth passing frequency was discriminated in their FRF, power spectrum and mode calculation.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.73-80
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• 1998

The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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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.