• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.69-73
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• 1996

Tool wear monitoring is very important aspect in metal cutting because tool wear effects quarity and precision of workpiece, tool life etc. In this study we detected force signal through tool dynamometer in turning and using it we conducted 6th AR modeling and fractal analysis. Finally the back-propagation model of the neural network is utilized to monitor tool wear and features are extracted through AR model and fractal analysis.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.1951-1962
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• 1993

The creation process of a typical machined surface is treated here as a dynamic system. An investigation is carried out to establish a relationship between the characteristics of cutting force fluctuations that cause vibration response of the tool-workpiece system and the formation of surface in face cutting by sintered carbide cutting tool. Cutting force is measured and analyzed in frequency domain. The power spectral densities of cutting force give a useful information in surface generation and it can be used to find out the control factor of surface roughness. The terms, PSD ratio & Normalized spindle frequency PSD, are defined and when the value of power in spindle frequency is absolutely little but relatively large, it is obtained high accuracy surface roughness. The aim of this research is to find surface profile by measured and analyzed cutting force signals. The simulation of surface generation gives the comprechension of its mechanism and help to predict and control the surface quality. In this study, it is suggested what informations about surface generation can be acquired from the cuttuing force signal and an way of generating a better surface.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.8
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• pp.1173-1182
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• 2001

Recent noticeable advances of CNC machine tools have considerably improved productivity and precision in manufacturing processes. However, in the respect of productivity some defects still remain because selection of machining conditions entirely depends on the experiences of programmers. Usually, machining conditions such as feed rate and spindle speed have been selected conservatively by considering the worst cases, and it has brought the loss of machining efficiency. Thus, the improvement of cutting force controller has been done to regulate cutting force constantly and to maximize feedrate simultaneously in case that machining conditions change variously. In this study, sliding mode control with boundary layer is applied to milling process for cutting force regulation and in a commercial CNC machining center data transfer between PC and PMC (programmable machine controller) of CNC machine is done using a standard interface method. And in the cutting force measurement, an indirect cutting force measuring system using current signal of AC servo is adopted in order not to use high-priced equipment like tool dynamometer. The purpose of this study is to maximize the productivity in milling process, thus its results can be applied to cases such as rough cutting process.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.1
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• pp.28-37
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• 2004

An on-line monitoring system of endmill failure such as weal, chipping, and fracture is developed using AE, cutting force Characteristic variations of AE and cutting force signals due to endmill failure are identified as follows. When endmill fracture occurs, AE count rate shows a rapid Increase in conjunction with a subsequent decrease while a standard deviation of the principal cutting force Increases significantly. The increase of AE count rate precedes the Increase of standard deviation of principal cutting force. Chipping results in relatively small increase and decrease of AE count rate without any significant variation of the cutting force Gradual increase of AE count rate and mean principal cutting force are Identified to be related with the wear of cutter. A cutter fracture detection algorithm is developed based on the present results. The signals me normalized to enhance the applicability of the algorithm to Wide those of fresh cutters, and qualitative characteristics of AE signals encountered at the moment of fracture are employed. It is demonstrated that the algorithm can detect the cutter fracture successfully.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.3
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• pp.150-159
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• 2000

In-process diagnosis of the cutting state is essential for the automation of manufacturing systems. Especially when the cutting process becomes unstable it induces self-exited vibrations a frequent case of poor tool life rough surface finish damage to the workpiece and the machine tool itself and excessive down time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time monitoring and controlling chatter. This paper describes the detection method of chatter vibration using cutting force in turning process. In order to detect a chatter vibra-tion the dynamic fluctuation of radial force is analyzed since this components is sensitive to the chatter. The envelope sig-nal of radial force has been calculated by the use of FIR Hilbert transformer and it was useful to classify the chatter signal from the dynamically unstable circumstances. It was found that the mode and the mode width were closely correlated with the chatter amplitude was well. Finally back propagation(BP) neural network have been applied to the pattern recognition for the classification of chatter signal in various cutting conditions. The validity of this systed was confirmed by the experiments under the various cutting conditions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.3
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• pp.24-31
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• 2004

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fine-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining, however, sensing and interpretation of signals ar more complex. In addition, the shafts of the mini-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm by LabVIEW was developed and the following results are obtained. It was possible to use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.259-264
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• 1995

Recently, in order to achieve high flexibilty, monitoring and control strategies of a new type have been developed. This paper investigates the fesability of using scoustic emission signal analysis for the detection of built-up edge during machining. Results for maching SM45C steel show that the presence of a built-up edge can significantil affect the generation of acoustic emission in metal cutting. When the cutting speed comes to the conditions conducive to development of built-up edge, it is shown that the slope of curve-fitted AErms signal undergoes a change. The fesability of utilizing AErms in built-up edge sensing is sugested.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.15-22
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• 2002

This study shows how the change of helix angle of different helix angle end mill affects machining accurracy. It was verified that cutting force are remarkably low when endmill has helix angle of different helix angle 250, 310, 370 and AE signal have less reationshap with the change of helix angle. Moreover, as the number of rotations are increases, the AE signal increased with the proportion to the number but cutting force are inversely proportional to the rotation.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.75-81
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• 1997

Automatic monitoring the cutting state is one of the important problems to increase the reliability of modern machining processes. In this study, cutting force signals were used in order to monitor the tool wear and fracture in the turning process. Turning experiments were performed using cemented carbide insert tools(K20) and STS304 steel as a workpiece. Cutting force signal characteristics and histogram analysis method were used to recognize the cutting states. It was found that tool wear and fracture can be diagnosed from the cutting force signal coefficient of variation(C.V.) and histogram analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.817-821
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and system, which were hitherto based on linear models. Theory of chaos, which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end millingprocess. Then, it will be verified that cutting force is low-dimensional deterministic chaos calculating Lyapunov exponents, Fractal dimension, Embedding dimension. Aen it will be investigated that the relations between characteristic parameter caculated form sensor signal and tool wear.