• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.982-986
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• 1997

A method using cutting force signal and neural network for detection tool damage is proposed. Cutting force signal is gained by tool dynamometer and the signal is prepocessed to normalize. Cutting force signal is changed by tool state. When tool damage is occurred, cutting force signal goes up in comparison with that in normal state. However,the signal goes down in case of catastrophic fracture. These features are memorized in neural network through nomalizing couse. A new nomalizing method is introduced in this paper. Fist, cutting forces are sumed up except data smaller than threshold value, which is the cutting force during non-cutting action. After then, the average value is found by dividing by the number of data. With backpropagation training process, the neural network memorizes the feature difference of cutting force signal between with and without tool damage. As a result, the cutting force can be used in monitoring the condition of cutting tool and neural network can be used to classify the cutting force signal with and without tool damage.

• 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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.144-149
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• 2000

The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc. In this study, time series sequence of cutting force was acquired by taking advantage of piezoelectric type tool dynamometer. Radial cutting force was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. ARMA(auto regressive moving average) model was selected for system model and second order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.131-134
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• 1995

The high efficiency and accuracy in machining the die material can be abtained in high speed machining, so it is necessary to analyze the mechanism of high speed cutting process : cutting force, flank wear. The tool dynomometer with high natural frequency is newly developed. With this device, the mechanism of high speed cutting process is investigated according to speed and feedate.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.1048-1051
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• 2001

This paper presents an analytical and experimental study of a cryogenic machining for precision hard turning. A cryogenic circulation system is designed and mounted on the top of the tool insert. The machining process used is facing operation on a CNC turning center with dry and cryogenic conditions. The tool temperature and cutting forces are measured by the K-type thermocouple and by a three-component Kistler dynamometer, respectively. Both data are fed into the data acquisition program through an A/D card. Surface roughness and form accuracy of the machined surface are measured by WYKO NT2000. It is also found that surface roughness and form accuracy with cryogenic cooling are better than those with no coolant.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.10
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• pp.37-45
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• 2007

End-milling is intermittent cutting process performed by a tool with a number of teeth. Its cutting forces are commonly measured by the tool dynamometer which has rectangular coordinates. In this case, the pattern of cutting forces is different according to cutting conditions. At a certain cutting condition, the sign of cutting force changes from positive to negative during a revolution of one tooth. The change of force direction excites a cutting tool and severe vibration arises when radial depth of cut increases. In this study, cutting experiments and simulations were carried out in order to explain the cause of the change of the cutting force direction. In addition, the effect of the cutting force change was discussed in terms of chatter vibration in end milling.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.466-471
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• 2003

In order to analyze linear motor driven feed system, preliminary studies have been conducted focusing on the performance evaluation of the system based on the various combination of control gain along with acceleration. Tentative simulation revealed that due to the complexity of control system reduced number of control condition is recommended. Actual machining process with conventional feed system using endmill tool was employed as a preliminary study. Several sensing methods including AE, acceleration sensors and tool dynamometer were used. Results revealed the consistency in AE and cutting resistance. There were inconsistent empirical results in accelerometer probably due to the insensitivity of the sensor signal with respect to the experimental system

• Journal of the Korean Society for Precision Engineering
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• v.14 no.8
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• pp.115-121
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• 1997

The in-process detection of the tool wear is one of the most important technologies in completely auto- matic operation of machine tool. In this research, using the tools having flank wear, the dynamic compo- nent of cutting forces is considered to be available for identifying the cutting process. In order to investi- gate this relation in detail, the cutting forces in turning of workpiece made of aluminum were measured by dynamometer of piezoelectric type, and the dynamic components of cutting force were analyzed. The fre- quency analysis, probability density analysis and RMS analysis of the dynamic components were carried out independently. Through the experiments, the characteristics of the tool system have a large effect on the dynamic component of cutting forces. As a result, it is shown that the dynamic cutting force was able to detect flank wear accurately.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.24-33
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• 1994

The main applications of CFRP are sports, aerospace and general industrial uses including automobiles. As this application fields expands the opportunity of machining, but CFRP is difficult to cut because of delamination of the composites and the short tool life. In this paper, the machinability of multidirectional CFRP by means of ultrasonic vibration cutting, which has been verified experimentally investigated.The experimentally to be highly effective in view of cutting force and surface quality.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.147-153
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• 1997

Fault diagnosis technique in machining system which is one of engineering techniques absolutely necessary to automation of manufacturing system has been proposed. As a whole, diagnosis process is explained by two steps: sensor data acquisition and reasoning current state of system with the given sensor data. Flexible disk grinding process implemented in milling machine was employed in order to obtain empirical manufacturing process information. Resistance force data during machining were acquired using tool dynamometer known as sensor which is comparably accurate and reliable in operation. Tool status during the process was analyzed using influnece diagram assigning probability from the statistical analysis procedure.