• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.8-13
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• 2000

Die polishing technology is very critical to determine quality and performance of the final products. Die polishing processes have not been automated because the automation requires a great deal of experience and skill of experts. Thus, to implement a fully automated polishing process, the development of polishing status monitoring system replacing the skill of experts is critical. AE is known to be closely related to material removal rate(MRR). As the surface is rougher, MRR gets larger and AE increased. The surface roughness can be indirectly estimated using the AE signal measured during automatic die polishing process. In this study, The polishing state monitoring system using AEms signal was developed. This system can be not only to monitor the abnormal state but also to estimate a state of surface roughness of polishing surface qualitatively.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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• pp.8-16
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• 2003

Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.442-445
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• 1997

A challenging activity in the manufacturing industry is to perform in real time the continuous monitoring of the process state, the situation assessment and identification of the problem on line and diagnosis of the cause and importance of the problem if he process does not work properly. This paper describes LAT(Ladder Analysis Tool) system for fault tree generation to improving the fault diagnosis of CNC machine tools. The system consists of 4 steps which can automatically ladder analysis from ladder diagram to two diagnosis function models. The two diagnostic models based on he ladder diagram is switching function model and step switching function model. This system tries to overcome diagnosis deficiencies present machine tool.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.6
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• pp.37-44
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• 2005

This paper presents fabrication techniques of the optical fiber position sensor (or spindle state monitoring. These include selection of components such as optical fibers, a laser-diode, a photo-diode, and op-amp IC of the signal process circuit. We also describe electric runout problem. The fabricated sensor has a linearity of $1.7\%$ FSO in the air gap range $0.1\~0.6mm$, a resolution of $0.37{\mu}m$ and a bandwidth of 6.3kHz. Finally, we have successfully operated a magnetic bearing spindle system using the sensors.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.108-114
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• 2007

A new cutting force estimating approach and machining state monitoring examples are presented which uses a cylindrical displacement sensor built into the spindle. To identify the tool-spindle system dynamics with frequency up to 2 kHz, a home-built electro-magnetic exciter is used. The result is used to build an algorithm to extract the dynamic cutting force signal from the spindle error motion; because the built-in spindle sensor signal contains both spindle-tool dynamics and tool-workpiece interactions. This sensor is very sensitive and can measure broadband signal without affecting the system dynamics. The main characteristic is that it is designed so that the measurement is irrelevant to the geometric errors by covering the entire circumferential area between the target and sensor. It is also very simple to be installed. Usually the spindle front cover part is copied and replaced with a new one with this sensor added. It gives valuable information about the operating condition of the spindle at any time. It can be used to monitor cutting force and chatter vibration, to predict roughness and to compensate the form error by overriding spindle speed or feed rate. This approach is particularly useful in monitoring a high speed machining process.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.57-63
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• 2022

This study describes a system that monitors the tool and cutting state of automatic beveling operation in real time. As a signal for cutting state monitoring, a motor current detected from the spindle drive system of the automatic beveling machine is used to monitor abnormal state. Because automatic beveling is processed using a face milling cutter, the cutting force mechanism is the same as the milling process. The predicted cutting torque is obtained using a cutting force model based on specific cutting resistance. Then, the predicted cutting torque is converted into the spindle motor current value, and cutting state stability is diagnosed by comparing it with the motor current value detected during beveling operation. The experimental results show that the spindle motor current can detect abnormal cutting state such as overload and tool wear during beveling operation, and can diagnose the cutting stability using the proposed equip-current line diagram.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.292-297
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• 2004

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) which is independent of the CNC vendor. The OAC and machine tools with OAC led the convenient environment where it is possible to implement user-defined application programs efficiently within CNC. Tis paper proposes a method of operational fault cause diagnosis which is based on the status of programmable logic controller (PLC) in machine tools with OAC. The operational fault is defined as a disability state occurring during normal operation of machine tools. The faults are occupied by over 70% of all faults and are also unpredictable as most of them occur without any warning. Two diagnosis models, the switching function (SF) and the step switching function (SSF), are propose in order to diagnose the fault cause quickly and exactly. The cause of an occurring fault is logically diagnosed through a fault diagnosis system (FDS) using the diagnosis models. A suitable interface environment between CNC and develope application modules is constructed in order to implement the diagnostic functions in the CNC domain. The diagnosed results were displayed on a CNC monitor for machine operators and provided to a remote site through a web browser. The result of his research could be a model of the fault cause diagnosis and the remote monitoring for machine tools with OAC.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.142-151
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• 1993

An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.1
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• pp.65-71
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• 2003

In a high speed spindle system it is very important to monitor the state of rotating rotor. Particularly in active control spindle system the position sensor must provide feedback to the control system on the exact position of the rotor. In order to monitor the state of a high speed spindle exactly, high accuracy and wide frequency bandwidth of sensors are important. The focus in this paper is to make a fiber optic sensor for monitoring rotor of magnetic bearing, to design the circuit for detecting optical signal, and to evaluation static and dynamic characteristics of fiber optic sensor.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.411-416
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• 2002

In a high speed spindle system, it is very important to monitor the state of rotating rotor. Particularly in active control spindle system, the position sensor must provide feedback to the control system on the exact position of the rotor. In order to monitor the state of a high speed spindle exactly, high accuracy and wide frequency bandwidth of sensors are important. The focus in this paper is to make a fiber optic sensor for monitoring rotor of magnetic bearing, to design the circuit for detecting optical signal, and to evaluation static and dynamic characteristics of fiber optic sensor.