• Journal of the Korean Society for Precision Engineering
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• v.13 no.12
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• pp.151-157
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• 1996

The tool condition monitoring is one of the most important aspects to improve productivity and quality of workpiece. In this study, the wear of ceramic tool (A1$_{2}$0$_{3}$-TiC Series) cutting the hardened die material(SKD11) was investigated. Flank wear was more dominant than crater wear. Therefore the modeling of cutting force related to flank wear has been performed. The cutting force model was construct- ed by an assumption that the stress distribution on the tool face is affected by tool wear. The relationship between characteristics as cutting force and tool wear can be suggested by machining parameters depending on cutting conditions. Experiments were performed under the various cutting conditions to ensure the validity of force models. The theoretical predictions on the flank wear are approximately in good agreement with experimental results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.131-137
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• 2005

The purpose of this paper is to evaluate the axial magnetic flux measurement could be used as a tool of the condition monitoring system for the induction motor and to develope the diagnostic algerian for the electric motors. The magnetic leakage flux signal is captured by the flux coil located at the end of motor without the disturbance of the operation. And the signal is analyzed both time and frequency bases to detect the failure of the motor. Specific signature can be described in time and frequency domain for each faults of the motor. The spectrum of the signal was found more useful for the monitoring purpose. The supply voltage imbalance and tin to turn failure of the stator winding could be detected by analysing the specific sidebands of the axial flux and sideband of the rotor bar pass frequency with the high resolution spectrum. The goal of this study verity that the axial flux measurement for the induction motor is a powerful tool for the diagnostic method and develope the algorithm to detect the fault.

• 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.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.427-434
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• 2011

This paper is focused on application of recursive least squares method to estimate rail irregularities from the acceleration measurement on an axle-box or a bogie for the rail condition monitoring with in-service high-speed trains. Generally, the rail condition was monitored by a special railway inspection vehicle but the monitoring method needs an expensive measurement system. A monitoring method using accelerometers on an axle-box or a bogie was already proposed in the previous study, and the displacement was successfully estimated from the acceleration data by using Kalman and frequency selective band-pass filters. However, it was found that the displacement included not only the rail irregularities but also phase delay of the applied filters, and effect of suspension of the bogie and conicity of the wheel. To identify the rail irregularities from the estimated displacement, a compensation filter method is proposed. The compensation filters are derived by using recursive least squares method with the estimated displacement as input and the measured rail irregularity as output. The estimated rail irregularities are compared with the true rail irregularity data from the rail inspection system. From the comparison, the proposed method is a useful tool for the measurement of lateral and vertical rail irregularity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1991.11a
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• pp.95-100
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• 1991

From a manufacturing standpoint it would be desirable to monitor the degradation of drawing die, that is essential for the maintenance of quality, the evaluation of product integrity and the reducing scrap. Acoustic emission is powerful method in monitoring fine wire drawing process, especially in detecting the die fracture at early stage. Experiments at so suggested that acoustic emission signals contained valuable information regarding the stage of a drawing process such as the surface appearance of products and the condition of lubrication. Using these informations makes AE monitoring techniques a possible tool in monitoring the drawing process operation. In order to approach this, this paper discusses the nature of acoustic emission signals produced in drawing process under various conditions. Experimental results are presented which illustrate the effects of wire and die material, lubricants, and drawing speed on the generation and the mean voltage level of acoustic emission signals. The results from these tests give controlling factors of acoustic emission generation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.59-64
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• 1997

This paper investigates the relationship between cutting conditions and Acoustic Emission(AE) signals; AEavg, AErms, AEmode, as the base working to monitor the tool wear with in-process. For this purpose, cutting tests were conducted on a CNC lathe with comprehensive cutting conditions.. It is known that AEavg and AErms are proportionaly increased as the increasing of cutting velocity and depth of cut respectively. It is also known that AEmode among three kinds of AE signals may be applied for in-process monitoring to make the self diagnosis system because of its stability to the variation of cutting condition.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.22-28
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• 1995

Micro Drills have found ever wider application. However micro drilling is a machining to integrate the difficult machinablities such as tool stiffness, position control and revolution accuracy, and is known to cost and time consuming. So, this study aimed to practice ultraminiature drilling(0.05 .phi. ) wiht simple component, if possible. System is developed as the three modules : feed drives, spindle and monitoring part. The dynamics of measured current signals from the spindle of Micro Hole Drilling machine are investigated to establish the criteria of stepfeed mechanism. Cutting experiments identify the relationship of spindle rpm, feed rate and tool life. The smaller drill diameter is, the more suitable cutting condition have to be selected because of chip packing.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.6
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• pp.709-715
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• 2011

Chattering in cutting operations are usually a cumbersome part of the manufacturing process in mechanical. Particular, machining performance such as that of the boring process is limited by cutting condition at the movable components. Among various sources of chatter vibration, detrimental point in cutting condition is found a mechanical condition on overhang. It limits cutting speed, depth, surface roughness and tool wear failure as result because the all properties are varying with the metal removal process. In this case, we have to observe the resonance frequencies of a boring bar for continuous cutting. In the established research, boring bar vibration of cutting system has been measured with the aid of accelerometer. However, the inherent parameters of internal turning operations are severely limit for the real time monitoring on accelerometers. At this point, this paper is proposed other method for real time monitoring during continuous cutting with optical fiber at the inside of boring bar. This method has been used a plastic fiber in the special jig on boring bar by based on experimental modal analysis. In this study, improvement of monitoring system on continuous internal cutting was attempted using optical fiber sensor of inside type because usually chattering is investigated experimentally measuring the variation in chip thickness. It is demonstrated that the optical fiber sensor is possibility to measure of chattering with real time in boring process.

• Design & Manufacturing
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• v.16 no.4
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• pp.46-51
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• 2022

The piercing process of creating holes in sheet metals for mechanical fastening generates high shear force. Real-time monitoring technology could predict tool damage and product defects due to this severe condition, but there are few applications for piercing high-strength aluminum. In this study, we analyzed the load signal to predict the punch's wear level during the process with a piezoelectric sensor installed piercing tool. Experiments were conducted on Al6061 T6 with a thickness of 3.0 mm using piercing punches whose edge angle was controlled by reflecting the wear level. The piercing load increases proportionally with the level of tool wear. For example, the maximum piercing load of the wear-shaped punch with the tip angle controlled at 6 degrees increased by 14% compared to the normal-shaped punch under the typical clearance of 6.7% of the aluminum piercing tool. In addition, the tool wear level increased compression during the down-stroke, which is caused by lateral force due to the decrease in the diameter of pierced holes. Our study showed the predictability of the wear level of punches through the recognition of changes in characteristic elements of the load signal during the piercing process.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.8
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• pp.1287-1294
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• 2003

The wear process of end mill is so complicated process that a more reliable technique is required for the monitoring and controlling the tool life and its performance. This research presents a new tool wear monitoring method based on the sound signal generated on the machining. The experiment carried out continuous-side-milling for 4 cases using the high-speed-steel end mill under wet condition. The sound pressure was measured at 0.5m from the cutting zone by a dynamic microphone, and was analyzed at frequency domain. As the cutter impacts the workpiece surface, a situation of farced vibration arises in which the dominant forcing frequency is equal to the tooth passing frequency of the cutter. The tooth passing frequency appears as a harmonics form, and end mill flank wear is related with the first harmonic. It is possible to detect end . mill flank wear. This paper proposed the new method of the end mill wear detection.