• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.1
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• pp.31-36
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• 2009

Micro-machining technology has been adopted for shape accuracy of micrometer and sub-micrometer scale, surface roughness of tens nanometer in industries. In micro-machining process the quality of machined surface is derived from machining condition and tooling. This paper investigates AE(acoustic emission) and cutting force signals according to machined surface quality related to machining condition. Machined surface quality was analyzed by the AE and cutting force parameter which reflect surface morphology. The characteristics of signal were extracted for process optimization by monitoring both the tool condition and the machined surface texture in micro end milling process.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.12
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• pp.1227-1236
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• 2012

The low speed machinery faults are usually caused by the bearing failure of the rolling elements. As the life time of the bearing is limited, the condition monitoring of bearing is very important to maintain the continuous operation without failures. A few monitoring techniques using time domain, frequency domain and fuzzy neural network vibration analysis are introduced to detect and diagnose the faults of the low speed machinery. This paper presents a method of fault detection for the rolling element bearing in the low speed machinery using the Wiener filtering and shock pulse counting techniques. Wiener filter is used for noise cancellation and it clearly makes the shock pulse emerge from the time signal with the high level of noise. The shock pulse counting is used to determine the various faults obviously from the shock signal with transient pulses not related with the bearing fault. Machine fault simulator is used for the experimental measurement in order to verify this technique is the powerful tool for the low speed machine compared with the frequency analysis. The test results show that the method proposed is very effective parameter even for the signal with high contaminated noise, speed variation and very low energy. The presented method shows the optimal tool for the condition monitoring purpose to detect the various bearing fault with high accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.281-286
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• 2004

The wear process of end mill is a so complicated process that a more reliable technique is required for the monitoring and controling 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 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. The tooth passing frequency appears as a harmonics form, and end mill wear is related with the first harmonic. It can be concluded from the result that the tool wear is correlate with the intensity of the measured sound at tooth passing frequency estimation of end mill wear using sound is possible through frequency analysis at tooth passing frequency under the given circumstances.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.242-250
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• 2010

For economical and environmental reasons, the aim of this research is hence to monitor the cutting conditions with the dry cutting, the wet cutting, and the mist cutting to obtain the proper cutting condition for the plain carbon steel with the ball end milling based on the consideration of the surface roughness of the machined parts, the life of the cutting tools, the use of the cutting fluids, the density of the particles of cutting fluids dispersed in the working area, and the cost of cutting. The experimentally obtained results of the relation between tool wear and surface roughness, the relation between tool wear and cutting force, and the relation between cutting force and surface roughness are correspondent with the same trend. The phenomena of surface roughness and tool wear can be explained by the in-process cutting forces. The models of the tool wear with the cutting conditions and the cutting times are proposed to estimate the tool cost for the different cooling strategies based on the experimental data using the multiple regression technique. The cutting cost is calculated from the costs of cutting tool and cutting fluid. The mist cutting gives the lowest cutting cost as compared to others. The experimentally obtained proper cutting condition is determined based on the experimental results referring to the criteria.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.587-593
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• 1996

Vibration analysis is one of the most powerful tools available for the detection and isolation of incipient faults in mechanical systems. The methods of vibration analysis in use today and under continuous study are broad band vibration monitoring, time domain analysis, and frequency domain analysis. In recent years, great interest has been generated concerning the use of time-frequency representation and its application for a machinery diagnostics and condition monitoring system. The objective of the research described in this paper was to develop a new diagnostic tool for the rotating machinery. This paper introduces a new time-frequency representation, Directional Wigner-Ville Distribution, which analyses the time- frequency structure of the rotating machinery vibration.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.61-66
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• 1994

Tool condition monitoring is one of the most important aspects to improve productivity and quality and to achieve intelligent machining system. The tool state is classified into three groups as chipping, wear and fracture. In this study, wear of a ceramic cutting tool for hardened die material (SKD11) was investigated. Flank wear was occured more dominant than crarer wear. Therefore, to predict flank wear, the modeling of cutting force has been performed. The modeling of cutting force by an assumption that act the stress distribution on the tool face obtained through a numerical analysis. The relationships between the cutting force and the tool wear can be constructed by machining paraneters with cutting conditions. Experiments were performed under the various cutting conditions to ensure the validity of force models. The theoretical predictions of the flank wear is approximately in good agreement with experimental result.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.5
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• pp.13-19
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• 2011

In this paper, the active monitoring and control system is developed. This system can monitor the status of high the speed spindle in real time during its processing, and can analyze its influence of dimensional accuracy and processing if any, and can control the machining condition to realize the machining system equipped with active monitoring and self-diagnostic features. Machining experiment was performed on 3 materials Al, Brass and S45C in order to derive the relation between active monitoring and control algorithm by the machining load. In addition, we measured surface roughness of processing specimen along with the data change of spindle rotating speed and conveying speed according to variation of machining load. Based on these experiments, we derived relations for each material that can be applied to the control algorithm to allow self control of the rotating speed and conveying speed according to the machining load.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.1
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• pp.43-50
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• 1996

From a manufacturing standpoint it would be desirable to monitor the degradation of drawing die, that is essential for the maintenance of die 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 also suggested that acoustic emission sigals contained valuable information regarding the stage of a drawing process such as the surface appearance of products and the condition of lubrication. These informations are 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 signal 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 signal. From these experimental, results, we understanded controlling factors of acoustic emission generation.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.5
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• pp.817-823
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• 2020

In recent, the machining of difficult-to-cut materials such as titanium alloys, stainless steel, Inconel, ceramic, glass, and carbon fiber reinforced plastics (CFRP) used in aerospace, automobile, medical industry is actively researched. Abrasive waterjet is a non-traditional processing method in which ultra-high pressure water and abrasive particles are mixed in a mixing chamber and shoot out jet through a nozzle, and removed by erosion due to collision with a material. In particular, the nozzle of the abrasive waterjet is one of the most important parts that affect the machining quality as with a cutting tool in general machining. It is very important to monitor the condition of the nozzle because the workpiece is uncut or the surface quality deteriorates due to wear, expanding of the bore, damage of the nozzle and clogging of the abrasive, etc. Therefore, in this paper, we propose a monitoring system based on Acoustic Emission(AE) sensor that can detect nozzle condition in real time during AWJ processing.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.989-995
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• 2010

This paper is focused on a simplified measurement of rail irregularity by some axle-box accelerometers for high-speed rail condition monitoring with in-service high-speed trains. Generally, the rail condition monitoring has been done by a special railway inspection vehicle with a 10m versine method. But, the monitoring method needs some expensive measurement system, and have been performed only at night due to its speed limit. In this research, a simplified measurement of rail irregularity using axle-box accelerometers is proposed to monitor the rail condition with in-service high-speed trains. The acceleration is measured by using two accelerometers on a axle-box, and stored in an on-board data acquisition system. The displacement is estimated from the acceleration data by a combination of Kalman filter and the frequency selective filter. The estimated results are compared with the measurement from a laser rail inspection system which is near the axle-box. From the comparison, the proposed method shows promise as a tool for the simplified measurement of rail irregularity at high-speed.