• Tribology and Lubricants
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• v.10 no.4
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• pp.51-58
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• 1994

Condition monitoring technology has recently been received much attention in the light of its significance on the maintenance of complex machineries such as turbines in power plants. Currently, turbines in power plants are maintained by scheduled overhaul based on the manufacturer's recommendations and the utility's experience. Although this preventive maintenance is known to be very effective, operators have less access to identify failure of elements when it happens between overhaul period. Therefore, in this study, a development of a on-line condition monitoring system through wear debris analysis of lubricating oils is aimed with a view to detecting abnormal wear behaviour of bearings and other wet-components at an early stage, allowing better outage scheduling and minimizing forced outages. For field application purposes, the on-line system developed was installed on the turbine of the No.4 unit at Ulsan Power Plant and its performance has been evaluated on site.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.808-817
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• 2016

Recently, the wearable computing technology with bio-sensors has been rapidly developed and utilized in various areas such as personal health, care-giving for senior citizens who live alone, and sports activities. In particular, the wearable computing equipment to measure vital signs by means of digital yarns and bio sensors is noticeable. The wearable computing devices help users monitor and manage their health in their daily lives through the customized healthcare service. In this paper, we suggest a system for monitoring and analyzing vital signs utilizing smart healthcare clothing with bio-sensors. Vital signs that can be continuously acquired from the clothing is well-known as unstructured data. The amount of data is huge, and they are perceived as the big data. Vital sings are stored by Hadoop Distributed File System(HDFS), and one can build data warehouse for analyzing them in HDFS. We provide health monitoring system based on vital sings that are acquired by biosensors in smart healthcare clothing. We implemented a big data platform which provides health monitoring service to visualize and monitor clinical information and physical activities performed by the users.

• 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.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.478-490
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• 2022

TBM disc cutter, which is the main cutting tool of tunnel boring machine (TBM), is replaced when it is excessively worn during the boring process. Disc cutters are usually monitored by workers at cutterhead chamber, and they check the status and wear amount of cutters. Because cutterhead chamber is usually in dangerous circumstance due to high pressure and instability of excavation surface, the measurement by manpower occasionally results in inaccuracy of measurement result. In order to overcome the limitations, the real-time disc cutter monitoring techniques have been developed in some foreign countries. This paper collected the current status of disc cutter monitoring system from the literature. Several types of sensors are used to measure the cutter wear, and it is believed that the collected information can be useful reference when similar domestic technologies are developed in the future.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.38-45
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• 1996

This study was focused on the prediction of the approprite tool life by clarifying the correlation between progressive drill wear and AE signal. on drilling SM45C the following results have been obtained; RMSAE, AE CUM-CNTS had a tendency to increase slowly according to wear size, at 1000rpm, 150mm/min However, these increased suddenly in the range of 0.20~0.22mm wear, about 102 holes and had a tendency to go up and down until the drilling was impossible. The sudden increase of AE signals shows that something is wrong and it is closely connected with drill wear and chipping. It also makes the working surface bad From the above results, AE signals could be used to monitor the drill's condition and to determine the right time to change tools.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.3
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• pp.15-21
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• 1996

This study is focused on the prediction of appropriate tool life by clarifying the correlation between progressive tool wear and AE(Acoustic Emission) signals, while cutting stainless steel by end mill on the machining center. The results of this study were that RMSAE tends to increase linearly along with the increase of the cutting speed, and it was more sensitive to depth of cut than to the variation of feed rate at the same cutting conditions, and RMSAE increases around 0.21mm flank wear hereby AE-HIT also increases. AE signals depend upon tool wear and fracture from the above results. Therefore, the AE signals can be utilized in order to monitor the tool condition.

• Tribology and Lubricants
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• v.22 no.5
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• pp.276-281
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• 2006

The fractal dimension is quantitatively to define the irregular characteristic of the shape in natural. It can be useful in describing morphological characteristics of various wear particles. This paper was undertaken to diagnose failure condition for sliding members in lubrication by fractal dimension. It will be possible to diagnose wear mechanism, friction and damage state of machines through analysis of shape characteristics for wear particle on driving condition by fractal parameters. In this study, the calculating and analyzing methods of fractal dimensions were constructed for the condition monitoring and wear particle analysis in lubricant condition. So, we carried out the Friction and wear test with the ball on disk type tester, and the fractal parameters of wear particle in lubricated conditions were calculated. Fractal parameters were defined as texture fractal dimension ($D_{t}$), structure fractal dimension ($D_{s}$) and total fractal dimension (D).

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.923-924
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• 2008

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.3
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• pp.7-15
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• 2018

Drilling processes require a cutting monitoring function that can be analyzed and gives feedback about strange conditions, tool collision and tool wear in real time. In this study, we proposed a drill monitor using the torque from the main spindle in CNC machine tools and a PROFIBUS network as a PLC-based interface. This paper studied drilling torque changes depending on drill size, the repetition cutting of the drilling and the drill's wear in the same cutting conditions. The material of the drills was high speed steel (HSS) and uncoated. The drills chosen were 2.7 mm, 6.7 mm, and 10.0 mm in diameter. These drills were selected because they had basic holes for their taps.