• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.50-57
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• 1997

In order to make unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstations to provide the required intelligence of the expert. This paper deals with condition monitoring for chatter, tool wear and breakage during turning operation. To develop economic sensing and identiffication methods for turning processes, sound pressure measurement and digital signal processing technique were proposed. We suppressed chatter by stability control methodology, which was studied through manipulation of spindle speeds regarding to chatter frequencies. It was shown that tool wear and fracture were identified and to be estimated by using the wear indices. The validity of the proposed system was confirmed through the large number of cutting tests.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.83-90
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• 2018

The purpose of this study is for fundamental research of meditation smart wear for physical and mental healing, and researching method for monitoring phase of meditation through textile by measuring the number of abdominal respiration when meditating. For this purpose, the research implemented Single Wall Carbon Nano-Tube (SWCNT) based strain gauges type textile sensor, considered reliability and validity of respiratory sensing, and analyzed efficiency of respiratory sensing based on body parts comparatively. The first preliminary experiment was to evaluate the performance of textile sensor through abdominal model dummy which open and shut of 5 cm repeatedly for 2 minutes at the rate of 0.1Hz in order to simulate abdominal respiration. It concluded signal efficiency between reference sensor(BIOPAC) and textile respiratory sensor appears statistically significant (p<0.001). The second experiment were conducted with 4 subjects doing abdominal respiration under same conditions, and after comparing the signal values between two sensors from 4 attached locations(around center and sides of omphali and phren), center of omphali and sides of phren were selected as suitable location for measuring meditational breathing as they showed large and stable signals. In result, this research aimed for implementing of the textile sensor for sensing meditational breathing of long respiration cycle, review of reliability and validity for sensing number of meditational respiration with the sensor and consideration of sensing efficiency by sensing location on body parts.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.82-87
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• 1997

In order to make unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstation to provide the required intelligence of the expert. This paper deals with condition monitoring for tool wear and fracture during turning operation. Developing economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. The validity of the proposed system is confirmed through the large number of cutting tests.

• Transactions of the Korean Society of Mechanical Engineers
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• v.8 no.5
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• pp.450-461
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• 1984

A new indirect tool wear sensing technique is proposed using time series analysis. The acceleration measured on the tool post in the vertical direction during turning is sampled with uniform interval, and fitted following the ARMA modeling procedures. Various signal characteristics are observed in respect with the progress of flank wear. From those observations it is believed that; *The variance of the signal is approximately proportional to the increase of flank wear. *The absolute power of a dynamic mode decreases in the beginning of cutting until the maximum flank wear increases up to 0.4-0.5mm, and then increases. *The other characteristics are not so much related to the tool wear as the signal variance and the absolute power of a dynamic mode. Hence, the absolute power of a dynamic mode seems to be a good factor for the indication of tool-change time regardless of tool material or cutting conditions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.269-273
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• 1997

In order to maker unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstations to provide the required intelligence of the expert. This paper deals with condition monitoring for chatter, tool wear and fracture during turning operation. To develop economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique were proposed. We suppressed chatter by stability control methodology, which was studied through manipulation of spindle speeds regarding to chatter frequencies. It was shown that tool wear and fracture were identified and to be estimated by using the wear indices. The validity of the proposed system was confirmed through the large number of cutting tests.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.2
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• pp.95-103
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• 1993

In the manufacturing field, some traditional manufacturing and machining methods become weakened the productivity, the external competitive power, and accuracies of the products. In these point of view, the unmanned and intelligent manufacturing systems are proposed by some manufacturing companies. The real-time monitoring technology of the cutting tool conditions i.e. tool wear, tool breakage, crack, and chipping anre necessarily reauired to realize those system, especially. In this study, we constructed the multi- sensing system using the acceleration sensor, the current sensor, and the loadmeter of a machine tool. Also, we analyzed the nose breakage, the massive signal, and some monitoring features by means of the developed system.

• Journal of Drive and Control
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• v.21 no.1
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• pp.53-58
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• 2024

With the recent development of intelligence and automation technologies for construction machinery, the demand for safety and efficiency of road-cutting operations has continued to increase. In response to this, a double-blade road cutter has been developed that can automatically cut roads. However, a double-blade road cutter has a load difference between the two blades due to the ground and wear conditions of the cutting blades. The difference in load between the two blades distorts the direction of travel of the cutter. In this study, a vision sensor-based driving guide technology was developed to correct the driving path of road cutters. In addition, we developed a load-sensing technology that detects blade loads in real-time and controls driving speed in the event of overload.

• Tribology and Lubricants
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• v.32 no.6
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• pp.189-194
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• 2016

Wear debris in lubricating oil can be indicative of potential damage to mechanical parts in rotating and reciprocating machinery. Therefore, on-line or in-line monitoring of lubricating components in machinery is of great importance. This work presents a device based on inductive measurement of lubricating oil to detect magnetic wear particles in a tested volume. The circuit in the device consists of Maxwell Bridge and LVDT to measure inductance differences between pure and contaminated oil. The device detects the passage of ferrous particles by monitoring inductance change in a coil. The sensing principle is initially demonstrated at the microscale using a solenoid. The device is then tested using iron particles ranging from $50{\mu}m$ to $100{\mu}m$, which are often found in severely worn mechanical components. The test results show that the device is capable of detecting and distinguishing ferrous particles in lubricating oil. The design concept demonstrated here can be extended to an in-line monitoring device for real-time monitoring of ferrous debris particles. A simulation using the CST code is performed to better understand the inductive response in the presence of magnetic bodies in the oil. The CST simulation further verifies the effectiveness of inductance measurement for monitoring magnetic particles within a tube.

• Fashion & Textile Research Journal
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• v.21 no.2
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• pp.133-140
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• 2019

This study developed smart fashion prototypes that provide utilitarian functionality by combining Fashion and Electronics regarding the IT focused convergence tendency in modern industries. A convergence R&D workshop was performed by Fashion design majors and Engineering majors for the study. As a result, 5 functional smart fashion prototypes were developed and the outline of each prototype are as follows. The $1^{st}$ prototype, 'Hidden Camera Detecting Coat' focused on gender-related crimes. The coat uses infrared lighting and LED technologies to provide a function to detect hidden cameras in suspicious public spaces such as toilets. The $2^{nd}$ prototype, 'Heating-massage Suit' targeted patients with musculoskeletal system difficulties. The suit uses heating and vibration technologies to provide a heating massage treatment for patients with ongoing difficulties in their daily lives. The $3^{rd}$ prototype is an air-bag jacket to prevent sexual molestation on public transportation. The jacket extends its volume through pressure sensing, air compressing, motors and 3D-printing technology to secure the wearer's personal preventive space between the user's body and others. The $4^{th}$ prototype is a town wear for people suffering from synesthesia. People with synesthesia inadvertently see colors when exposed to certain sounds. This town wear uses sound sensing, air compressing, motors and 3D-printing technology to provide sound prevention and a comfortable sound playing function. The $5^{th}$ prototype is a set of a vest and a gloves for visually impaired people. The vest and gloves uses DMS, voice playing, vibration technology to provide distance measuring and warning functions.

• Journal of the Korean Society for Precision Engineering
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• v.7 no.3
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• pp.75-82
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• 1990

Automatic monitoring of the cutting conditions is one of the most improtant technologies in machining. In this study, the feasibility in applying acoustic emission(AE) signals for the in-process detection of endmill wear and fracture has been investigated by performing experimental test on the NC vertical milling machine with SM45C for specimen. As the results of detecting and analyzing AE signals on various cutting conditions, the followings have confirmed. (1) The RMS value of acoustic emission is related sensitively to the cutting velocity, but is not affected largely by feed rate. (2) The burst type AE signals of high level have been observed when removing chips distorderly and discontinuously. (3) When the RMS value grows up rapidly due to the increase of wear the endmill are generally broken or fractured, but when the endmills fracture at the conditions of smooth chip-flow or built-up-edge(BUE) occurred frequently, the rapid change of the RMS arenot found. And it is expected that this technigue will be quite useful for in-process sensing of tool wear and fracture.