• Korean Journal of Environmental Agriculture
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• v.42 no.2
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• pp.121-130
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• 2023

The RGB (red, green, and blue) imagery analysis is an important remote sensing tool, which estimates the effect of environmental stress on turfgrass growth and physiology. Therefore, this study investigated the effect of continuous wear stress treatment on Zoysia japonica through RGB imagery analysis. The results of the growth measurement showed that the plant height substantially decreased, after nine hours of treatment with no considerable difference thereafter. Dry weight measurement showed a substantial difference in the morphological growth characteristics of the aerial part of the turfgrass, but none in the stolon and root zone. This could be attributed to the short period of compaction treatment. The ROS (reactive oxygen species) analysis showed that ROS rapidly increased due to wear stress treatment. The MDA content increased during the traffic process, whereas the green pixels increased and decreased repeatedly; however, overall, the trend declined but the overall trend decreased. Thus, this study confirmed that MDA was effective in reflecting the wear stress of turfgrass; however, it could through RGB image analysis.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.3
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• pp.13-19
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• 2003

The high speed machining technology has been improved remarkably in die/mold industry with the growth of parts and materials industries. Though the spindle speed of machine tool increases, the condition monitoring techniques of the machine tool, tool and workpiece in high speed machining ate incomplete. In tins study, efficient sensing technology in high speed machining is suggested by observing the characteristics of cutting force, gap sensor and accelerometer signal also, machinability of high-speed machining is experimentally evaluated sensing technique to monitor the machine tool and machining conditions was performed.

• Journal of Power System Engineering
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• v.14 no.6
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• pp.47-53
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• 2010

A stabilizer link connects the stabilizer bar to the lower arm of the suspension. When a vehicle is turning, lateral forces from the tire are transmitted through the stabilizer link into the stabilizer bar. The stabilizer bar will twist, thus adding rigidity to the vehicle body. In this study, the stabilizer link body was manufactured by using composite material with POM-GF25%. Therefore, the strength evaluation of stability link body with composite material carried out from tensile, wear and fatigue test. The tensile strength between the stability link body with composite material and the rod with knurling was the largest of four types of rod. In Analyzing materials property using optical sensing technique of stabilizer link for automobile parts, its has been identified the safety.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.17-23
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• 2002

A cylindrical capacitance-type spindle displacement sensor was developed and its effectiveness as a system to monitor cutting forces during hard turning was tested in this research. The sensor was installed between the face of spindle cover and the chucking element and measured pure radial motion of the spindle under the condition with presence of roundness error at measured surface. To prove the effectiveness of the developed system hard aiming tests using ceramic inserts and tool steel as workpiece were conducted. The workpiece was hardened up to 65 Rc. The variations of pure radial motion of the spindle ware measured during the cutting tests. The signals from the sensor showed the same pattern of cutting force variations from the tool dynamometer due to the progress of tool wear. As the flank wear of the ceramic tool increased both static component of cutting forces and the amount of center shift of spindle orbit increased, Results from the research showed that the developed sensor could be utilized as an effective and cheap on-line sensing device to monitor cutting conditions and tool performance in the un-manned machining center.

• Transactions of Materials Processing
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• v.18 no.2
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.245-250
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• 2002

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fee-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining; however, sensing and interpretation of signals are more complex. In addition, the shafts of the micro-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm was developed and the fellowing results are obtained. In data analysis, didn't use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.195-198
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• 1995

In this paper We propose one computer interface device for handicapped people. Input signals of the interface device are movements of eyeballs and head of handicapped. The movements of the eyeballs and head are detected by an image processing system. One feature of our system is that the operator is not obliged to wear any burdensome device like glasses and a helmet. The sensing performance of the image processing of the eyeballs and head is evaluated through experiments. Experimental results reveal the applicability of our system.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.136-142
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• 1996

Automatic monitoring of cutting process is one of the most important technology in machining. AE sensing technology has been applied to monitoring process and proved to be effective in detecting tool abnor- malities such as tool wear and fracture. In this experimental study. AE signals were detected from the tool holder for continuous and interrupted cutting, which obtained from changing workpice material configuration, under control of constant cutting speed from CNC lathe. From statistical and frequency analysis, the AE signals were analyzed to obtaining the characteristics of continuous and interrupted cutting conditions and tool failure. The Kurtosis values decreased but RMS voltages increased as the cutting speed increased, in both continuous and interrupted cutting. RMS voltage is suddenly increased but Kurtosis value is suddenly decreased when tool failure condition. Power spectrum density of AE signals when tool failure reaches extreme value around 0.065 cycles/ .mu. m.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.119-124
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• 1994

Morden industrial society pursues unmanned system and automation of manufacturing rocess. Abreast with this tendensy, prodution of goods which requires advaned accuracy is increasing as well. According to this, the work sensing time of dressing by monitoring and diagnosis the condition of grinding, which is the representative way in accurate manufacturing, is a important work to prevent serios damages which affect grinding process or products by wearing wheel. Computer vision system is composed, so that grind wheel wurface was acquired by CCD camera and the change of cutting is composed. Then we used autometic threshoding technique from histogram as a way of deviding cutting edge which is used in manufacturing from the other parts. As a result, we are trying to approach unmanned system and sutomation by deciding more accurate time of dressing and by visualizing behavior of grinding wheel by marking use of computer vision.

• 한국기계연구소 소보
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• s.19
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• pp.61-68
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• 1989

As the system monitoring technology become required in order to improve the system performance and the productivity, we’ve studied to the detection for the tool wear and the tool breakage using AE sensors that is able to detection of generated high frequency stress pulse at cutting. The detection system is consist of a sensing part, a amplifier part, a signal processing part, and a analysis & output part. The moment (a rms and a kurtosis) of statistical method is used for analysis of AE singnal. The experiment are carried out in a CNC lathe. In this study, we achieved that the amplitude level of the AE signal and statistical moments was largely changed as the tool failure. The change rate of Kurtosis was especially large, but the change rate of the rms was small.