• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.728-732
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• 2010

GIS(Gas insulated switching gear) is power equipment with excellent dielectric strength and is economy merit in high confidence and stability. Recently, because equipment of GIS was occurring problem of confidence used for a long time, partial discharge on-line diagnosis systems have been importantly recognized. Partial discharge (PD) detection is an effective means for monitoring and evaluation of dielectric condition of gas insulated system (GIS). The ultra-high-frequency (UHF) PD detection technique can detect and locate the PD sources inside GIS by detecting electromagnetic wave emitted from PD source. Therefore, real-time diagnostic system using UHF detection method has been developed for this application is being expanded gradually. However, the signal of partial discharge occurring in SF6 gas is very weak and susceptible to external noises which mainly consist of PD in air. Thus, it is important to distinguish the PD in SF6 gas more sensitively from the external noises. Unfortunately, these external noise signals and the partial discharge signals have very similar characteristics. Therefore, to solve this problem, we need the signal processing method for distinguish partial discharge signals with external noise signals for improvement of SNR(signal to noise ratio) and sensitivity. In this paper, we proposed internal signal processing method for removing external noise signals with built-in pre.amplifier and frequency conversion circuit.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.33-38
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• 2012

EMB is considered as the next generation braking mechanism because it has simple structure and is environment friendly. However, as other brake mechanisms, EMB should be operated reliably for any operating conditions. EMB should be designed with fail-safe and fault-tolerant control concepts which require robust fault detection algorithms for various possible faults. In the design of fault detection algorithms, it is very difficult to construct faulty conditions in real EMB and thus, simulations are often used to emulate the faulty conditions. In this paper, a simulation tool is developed using the commercial software to emulate gear faults in the EMB mechanism. A backlash compensation algorithm is introduced based on contact point detection because screw backlash causes a delay in clamping force response time.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.571-580
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• 2022

Marine deposited waste is a major cause of problems such as a lot of damage and an increase in the estimated amount of garbage due to abandoned fishing grounds caused by ghost fishing. In this paper, we implement a real-time marine deposited waste detection artificial intelligence system to understand the actual conditions of waste fishing gear usage, distribution, loss, and recovery, and study methods for performance improvement. The system was implemented using the yolov5 model, which is an excellent performance model for real-time object detection, and the 'data screening process' and 'class segmentation' method of learning data were applied as performance improvement methods. In conclusion, the object detection results of datasets that do screen unnecessary data or do not subdivide similar items according to characteristics and uses are better than the object recognition results of unscreened datasets and datasets in which classes are subdivided.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.780-785
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• 2012

Wind energy is currently the fastest growing source of renewable energy used for electrical generation around the world. Generally, wind turbine systems are designed to be operated for twenty years long, Therefore, various faults in the wind turbine system inevitably occur during their long term period of operation. Especially, rotor shaft, gear-box and generator are installed inside of nacelle, furthermore, some cooling systems for normal operation of these devices are also required. If these cooing systems have failed in their operation, it is impossible for the entire system to be operated normally. In this work, IR(Infra Red) camera based fault detection system for the preventive detection of various cooling systems faults is proposed. To verify the applicability of the proposed system, physical implementation is embodied and various experiments are carried out.

• Journal of Sensor Science and Technology
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• v.7 no.4
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• pp.225-233
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• 1998

The principle, design, and application of a gear-tooth sensor for the rough environmental conditions such as high temperatures of up to $150^{\circ}C$ are studied. The rotation of a tooth wheel is detected by a couple of Hall elements manufactured on the SIMOX wafer by a methode of differential detection using bipolar silicon technology. The product sensitivity of the Hall element is about 510 V/AT over a wide temperature range of $-40^{\circ}C{\sim}150^{\circ}C$. The differential Hall sensor makes the maximum possible distance between sensor and tooth wheel wider than that when single Hall element is used over a wide temperature range, and the maximum detectable distance is 4.5mm at driving current of 4mA.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.531-536
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• 1994

Wrapping machines in cigarette factories are equipped with indexing drive units with roller gear cam. At present there are no simple, visual, diagnostic techniques for predicting failure in these nits at an early stage. This paper proposes that failure could be predicted by using either a modified version of kurtosis, or the Wigner distribution method. The nonlinear vibration model proposed in this paper takes into consideration the play between the m and the cam follower, and precisely simulates the actual vibration. Statistics on the variance in play, obtained from the data on time history, call then be used to evaluate the effects of tile mage oil the cam and cam follower.

• Convergence Security Journal
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• v.5 no.2
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• pp.65-74
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• 2005

The hacking accident is increasing repidly according to development of latest computer network and the method becomes various. But, to correspond to hacking, it is lot of difficulties to cope gear and security element between product because most radiant mercuries apply technology between individual digenomic species and It is real condition that great setup, equipment, manpower disturbance are enlarged to apply this. Designed and embody Site-Based executive system that can integrate security element about IDS information between digenomic species to solve these problem and correspond efficiently from hacking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2223-2228
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• 2014

Available shafts with gears at each end of the cylinder-shaped steel are widely used as power train components for automobiles. In order to automate the production of a geared shaft, there are problems to be solved. After one side of the cylinder is cut in gears, one of the problems is to determine the position of the cylinder which has been already cut. The shaft is then to be fed ahead with geared position to the chuck with jaws in geared shape. The other problem is to acquire information on an angular position of the shaft to fit to the jaws of the chuck. This paper deals with the magnetic detection sensor of gear position. Coils are installed in two places. Self-inductances of coils are detected by the changes of reluctance and are then compared. The magnetic analysis also has been carried out by the finite element analysis (FEM).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.7
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• pp.665-671
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• 2015

The performance of fault diagnostics for a planetary gearbox depends on vibration modulation characteristics, which can vary with manufacturing & assembly tolerance, and load condition. In this paper, a fault diagnostics technique that considers vibration modulation characteristics is proposed for the effective fault detection of planetary gearboxes in wind turbines. For identifying the vibration modulation characteristics in practice, re-sampled vibration signals are processed with narrow band-pass filters. Thereafter, the optimal position of the vibration extraction window is identified for effective detection of faulty signals under the varying vibration modulation characteristics. The proposed diagnostics technique makes it possible to perform robust diagnostics of the planetary gearbox with regard to the changeable vibration modulation effect. For demonstrating the proposed fault diagnostics technique, a 2-kW WT testbed is designed with two DC motors and gearboxes. A faulty gear with partial tooth breakage is machined and assembled into the gearbox.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.20-32
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• 2018

Purpose: The purpose of this study is to set up an anomaly detection criteria for sensor data coming from a motorcycle. Methods: Five sensor values for accelerator pedal, engine rpm, transmission rpm, gear and speed are obtained every 0.02 second from a motorcycle. Exploratory data analysis is used to find any pattern in the data. Traditional process control methods such as X control chart and time series models are fitted to find any anomaly behavior in the data. Finally unsupervised learning algorithm such as k-means clustering is used to find any anomaly spot in the sensor data. Results: According to exploratory data analysis, the distribution of accelerator pedal sensor values is very much skewed to the left. The motorcycle seemed to have been driven in a city at speed less than 45 kilometers per hour. Traditional process control charts such as X control chart fail due to severe autocorrelation in each sensor data. However, ARIMA model found three abnormal points where they are beyond 2 sigma limits in the control chart. We applied a copula based Markov chain to perform statistical process control for correlated observations. Copula based Markov model found anomaly behavior in the similar places as ARIMA model. In an unsupervised learning algorithm, large sensor values get subdivided into two, three, and four disjoint regions. So extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior in the sensor values. Conclusion: Exploratory data analysis is useful to find any pattern in the sensor data. Process control chart using ARIMA and Joe's copula based Markov model also give warnings near similar places in the data. Unsupervised learning algorithm shows us that the extreme sensor values are the ones that need to be tracked down for any sign of anomaly behavior.