• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.155-159
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• 2002

Wire ropes are used in a myriad of various industrial applications such as elevator, mine hoist, construction machinery, lift, and suspension bridge. Especially, wire rope of crane is important component to container transfer. If it happens wire rope failures in operating, it may lead to safety accident, economic power loss by productivity decline, competitive power decline of container terminal and so on. To solve this problem, we developed wire rope fault detecting system as a portable instrument, and this system is consisted of 3 parts that fault detecting part using hall sensor, permanent magnets and analog unit, and digital signal processing part using data acquisition card, monitoring part using wavelet transform, denoising method. In this paper, a wire rope is scanned by this system after makes several broken parts on the surface of wire rope artificially. All detected signal has external noise or disturbance according to circumstances. So, we applied to discrete wavelet transform to extract a signal from noisy data that was used filter. In practical applications of denoising, it is shown that wavelet pursue it with little information loss and smooth signal display. It is verified that the detecting system by denoising has good efficiency for inspecting faults of wire ropes in service. As a result, by developing this system, container terminal could reduce expense because of extension of wire ropes exchange period and could competitive power. Also, this system is possible to apply in several fields like that elevator, lift and so on.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.1
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• pp.7-12
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• 2003

The purpose of testability analysis is to estimate the difficulty of testing a stuck-at fault in logic circuits. A good testability measurement can give an early warning about the testing problem so as to provide guidance in improving the testability of a circuit. There have been researches attempting to efficiently compute the testability analysis. Conventional testability measurements, such as COP and SCOAP, can calculate the testability value of a stuck-at fault efficiently in a tree-structured circuit but may be very inaccurate for a general circuit. The inaccuracy is due to the ignorance of signal correlations for making the testability analysis linear to a circuit size. This paper proposes an efficient method for computing testability analysis, which takes into account signal correlation to obtain more accurate testability. The proposed method includes the algorithm for identifying all reconvergent fanouts in a given n circuit and the gates reachable from them, by which information related to signal correlation is gathered.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.30-38
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• 2017

In this paper, we propose an underwater acoustic sensor fault detection method for passive sonar systems. In general, a passive sonar system displays processed results of array signals obtained from tens of the acoustic sensors as a two-dimensional image such as displays for broadband or narrowband analysis. Since detection result display in the operation software is to display the accumulated result through the array signal processing, it is difficult to determine the possibility where signal may be contaminated by the fault or failure of a single channel sensor. In this paper, accordingly, we propose a detection method based on the analysis of RMSCR (Root Mean Square Crossing-Rate), and the processing techniques for the faulty sensors are analyzed. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured by using signals acquired from real array being operated in several coastal areas. Besides, we compare performance of fault processing techniques. From the experiments, it is shown that the proposed method works well in underwater environments with high average RMS, and mute (set to zero) shows the best performance with regard to fault processing techniques.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1287-1294
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• 2004

Hub bearings not only sustain the body of a cat, but permit wheels to rotate freely. Excessive radial or axial load and many other reasons can cause defects to be created and grown in each component. Therefore, nitration and noise from unwanted defects in outer-race, inner-race or ball elements of a Hub bearing are what we want to detect as early as possible. How early we can detect the faults has to do with how the detection algorithm finds the fault information from measured signal. Fortunately, the bearing signal has Periodic impulse train. This information allows us to find the faults regardless how much noise contaminates the signal. This paper shows the basic signal processing idea and experimental results that demonstrate how good the method is.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1033-1037
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• 2010

Railway signal facilities are very important because they are directly related to safe train operation. By the result of the unification of signal and station control, station control staffs have been having a hard time to grasp the knowledge about signal facilities and the fault restoration ability in a short term since the existing manuals were only made with text materials. To meet the growing demand to educate the maintenance work in actual and effective way, the maintenance manuals and periodic procedures was developed in the forms of video clips and animations with quality contents onto a DVD enabling not only to improve the maintenance works for signal facilities but to contribute budget saving and profit generating.

• Proceedings of the KSR Conference
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• 1999.05a
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• pp.143-150
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• 1999

The vibration signals of driving parts of electric train are distorted its signal patterns due to the impact components, which occurs when wheel passes rail joints. An elimination method of the impact components is investigated using adaptive signal processing technique in this study. The result shows that adaptive interference canceling method seems to be more effective than line enhancement technique. The application of adaptive interference canceling method to the signal measured at bogie shows that the extractions of the signals of driving parts of traction motor, reduction gear, and axle bearing are successful. Therefore, only the signals of bogie, which is the place to attach an accelerometer easily, is sufficient for the fault diagnosis and the safety evaluation of electric train. Also, adaptive interference canceling method can be applicable to evaluate the performance of vibration isolation between bogie and car body and to investigate the characteristics of indoor sound.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.75-83
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• 2004

With the rotating machinery getting more accurate and diversified, the necessity fur an appropriate diagnosis technique and maintenance system has been greatly recognized. However, until now, the operator has executed a monitoring of the machine by the senses or simple the change of RMS (root mean Square) value. So, the diagnostic expert system using the fuzzy inference which the operator can judge easily and expertly a condition of the machine is developed through this study. In this paper, the hardware and software of the diagnostic expert system was composed and the identification of the diagnostic performance of the developed system for 5 fault phenomena was carried out.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.4
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• pp.108-116
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• 2000

Undesired trouble such as chatter vibration and burning on the ground surface appears frequently in the cylindrical plunge grinding process. Establishment of a credible fault diagnostic system for the grinding process is the major purpose of this study. Power signals generated during the grinding operation were sampled and analyzed to determine the relationship between grinding troubles and behavior of signal changes. In addition, a neural network was optimized with a momentum coefficient a learning rate, and a structure of the hidden layer through the iterative learning process. Based on the established system, success rates of the trouble recognition were verified.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.12
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• pp.1128-1133
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• 2006

The most important thing to secure safety and reliability of railway vehicles is to verify performance characteristics of equipments, and related companies or research institutes had many efforts to verify performances and functions of equipments synthetically and efficiently. KHST(Korean High Speed Train) has been developed by KRRI (Korea Railroad Research Institute). An electric railway system is composed of high-tech subsystems, among which main electric equipment such as transformers and converter are critical components determining the performance of rolling stock. We developed a measurement system for on-line test and evaluation of performances of KHST. The measurement system is composed of software part and hardware part. Perfect interface between multi-users is possible. A new method to measure temperature was applied to the ]measurement system. By using the system, fault diagnosis and performance evaluation of electric equipment in Korean High Speed Train was conducted during test running.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1357-1359
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• 1999

This paper presents fault detection in cables. We developed the device for detecting pinpoint location of faults in power cables using acoustic method. The proposed device consists of hardware and software for the fault detection. Using the device, we explain how to detect the pinpoint of faults and introduce that the other method use the time delay between electro-magnetic and acoustic signals for the pinpoint of the faults.