• Smart Structures and Systems
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• v.21 no.5
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.125-130
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• 1994

Recently,manufacturing work been transformed to small acale production from with various items to act up to user's expectation from mass production with a little items required in the past. The FMS using NC type mother machinaries has been applied actively also in domestic manufacturing line to meet thus tendancy, but there are many machining troubles occured in work process not be settled yet. Nowdays high efficiency has been required no less than high precision in grinding work for the improvement of productivity. In this study, to represent more advanced FMS can be adapted to thus situation In-process type monitoring method using AE and Current sensors is suggested to investigatethe machining condition in grinding process. As results from this experimental study, is is recoqnized well that grinding conditions and dressing point of in time can be estimated effectively using monitoring method suggested. Furthermore, surface shape of grinding wheel on voluntary point of in time can be predicted indirectly through the observation and comparison of AE signal waveform obtained as performance of continuous dressing work.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.28-33
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• 2016

Since defects in the wheels of railway vehicles, which occur due to wears with the rail, cause serious damage to the running device, the diagnostic monitoring system for condition-based maintenance is required to secure the driving safety. In this paper, we studied to apply a useful Cepstrum analysis to detect periodic structure in spectrum among the vibration signal processing techniques for the fault diagnosis of a rotating body such as wheel. In order to analyze in variations of train velocity, the Cepstrum analysis was performed after a domain change of the vibration signal from time domain to rotation angle domain. When domains change, it is important to use a interpolation for a uniform interval of the rotation angle. Finally, the Cepstrum analysis for wheel flat detection was verified by using the vibration signal including the disturbance resulting from the rail irregularities and the vibration of bogie components.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.1
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• pp.74-80
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• 1999

Recently, manufacturing work has been transformed to small scale production form with various types to act up to user's expectation from mass production with a little items required in the past. Then FMS using NC type machinaries has been applied actively also in domestic manufacturing line to meet thus tendency, but there are many machining troubles occured during work process not be settled yet. Nowdays high efficiently has been required no less than high precision in grinding work for the improvement of productivity. In this study, to represent more advance FMS can be adapted to thus situation In-process type monitoring method using AE and Current sensors is suggested to investigate the machining condition in grinding process. As results form this experimental study, it is recognized well that grinding conditions and dressing point of in time cab be estimated effectively using monitoring method suggested. Furthermore, surface shape of grinding wheel on voluntary point of in time can be predicted indirectly through the observation and comparison of AE signal waveform obtained as performance of continuous dressing work.

• Journal of Hydrogen and New Energy
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• v.20 no.1
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• pp.64-72
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• 2009

In order to convert efficiently vibration energy of a car tire wheel into electrical power by using piezoelectric materials, the design of the materials must be performed for the dynamic characteristics of the piezoelectric materials to be matched with them of the vibration energy sources well. An accelerometer was installed on the tire wheel with a slip ring to investigate the dynamic mode of the wheel as one of the vibration energy sources. During road test, the measurement on the vibration mode of the tire wheel was performed with variations of car speed and road condition. The experimental data were analyzed details for availability as a micro power source for wireless TPMS(Tire Pressure Monitoring System).

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.6
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• pp.600-606
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• 2012

Upon investigation of the damaged wheels for high speed train it was determined that the damage was caused by rolling contact fatigue during operation of train. The major problems that railway vehicle system using wheel-rail has to face during operation of railway vehicle are rolling contact fatigue, cracks in wheels, cracks in rails and wheel-rail profile wear. If these deficiencies are not controlled at early stages the huge economical problems due to unexpected maintenance cost in railway vehicle can be happened. Also, If the accurate knowledge of contact conditions between wheel and rail can be evaluated, the damage of wheel can be prevented and the maintenance operation can save money. This paper presents the applicability of electro-magnetic technique to the detection and sizing of defects in wheel. Under the condition of continuous rolling contact fatigue the damage of wheel has continuously monitored using the applied sensor. It was shown that the usefulness of the applied sensor was verified by twin disc test and the measured damaged sizes showed good agreement with the damaged sizes estimated by electro-magnetic technique.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.57-63
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• 2013

The mission of a lot of satellites on geostationary orbit is the communication and/or the broadcasting. These satellites need a big power, so these have a large solar array. Recently, the new satellite for Earth environment monitoring is developing on geostationary orbit. The payload of Earth monitoring satellite requires better thermal condition on detector. Therefore this satellite uses a boom for the attitude stability instead of rejecting one-side solar array as a heat source. The other hand, it uses some momentum wheels being a more momentum capacity to control the large disturbance by solar pressure due to the asymmetric solar array configuration. In this paper, the analysis on the wheel allocation and the wheel off-loading for COMS is summarized and the results are verified by telemetry of COMS. COMS has no boom and a perfectly asymmetric solar array configuration, and it is operating well on geostationary orbit.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.9
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• pp.1531-1540
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• 1997

Mordern industrial society pursues unmanned system and automation of manufacturing process. Abreast with this tendensy, production of goods which requires advanced accuracy is increasing as well. According to this, the work sensing time of dressing by monitoring and diagnosing the condition of grinding, which is th representative way in accurate manufacturing, is an important work to prevent serious damages which affect grinding process or products by wearing grinding wheel. Computer vision system was composed, so that grinding wheel surface was acquired by CCD camera and the change of cutting edge ratio was measured. Then we used automatic thresholding technique from histogram as a way of dividing grinding cutting edge from grinding surface. As a result, we are trying to approach unmanned system and automation by deciding more accurate time of dressing and by visualizing behavior of grinding wheel by making use of computer vision.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.427-434
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• 2011

This paper is focused on application of recursive least squares method to estimate rail irregularities from the acceleration measurement on an axle-box or a bogie for the rail condition monitoring with in-service high-speed trains. Generally, the rail condition was monitored by a special railway inspection vehicle but the monitoring method needs an expensive measurement system. A monitoring method using accelerometers on an axle-box or a bogie was already proposed in the previous study, and the displacement was successfully estimated from the acceleration data by using Kalman and frequency selective band-pass filters. However, it was found that the displacement included not only the rail irregularities but also phase delay of the applied filters, and effect of suspension of the bogie and conicity of the wheel. To identify the rail irregularities from the estimated displacement, a compensation filter method is proposed. The compensation filters are derived by using recursive least squares method with the estimated displacement as input and the measured rail irregularity as output. The estimated rail irregularities are compared with the true rail irregularity data from the rail inspection system. From the comparison, the proposed method is a useful tool for the measurement of lateral and vertical rail irregularity.