• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.53-60
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• 2005

The wire rope of container crane is a important component to container transfer system and is used in a myriad of various applications such as elevator, mine hoist, construction machinery, and so on. If it happen wire rope failures in operating, it may lead to the safety accident and economic loss, which is productivity decline, competitive decline of container terminal, etc. To solve this problem, we developed the active and portable wire rope fault detecting system. The developed system consists of three parts that are the fault detecting, signal processing, and remote monitoring part. All detected signal has external noise or disturbance according to circumstances. Therefore we applied to discrete wavelet transform to extract a signal from noisy data that was used filter. As experimental result, we can reduce the expense for container terminal because of extension of exchange period of wire rope for container crane and this system is possible to apply in several fields to use wire rope.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.2
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• pp.213-220
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• 2017

Pyroshock produced by the pyrotechnic devices can induce failures in nearby electronic devices. To handle and mitigate pyroshock inducing problems, appropriate measurement of pyroshock is essential. In this study, pyroshock measurement technique is established using laser Dopper vibrometers (LDVs) and shock accelerometers. Pyroshock produced by the explosive bolts and the pyrotechnic initiators under various environments is measured. The characteristics of pyroshock including the effects of supporting structures, propagation form on thin plate, sensor (contact and non-contact) types are discussed.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.5
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• pp.69-82
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• 1992

Vibration of intake menifold is important as it could worsen the noise levels radiated from surface itself and support bracket, and it eventually leads to the failures of a Throttle Position Sensor and an Idle Air Control Valve. In this study, structural modification method is proposed to reduce structural vibration of an intake manifold system. At first, vibration problems are identified through tests on a running engine. Then modal data acquired by modal testing and finite element analysis are helpful to understand vibration mechanism of the system, and used as the design guide when structural modifications are attempted. After the system model is validated by comparison of the modal data obtained from analysis and experiment, iterative calculations are performed to find optimized structure of the system by finite element analysis. As a result, a newly designed plenum bracket is suggested in such a way that the intake manifold is stiffened, and that design of the support bracket is suggested in such a way that the intake manifold is stiffened, and that design of the support bracket is changed in terms of bolting position, thickness, shape, and minimum weight increase. Finally, it is shown that a new design achieves a significant reduction of vibration of an intake manifold system and it is confirmed by tests on a running engine.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.3
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• pp.307-314
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• 2015

In this paper, the embedding type novel liquid metal strain gauge was developed for measuring the deformation of wind turbine blades. In general, the conventional methods for the SHM have many disadvantages such as frequency distortion in FBG sensors, the low gauge factor and mechanical failures in strain gauges and extremely sophisticated filtering in AE sensors. However, the liquid metal filled in a pre-confined micro channel shows dramatic characteristics such as high sensitivity, flexibility and robustnes! s to environment. To adopt such a high feasibility of the liquid metal in flexible sensor applications, the EGaIn was introduced to make flexible liquid metal strain gauges for the SHM. A micro channeled flexible film fabricated by the several MEMS processes and the PDMS replication was filled with EGaIn and wire-connected. Lots of experiments were conducted to investigate the performance of the developed strain gauges and verify the feasibility to the actual wind turbine blades health monitoring.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.8
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• pp.965-970
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• 2011

We develop a diagnostic system to monitor failures in an engine-assembly line. Existing techniques such as sensory analysis, time domain analysis, frequency analysis, and statistical analysis have limitations in the diagnosis of engine-assembly failure when there are abnormal vibration waveforms (crashing and damping signals) during the assembly. We use a wavelet technique to deal with crashing and damping signals. We also implement a new technique for developing diagnostic rules from sensor data, and we demonstrate its validity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.12-23
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• 2014

The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and more efforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previous studies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data of equipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to having much concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM (Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressor which is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloading vessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.5
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• pp.72-78
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• 2010

A CFRP (Carbon Fiber-Reinforced Plastic) strengthening method is being very widely used to increase the load-carrying capacity of host structures, especially for bridges. However, not only flexure and shear failures but debonding failure also might occur in CFRP strengthened concrete structures. The CFRP debonding failure would cause a collapse accident of the host structure. Therefore, real-time health monitoring about the CFRP bonding condition is strongly required. In this study, a feasibility of the impedance-based damage detection method using PZT sensors is investigated through a series of experimental study monitoring both concrete cracks and CFRP debonding defects.

• Tribology and Lubricants
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• v.36 no.6
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• pp.297-306
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• 2020

This paper reviews studies on the types and functions of oil sensors used for machine condition monitoring. Machine condition monitoring is essential for maintaining the reliability of machines and can help avoid catastrophic failures while ensuring the safety and longevity of operation. Machine condition monitoring involves several components, such as compliance monitoring, structural monitoring, thermography, non-destructive testing, and noise and vibration monitoring. Real-time monitoring with oil analysis is also utilized in various industries, such as manufacturing, aerospace, and power plants. The three main methods of oil analysis are off-line, in-line, and on-line techniques. The on-line method is the most popular among these three because it reduces human error during oil sampling, prevents incipient machine failure, reduces the total maintenance cost, and does not need complicated setup or skilled analysts. This method has two advantages over the other two monitoring methods. First, fault conditions can be noticed at the early stages via detection of wear particles using wear particle sensors; therefore, it provides early warning in the failure process. Second, it is convenient and effective for diagnosing data regardless of the measurement time. Real-time condition monitoring with oil analysis uses various oil sensors to diagnose the machine and oil statuses; further, integrated oil sensors can be used to measure several properties simultaneously.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.3
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• pp.1-7
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• 2021

With the advent of industry 4.0, big data and machine learning techniques are being widely adopted in the maintenance domain. Inverters are widely used in many engineering applications. However, overloading and complex operation conditions may lead to various failures in inverters. In this study, failure mode effect analysis was performed on inverters and voltages collected to investigate the over-voltage effect on capacitors. Several features were extracted from the collected sensor data, which indicated the health state of the inverter. Based on this correlation, the best features were selected for classification. Moreover, random forest classifiers were used to classify the healthy and faulty states of inverters. Different performance metrics were computed, and the classifiers' performance was evaluated in terms of various health features.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.23-29
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• 2022

Among the various functions of ADAS (Advanced Driver Assistance System), the most important and representative function to the safety of vehicle passengers is AEB (Autonomous Emergency Braking system). In South Korea, laws are in progress from 2022 for making it mandatory for passenger vehicles to be installed. And as AEB-equipped vehicles continues to increase in the future, the demand for accident analysis related to the AEB function is expected to increase in the future. In order to find out the operating limits of AEB, it is necessary to consider the situations exceeding the standards covered by EuroNCAP. Therefore we have performed four experiments in this study, including situations encountered in real-word traffic conditions, i.e., an oblique stop of Global Vehicle Target (GVT) and ADAS sensor failures. These experimental results are expected to be of great help in accurate and reliable accident analysis by considering them when analyzing traffic accidents for ADAS vehicles.