• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.297-302
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• 2007

Vibrating test of vehicle component can be possible in lab-based simulators instead of field testing owing to the development of technology in control algorithm as well as computational process. Currently, Multi-Axial Simulation Table(MAST) is recommended as a vibrating equipment, which excites a target component for 3-directional translation and rotation motion simultaneously and hence, vibrational condition can be fully approximated to that of real road test. But, the vibration-free performance of target component is not guaranteed with MAST system, which is only simulator subjective to the operator. Rather, the reliability of multi-axial vibration test is dependent on the quality of input profile which should cover the required severity of vibrating condition on target component. In this paper, multi-axial vibration testing methodology of vehicle component is presented here, from data acquisition of vehicle accelerations to the obtaining the input profile of MAST using severe data at proving ground. To compare the severity of vibration condition, between real road test and proving ground one, energy principle of equivalent damage is proposed to calculate energy matrices of acceleration data and then, it is determined the optimal combination of special events on proving ground which is equivalent to real road test at the aspects of vibration fatigue using sequential searching optimal algorithm. To explain the vibration methodology clearly, seat and door component of vehicle are selected as a example.

• International Journal of Reliability and Applications
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• v.7 no.1
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• pp.41-53
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• 2006

The exact cause of the system's failure is often unknown in the masked system lifetime data. In such type of data, there are two observable quantities, namely (i) the systems time to failure and (ii) the set of systems components that contains the component, which might cause the system to fail. Our objective in this paper is to use the maximum likelihood procedure in the presence of masked data to make inference for the reliability of the system's components. We assume a multi-component series system where each component has a constant failure rate. Different cases that permit for closed form solutions of point estimates are considered. The results obtained in this paper generalize other published results.

• Transactions of Materials Processing
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• v.24 no.6
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• pp.418-425
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• 2015

Based on eco-friendly advantages and the enhanced development in the chemical and physical characteristics, liquid silicone rubber (LSR) is widely used in producing precision parts in the automotive, medical, electronics, aeronautical and many other industries. In the current work, a thermoplastic-thermoset multi component injection molding (MCM) was developed for a waterproof automotive connector housing using PBT and LSR resins. Measurements of the rheological characteristics of PBT and LSR were made to improve the reliability of the numerical analysis for the multi component injection process. With the measured viscosity, pvT and curing data, numerical analysis of the multi cycle injection molding was conducted using simulation software (Sigma V5.0).

• Journal of Applied Reliability
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• v.15 no.4
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• pp.233-240
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• 2015

We analyse reliability of multi-state UH-60 helicopter hydraulic pump system with a multi-functional standby component using Markov analysis method. The system consists of seven components: 2 main pumps, 1 standby pump, 2 primary servos, and 2 tail rotor servos. The standby pump can take over when one more than components fail. Therefore the standby pump is multi-functional standby component. The system has four states: good, deteriorated, dangerous, and failed. The components have 2 states: working and failed. We assume the system is unrepairable when the components fail. We estimate failure distributions and rates using collected failure time data in field. And we classify multi-state of the system according to emergency procedure of UH-60A student handout. We obtain the reliabilities of multi-state system using Visual Basic program because the differential equations is extremely complicated and tedious to solve.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.368-374
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• 2008

Multi-axial simulation table(MAST) is widely used in motor companies as the multi-axial excitor for vibration fatigue of target component, which provides the vibrational condition as close as the vehicle test. However, the vibration fatigue performance of target component can be guaranteed with MAST system only in case the input profile covers the required severity of the target component on field test. In this paper, the signal processing for multi-axial vibration fatigue test on vehicle component is presented, from the data acquisition of the target component to the derivation of input profile. To compare the severity of vibration condition between field and proving ground, the energy principle of a equivalent damage is proposed and then, it is determined the optimal combination of special events on proving ground using a sequential searching optimal algorithm. To explain the vibration methodology clearly, seat and door component of vehicle are selected as a example.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.609-620
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• 2008

There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

• Geophysics and Geophysical Exploration
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• v.23 no.1
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• pp.38-49
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• 2020

Full-waveform inversion (FWI) is an optimization process of fitting observed and modeled data to reconstruct high-resolution subsurface physical models. In acoustic FWI (AFWI), pressure data acquired using a marine streamer has mainly been used to reconstruct the subsurface P-wave velocity models. With recent advances in marine seismic-acquisition techniques, acquiring multi-component data in marine environments have become increasingly common. Thus, AFWI strategies must be developed to effectively use marine multi-component data. Herein, we proposed an AFWI strategy using horizontal and vertical particle-acceleration data. By analyzing the modeled acoustic data and conducting sensitivity kernel analysis, we first investigated the characteristics of each data component using AFWI. Common-shot gathers show that direct, diving, and reflection waves appearing in the pressure data are separated in each component of the particle-acceleration data. Sensitivity kernel analyses show that the horizontal particle-acceleration wavefields typically contribute to the recovery of the long-wavelength structures in the shallow part of the model, and the vertical particle-acceleration wavefields are generally required to reconstruct long- and short-wavelength structures in the deep parts and over the whole area of a given model. Finally, we present a sequential-inversion strategy for using the particle-acceleration wavefields. We believe that this approach can be used to reconstruct a reasonable P-wave velocity model, even when the pressure data is not available.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.185-189
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• 2004

For face recognition system, a face detector which can find exact face region from complex image is needed. Many face detection algorithms have been developed under the assumption that background of the source image is quite simple . this means that face region occupy more than a quarter of the area of the source image or the background is one-colored. Color-based face detection is fast but can't be applicable to the images of which the background color is similar to face color. And the algorithm using neural network needs so many non-face data for training and doesn't guarantee general performance. In this paper, A multi-scale, multi-face detection algorithm using PCA is suggested. This algorithm can find most multi-scaled faces contained in static images with small number of training data in reasonable time.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.998-999
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• 2006

A new mathematical simulation technique for physico-mechanical properties of multi-component powder materials is proposed in this paper. The main advantage of the technique is that finite elements representing different components are placed into a common mesh and may exchange their properties. The output data are properties of material after sintering. The technique allows us to investigate the influence of each component of a material on the properties and distribution of properties inside the sample. The comparative analysis of materials with different compositions is based on simulation results that are well concordant with the results of the laboratory experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.8
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• pp.1004-1009
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• 2014

The redundancy allocation problem has usually considered only the component redundancy at the lowest-level for the enhancement of system reliability. A system can be functionally decomposed into system, module, and component levels. Modular redundancy can be more effective than component redundancy at the lowest-level because in modular systems, duplicating a module composed of several components can be easier, and requires less time and skill. We consider a multi-level redundancy allocation problem in which all cases of redundancy for system, module, and component levels are considered. A tabu search of memory-based mechanisms that balances intensification with diversification via the short-term and long-term memory is proposed for its solution. To the best of our knowledge, this is the first attempt to use a tabu search for this problem. Our tabu search algorithm is compared with the previous genetic algorithm for the problem on the new composed test problems as well as the benchmark problems from the literature. Computational results show that the proposed method outstandingly outperforms the genetic algorithm for almost all test problems.