• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.123-131
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• 2020

There have been a lot of studies in the past for the method of predicting the failure of a machine, and recently, a lot of researches and applications have been generated to diagnose the physical condition of the machine and the parts and to calculate the remaining life through various methods. Survival models are also used to predict plant failures based on past anomaly cycles. In particular, special machine that reflect the fluid flow and process characteristics of chemical plants are connected to hundreds or thousands of sensors, so there are not many factors that need to be considered, such as process and material data as well as application of derivative variables. In this paper, the data were preprocessed through time series anomaly detection based on unsupervised learning to predict the abnormalities of these special machine. Next, clustering results reflecting clustering-based data characteristics were applied to produce additional variables, and a learning data set was created based on the history of past facility abnormalities. Finally, the prediction methodology based on the supervised learning algorithm was applied, and the model update was confirmed to improve the accuracy of the prediction of facility failure. Through this, it is expected to improve the efficiency of facility operation by flexibly replacing the maintenance time and parts supply and demand by predicting abnormalities of machine and extracting key factors.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.44-53
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• 1998

Bolt degradation has become a major issue in the nuclear industry since the 1980's due to failure during operation. If small cracks in stud bolt are not detected early enough, they grow rapidly and cause catastrophic disasters. Their detection, despite its importance, is known to be a very difficult problem due to the complicated structures of the stud bolts. This paper presents a method of detecting and sizing a small crack in the root between two adjacent crests in threads. The key idea is from the fact that the Rayleigh wave propagates slowly along a crack from the tip to the opening and is reflected from the opening mouth. When there exists a crack, a small delayed pulse due to the Rayleigh wave is detected between large regularly spaced pulses from the thread. The delay time is the same as the propagation delay time of the slow Rayleigh wave and is proportional to the size of the crack. To efficiently detect the slow Rayleigh wave, three methods based on digital signal processing are proposed : modified wave shaping, dynamic predictive deconvolution, and dynamic predictive deconvolution combined with wave shaping.

• Nuclear Engineering and Technology
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• v.41 no.7
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• pp.979-988
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• 2009

Tensioned metastable fluids provide a powerful means for low-cost, efficient detection of a wide range of nuclear particles with spectroscopic capabilities. Past work in this field has relied on one-component liquids. Pure liquids may provide very good detection capability in some aspects, such as low thresholds or large radiation interaction cross sections, but it is rare to find a liquid that is a perfect candidate on both counts. It was hypothesized that liquid mixtures could offer optimal benefits and present more options for advancement. However, not much is known about radiation-induced thermal-hydraulics involving destabilization of mixtures of tensioned metastable fluids. This paper presents results of experiments that assess key thermophysical properties of liquid mixtures governing fast neutron radiation-induced cavitation in liquid mixtures. Experiments were conducted by placing liquid mixtures of various proportions in tension metastable states using Purdue's centrifugally-tensioned metastable fluid detector (CTMFD) apparatus. Liquids chosen for this study covered a good representation of both thermal and fast neutron interaction cross sections, a range of cavitation onset thresholds and a range of thermophysical properties. Experiments were devised to measure the effective liquid mixture viscosity and surface tension. Neutron-induced tension metastability thresholds were found to vary non-linearly with mixture concentration; these thresholds varied linearly with surface tension and inversely with mixture vapor pressure (on a semi-log scale), and no visible trend with mixture viscosity nor with latent heat of vaporization.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.49.3-49.3
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• 2009

Geostationary Ocean Colour Imager (GOCI) is the first ocean color instrument that will be operating in a geostationary orbit from 2010. GOCI will provide the crucial information of ocean environment around the Korean peninsula in high spatial and temporal resolutions at eight visible bands. We report an on-going development of imaging and radiometric performance prediction model for GOCI with realistic data for reflectance, transmittance, absorption, wave-front error and scattering properties for its optical elements. For performance simulation, Monte Carlo based ray tracing technique was used along the optical path starting from the Sun to the final detector plane for a fixed solar zenith angle. This was then followed by simulation of red-tide evolution detection and their radiance estimation, following the in-orbit operational sequence. The simulation results proves the GOCI flight model is capable of detecting both image and radiance originated from the key ocean phenomena including red tide. The model details and computational process are discussed with implications to other earth observation instruments.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.224-230
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• 2013

Lane boundary detection plays a key role in the driver assistance system. This study proposes a robust method for detecting lane boundary in severe environment. First, a horizontal line detects form the original image using improved Vertical Mean Distribution Method (iVMD) and the sub-region image which is under the horizontal line, is determined. Second, we extract the lane marking from the sub-region image using Canny edge detector. Finally, K-means clustering algorithm classifi left and right lane cluster under variant illumination, cracked road, complex lane marking and passing traffic. Experimental results show that the proposed method satisfie the real-time and efficient requirement of the intelligent transportation system.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2429-2432
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• 2000

Adaptive filter algorithm has been used for plant identifier and noise cancellation. This algorithm has been researched for performance enhancement of filtering. The design and development of a reliable system has been becoming a key issue in industry field because the reliability of a system is considered as an important factor to perform the system's function successfully. And the computing with reliability and fault tolerance is a important factor in the case of aviation and nuclear plant. This paper presents design of reliable adaptive filter with fault tolerance. Generally, redundancy is used for reliability. In this case it needs computing or circuit for voting mechanism or computing for fault detection or switching part. But this presented Filter is not in need of computing for voting mechanism, or fault detection. Therefore it has simple computing, and practicality for application. And in this paper, reliability of adaptive filter is analyzed. The effectiveness of the proposed adaptive filter is demonstrated to the case studies of plant identifier and noise cancellation by using DSP.

• 한국HCI학회:학술대회논문집
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• 2008.02c
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• pp.172-177
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• 2008

Biometrics is essential for person identification because of its uniqueness from each individuals. Face recognition technology has advantage over other biometrics because of its convenience and non-intrusive characteristics. In this paper, we will present a overview of face recognition technology including face detection, feature extraction, and face recognition system. For face detection, we will describe template based method and face component based approach. PCA and LDA approach will be discussed for feature extraction, and nearest neighbor classifiers -will be covered for matching. Large database and the standardized performance evaluation methodology is essential in order to support state-of-the-art face recognition system. Also, 3D based face recognition technology is the key solution for the pose, lighting and expression variations in many applications.

• KSBB Journal
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• v.31 no.1
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• pp.33-39
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• 2016

Developing the method for the selection of animal cell line producing therapeutic monoclonal antibody (mAb) is invaluable as its market is rapidly growing. Although the quality of produced mAb is as important as quantity, however there is no method developed for the selective screening of cell lines on the basis of both quantity and quality. From recent reports, the ratio of light and heavy chain mRNAs of mAb in the cell is a key parameter for the indication of product quality. Therefore, it is obvious that developing the novel method that can detect both light and heavy chain mRNAs in single live cell will provide unprecedented opportunities in bio-industry. Here, we have constructed oligonucleotide probes, molecular beacons for the detection of light or heavy chain mRNAs, respectively, in the live cells producing mAbs. Both beacons showed increased fluorescent intensity after transient transfection of plasmid expressing mAbs analyzed by fluorometer. Flow cytometric analysis clearly demonstrated that both molecular beacons can simultaneously detect the expression of light and heavy chain mRNAs of mAb in the same cell. The technique described in the thesis provides the new direction and concept for developing the method for the smart selection of cell lines producing recombinant proteins including therapeutic mAbs.

• The Journal of the Korean dental association
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• v.49 no.3
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• pp.136-145
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• 2011

Oral cavity cancer accounts for approximately 3-4% of all malignancies and is a significant worldwide health problem. The Korea Central Cancer Registry estimates that there will be approximately 1500 new cases of oral cancer in Korea. Oral cancer occurs most commonly in middle-aged and elderly individuals. The majority of oral malignancies occur as squamous cell carcinomas and despite remarkable advances in treatment modalities, the 5-year survival rate has not significantly improved over the past several decades, hovering at about 50% to 60%. The unfavorable 5-year survival rate may be attributable to several factors. First, oral cancer is often diagnosed at a late stage, with late stage 5-year survival rates as low as 22%. Additionally, the development of secondary primary tumors in patients with early stage disease has a major impact on survival. The early detection of oral cancer and premalignant lesions offers the promise to cure chance of oral cancer. The major diagnostics moddalities for oral cancer include oral cavity examination, supravital staining, oral cytology, and optical detection systems. But the clinical finding of oral mucosa is the most important key to confirm the oral cancer until now. The traditional clinical examination of oral cavity can be performed quickly, is without additional diagnostic expense to patients, and may be performed by health care professionals. Therefore, clinicians must be well-acquainted with clinical characteristics of oral cancer and practice routine screening for oral cancer in dental clinic to decrease the morbidity and mortality of disease.