• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.207-216
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• 2000

This paper introduces an effective system design method to develop a customer oriented product using a design optimization process and to select a set of critical design paramenters,. The process results in the development of a successful product satisfying customer needs and reducing development risk. The proposed scheme adopted a five step QFD(Quality Function Deployment) in order to extract design parameters from customer needs and evaluated their priority using risk factors for extracted design parameters. In this process we determine critical design parameters and allocate them to subsystem designers. Subsequently design engineers develop and test the product based on these parameters. These design parameters capture the characteristics of customer needs in terms of performance cost and schedule in the process of QFD, The subsequent risk management task ensures the minimum risk approach in the presence of design parameter uncertainty. An application of this approach was demonstrated in the development of weld quality monitoring system. Dominant design parameters affect linearity characteristics of weld defect feature vectors. Therefore it simplifies the algorithm for adopting pattern classification of feature vectors and improves the accuracy of recognition rate of weld defect and the real time response of the defect detection in the performance. Additionally the development cost decreases by using DSP board for low speed because of reducing CPU's load adopting algorithm in classifying weld defects. It also reduces the cost by using the single sensor to measure weld defects. Furthermore the synergy effect derived from the critical design parameters improves the detection rate of weld defects by 15% when compared with the implementation using the non-critical design parameters. It also result in 30% saving in development cost./ The overall results are close to 95% customer level showing the effectiveness of the proposed development approach.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.101-109
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• 2012

To develop high quality software, quality control plan is required about fault correction that is latent within software. We should describe fault correction profile properly for this. The tank and pipe model performs complex processes to calculate fault that is remove and escapes. Also, we have to know in which phase the faults were inserted, removed and escaped and know the fault detection rate at any phases. To simplify such complex process, this paper presented model to fault filtering concept. Presented model has advantage that can describe fault more shortly because need not to consider whether was involved in fault that escaped fault is inserted at any step at free step. Also, presented effort estimating model that do fetters in function of fault removal quality and productivity measure and is required in fault detection.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.92-99
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• 2003

Quality inspection of textile products is an important problem for fabric manufacturers. This paper presents an automatic vision-based system for quality control of web textile fabrics. Typical web material is 1-3m wide and is driven with speeds ranging from 20m/min to 200m/min. At the present, the quality assessment procedures are performed manually by expert. But worker can not detect more than 60％ of the present defect and inspect the fabric if moving faster than 30m/min. To increase the overall quality and homogeneity of textile, an automated visual inspection system is needed fur the productivity. However, the existing inspection system are too expensive to purchase for small companies. In this paper, the proposed PC based real-time inspection algorithm gives low cost textile inspection system, high detection rate with good accuracy and low rate of false alarms. The method shows good results in the detection of several types of fabric defects.

• Childhood Kidney Diseases
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• v.21 no.2
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• pp.107-113
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• 2017

Purpose: This study aimed to evaluate the relationships between 99mTecnicium-dimercaptosuccinic acid (DMSA) scan findings and clinical parameters including age and fever duration. Methods: The positive rates for abnormal DMSA scans were analyzed according to the age of patients, fever duration prior to admission, and total fever duration. DMSA scan findings were divided into 3 categories: single defect, multifocal defects, and discrepant defects. We evaluated the detection rates of vesicoureteral reflux according to DMSA scan lesions. Results: Among a total 320 cases, 141 (44.1%) had abnormal DMSA scans. The infant group (0-1 year of age) had a shorter total fever duration, and a lower C-reactive protein (CRP) value and DMSA positive rate (39.8% vs. 60.6%, P=0.002) compared to children group (2-15 years of age). Patients with abnormal scans had a longer total fever duration and higher CRP compared to those with normal scans. The positivity rate of abnormal scans did not differ between the patients with a short fever duration prior to admission of ${\leq}2$ days and those with longer fever duration of ${\geq}3$ days. However, patients with longer total fever duration had a higher rate of abnormal DMSA scans (P=0.02). Among cases with a single defect, multifocal defects, and discrepant defects, vesicoureteral reflux was observed in 22.4%, 60% and 70.6% of cases, respectively (P=0.004). Conclusion: Although DMSA scan has limitations in early diagnosis, DMSA scan findings may aid in the prediction of the severity of systemic inflammation and detection of vesicoureteral reflux.

• Journal of Biosystems Engineering
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• v.20 no.4
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• pp.368-375
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• 1995

A computer vision system was built to generate images of a stationary egg. This system includes a. CCD camera, a frame grabber, and an incandescent back lighting system An image processing algorithm was developed to accurately detect surface holes and surface cracks on eggs. With 20W of incandescent back light, the detection rate was shown to be the highest. The Sobel operator was found to be the best among various enhancing filters examined. The threshold value to distinguish between the crack and the translucent spots was found to be linear with the average gray level of a whole egg image. Those values of both gray level and area were used as criteria to detect holes in egg and those values of both area and roundness were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. On the average, it took 59.5 seconds to analyze an egg image and determine whether or not it was defected.

• Textile Coloration and Finishing
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• v.21 no.1
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• pp.53-58
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• 2009

A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which were one of the frequently occurring defects. Multi-resolution analysis(MRA) algorithm were used and evaluated according to both their processing time and detection rate. Standard value for defective inspection was the mean of the non-defect image feature. Similarity was decided via comparing standard value with sample image feature value. Totally, we achieved defective inspection accuracy above 95%.

• Smart Structures and Systems
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• v.2 no.3
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• pp.253-274
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• 2006

The structural monitoring of multi-wire strands is of importance to prestressed concrete structures and cable-stayed or suspension bridges. This paper addresses the monitoring of strands by ultrasonic guided waves with emphasis on the signal processing and automatic defect classification. The detection of notch-like defects in the strands is based on the reflections of guided waves that are excited and detected by magnetostrictive ultrasonic transducers. The Discrete Wavelet Transform was used to extract damage-sensitive features from the detected signals and to construct a multi-dimensional Damage Index vector. The Damage Index vector was then fed to an Artificial Neural Network to provide the automatic classification of (a) the size of the notch and (b) the location of the notch from the receiving sensor. Following an optimization study of the network, it was determined that five damage-sensitive features provided the best defect classification performance with an overall success rate of 90.8%. It was thus demonstrated that the wavelet-based multidimensional analysis can provide excellent classification performance for notch-type defects in strands.

• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.251-261
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• 2010

This article demonstrated the application of the Fuzzy Data Envelopment Analytical Hierarchy Process (FDEAHP) to evaluate the root causes of critical defect problems occurring in the production of liquid medicine. The methodology of the research began by collecting the defect data by using Check Sheets, and ranking the significant problems by using a Pareto Diagram. Two types of major problems were found to occur, including glass fragments in the medicine and damaged lid threads. The causes of each problem were then analyzed by using Cause and Effect Diagrams. The significant causes were ranked by FDEAHP under three criteria, Severity (S), Occurrence (O) and Detection (D), followed by the framework of the FMEA Technique. Two causes with the highest Final Weight (FW) of each problem were selected to be improved, such as installing auxiliary equipment, using the Poka-Yoke system, setting the scale of the shaft and lathing the bushes of each bottle size. The results demonstrated a reduction in defects from 3.209% to 1.669% and showed that improving a few significant root causes, identified by an experienced decision maker, was sufficient to reduce the defect rate.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.167-174
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• 1998

The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.6
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• pp.594-602
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• 2022

Cast-resin transformers are widely installed in various electrical power systems because of their low operating cost and low influence on external environmental factors. However, when they have an internal defect during the manufacturing process or operation, a partial discharge (PD) occurs, and eventually destroys the insulation. In this paper, a Rogowski-type PD sensor was studied to replace commercial PD sensors used for the insulation diagnosis of power apparatus. The proposed PD sensor was manufactured with four different types of PCB-based winding structures, and it was analyzed in terms of the detection characteristics for standard calibration pulses and the changes of the output voltage according to the distance. The output increased linearly in accordance with the applied discharge amount. It was confirmed that the hexagon structure sensor had the highest sensitivity, because the winding cross-sectional area of the sensor was larger than others. In addition, as the distance from the defect increased, the output voltage of the sensors decreased by 7.32% on average. It was also confirmed that the attenuation rate according to the distance decreased as the input discharge amount increased. For the application of this new type sensor, PD electrode system was designed to simulate the void defect. Waveforms and PRPD patterns measured by the proposed PD sensors at DIV and 120% of DIV were the same as the results measured by MPD 600 based on IEC 60270. The proposed PD sensors can be installed on the inner wall of the transformer tank by coating its surfaces with a non-conductive material; therefore, it is possible to detect internal defects more effectively at a closer distance from the defect than the conventional sensors.