• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1493-1499
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• 2004

This paper describes the speckle shearing interferometry, a non-destructive optical method, for quantitative estimation of void defect and monitoring separation defect inside of a pneumatic tire. Previous shearing interferometry has not supplied quantitative result of inside defect, due to effective factors. In the study, factors related to the details of an inside defect are classified and optimized with pipeline simulator. The size and the shape of defect can be estimated accurately to find a critical point and also is closely related with shearing direction. The technique is applied for quantitative estimation of defects inside of a pneumatic tire. The actual traveling tire is monitored to reveal the cause of separation and the starting points. And also unknown void defects on tread are inspected and the size and shape of defects are estimated which has good agreement with the result of visual inspection.

• Journal of Biosystems Engineering
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• v.32 no.5
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• pp.324-331
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• 2007

The purpose of this study is to analysis effects of defect factors of combine header for cutting speed of combine header, feeding depth of straw, and cylinder speed of thresher. Measurement system for defect factors was consists of sensors to monitor the combine operation and I/O interface to convert the signals. Cutting speed of combine header, feeding depth of straw, cylinder speed of thresher were measured and analyzed. The data were collected from three paddy field during rice harvesting. The tests were conducted at different grounding speeds, lug troubles, and cutter condition. The one way ANOVA and the multiple comparison tests were performed. The results showed that the measured data were useful to monitor the defect factors of combine during harvesting. The faults conditions of grounding speeds, lug troubles, and cutter conditions affected cutting speeds, feeding depths and cylinder speeds of the combine. The data seem to be useful to analysis the faults conditions of combine header.

• Journal of the Korea Institute of Building Construction
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• v.20 no.6
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• pp.567-576
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• 2020

This study proposes additional items to be recognized as defects in a defect lawsuit through a case analysis of lawsuit cases in apartment housing. Identifying these defects prevents an unexpected increase in litigation costs, delays in the date of litigation, and emotion repercussions or additional lawsuits. In this study, the defects that were not discovered by the existing occupants and construction companies, but were newly discovered in litigation, were defined as defects in lawsuits. Fifteen cases of lawsuits were analyzed and a total of 77 defects were derived. Each item was then reviewed for location, work type, number of occurrences, and cost. The results were yielded 23 defect items, which were validated by appraisers who directly appraised the cases. In addition, the derived defect factors were analyzed. Finally, the 23 defect items were categorized into 10 main factors which include attributes such as causes of occurrence and characteristics. This can provide an overall area of defects to be considered in addition to existing defect items in the life cycle of the housing. The results of this study can contribute to reducing the actual occurrence of defects and minimizing the disputes in the case of defect lawsuits.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.187-188
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• 2019

The supply of apartments has continuously increased, and the housing supply rate has exceeded 100 percent and the demands and standards of tenants have also been raised as technology has developed. This has led to the conflict and caused social and economic losses. In this study, the case investigation and research methods of the prior research are analyzed as the basis for identifying the defects cases of causes and influences occurring in the apartment building. To analyze various studies, we divided the prior research into the defect management process and the study on the type of defects and countermeasures, and investigated the features and limitations. Future research will be conducted on apartment buildings within 10 years of completion among conglomerate's nationwide apartments to compensate for the limitations of prior research. In addition, AHP static method and relational chart will be used to identify the relationship between the type of defect and the cause and the importance of the influencing factors.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.270-279
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• 2003

Parametric studies have been conducted into the variability of the factors affecting the ultrasonic testing applied to weldments. The influence of ultrasonic equipment, transducer parameters, test technique, job parameters, defect type and characteristics on reliability far defect detection and sizing was investigated by experimentation. The investigation was able to build up substantial bank of information on the reliability of manual ultrasonic method for testing weldments. The major findings of the study separate into two parts, one dealing with correlation between ultrasonic techniques, equipment and defect parameters and inspection performance effectiveness and other with human factors. Defect detection abilities are dependent on the training, experience and proficiency of the UT operators, the equipment used, the effectiveness of procedures and techniques.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.627-628
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• 2015

Construction defect which can causes economic damage such as schedule delay, cost overrun is a considerably important factor in construction industry. In general, a construction defect features a difficulty to find out causes precisely because it occurs when several interrelated causes combine. Yet, studies have tried to understand the interrelationships between factors are limited. In addition, despite of a tremendous amount of construction data, it's not still enough to analyze them, but tends to depend on experience or know-how of practitioners. Thus, it is necessary to identify underlying causes in influential factors by utilizing related data. This paper analyses Interrelationships between causal factors using Association Rule Mining to discover root causes of construction defects. Confidence and Lift that can be used for presenting the interrelationships of the causes were extracted from 1241 cases in 30 projects in Korea. It is expected that this paper allows the construction managers to discover key factors and make right decisions to reduce occurrence of construction defects. Furthermore, analysis of interrelationships can improve understanding of structural patterns of construction defects.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.158-159
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• 2014

There is urgent for defect consulting work to standardize the investigated method, repaired and reinforced method, and estimated cost about defect in increasing a defect lawsuit of apartment building. For the purpose of developing the standard process of defect consulting work, the review that a used process in law and institution should take precedence. There is not prepared the national standard for defect consulting but is dependent on an experience and a practice of consultants. This study analyzes defect consulting case, defines main steps for developing the standard process, and draws phased work factors. As systemizing this, it is expected to apply to basic structure for developing the standard process of defect consulting work for the next.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.974-978
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• 2013

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because different images are provided. This is caused by possible variations from the image acquisition process including optical factors, nonuniform illumination, random noises, and so on. For this reason, conventional area based defect measuring methods have problems of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome this problem, utilizing volume information that is completely ignored in the area based defect measuring method. The results show that our proposed method dramatically improves the robustness and consistency of defect size measurement.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.29-30
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• 2022

Tile defects in apartment houses are caused by a combination of various factors. These factors cannot be specified, and it is difficult to determine the exact cause because a number of causes are intertwined. In addition, because the climate of Korea is different by season, the coefficient of thermal expansion between materials is different, which is a major cause of tile defects. Therefore, this study analyzed the difference between the construction location and the period of defect occurrence according to the types of tile defects caused by environmental differences between indoor and outdoor environments. Two-way ANOVA was used, indoor and outdoor spaces were selected, and defect types were selected accordingly to show the difference in the occurrence period of each defect.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.109-117
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• 2023

Defect detection is one of the key factors in fabric quality control. To improve the speed and accuracy of denim fabric defect detection, this paper proposes a defect detection algorithm based on cascading feature extraction architecture. Firstly, this paper extracts these weight parameters of the pre-trained VGG16 model on the large dataset ImageNet and uses its portability to train the defect detection classifier and the defect recognition classifier respectively. Secondly, retraining and adjusting partial weight parameters of the convolution layer were retrained and adjusted from of these two training models on the high-definition fabric defect dataset. The last step is merging these two models to get the defect detection algorithm based on cascading architecture. Then there are two comparative experiments between this improved defect detection algorithm and other feature extraction methods, such as VGG16, ResNet-50, and Xception. The results of experiments show that the defect detection accuracy of this defect detection algorithm can reach 94.3% and the speed is also increased by 1-3 percentage points.