• 제목/요약/키워드: visual grading rule

검색결과 5건 처리시간 0.023초

개정된 육안등급 구분에 따른 휨강도 특성 평가 (Characteristic Evaluation of Bending Strength Distributions on Revised Korean Visual Grading Rule)

  • 방성준;오정권;박천영;박주생;박문재;이전제
    • Journal of the Korean Wood Science and Technology
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    • 제39권1호
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    • pp.1-7
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    • 2011
  • 최근 재종에 따른 등급별 품질기준 및 결점의 측정방법이 개정되었다. 외국 규격과의 호환성을 비롯하여 보다 현실에 맞고 적용하기 쉽게 개선하기 위해서는 개정에 따른 구조용제재의 구조성능에 대한 고찰이 필요하다. 본 연구에서는 국산 침엽수재 중 대표적으로 사용되는 낙엽송과 잣나무를 대상으로 구조용제재 규정 개정에 따른 휨강도 성능을 구명하였다. 개정된 등급구분규정은 구조재로 적합한 1, 2등급의 비율을 높인다는 측면과 1, 2 등급과 3등급 이하 등급과의 구분을 보다 명료하게 한다는 점에서 개정전의 등급구분에 비해 효과적인 것으로 나타났고, 각 등급별 5% 하한치와 허용응력은 전체적으로 감소하였다. 특히, 건축구조기준(KBC 2009)에서 제시하고 있는 기준허용응력은 실대재 실험값에 비해 더 낮은 값을 제시하고 있으므로 보다 정확한 허용응력의 사용과 효율적인 구조설계를 위해서는 기준허용응력의 개선 또한 필요할 것으로 판단된다.

국산 백합나무 구조용 제재목의 이용가능성 평가 (Feasibility of Domestic Yellow Poplar (Liriodendron tulipifera) Dimension Lumber for Structural Uses)

  • 임진아;오정권;여환명;이전제
    • Journal of the Korean Wood Science and Technology
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    • 제38권6호
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    • pp.470-479
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    • 2010
  • 본 연구는 국산 백합나무의 육안 특성을 이용한 등급구분과 실대재 휨시험을 실시하여 이들의 강도 및 강성의 특성 구명을 통해 국산 백합나무의 구조용재로서의 이용가능성을 평가하였다. 활엽수의 육안등급구분규정이 국내에 존재하지 않아 몇몇 활엽수 제재목에 대한 규정을 포함하고 있는 NSLB (Northern Softwood Lumber Bureau) 규정에 따라 육안등급을 수행하였다. 수행 결과로부터 계산된 백합나무의 휨허용응력을 NDS (National Design Specification)에 제시된 설계치와의 비교를 통해 국산 백합나무가 충분한 강도성능을 가지고 있음을 확인 하였다. 또한 백합나무 제재목을 국내 등급규정에 따라 허용응력을 산정하여 이를 적용하는 데 있어 타당성을 평가하기 위해 국내 국립산림과학원 고시에 따라 육안등급을 수행하였다. 백합나무는 국립산림과학원 고시에 제시된 비중에 따른 수종군 중 소나무류에 포함되었다. 적합분포로 판단된 웨이블분포에 따른 휨허용응력은 1등급 10.0 MPa, 2등급 7.4 MPa, 3등급 4.1 MPa로 제시된 설계치보다 높은 값이 나타났다. 본 실험의 결과로부터 국내 규정에 준하여 국산 백합나무를 구조용재로 이용이 가능함을 확인하였다. 국산 백합나무의 휨탄성계수는 국내외 기준 설계치를 모두 충족시키지 못하였으나, 국산백합나무를 구조용재로 이용하기 위해 본 실험을 통해 얻어진 백합나무의 평균 휨탄성계수를 제안하되, 1등급과 2등급은 9,000 MPa, 3등급 이하는 8,000 MPa를 적용 하는 것이 타당한 것으로 보인다.

Feasibility of Ultrasonic Log Sorting in Manufacturing Structural Lamination from Japanese Cedar Logs

  • Oh, Jung-Kwon;Yeo, Hwan-Myeong;Choi, In-Gyu;Lee, Jun-Jae
    • Journal of the Korean Wood Science and Technology
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    • 제39권2호
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    • pp.163-171
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    • 2011
  • Because Japanese cedar shows lower mechanical performance, glued-laminated timber (glulam) can be a better way to utilize Japanese cedar for structural purpose. However, low yield of higher grade lamination from log makes it difficult to design structural glulam. This study was aimed to increase the yield of higher grade lamination and provide higher efficiency of manufacturing structural lamination by ultrasonic log sorting technology. Logs were sorted by an existing log grading rule regulated by Korea Forest Research Institute (KFRI). It was found that the KFRI log grading rule contributed to finding better logs in viewpoint of the volumetric yield and it can reduce the number of rejected lumber by visual grading. However, it could not identify better logs to produce higher-grade products. To find an appropriate log-sorting-method for structural products, log diameter and ultrasonic time of flight (TOF) for the log were considered as factors to affect mechanical performance of resulting products. However, it was found that influence of log diameter on mechanical performance of resulting products was very small. The TOF showed a possibility to sort logs by mechanical performance of resulting products even though a coefficient of correlation was not strong (R = 0.6). In a case study, the log selection based on the ultrasonic TOF of the log increased the yield of the outermost tension lamination (E8 or better grade, KS F 3021) from 2.6% to 12.5% and reduced LTE5 (lower than E5 grade) lamination from 43.6% to 10.3%, compared with the existing KFRI log grading rule.

버섯 전후면과 꼭지부 상태의 자동 인식 (Automatic Recognition of the Front/Back Sides and Stalk States for Mushrooms(Lentinus Edodes L.))

  • 황헌;이충호
    • Journal of Biosystems Engineering
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    • 제19권2호
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    • pp.124-137
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    • 1994
  • Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

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밀 품질평가 현황과 검사제도 (Current Wheat Quality Criteria and Inspection Systems of Major Wheat Producing Countries)

  • 이춘기;남중현;강문석;구본철;김재철;박광근;박문웅;김용호
    • 한국작물학회지
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    • 제47권
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    • pp.63-94
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    • 2002
  • On the purpose to suggest an advanced scheme in assessing the domestic wheat quality, this paper reviewed the inspection systems of wheat in major wheat producing countries as well as the quality criteria which are being used in wheat grading and classification. Most wheat producing countries are adopting both classifications of class and grade to provide an objective evaluation and an official certification to their wheat. There are two main purposes in the wheat classification. The first objectives of classification is to match the wheat with market requirements to maximize market opportunities and returns to growers. The second is to ensure that payments to glowers aye made on the basis of the quality and condition of the grain delivered. Wheat classes has been assigned based on the combination of cultivation area, seed-coat color, kernel and varietal characteristics that are distinctive. Most reputable wheat marketers also employ a similar approach, whereby varieties of a particular type are grouped together, designed by seed coat colour, grain hardness, physical dough properties, and sometimes more precise specification such as starch quality, all of which are genetically inherited characteristics. This classification in simplistic terms is the categorization of a wheat variety into a commercial type or style of wheat that is recognizable for its end use capabilities. All varieties registered in a class are required to have a similar end-use performance that the shipment be consistent in processing quality, cargo to cargo and year to year, Grain inspectors have historically determined wheat classes according to visual kernel characteristics associated with traditional wheat varieties. As well, any new wheat variety must not conflict with the visual distinguishability rule that is used to separate wheats of different classes. Some varieties may possess characteristics of two or more classes. Therefore, knowledge of distinct varietal characteristics is necessary in making class determinations. The grading system sets maximum tolerance levels for a range of characteristics that ensure functionality and freedom from deleterious factors. Tests for the grading of wheat include such factors as plumpness, soundness, cleanliness, purity of type and general condition. Plumpness is measured by test weight. Soundness is indicated by the absence or presence of musty, sour or commercially objectionable foreign odors and by the percentage of damaged kernels that ave present in the wheat. Cleanliness is measured by determining the presence of foreign material after dockage has been removed. Purity of class is measured by classification of wheats in the test sample and by limitation for admixtures of different classes of wheat. Moisture does not influence the numerical grade. However, it is determined on all shipments and reported on the official certificate. U.S. wheat is divided into eight classes based on color, kernel Hardness and varietal characteristics. The classes are Durum, Hard Red Spring, Hard Red Winter, Soft Red Winter, Hard White, soft White, Unclassed and Mixed. Among them, Hard Red Spring wheat, Durum wheat, and Soft White wheat are further divided into three subclasses, respectively. Each class or subclass is divided into five U.S. numerical grades and U.S. Sample grade. Special grades are provided to emphasize special qualities or conditions affecting the value of wheat and are added to and made a part of the grade designation. Canadian wheat is also divided into fourteen classes based on cultivation area, color, kernel hardness and varietal characteristics. The classes have 2-5 numerical grades, a feed grade and sample grades depending on class and grading tolerance. The Canadian grading system is based mainly on visual evaluation, and it works based on the kernel visual distinguishability concept. The Australian wheat is classified based on geographical and quality differentiation. The wheat grown in Australia is predominantly white grained. There are commonly up to 20 different segregations of wheat in a given season. Each variety grown is assigned a category and a growing areas. The state governments in Australia, in cooperation with the Australian Wheat Board(AWB), issue receival standards and dockage schedules annually that list grade specifications and tolerances for Australian wheat. AWB is managing "Golden Rewards" which is designed to provide pricing accuracy and market signals for Australia's grain growers. Continuous payment scales for protein content from 6 to 16% and screenings levels from 0 to 10% based on varietal classification are presented by the Golden Rewards, and the active payment scales and prices can change with market movements.movements.