• 제목/요약/키워드: Slag Inclusion

검색결과 26건 처리시간 0.02초

미소결함의 형상인식을 위한 디지털 신호처리 적용에 관한 연구 (A Study on the Application of Digital Signal Processing for Pattern Recognition of Microdefects)

  • 홍석주
    • 한국생산제조학회지
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    • 제9권1호
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    • pp.119-127
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    • 2000
  • In this study the classified researches the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing feature extraction feature selection and classifi-er selection is teated by bulk,. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function the empirical Bayesian classifier. Also the pattern recognition technology is applied to classifica-tion problem of natural flaw(i.e multiple classification problem-crack lack of penetration lack of fusion porosity and slag inclusion the planar and volumetric flaw classification problem), According to this result it is possible to acquire the recognition rate of 83% above even through it is different a little according to domain extracting the feature and the classifier.

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신경회로망을 이용한 페라이트계 탄소강 용접부의 초음파 신호 인식 향상에 관한 연구 (A Study on the Enhancement of Ultrasonic Signal Recognition in Ferrite Carbon Steel Weld Zone Using Neural Networks)

  • 윤인식;박원규;이원
    • 한국정밀공학회지
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    • 제19권1호
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    • pp.158-164
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    • 2002
  • This paper proposes the optimization of ultrasonic signal recognition in ferrite carbon steel weld zone using neural networks. For these purposes, the ultrasonic signals for defects as porosity, incomplete penetration and slag inclusion in the weld zone are acquired in the type of time series data. And then their applications evaluated feature extraction based on the time-frequency-attractor domain(peak to peak, rise time, rise slope, fall time, fall slope, pulse duration, power spectrum, and bandwidth) and attractor characteristics (fractal dimension and attractor quadrant) etc. The proposed neural networks system in this study can enhances performance of ultrasonic signal recognition.

SMAW의 슬래그 혼입에 대한 각종 요인의 영향 (Factors Causing Slag Inclusion in SMAW)

  • 구정서;백승호;김영환
    • Journal of Welding and Joining
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    • 제2권2호
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    • pp.29-37
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    • 1984
  • 발전설비를 비롯한 산업설비, 각종 압력용기 및 철구조물 제작시 발생하는 여러가지의 용접불량 중에서 슬래그 혼입이 차지하는 비율이 전체 불량의 절반 이상을 차지하고 있다. 특히 여타의 용접법에 비해 SMAW에 의한 슬래그 혼입의 발생이 가장 많으므로 이에 대한 결함 발생의 경향을 조사하고 그 방지대책을 설정하기 위하여 이번 실험을 실시하게 되었다. 수동 용접봉의 피복제 중 가스 발생 원인은 아아크 분위기를 생성하고 기타 부분은 슬래그가 되어 용융금속을 둘러싸서 이것을 보호하면서 용융지로 이행한다. 슬래그는 용융지 내에서 비이드 표면으로 부상하면서 탈산반응이나 불순물을 제거하는 정련작용을 한다. 또한 적당한 합금 원소의 보충, 용융금속의 유동성 증가 등에 의하여 양호한 용착금속의 생성을 돕는다. 한편, 슬래그는 고온금속을 덮어 이것을 보호함과 동시에 급냉을 완화하는 작용을 한다. 그러나 이러한 슬래그가 응고하는 용착금속 사이에 혼입된다면 용착금속의 기계적 성질을 저하시키는 중요한 요인이 된다. 슬래그 혼입에 대하여 간단하고 일반적인 방지대책은 많이 언급되어 있으나 슬래그 혼입의 방지대책에 대해 깊이 있는 연구가 거의 없다. 이번 실험에서는 광범위한 요인의 선제, 싯수의 제안으로 인하여 새로운 슬래그 혼입 기구의 설정이나 특정한 요인의 영향에 대한 정확한 한계치의 설정보다는 각 요인에 대한 정성적인 영향을 분석하였다.

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초음파신호의 신경망 형상인식법을 이용한 오스테나이트 스테인레스강의 용접부결함 분류에 관한 연구 (Classification of Welding Defects in Austenitic Stainless Steel by Neural Pattern Recognition of Ultrasonic Signal)

  • 이강용;김준섭
    • 대한기계학회논문집A
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    • 제20권4호
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    • pp.1309-1319
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    • 1996
  • The research for the classification of the natural defects in welding zone is performd using the neuro-pattern recognition technology. The signal pattern recognition package including the user's defined function is developed to perform the digital signal processing, feature extraction, feature selection and classifier selection, The neural network classifier and the statistical classifiers such as the linear discriminant function classifier and the empirical Bayesian calssifier are compared and discussed. The neuro-pattern recognition technique is applied to the classificaiton of such natural defects as root crack, incomplete penetration, lack of fusion, slag inclusion, porosity, etc. If appropriately learned, the neural network classifier is concluded to be better than the statistical classifiers in the classification of the natural welding defects.

고급강 제조 반응 모델의 검토 : Part. 2. 종합 모델 및 단일 반응 모델 (A Review of Kinetic Model for Production of Highgrade Steel : Part. 2. Complex Reaction Model and Single Reaction Model)

  • 김정인;김선중
    • 자원리싸이클링
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    • 제30권1호
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    • pp.14-25
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    • 2021
  • 고품질 철강의 수요가 증가함에 따라 2차 정련 공정의 중요성이 높아지고 있다. 하지만 공정 시간에 따라 변화하는 용강, 슬래그 및 비금속 개재물의 조성은 정련 공정이 평형 상태가 아님을 의미하며, 정련 공정에서는 용강, 슬래그, 비금속 개재물, 내화물 및 합금 원소 간의 동시 다발적 반응이 일어난다. 다양한 상들의 비평형 상태에서 복잡한 반응을 고려하기 위해, 이전 연구자들은 실험을 통해 도출된 반응 속도 수식들을 기반으로 kinetic 기반의 고급강 제조 정련 시뮬레이션 모델을 발표하였다. 정밀한 시뮬레이션 모델의 개발을 위해 보고된 2차 정련 모델들의 분석 및 검토가 필요하다. 본 연구에서는 국내외로 발표된 정련 공정 관련 종합 모델들 및 단일 반응 모델들에 대하여 검토하고 소개하였다.

용접결함의 패턴인식을 위한 디지털 신호처리에 관한 연구 (A Study on the Digital Signal Processing for the Pattern fiecognition of Weld Flaws)

  • 김재열;송찬일;김병현
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 추계학술대회 논문집
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    • pp.393-396
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    • 1995
  • In this syudy, the researches classifying the artificial and natural flaws in welding parts are performed using the smart pattern recognition technology. For this purpose the smart signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing,feature extraction , feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear disciminant function classifier, the empirical Bayesian classifier. Also, the smart pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack,lack of penetration,lack of fusion,porosity,and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately learned the neural network classifier is better than ststistical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

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오스테나이트계 스테인리스강 304 용접부의 초음파 형상 인식 평가를 위한 카오스 시뮬레이터의 구축 (Construction fo chaos simulator for ultrasonic pattern recognition evaluation of weld zone in austenitic stainless steel 304)

  • 이원;윤인식;장영권
    • Journal of Welding and Joining
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    • 제16권5호
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    • pp.108-118
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    • 1998
  • This study proposes th analysis and evaluation method of time series ultrasonic signal using the chaos feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaos time series signal analyze quantitatively weld defects. For this purpose, analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaosity resulting from distance shifts such as 0.5 and 1.0 skip distance. Such differences in chaosity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos feature extraction, feature values of 4.511 and 0.091 in the case of side hole and 4.539 and 0.115 in the case of vertical hole were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaos feature extraction in this study can enhances ultrasonic pattern recognition results from defect signals of weld zone such as side hole and vertical hole.

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Mechanical and fracture properties of glass fiber reinforced geopolymer concrete

  • Midhuna, M.S.;Gunneswara Rao, T.D.;Chaitanya Srikrishna, T.
    • Advances in concrete construction
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    • 제6권1호
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    • pp.29-45
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    • 2018
  • This paper investigates the effect of inclusion of glass fibers on mechanical and fracture properties of binary blend geopolymer concrete produced by using fly ash and ground granulated blast furnace slag. To study the effect of glass fibers, the mix design parameters like binder content, alkaline solution/binder ratio, sodium hydroxide concentration and aggregate grading were kept constant. Four different volume fractions (0.1%, 0.2%, 0.3% and 0.4%) and two different lengths (6 mm, 13 mm) of glass fibers were considered in the present study. Three different notch-depth ratios (0.1, 0.2, and 0.3) were considered for determining the fracture properties. The test results indicated that the addition of glass fibers improved the flexural strength, split tensile strength, fracture energy, critical stress intensity factor and critical crack mouth opening displacement of geopolymer concrete. 13 mm fibers are found to be more effective than 6 mm fibers and the optimum dosage of glass fibers was found to be 0.3% (by volume of concrete). The study shows the enormous potential of glass fiber reinforced geopolymer concrete in structural applications.

디젤기관 실린더 블록의 보수용접법에 관한연구 (A Study on the Repair Welding Methods for Cylinder Block of Diesel Engines)

  • 김종호
    • Journal of Advanced Marine Engineering and Technology
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    • 제23권3호
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    • pp.331-337
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    • 1999
  • Cracks on the cylinder block of diesel engines will often happen due to cyclic load and thermal stress. According to the Classification Societies' rules welding reparis of cylinder block made of cast irons are generally not permitted. However such welding repairs became inevitable taking enormous cost and time for their renewal into consideration. In this study repair welding methods for the clinder blocks made of gray cast irons were reviewed and the tests of their welds were carried out in order to purpose the repair welding meth-ods of packing seat and o-ring seat of cylinder block and apply them to the practice. The following conclusions are botained :1 The tensile strength of weld of cast iron more than that of base metal can be obtained by means of preheating keeping temperature above $100^{\circ}C$ between welding pass-es preventing slag inclusion peening and cramping weld metal by studs. 2. The suspected crack by a magnetic particle test due to different magnetic permeability can be identified which are not associated with a mechanical discotinuity.

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Porous concrete with optimum fine aggregate and fibre for improved strength

  • Karanth, Savithri S.;Kumar, U. Lohith;Danigond, Naveen
    • Advances in concrete construction
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    • 제8권4호
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    • pp.305-309
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    • 2019
  • Pervious concrete pavements are the need of the day to avoid urban flooding and to facilitate ground water recharge. However, the strength of pervious or porous concrete is considerably less compared to conventional concrete. In this experimental investigation, an effort is made to improve the strength of pervious concrete by adopting fibres and a small amount of fine aggregate. A porous concrete with cement to aggregate ratio of 1:5 and a water-powder ratio of 0.4 is adopted. 30% of the cement is replaced by cementitious material ground granulated blast furnace slag (GGBS) for better strength and workability. Recron fibres at a dosage of 0.5, 1.0 and 1.5% by weight of cement were included to improve the impact strength. Since concrete pavements are subjected to impact loads, the impact strength was also calculated by "Drop ball method" in addition to compressive strength. The effect of fine aggregate and recron fibres on workability, porosity, compressive and impact strength was studied. The investigations have shown that 20% inclusion of fine aggregate and 1.5% recron fibres by weight of cement give better strength with an acceptable range of porosity.