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블록 정합 재작업 시수 예측 시스템에 관한 연구

A Study on the Prediction System of Block Matching Rework Time

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초록

In order to evaluate the precision degree of the blocks on the dock, the shipyards recently started to use the point cloud approaches using the 3D scanners. However, they hesitate to use it due to the limited time, cost, and elaborative effects for the post-works. Although it is somewhat traditional instead, they have still used the electro-optical wave devices which have a characteristic of having less dense point set (usually 1 point per meter) around the contact section of two blocks. This paper tried to expand the usage of point sets. Our approach can estimate the rework time to weld between the Pre-Erected(PE) Block and Erected(ER) block as well as the precision of block construction. In detail, two algorithms were applied to increase the efficiency of estimation process. The first one is K-mean clustering algorithm which is used to separate only the related contact point set from others not related with welding sections. The second one is the Concave hull algorithm which also separates the inner point of the contact section used for the delayed outfitting and stiffeners section, and constructs the concave outline of contact section as the primary objects to estimate the rework time of welding. The main purpose of this paper is that the rework cost for welding is able to be obtained easily and precisely with the defective point set. The point set on the blocks’ outline are challenging to get the approximated mathematical curves, owing to the lots of orthogonal parts and lack of number of point. To solve this problems we compared the Radial based function-Multi-Layer(RBF-ML) and Akima interpolation method. Collecting the proposed methods, the paper suggested the noble point matching method for minimizing the rework time of block-welding on the dock, differently the previous approach which had paid the attention of only the degree of accuracy.

Abstract

In order to evaluate the precision degree of the blocks on the dock, the shipyards recently started to use the point cloud approaches using the 3D scanners. However, they hesitate to use it due to the limited time, cost, and elaborative effects for the post-works. Although it is somewhat traditional instead, they have still used the electro-optical wave devices which have a characteristic of having less dense point set (usually 1 point per meter) around the contact section of two blocks. This paper tried to expand the usage of point sets. Our approach can estimate the rework time to weld between the Pre-Erected(PE) Block and Erected(ER) block as well as the precision of block construction. In detail, two algorithms were applied to increase the efficiency of estimation process. The first one is K-mean clustering algorithm which is used to separate only the related contact point set from others not related with welding sections. The second one is the Concave hull algorithm which also separates the inner point of the contact section used for the delayed outfitting and stiffeners section, and constructs the concave outline of contact section as the primary objects to estimate the rework time of welding. The main purpose of this paper is that the rework cost for welding is able to be obtained easily and precisely with the defective point set. The point set on the blocks’ outline are challenging to get the approximated mathematical curves, owing to the lots of orthogonal parts and lack of number of point. To solve this problems we compared the Radial based function-Multi-Layer(RBF-ML) and Akima interpolation method. Collecting the proposed methods, the paper suggested the noble point matching method for minimizing the rework time of block-welding on the dock, differently the previous approach which had paid the attention of only the degree of accuracy.

참고문헌 (8)

  1. Akima, H., "A New method of interpolation and smooth curve fitting based on local procedures", Journal of the Association for Computing Machinery, 17(4), pp.589~602 (1970)[DOI]
  2. Besl, P.J., "A method for registration of 3-D shapes", IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2), pp.239~256 (1992)[DOI]
  3. Buhmann, M.D., "Radial basis functions: theory and implementations" (2003), Cambridge University Press, Inc
  4. Heo, H.Y., "A stochastic assessment method and its applications to the effect of welding distortion on production cost of ship and ocean plant", Ph.D., pp.2014
  5. 이호철, "선박블록의 정도관리를 위한 3차원 좌표의 패턴매칭 알고리즘에 대한 연구", 한국통신학회논문지C, 37(10), pp.933~939 (2012), 한국통신학회
  6. 노재규, "선박 블록 조립 후 최적 정도 계산을 위한 알고리즘 연구", 해양환경안전학회지, 19(5), pp.552~560 (2013), 해양환경안전학회[DOI]
  7. Park, J.S., "A New concave hull algorithm and concaveness measure for n-dimensional datasets", Journal of Information Science and Engineering, 29(2), pp.587~600 (2012)
  8. Pham, T., "Selection of K in K-means clustering", Journal of Mechanical Engineering Science, 219(1), pp.103~120 (2004)

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