Fast recognition algorithm of underwater micro-terrain based on ultrasonic detection
An algorithm was proposed to fast recognize three types of underwater micro-terrain, i.e. the level, the gradient and the uneven. With pendulum single beam bathymeter, the hard level concrete floor, the random uneven floor and the gradient wood panel (8°) were ultrasonically detected 20 times, respe...
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Published in | Journal of Central South University of Technology. Science & technology of mining and metallurgy Vol. 15; no. 5; pp. 738 - 741 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Changsha
Central South University
01.10.2008
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Subjects | |
Online Access | Get full text |
ISSN | 1005-9784 1993-0666 |
DOI | 10.1007/s11771-008-0136-2 |
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Abstract | An algorithm was proposed to fast recognize three types of underwater micro-terrain, i.e. the level, the gradient and the uneven. With pendulum single beam bathymeter, the hard level concrete floor, the random uneven floor and the gradient wood panel (8°) were ultrasonically detected 20 times, respectively. The results show that the algorithm is right from fact that the first clustering values of the uneven are all less than the threshold value of 60.0% that is obtained by the level and gradient samples. The algorithm based on the dynamic clustering theory can effectively eliminate the influences of the exceptional elevation values produced by the disturbances resulted from the grazing angle, the characteristic of bottom material and environmental noises, and its real-time capability is good. Thus, the algorithm provides a foundation for the next restructuring of the micro-terrain. |
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AbstractList | An algorithm was proposed to fast recognize three types of underwater micro-terrain, i.e. the level, the gradient and the uneven. With pendulum single beam bathymeter, the hard level concrete floor, the random uneven floor and the gradient wood panel (8°) were ultrasonically detected 20 times, respectively. The results show that the algorithm is right from fact that the first clustering values of the uneven are all less than the threshold value of 60.0% that is obtained by the level and gradient samples. The algorithm based on the dynamic clustering theory can effectively eliminate the influences of the exceptional elevation values produced by the disturbances resulted from the grazing angle, the characteristic of bottom material and environmental noises, and its real-time capability is good. Thus, the algorithm provides a foundation for the next restructuring of the micro-terrain. |
Author | Zhou, Zhi-jin Bu, Ying-yong Luo, Bo-wen Zhao, Hai-ming |
Author_xml | – sequence: 1 givenname: Bo-wen surname: Luo fullname: Luo, Bo-wen email: luobow75@126.com organization: School of Mechanical and Electrical Engineering, Central South University – sequence: 2 givenname: Zhi-jin surname: Zhou fullname: Zhou, Zhi-jin organization: School of Mechanical and Electrical Engineering, Hunan University of Science and Technology – sequence: 3 givenname: Ying-yong surname: Bu fullname: Bu, Ying-yong organization: School of Mechanical and Electrical Engineering, Central South University – sequence: 4 givenname: Hai-ming surname: Zhao fullname: Zhao, Hai-ming organization: School of Mechanical and Electrical Engineering, Central South University |
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Cites_doi | 10.1007/s11771-005-0035-8 10.1109/91.413225 10.1117/12.135859 10.1080/10641190009353782 10.1109/91.366565 10.1016/S0167-8655(02)00109-5 10.1109/91.940965 10.1007/11430919_56 |
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Keywords | single beam exceptional elevation values underwater micro-terrain threshold value ultrasonic detection dynamic clustering |
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Title | Fast recognition algorithm of underwater micro-terrain based on ultrasonic detection |
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