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Imabuchi, Takashi; Kawabata, Kuniaki
Proceedings of 2023 IEEE/SICE International Symposium on System Integration (SII 2023) (Internet), p.396 - 400, 2023/01
Imabuchi, Takashi; Tanifuji, Yuta; Kawabata, Kuniaki
Proceedings of 2022 IEEE/SICE International Symposium on System Integration (SII 2022) (Internet), p.1036 - 1040, 2022/01
This paper describes a method for discrimination of the structures in nuclear power station by deep learning based on 3D point cloud data. In order to promote safe and steady decommissioning work, it is important to estimate and assume the condition in nuclear power station based on the measured sensor data. Especially, the data of the dose rate in the workspace is useful to plan the decommissioning task and, the shape and the material property of the structures in the workspace are required for the dose rate simulation. Shape data can be obtained by such as 3D Scan, however, it is difficult to acquire the material property data of the objects. Therefore, we consider that it is possible that the major material property can be estimated from the category of the structures in nuclear power station. In this paper, we proposed a structure discrimination method by 3D semantic segmentation with 3D point cloud data that consists of labeled points by referring category labels of CAD data of existing nuclear facility. We reported discrimination performance of the proposed method by hold-out validation.
Imabuchi, Takashi; Kawabata, Kuniaki
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no abstracts in English
Kawabata, Kuniaki; Shirasaki, Norihito*; Abe, Hiroyuki*; Hanari, Toshihide; Ito, Rintaro; Imabuchi, Takashi; Yamada, Taichi
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This paper describes a system for realizing simultaneous and synchronized collection of air dose rates and measurement locations for efficient dosimetry survey and spatio-temporal dosimetry data logging in nuclear facilities. The prototype system, which is currently under development, mainly consists of a 3D LiDAR-SLAM unit and a dosimeter integrated in a ROS framework. In this paper, we present the configuration of the prototype and the preliminary experimental results of dosimeter position estimation using it.
Imabuchi, Takashi
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no abstracts in English
Kawabata, Kuniaki; Imabuchi, Takashi; Shirasaki, Norihito*; Suzuki, Soichiro; Ito, Rintaro
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Imabuchi, Takashi; Prima, O. D. A.*
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no abstracts in English
Kawabata, Kuniaki; Imabuchi, Takashi; Shirasaki, Norihito*; Ito, Rintaro; Suzuki, Soichiro
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Hanari, Toshihide; Imabuchi, Takashi; Tanifuji, Yuta; Ito, Rintaro
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no abstracts in English
Doi, Akio*; Yamashita, Meguru*; Takahashi, Hiroki*; Kato, Toru*; Imabuchi, Takashi; Hanari, Toshihide; Tanifuji, Yuta; Ito, Rintaro
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Doi, Akio*; Yamashita, Meguru*; Takahashi, Hiroki*; Kato, Toru*; Imabuchi, Takashi; Hanari, Toshihide; Tanifuji, Yuta; Ito, Rintaro
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no abstracts in English
Imabuchi, Takashi; Kawabata, Kuniaki
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Nakamura, Keita*; Hanari, Toshihide; Madokoro, Hirokazu*; Imabuchi, Takashi; Kawabata, Kuniaki; Nix, S.*; Doi, Akio*
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This paper introduces a research effort for faster 3D environment modeling of the workspace for decommissioning activities at the Fukushima Daiichi Nuclear Power Plant, applying as input video images shot during an investigation of the reactor containment vessel and reactor building. Especially, we construct a system that allows the selection of a 3D reconstruction method with as much information as possible within a specified time limit. We challenge this study with three methods: photogrammetry, simulation, and AI technology. Finally, we aim to integrate the results of each research to build a prototype system that automatically generates a more informative 3D reconstruction result within a specified time and according to the extracted feature values.
Hanari, Toshihide; Imabuchi, Takashi; Nakamura, Keita*; Kawabata, Kuniaki
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This paper introduces an image quality assessment on a 3D modeling to grasp the internal state of the nuclear reactor for a decommissioning of the Fukushima Daiichi Nuclear Power Station. We try a quantitative evaluation of videos or images acquired by the investigation inside the primary containment vessels and the reactor buildings for an efficient 3D reconstruction. Finally, we aim to develop a rapid 3D reconstruction method based on the image quality assessment.
Imabuchi, Takashi; Kawabata, Kuniaki
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no abstracts in English
Miyauchi, Satoru*; Imabuchi, Takashi; Hotta, Katsuyoshi*; Prima, O. D. A.*; Takeichi, Hiroshige*
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Imabuchi, Takashi
no journal, ,
no abstracts in English