Presentation information

Oral presentation

General Session » [General Session] 10. Vision / Speech

[4M1] [General Session] 10. Vision / Speech

Fri. Jun 8, 2018 12:00 PM - 1:40 PM Room M (2F Amethyst Hall Hoo)

座長:金崎 朝子(産業技術総合研究所)

12:20 PM - 12:40 PM

[4M1-02] Determination of Muck Properties using Image Analysis by Deep-Learning

〇Shinichi Honma1, Junya Morita1, Kazuo Yoshizako1, Kazuyuki Honda1 (1. KAJIMA Corporation)

Keywords:Image Analysis, Deep-Learning, Muck Properties

In the muddy soil pressure balanced shield method, it is necessary to grasp the properties of the muck and to take appropriate measures in order to proceed with stable excavation. Confirming the properties of the muck so far has been done by collecting the muck, performing a slump test, checking with a touching with hand, etc. However, it was dangerous to collect the muck flowing on the belt conveyor. Therefore, the operator sees the image shown on the monitor and discriminates the muck properties. In this study, we tried to determine the muck properties shown in the monitor using image analysis by Deep-Learning such as convolutional neural networks(CNN). Since the possibility of discriminating muck properties can be found by this verification, we will report on the implementation contents and results.