Abstract
There is an obvious tendency towards increasing the information content of surveys of hard-to-reach objects at high altitudes through the use of remote-controlled robot crawlers. This can be explained by the reasonable desire of industrial objects owners to maintain their property: pipelines, containers, metal structures in operating technical condition, which contributes to reducing accident risks and increasing the economic efficiency of operation (optimization of repair planning, etc.) This paper presents the concept of a robotic device equipped with LIDAR and EMAT which can move over pipes from a diameter of 100 mm by using a special type of magnetic wheel. The robot uses convolutional neural networks to detect structural elements and classify their defects. The article contains information about tests held on a specially developed test rig. The results showed that the device could increase the information level of survey and reduce the labour intensity. In this work, we consider a prototype of the device which has not started mass operation at industrial facilities yet.
Funder
Saint Petersburg Mining University
Subject
Computer Science Applications,Geotechnical Engineering and Engineering Geology,General Materials Science,Building and Construction,Civil and Structural Engineering
Cited by
19 articles.
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