Automatic Inspection Drone with Deep Learning-based Auto-tracking Camera Gimbal to Detect Defects in Power Lines
DC Field | Value | Language |
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dc.contributor.author | Park, J.-Y. | - |
dc.contributor.author | Kim, S.-T. | - |
dc.contributor.author | Lee, J.-K. | - |
dc.contributor.author | Ham, J.-W. | - |
dc.contributor.author | Oh, K.-Y. | - |
dc.date.accessioned | 2021-12-22T01:41:45Z | - |
dc.date.available | 2021-12-22T01:41:45Z | - |
dc.date.issued | 2019-08-26 | - |
dc.identifier.issn | 2153-1633 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/52675 | - |
dc.description.abstract | The traditional drone inspection performed by human operators is unsuited for the purpose of inspecting power transmission lines, because steel towers and their spans are too high and wide to be inspected with a 250 m line of sight. For this reason, the KEPCO Research Institute developed a new inspection drone system that can automatically fly a predetermined flight path based on the GPS coordinates of steel towers, filming a video of power transmission lines with a high definition camera and a thermal imaging camera. In this system, a camera gimbal with the cameras was still controlled by a human operator from a long distance away. When the drone approached close to a steel tower, however, the camera gimbal was often unable to be controlled and real-time video transmission for the gimbal operator was sometimes interrupted due to radio-frequency interference from steel structure and energized power conductors. To solve such a control problem in the field, we also developed an auto-tracking camera gimbal that can automatically track and photograph power facilities on the basis of Deep Learning. With the automatic gimbal, the entire inspection process can be fully automated. The effectiveness of the developed overall system was confirmed through field tests. © 2019 ACM. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | ICST | - |
dc.title | Automatic Inspection Drone with Deep Learning-based Auto-tracking Camera Gimbal to Detect Defects in Power Lines | - |
dc.type | Article | - |
dc.identifier.doi | 10.1145/3387168.3387176 | - |
dc.identifier.bibliographicCitation | PervasiveHealth: Pervasive Computing Technologies for Healthcare | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000631898400008 | - |
dc.identifier.scopusid | 2-s2.0-85117543024 | - |
dc.citation.title | PervasiveHealth: Pervasive Computing Technologies for Healthcare | - |
dc.type.docType | Proceedings Paper | - |
dc.publisher.location | 벨기에 | - |
dc.subject.keywordAuthor | Auto-tracking | - |
dc.subject.keywordAuthor | Automatic Drone | - |
dc.subject.keywordAuthor | Camera | - |
dc.subject.keywordAuthor | Deep Learning | - |
dc.subject.keywordAuthor | Gimbal | - |
dc.subject.keywordAuthor | Power Line Inspection | - |
dc.subject.keywordPlus | Aircraft detection | - |
dc.subject.keywordPlus | Cameras | - |
dc.subject.keywordPlus | Drones | - |
dc.subject.keywordPlus | Electric lines | - |
dc.subject.keywordPlus | Image communication systems | - |
dc.subject.keywordPlus | Infrared imaging | - |
dc.subject.keywordPlus | Inspection | - |
dc.subject.keywordPlus | Power transmission | - |
dc.subject.keywordPlus | Radio interference | - |
dc.subject.keywordPlus | Radio transmission | - |
dc.subject.keywordPlus | Automatic inspection | - |
dc.subject.keywordPlus | Control problems | - |
dc.subject.keywordPlus | Fully automated | - |
dc.subject.keywordPlus | Inspection process | - |
dc.subject.keywordPlus | Radio frequency interference | - |
dc.subject.keywordPlus | Real-time video transmission | - |
dc.subject.keywordPlus | Research institutes | - |
dc.subject.keywordPlus | Thermal imaging cameras | - |
dc.subject.keywordPlus | Deep learning | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Imaging Science & Photographic Technology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Imaging Science & Photographic Technology | - |
dc.description.journalRegisteredClass | scopus | - |
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