Latest revision as of 14:49, 12 February 2021

Abstract

Maintenance tasks are crucial for all kind of industries, especially in extensive industrial plants, like solar thermal power plants. The incorporation of robots is a key issue for automating inspection activities, as it will allow a constant and regular control over the whole plant. This paper presents an autonomous robotic system to perform pipeline inspection for early detection and prevention of leakages in thermal power plants, based on the work developed within the MAINBOT (http://www.mainbot.eu) European project. Based on the information provided by a thermographic camera, the system is able to detect leakages in the collectors and pipelines. Beside the leakage detection algorithms, the system includes a particle filter-based tracking algorithm to keep the target in the field of view of the camera and to avoid the irregularities of the terrain while the robot patrols the plant. The information provided by the particle filter is further used to command a robot arm, which handles the camera and ensures that the target is always within the image. The obtained results show the suitability of the proposed approach, adding a tracking algorithm to improve the performance of the leakage detection system.

Document type: Article

Full document

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.3390/s131013560 under the license https://creativecommons.org/licenses/by

• http://europepmc.org/articles/PMC3859078 under the license http://creativecommons.org/licenses/by/3.0/

• http://www.mdpi.com/1424-8220/13/10/13560/pdf

• http://www.mdpi.com/1424-8220/13/10/13560,

https://doaj.org/toc/1424-8220 under the license cc-by

• http://www.mdpi.com/1424-8220/13/10/13560/pdf,

http://dx.doi.org/10.3390/s131013560

• https://www.mdpi.com/1424-8220/13/10/13560/pdf,

https://dblp.uni-trier.de/db/journals/sensors/sensors13.html#IbargurenMSM13,

https://www.mdpi.com/1424-8220/13/10/13560,

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859078,

http://europepmc.org/articles/PMC3859078,

https://doi.org/10.3390/s131013560,

https://academic.microsoft.com/#/detail/1969040860 under the license https://creativecommons.org/licenses/by/4.0/