TY - GEN
T1 - Design and Implementation of an Inspection Robot for Crack Detection in Flooded Pipes
AU - Solano, Jans
AU - Cisneros, Jimm
AU - Sarmiento, Lucia
AU - Quispe, Henry
AU - Hermitano, Albert
AU - Quiroz, Diego
AU - Balbuena, Jose
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The pipeline used to supply drinking water to Andean communities is a crucial component of the water management project in mining complexes that aims to preserve local resources. However, the degraded state of the pipeline poses significant environmental, social and economic risks. To overcome these challenges, the present work proposes the development of a teleoperated robot for the inspection of flooded pipelines. The vehicle features an IP68 protection system to ensure underwater operation, along with measurement and analysis capabilities to assess the pipeline profile. In addition, it incorporates real-time video transmission and visual inspection aids through a graphical interface. Effective communication is ensured within a distance of 600 meters between the vehicle and the command post with a latency of less than 100 ms. Furthermore, an important aspect of this work is the successful segmentation of cracks and fissures using a hybrid CNN-RNN architecture, trained on a dataset comprising online repository images and images captured inside the pipeline.
AB - The pipeline used to supply drinking water to Andean communities is a crucial component of the water management project in mining complexes that aims to preserve local resources. However, the degraded state of the pipeline poses significant environmental, social and economic risks. To overcome these challenges, the present work proposes the development of a teleoperated robot for the inspection of flooded pipelines. The vehicle features an IP68 protection system to ensure underwater operation, along with measurement and analysis capabilities to assess the pipeline profile. In addition, it incorporates real-time video transmission and visual inspection aids through a graphical interface. Effective communication is ensured within a distance of 600 meters between the vehicle and the command post with a latency of less than 100 ms. Furthermore, an important aspect of this work is the successful segmentation of cracks and fissures using a hybrid CNN-RNN architecture, trained on a dataset comprising online repository images and images captured inside the pipeline.
KW - CNN
KW - RNN
KW - Service robots
KW - crack detection
KW - pipe inspection
UR - http://www.scopus.com/inward/record.url?scp=85179886859&partnerID=8YFLogxK
U2 - 10.1109/INTERCON59652.2023.10326039
DO - 10.1109/INTERCON59652.2023.10326039
M3 - Conference contribution
AN - SCOPUS:85179886859
T3 - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
BT - Proceedings of the 2023 IEEE 30th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2023
Y2 - 2 November 2023 through 4 November 2023
ER -
