FBG-Based Accelerometer for Buried Pipeline Natural Frequency Monitoring and Corrosion Detection

• Type: Article in International Scientific Journal
• Date: 2024

Authors

Pereira, L (Author) Other; Sousa, I (Author) Other; Mesquita, E (Author) Other; Cabral, A (Author) Other; Alberto, N (Author) Other; Diaz, C (Author) Other; Humberto Varum (Author) FEUP; Antunes, P (Author) Other

Journal

Title: Buildings

Vol. 14

Final page: 456

ISSN: 0007-3725

Publisher: MDPI

Indexing

ISI Web of Knowledge - 0 Citations

Scopus

Other information

Authenticus ID: P-010-2EN

DOI: 10.3390/buildings14020456

Abstract (EN): Pipelines are structures with great relevance in different industrial sectors and are essential for the proper functioning of the logistics that support today's society. Due to their characteristics, locations, and continuous operation, allied with the huge network of pipelines across the world, they require specialized labor, maintenance, and adequate sensing systems to access their proper operation and detect any damage they may suffer throughout their service life. In this work, a fiber Bragg grating (FBG)-based optical fiber accelerometer (OFA), which was designed and calibrated to operate through wavelength and optical power variations using different interrogation setups, was fixed together with a pair of FBG arrays along a 1020 carbon steel pipeline section with the objective of monitoring the pipeline natural frequency (fn_pipeline) to indirectly evaluate the detection and evolution of corrosion when this structure was buried in sand. Here, corrosion was induced in a small area of the pipeline for 164 days, and the OFA was able to detect a maximum fn_pipeline variation of 3.8 Hz in that period. On the other hand, the attached FBGs showed a limited performance once they could successfully operate when the pipeline was unburied, but presented operational limitations when the pipeline was buried in sand. This was due to the inability of the structure to vibrate long enough under these conditions and obtained data from these sensors were insufficient to obtain the fn_pipeline.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 22