Reorganization of ptc 2020 because of COVID-19 and announcement of the 1st Virtual Pipeline Summit (latest update: 3 June 2020)
Pipelines and industrial piping systems are particularly relevant regarding technical safety, availability and maintenance. Large flow rates of hazardous substances imply that even smallest leakages can lead to high environmental impacts. Therefore, and to ensure the availability of infrastructure, an early detection and localization of potentially hazardous degradations to the walls (e.g. cracks, pitting, sedimentation, etc.) of the containments is necessary. However, in many cases it is not feasible to equip pipelines with a large number of point sensors at reasonable expense.
The principle of distributed fibre optic sensing relies on one single optical fibre, which simultaneously acts as a spatially continuous sensor as well as the signal transducer. Therefore, extensive structures can be provided with this type of sensor with comparatively low efforts.
As a consequence, monitoring oil and gas pipelines using distributed fibre optic sensors is on the upswing. Besides the established methods to measure temperature and strain, distributed acoustic sensing (DAS) has lately received considerable attention as a means to detect and localize third party threats to pipelines (approach of vehicles, digging, mechanical manipulation).
The so far not utilized potential of DAS as a means for continuous condition monitoring of pipes by detecting and localizing acoustic signals that point to certain damage scenarios, is currently under investigation in an interdisciplinary research project at BAM (AGIFAMOR, Ageing Infrastructures – Fibre Optic Monitoring of Pipes).
In order to qualify distributed acoustic fibre optic sensors for this application area, we especially focus on detecting and identifying the relevant acoustic emissions of interesting degradations as well as on the optimal way of application for the optical fibres to the specimen to achieve an optimal signal transmission of acoustic signals.