Robots monitor pipes with acoustic wave sensors

Led by Professor Bruce Drinkwater and Professor Anthony Croxford,  the approach developed at Bristol University was used to review a long steel pipe with multiple defects - including circular holes of differing size, a crack-like defect and pits - through a designed inspection path to achieve complete detection coverage for a defined reference defect. The team’s findings are detailed in NDT and E International.

In the study, which was divided into a defect detection and a defect localisation stage, they show how they were able to effectively examine large plate-like structures using a network of independent robots, each carrying sensors capable of sending and receiving guided acoustic waves working in pulse-echo mode.

This approach is claimed to have the advantage of minimising communication between robots, requires no synchronisation and raises the possibility of onboard processing to lower data transfer costs, which will reduce overall inspection expenses.

In a statement, lead author Dr Jie Zhang said: “There are many robotic systems with integrated ultrasound sensors used for automated inspection of pipelines from their inside to allow the pipeline operator to perform required inspections without stopping the flow of product in the pipeline. However, available systems struggle to cope with varying pipe cross-sections or network complexity, inevitably leading to pipeline disruption during inspection. This makes them suitable for specific inspections of high value assets, such as oil and gas pipelines, but not generally applicable.

“As the cost of mobile robots has reduced over recent years, it is increasingly possible to deploy multiple robots for a large area inspection. We take the existence of small inspection robots as its starting point, and explore how they can be used for generic monitoring of a structure. This requires inspection strategies, methodologies and assessment procedures that can be integrated with the mobile robots for accurate defect detection and localization that is low cost and efficient.

“We investigate this problem by considering a network of robots, each with a single omnidirectional guided acoustic wave transducer. This configuration is considered as it is arguably the simplest, with good potential for integration in a low-cost platform.”

According to the university, the methods from the study could be used across other materials, pipe geometries, noise levels or guided wave modes, allowing the full range of sensor performance parameters, defects sizes and types and operating modalities to be explored. The techniques can be used also to assess the detection and localisation performance for specified inspection parameters, such as for predicting the minimum detectable defect under a specified probability of detection and probability of false alarm.

The team will now investigate collaboration opportunities with industries to advance current prototypes for actual pipe inspections. The work is funded by the Engineering and Physical Sciences Research Council (EPSRC) as a part of the Pipebots project.