Bill D. Cook Associate Professor of Mechanical & Aerospace Engineering Zheng Chen, Principal Investigator, and Moores Professor of Mechanical & Aerospace Engineering Gangbing Song, co-PI, have received a combined $500,000 grant for their Ocean Energy Safety Institute (OESI) proposal, Integration of Percussion with Robotics for Offshore Bolted Structure Inspection. It is one of 14 OESI-funded project proposals out of 91 submissions geared toward innovation and technology development to improve the safety and environmental stability of offshore energy development.
“For decades, there have been many offshore pipelines deployed in the Gulf of America, and their bolt structures need constant monitoring for tightness,” said Chen. “If the bolts lose their tightness, leaks from the pipeline can cause environmental issues along the coastal area. I am working with Dr. Song, who is working on smart-touch inspection using smart-touch sensors to inspect bolt structure failure, to deploy sensors to the bolt structures with remotely operated robotic vehicles.”
The sheer length of pipeline currently in operation means that there are greater chances for failure at any given moment, and timely subsea inspections are necessary to prevent leaks and spills.
“Instead of using a smart-touch sensor, we use a percussion tool to tap the bolt structure. By listening to the sound, we can detect if this bolt has lost its tightness with the use of machine learning algorithms,” Chen said.
This advanced approach, guided by remote operated vehicle (ROV), will enable time-efficient and cost-effective management of subsea connection integrity, and it will open the door to applications for inspection of other types of subsea structures as well.
“Ultimately, the project will push the boundaries of what can be accomplished by integrating robotics and structural health monitoring technologies,” he said.
This year-long project is already underway, and Chen reports that they have received “very good feedback” from industry.
“We are working closely with Chevron and Oceaneering International to come up with an industry partnership plan, which will allow us to work closely with oil and gas companies to address this bolt structure failure issue,” he added.
Next steps include methods validation via lab testing. Chen and Song will develop the percussion tool to be used by the ROV for inspection as well as the machine learning, or AI-enhanced, algorithm to analyze the collected percussive data to assess tightness or looseness of fit.
“This approach will really benefit oil and gas companies and the inspectors of our offshore energy assets,” Chen said. “And this project very important for the environmental protection of our coastal areas.”