Ultrasonic robot enabled smart diagnosis of pipeline integrity
Project Description
Petrochemical/gas pipeline is the key infrastructure supporting energy industrial sectors. They are important assets to the operators, and structural integrity of pipelines needs to be assessed in a timely manner to mitigate safety risks and potential financial loss. Corrosion is the most common defect type of any pipelines, but currently remotely quantifying corrosion severity is challenging because most of the pipeline sections are difficult to access physically posing difficulties to examine the pipeline part. In this project, we will develop long-distance guided wave inspection method with particular improvement in the detection sensitivity and defect imaging capabilities towards micrometre scales; such as level of capability would enable a revolutionary change compared to he current inspection methods. The students will be work on both simulations and experiments, including developing imaging methods and collaborate with our industrial partners in HK.
Supervisor
SHI, Fan
Quota
2
Course type
UROP1100
UROP2100
Applicant's Roles
1) Learn knowledge about ultrasound physics and signal processing
2) Learn experimental skills
3) Run simulations and test different imaging detection algorithms
4) Build experimental test rig with system integration
5) conduct ultrasonic experiments with different pipeline samples
Applicant's Learning Objectives
1) ultrasonic knowledge and NDE principles
2) Pipeline mechanics and structural integrity
3) Signal processing, imaging and mathematics
4) Software programing (mainly matlab or python) and machine learning algorithms
5) Skills of building experiment test rigs
Complexity of the project
Moderate