About the LNG Tank Inspection Robot:
The LNG Tank Inspection Robot is an advanced robotic system developed to address critical challenges in inspecting LNG, LPG, and condensate tank floors, especially under extreme cryogenic conditions. Traditionally, these inspections require prolonged shutdowns and pose safety risks to human operators due to the time-intensive annealing process needed before inspection. This robot dramatically reduces inspection time by operating at much lower temperatures without the need for human entry, enhancing both safety and efficiency. Developed in 2024 as part of Qatar's strategic initiative to modernize the energy sector, the robot is an indigenous innovation by Qatar University's engineering research team. Its modular, tethered design and deployment of magnetic flux leakage (MFL) sensing technology make it a pioneering solution in cryogenic tank inspection.
Scientific or Technical Area:
Robotics, Sensing, Non-destructive testing and Artificial Intelligence.
Project Timeline:
Ongoing.
Main Objectives of the Project:
- Remotely controlled Inspection robot for metallic surfaces.
- Uses MFL, Low-lux imaging, and laser-based orientation strategies.
- AI-based detection and classification algorithms to detect and label defects and their locations.
Anticipated Impact and Relevance:
The LNG Tank Inspection Robot has numerous applications across various industries:
- Target Sector: Oil and Gas, specifically LNG and LPG industries
- Application Scenarios: Cryogenic tank floor inspection, industrial safety monitoring, and non-destructive defect detection
- Impact: Reduces shutdown times by 50%, eliminates human safety hazards, and enhances defect detection accuracy
Students' involvement is a key aspect of this project that guarantees capacity building and developing of local expertise in a number of areas that will impact the industrial and economic footprints in Qatar, essentially aligning with Qatar Vision 2030.
Supervisor(s) Details:
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Full Name: Prof. Uvais Qidwai
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Job Title/Position: Professor (Computer Engineering)
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Department or Unit: Department of Computer Science and Engineering
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Institution/Affiliation: Qatar University
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Email Address: uqidwai@qu.edu.qa
Team Members Involved:
- Dr. Noora Al-Qahtani, Research Assistant Professor, Centre for Advance Materials (CAM)
- Amna Osman, Student, Computer Science & Engineering, College of Engineering
Picture of the Prototype:
