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Remote, Visual Inspection And Digital Analysis For External Corrosion Assessment In Refining Unit Applications

Picture for Remote, Visual Inspection And Digital Analysis For External Corrosion Assessment In Refining Unit Applications
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Product Number: 51321-16542-SG
Author: Slawomir Kus/ Sridhar Srinivasan
Publication Date: 2021
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External corrosion of coated pipelines and equipment is a common problem in refineries and petrochemical plants, especially at locations with elevated humidity e.g. near cooling towers. Usually manifest as damage to the coating layer (spot or uniform), external corrosion will require timely detection and repair in order to ensure sustained reliability in operations. Locations of coating damages are typically revealed by traditional visual inspection. Sometimes, visual inspection is supported by thermographic imaging and may provide additional insights on potential for Corrosion Under Insulation (CUI). Visual inspection is typically considered to be a low cost and uncomplicated technique. However, it requires significant effort in terms of time and skilled manpower as well as the need for complex infrastructure (scaffolding and / or crane operation are often required), resulting in significant cost of visual characterization. Recent advances in drone technology offer an attractive and cost-efficient alternative to manual methods and are designed to automate many aspects of visual inspection. Automated drone systems for remote imaging facilitate rapid photographic documentation of relevant unit structures or areas without complex and expensive support infrastructure. When integrated with intelligent data processing systems for rapid analysis and mapping of surfaces with damaged coating, cracked supports, damaged insulation jacketing, drone based visual inspection and data analyses techniques provide a robust and low-cost alternative. This can also be easily combined with thermographic imaging to help identify locations where CUI may be occurring. An important element in remote visual inspection is automated post processing and data analysis utilizing special algorithms for e.g. crack detection in concrete supports or coating damages (size, type, density etc.). The current paper provides a conceptual framework for automated visual inspection utilizing remote drone systems. It also presents results from a field case study on inspection of multi-level pipe-racks in a refinery environment. Examples of automated image analysis using dedicated algorithms are also given. Potential benefits and challenges of drone-based data acquisition and analyses are also discussed.

Keywords: visual inspection, remote drone system, external corrosion, data analysis

External corrosion of coated pipelines and equipment is a common problem in refineries and petrochemical plants, especially at locations with elevated humidity e.g. near cooling towers. Usually manifest as damage to the coating layer (spot or uniform), external corrosion will require timely detection and repair in order to ensure sustained reliability in operations. Locations of coating damages are typically revealed by traditional visual inspection. Sometimes, visual inspection is supported by thermographic imaging and may provide additional insights on potential for Corrosion Under Insulation (CUI). Visual inspection is typically considered to be a low cost and uncomplicated technique. However, it requires significant effort in terms of time and skilled manpower as well as the need for complex infrastructure (scaffolding and / or crane operation are often required), resulting in significant cost of visual characterization. Recent advances in drone technology offer an attractive and cost-efficient alternative to manual methods and are designed to automate many aspects of visual inspection. Automated drone systems for remote imaging facilitate rapid photographic documentation of relevant unit structures or areas without complex and expensive support infrastructure. When integrated with intelligent data processing systems for rapid analysis and mapping of surfaces with damaged coating, cracked supports, damaged insulation jacketing, drone based visual inspection and data analyses techniques provide a robust and low-cost alternative. This can also be easily combined with thermographic imaging to help identify locations where CUI may be occurring. An important element in remote visual inspection is automated post processing and data analysis utilizing special algorithms for e.g. crack detection in concrete supports or coating damages (size, type, density etc.). The current paper provides a conceptual framework for automated visual inspection utilizing remote drone systems. It also presents results from a field case study on inspection of multi-level pipe-racks in a refinery environment. Examples of automated image analysis using dedicated algorithms are also given. Potential benefits and challenges of drone-based data acquisition and analyses are also discussed.

Keywords: visual inspection, remote drone system, external corrosion, data analysis

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