Imaging Technology Estimates Corrosion Depth

WEDNESDAY, MAY 15, 2024


NTT Corporation in Japan has reportedly developed an image recognition technology to detect and estimate the depth of steel corrosion from infrastructure images taken with a digital camera.

The company says that it was confirmed that the defect amount of the steel section can be estimated with an accuracy of 0.44 millimeters during verification using steel pipeline facilities.

The technology can reportedly automatically grasp the corroded areas of the equipment and the thickness of the remaining steel material from the images, enabling accurate evaluation of equipment durability and load-bearing performance.

This offers the potential to reduce maintenance costs by allowing repairs to be performed in a timely manner.

NTT has scheduled the technology to be integrated into its companies by the end of fiscal year 2024 and plans to expand use to other infrastructure facilities such as bridges, steel towers and guardrails.

Additionally, the recognition technology is anticipated to be introduced at the Tsukuba Forum 2024 from May 16-17.

About the Testing

The company says that the research was established using steel conduit facilities, which are telecommunication infrastructure facilities owned by NTT.

For the corrosion detection, the areas were classified into areas where minor corrosion has occurred without defects in the steel section, areas where corrosion has occurred with defects in the section and healthy areas where no corrosion has occurred.

Using NTT’s proprietary database, the team built a machine learning model for “highly accurate” estimation. Among the various appearance features that change with the progress of corrosion, such as the extent of corrosion, color and the size of the rust hump, they selected the features that are highly related to the amount of defect in the steel section.

Based on this feature, the team says, corrosion images with various degrees of progress were then grouped, and corrosion images and cross-sectional defect measurements in the images were prepared so that each group was sufficiently and equally corroded.

The high-quality database was constructed by selecting images based on appropriate features and accurately measuring the amount of defects enables highly accurate estimation of defects. Areas of corrosion with cross-sectional defects are then detected on the pipes.

Using the steel pipe installed at the site, they photographed the inner surface of the steel pipe with a pipe camera. Afterwards, the amount of loss in the steel section due to corrosion from the images was estimated.

The amount of loss in the pipe cross-section is reportedly estimated by analyzing the degree of corrosion progression. Since the thickness of the communication steel pipe is 4.20 millimeters in its sound state, the remaining steel thickness in the corroded area can be calculated to be 2.95 millimeters by subtracting the amount of sectional loss.

   

Tagged categories: Asia Pacific; Corrosion; Corrosion protection; EMEA (Europe, Middle East and Africa); Infrastructure; Infrastructure; Latin America; North America; Pipeline; Pipelines; Pipes; Program/Project Management; Research; Research and development; Steel; Technology; Z-Continents

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