One of the biggest issues facing the oil industry is the steel corrosion phenomenon, which affects underground transmission pipelines that are used to transport high gas pressure across long distances. Steel is shielded from external soil corrosion by a bituminous coating with an active cathodic protection system in order to keep the steel in its protective field and minimize the corrosion risk. However, steel protection can fail, bare steel may interact mechanically or electrochemically with an aggressive soil solution, resulting in external surface defects such as corrosion pitting and cracking on steel. These are concerning phenomena and are the major threats to the pipeline transmission system’s reliability and ecological safety. Corrosion mechanisms vary and can be studied using a variety of approaches, including electrochemical measures, which are influenced by temperature, pH, soil properties, resistivity, water content, and mechanical forces. Corrosion studies from simulated artificial soil solutions demonstrated that steel is susceptible to soil corrosion. Non-destructive ultrasonic techniques such as C-Scan Emission testing and the time of flight diffraction technique (TOFD) ultrasonic non-contact testing method were used to detect surface defects. After propagation of the ultrasonic waves, the diffracted ultrasonic reflected wave occurring at the edges of the defects appears due to the presence of a corrosion defect by generating defect echoes. The C-Scan ultrasonic image shows surface reflection, including corrosion defects on interfaces with varying acoustic impedances. The cross-transverse speed ultrasonic propagation through the plate, including defects, is modified, revealing more surface defects. Cross-transverse speed is shown to increase ultrasonic detection presents some advantages, such as precision and speed of detection without alteration to the structure. The application of the ultrasonic method as an intelligent industrial robotics method in an industrial setting is possible provided that the data processing and acquisition instruments are highly detectable, autonomous, and automatic. The maintenance method can be used to schedule routine in-line inspections to find and size, position, and identify defects as a preventive measure.
Author (s)
Details
Fatima
Benkhedda
Materials Research Team, LAEPO Research Laboratory, University of
Tlemcen,13000, Algeria.
Ismail
Bensaid
Materials Research and Structure Laboratory, University of
Tlemcen, 13000, Algeria.
Abderrahim
Benmoussat
Materials Research Team, LAEPO Research Laboratory, University of
Tlemcen,13000, Algeria.
Abderrahim
BenmoussatMaterials Research Team, LAEPO Research Laboratory, University of
Tlemcen,13000, Algeria.
Abdeldjelil
Amara Zenati
Materials Research Team, LAEPO Research Laboratory, University of
Tlemcen,13000, Algeria.
Please see the book here:- https://doi.org/10.9734/bpi/srnta/v1/1780
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