Artificial Intelligence-Based Inspection Methods for Pipeline Monitoring

Nowadays, artificial intelligence (AI) emerged as a promising innovation for all aspects of human life. One of the fascinating motivations behind AI technology is in robotics and engineering. The monitoring of pipelines all over the world can be a crucial part as an instance in this field. The inspection of massive pipeline infrastructures, such as sewers and waterworks, is a vital assignment to prevent viable failures. For the sake of protect pipelines from leakage and corrosion and or different troubles like burst and fractures etc., myriad conventional techniques are used for monitoring. This paper investigates the latest improvements and also researches the review on the proficiency of inspection applications such as Visual Testing (VT), Ultrasonic Testing (UT), Eddy Current Testing (EC), Electromagnetic Testing (ET), Sonar Testing, Impact-Echo Testing (IE) and Acoustic Emission (AE) with respect to advantages and drawbacks of these methods. Further techniques are categorized on the fundamental of their inherent characteristics and their applications. In this study, the significance of pipeline inspection is firstly accentuated based on the literature. Finally, this paper provides an overview of exterior and interior inspection methods and a summary of comparisons associated with the overall performance of every system.

Keywords:

Artificial intelligence , Leakage and corrosion , Pipeline inspection , Ultrasonic testing , Visual testing