Smart Robotic System Tracks Buried Pipelines, Inspects for External Damage
- Judy Feder (JPT Technology Editor)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- December 2019
- Document Type
- Journal Paper
- 59 - 62
- 2018. Society of Petroleum Engineers
- 3 in the last 30 days
- 16 since 2007
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This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 192773, “A Smart Robotic System for Noncontact Condition Monitoring and Fault Detection in Buried Pipelines,” by Xiaoxiong Zhang and Amit Shukla, Khalifa University; Abdulla Al Ali, ADNOC; and Hamad Karki, Khalifa University, prepared for the 2018 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 12–14 November. The paper has not been peer reviewed.
The complete paper describes the development of a smart robotic inspection system for noncontact condition monitoring and fault detection in buried pipelines. Steered by a pipe locator, the smart robot, called an autonomous ground vehicle (AGV), can autonomously track the buried pipeline and simultaneously inspect it externally with a metal magnetic memory (MMM) sensor. The smart robotic system is designed to overcome the shortcomings of both manual external inspection and noninvasive magnetometric diagnosis (NIMD), making pipeline inspection safer, more efficient, and less expensive.
Condition monitoring and defect inspection of buried pipelines has been a constant challenge for all oil and gas operations. Maintaining safety and prolonging the service life of ferrous metal pipelines that are exposed to harsh operating environments and damage from corrosion, erosion, and cracking requires regular inspection to diagnose existing or potential defects.
Pipelines can be inspected in two ways: internally and externally. Internal, or inline, inspection primarily uses an intelligent pipeline inspection gauge equipped with sensors to measure the size, location, and orientation of defects inside the pipeline. In external inspection, which is the subject of the paper, workers drive a vehicle along the pipeline to visually inspect for detection of leakage or any other kind of visible damage. Such manual external inspection is highly inefficient, expensive, and hazardous. It is also difficult to obtain any important information about anomalies brewing in the buried pipes or cathodic protection layers using this method.
Much work has been undertaken to develop nondestructive testing (NDT) technologies to inspect pipelines. However, most of these NDT sensors work only in close vicinity to the pipeline surface, so this method requires excavating the pipeline and exposing the structure. This shortcoming has instigated research toward other NDT techniques such as NIMD, which allows noncontact detection of anomalies from a distance in the core metal of pipelines buried deeply underground. NIMD sensors work on the principle of measuring distortions of residual magnetic fields caused by the variation in the pipeline’s metal magnetic permeability in a stress concentration zone (SCZ). The SCZ, and the potential changes in metal magnetic permeability, result from the combined influence of residual stress, vibration, bending and loading of pipelines, installation stress, temperature fluctuations, and other factors. These handheld magnetic sensors are used by field operators, making inspection of long pipelines in extreme environmental conditions unfeasible.
Efforts to develop more-intelligent and -efficient methods of external inspection led to the design of various types of in-pipe inspection robots. Overall, all types of in-pipe robots are designed for solving specific problems relating to the pipeline’s interior environment, which is complex, invisible, and unpredictable. The technology presented in this paper resulted from the idea of using a robot that can simultaneously track and externally inspect the pipeline.
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