Autonomous tracking and tagging of buried pipelines based on Pipe-Locator data

Inspection and maintenance of aging ferrous pipelines of oil and gas industry is a major challenge especially when pipelines are buried in extreme environmental conditions like a desert. Condition monitoring of the metallic pipelines involves two layers of inspection, at first, the inspection of the quality of the cathodic protection (CP) layer and the second is to diagnose the condition of the metallic core of the pipeline. For performing, any kind of external inspection, maintenance or repair of the pipeline or its CP layer, from the above ground position, accurate location of the buried pipelines has to be known beforehand. Novel non-contact external inspection technique based on metal magnetic memory (MMM) also require to know the accurate location of the buried pipeline for the collection of reliable data. Currently, the task of locating the buried pipeline from above ground is performed manually with the help of handheld pipe-locators (PL) where the ground operator carries the PL while looking at the display screen of PL to navigate just above the pipeline over the ground. There are situations due to bad terrain and difficult environmental conditions like the extremely hot or cold climate where manual walking of a human operator for a long distance is not feasible and in such situations, an autonomous robotic device moving above the buried pipeline can be of great help. This paper presents the complete automation of detecting, locating, navigating and tagging of the buried pipeline based on PL data. The robotic mechanism has two primary components, the first non-contact sensors (NCS) and the second Autonomous Ground Vehicle (AGV) to carry the sensors. Further NCS has three sub-categories like detection sensor, navigation sensor, and inspection sensors. Detection sensors locate the pipeline; navigation sensor helps mobile platforms to navigate along the detected pipeline and finally inspection gather inspection data from the pipeline. Since, all the process of detection, navigation, and inspection is noncontact and completely autonomous; therefore, no human intervention is required after the initial set-up of the mission. PL based automated tracking of buried pipelines involve the implementation of the two-level controller the first for angular correction and the second for lateral correction. A high level of accuracy is achieved in pipeline tracking leading to better data collection for non-contact external inspection by magnetic sensors.