Autonomous Tracking Performance Analysis of Hierarchical Controller on Various Laying Conditions of Buried Oil and Gas Pipelines

Vidya Sudevan, Amit Shukla, Arjun Sharma, V. Bhadran, H. Karki
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引用次数: 1

Abstract

Middle Eastern countries have the most complex and extensive oil and gas pipeline network in the world and are expected to have a total length of 24066.9km of pipelines by 2022. Routine inspection and active maintenance of these structures thus have high priority in the oil and gas operations. Pigging, the commonly used internal inspection method is expensive and the need for pre-installation procedures for flawless pig operations makes it time-consuming. The external inspection is currently done manually by a group of operators who either drives or walks over the buried pipeline structures. The visual/sensor data collected using various handheld devices are then analyzed manually to identify/locate the possible anomalies. The accuracy of data collected and their analysis highly depends upon the experience of the operators. Also, the extreme environmental conditions like high temperature and uneven terrain make the manual inspection a tedious task. The challenges in the current manual inspection methods can be tackled by using a robotic platform equipped with various sensors that can detect, navigate and tag the buried oil and gas pipelines. In UAE, the oil and gas pipelines are mostly buried under a berm, a raised trapezoidal structure made up of sand over the buried pipeline structure. The pipelines are buried under the berm either as (i) single pipeline buried in the middle of the berm or as (ii) two pipelines buried on the two edges of the berm. To conduct any external inspection of buried pipelines using a robotic platform, the accurate location of the buried pipeline has to be known beforehand. The proposed Autonomous Robotic Inspection System (ARIS) should have the capability to precisely locate the buried pipeline structure and navigate along with these structures without any fail/skid. A novel hierarchical controller based on a pipe-locator and ultrasonic sensor data is developed for ARIS for detection and navigation over the buried pipeline structures. The hierarchical controller consists of two modules: (i) pipe-locator based tracking controller, that allows the vehicle to autonomously navigate over the buried pipeline and (ii) a sonar-based anti-topple controller which provides an extra layer of protection for vehicle navigation under extreme conditions. An experimental setup, similar to the real buried pipeline condition was built in a lab environment. The autonomous tracking performance of ARIS was tested under various buried pipeline laying conditions. The results obtained show the ability of ARIS to track and navigate along the buried pipeline even in extreme conditions without any fall/skid.
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埋地油气管道不同敷设条件下层次控制器的自主跟踪性能分析
中东国家拥有世界上最复杂和最广泛的石油和天然气管道网络,预计到2022年管道总长将达到24066.9公里。因此,在油气作业中,对这些结构进行日常检查和积极维护是重中之重。清管,常用的内部检查方法是昂贵的,并且需要安装前的程序来进行完美的清管器操作,这使得它非常耗时。目前,外部检查是由一组操作员手动完成的,他们要么开车,要么步行穿过埋地的管道结构。使用各种手持设备收集的视觉/传感器数据然后进行手动分析,以识别/定位可能的异常。数据收集和分析的准确性在很大程度上取决于操作者的经验。此外,高温、不平坦地形等极端环境条件也使人工检测变得繁琐。通过使用配备各种传感器的机器人平台,可以解决当前人工检测方法中的挑战,这些传感器可以检测、导航和标记埋藏的油气管道。在阿联酋,石油和天然气管道大多被埋在护堤下,护堤是一种由沙子组成的凸起的梯形结构,覆盖在被埋的管道结构上。管道埋在护堤下面的方式有两种:一种是单管道埋在护堤中间,另一种是双管道埋在护堤两侧。要使用机器人平台对埋地管道进行外部检查,必须事先知道埋地管道的准确位置。拟议的自主机器人检测系统(ARIS)应该能够精确定位埋在地下的管道结构,并沿着这些结构导航,而不会出现任何故障/打滑。提出了一种基于管道定位器和超声传感器数据的分层控制器,用于对埋地管道结构进行探测和导航。分层控制器由两个模块组成:(i)基于管道定位器的跟踪控制器,允许车辆在埋地管道上自主导航;(ii)基于声纳的抗倾覆控制器,为极端条件下的车辆导航提供额外的保护。在实验室环境中建立了与实际埋地管道条件相似的实验装置。在不同埋地管道敷设条件下测试了ARIS的自主跟踪性能。结果表明,即使在极端条件下,ARIS也能够沿着埋地管道跟踪和导航,而不会发生坠落/打滑。
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