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

机译:埋藏油气管道各种铺设条件的分层控制器自主跟踪性能分析

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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.
机译:中东国家拥有世界上最复杂和广泛的石油和天然气管道网络,预计到2022年的管道总长度为24066.9公里。因此,这些结构的常规检查和积极维护在石油和天然气中具有高优先级操作。流化,常用的内部检查方法昂贵,需要预先安装程序,无瑕疵的猪操作使其耗时。外部检查目前由一组运营商手动完成,他们可以在埋地管道结构上散步或走过。然后手动分析使用各种手持设备收集的视觉/传感器数据以识别/定位可能的异常。收集的数据的准确性和分析高度取决于运营商的经验。此外,极端的环境条件如高温和不均匀的地形,使手动检查是一个繁琐的任务。目前手动检查方法中的挑战可以通过使用配备有各种传感器的机器人平台来解决,可以检测,导航和标记埋地的油气管道。在阿联酋,石油和天然气管道大多埋在埋藏管道结构上的凸起梯形结构。潜水线埋在皮肤下,如(i)埋在药物中间的单个管道,或者(ii)两个管道埋在埋藏在皮塞的两个边缘。要使用机器人平台进行任何外部检查埋地管道的外部检查,必须预先知道埋地管道的精确位置。拟议的自主机器人检查系统(ARIS)应具有精确定位埋地管道结构的能力,并与这些结构一起导航,而无需任何故障/滑动。用于基于管道定位器和超声波传感器数据的新型等级控制器用于ARIS,用于在掩埋管道结构上检测和导航。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,允许车辆通过埋入的管道自动导航(ii)基于声纳的防拓控制器,为车辆提供额外的保护层在极端条件下导航。实验设置类似于真实埋地管道状况,建立在实验室环境中。在各种埋地管道铺设条件下测试了ARI的自主跟踪性能。所获得的结果表明,aris沿着埋地管道追踪和导航的能力,即使在没有任何秋季/滑行的极端条件下也是如此。

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