Robotic digital X-ray scanning system for deep water flexible riser inspection (RobotX)

“海上石油和天然气运营商面临着新的挑战，因为生产设施正在进入深水区，因此要为其资产提供充分的完整性保证。腐蚀性更强的环境、更高的压力和温度会产生腐蚀条件。在深水和恶劣的环境中，载荷高且复杂，设计方法通常被推到当前行业能力和经验的极限，立管系统受到了越来越多的关注，鉴于几起操作事故（如墨西哥湾的深水地平线事故），比以往任何时候都更加关注。这些事故导致运营商和监管机构质疑和更新业务守则。柔性波纹管的设计本质上是复杂的，具有许多不同的材料类型，对应于检查和完整性评估中的挑战。目前市场上可用的检测技术仅包括不定期的潜水员或遥控潜水器（Remote Operated Vehicle，简称ROV）检测，并且只能检测近侧层的电线中断，远侧层则不进行检测。RobotX项目将研究机器人数字X射线扫描系统的可行性，以满足深水柔性电缆检测的需求和挑战。机器人和数字X射线摄影设备必须承受恶劣的环境条件，即高压（100 bar）。该系统将执行透视快速扫描，因为它使用创新的图像处理方法抓取和处理数据，并使用机器学习对其进行分类。如果检测到缺陷，机器人系统将能够转动立管并执行更彻底的扫描。使用从多个角度拍摄的图像，将正确识别缺陷。这些创新不仅可以检测和定位缺陷，还可以根据现有的历史数据库对其进行分类，并自动决定定制扫描，以评估严重程度和未来干预的需求。"

"New challenges are present for offshore oil and gas operators to provide adequate integrity assurance of their assets as the production facilities are reaching for the deep-water areas. Challenging conditions arise from more corrosive environments, higher pressures and temperatures. In deep water and hostile environments, where loading is high and complex and often design methods are pushed to the limit of current industry capability and experience, the riser systems have received an increased focus, more than ever in the light of several operational incidents (like the Deepwater Horizon accident in the Gulf of Mexico). These accidents have caused operators and regulators to question and update codes of practice. Flexible risers pipes are by nature complicated in design with many varying material types, corresponding to challenges in the inspection and integrity evaluation. The inspection techniques currently available in the market consist of only irregular diver or Remotely Operated Vehicle (ROV) inspections and are able to inspect only the near side layers for wire disruptions, with the far side layers remaining uninspected.The RobotX project will investigate the feasibility of a robotic digital x-ray scanning system that will address the needs and challenges of deep water flexible risers inspection. The robot and digital radiography equipment would have to withstand harsh environmental conditions i.e. high pressure (100bar). The system will perform a see--through quick scan as it crawls and process the data using innovative image processing methods and categorise them using machine learning. If defects are detected the robotic system will be able to turn around the riser and perform a more thorough scan. The defect will be correctly identified, using images taken at several angles. These innovations will allow not just to detect and locate the defects, but also classify them according to an existing historical database and automatically decide on bespoke scans for assessing the severity and needs for future intervention."