Collaborative Research: FW-HTF-P: Efficient Inspection of Unpiggable Pipelines through Human-Robot Integration

合作研究：FW-HTF-P：通过人机集成有效检查不可清管的管道

• 批准号: 2222635
• 负责人: Xiaobo Tan
• 金额: $ 6万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222635&HistoricalAwards=false
• 关键词: Collaborative; Research; FW; HTF; Efficient

Recent trends in emerging fuels, such as renewable natural gas and hydrogen, provide the United States a golden opportunity to become a powerhouse in global energy markets and truly achieve full energy independence. However, recent economic and business analytics has indicated that the US conventional oil and gas revolution is being held back by its aging pipeline infrastructure, more than half of which is over 60 years old. Therefore, within the gas pipeline industry, an urgent need is to inspect and certify existing infrastructure for emerging fuel transport. A grand challenge in gas pipeline infrastructure is aging-related deterioration that often leads to catastrophic consequences. Ensuring the integrity of pipelines requires advanced inspection and diagnostic tools in the next few decades. Due to the complex geometries of pipelines, over or under-sized valves, short-radius bends, and other conditions, a significant portion of pipeline infrastructure in the US remains “unpiggable” – unable to be inspected by the conventional inline inspection robots. Allowing pipeline operators to inspect unpiggable gas pipelines with newly developed robots, analytics, and human integration will significantly help the gas industry to manage critical infrastructure. The proposed study aims to tackle this challenging problem to reduce risk and improve efficiency for an industry with inherent dangers related to transporting, storing, and accessing combustible and corrosive materials. The robotic, decision-support, and training tools created in this project will provide a conduit to recruiting and retaining individuals who have not traditionally been considered for pipeline inspection positions, such as persons with disabilities and operators with insufficient field experience and education.This project explores how a cyber-physical-human interplay enables a more responsive and effective translation of new technology advancements for oil and gas pipeline workers. The overall goal of this project is to understand the work context of pipeline inspection, examine the feasibility of a novel robotic inspection system, and generate the empirical groundwork for a larger project proposal to the NSF’s Future of Work at the Human-Technology Frontier (FW-HTF) Initiative. The future FW-HTF proposal aims to create a novel human-robot-AI framework to enable automated inspection, safety assessment, and worker training. Specific plans for this development grant involve (a) interviewing stakeholders to understand the current work practices of pipeline inspection and assess their needs and perceptions of robotics and automation technologies; (b) gaining an understanding of human factors (such as trust) that strengthen the partnership between humans and robots by conducting artifact analysis of robot prototypes with stakeholders; (c) understanding potential safety hazards of robotic pipeline inspection tools and developing guidelines on robot design for mitigating such risks; and (d) understanding the human knowledge and inspection data fusion and their impact on the risk assessment for the pipeline with the preliminary results from the above tasks. The proposed study will significantly advance the understanding of the future of work, workers, and technology for efficient inspection of critical pipeline infrastructure. If successful, this development grant will lead to a comprehensive FW-HTF research proposal for designing and implementing cyber-physical-human systems that best utilize the capacities of human workers and new technologies to achieve high productivity and safe work conditions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

新兴燃料（例如可再生天然气和氢）的最新趋势为美国提供了成为全球能源市场中强大的巨大机会，并真正实现了充分的能源独立性。但是，最近的经济和商业分析表明，美国传统的石油和天然气革命被其老化的管道基础设施阻止，其中一半以上已有60多年的历史了。因此，在天然气管道行业中，迫切需要是检查和证明现有的新兴燃料运输基础设施。天然气管道基础设施的巨大挑战是与老化有关的决定，这通常会导致灾难性后果。确保管道的完整性需要在接下来的几十年中进行高级检查和诊断工具。由于管道的复杂几何形状，大小或不足的阀，短草丁弯曲和其他条件，美国的大部分管道基础设施仍然“不可辨” - 无法受到常规内线检查机器人的检查。允许管道运营商通过新开发的机器人，分析和人类整合检查不可使用的天然气管道，将大大帮助天然气行业管理关键的基础设施。拟议的研究旨在解决这个挑战问题，以降低风险并提高具有与运输，存储和获取混合和腐败材料有关的危险的行业的效率。该项目中创建的机器人，决策支持和培训工具将为招聘和保留传统上不考虑管道检查职位的个人提供渠道，例如残疾人和具有足够的现场经验和教育的运营商。该项目探讨了网络物理 - 人类相互作用如何响应于新技术的响应性和有效的技术，并有效地翻译了油性的技术和油性的工具。该项目的总体目标是了解管道检查的工作背景，检查新型机器人检查系统的可行性，并为NSF在人类技术领域（FW-HTF）计划中为NSF的工作未来提供更大的项目建议的经验基础。未来的FW-HTF提案旨在创建一个新型的人类机器人框架，以实现自动检查，安全评估和工人培训。该发展赠款参与的具体计划（a）采访利益相关者，以了解当前的管道检查和评估他们对机器人技术和自动化技术的看法的工作实践； （b）通过与利益相关者对机器人原型进行人工制品分析来了解人类与机器人之间的伙伴关系的理解（例如信任）； （c）了解机器人管道检查工具的潜在安全危害，并制定有关缓解此类风险的机器人设计指南； （d）了解人类的知识和检查数据融合及其对管道风险评估的影响，并从上述任务的初步结果。拟议的研究将大大提高对工作，工人和技术未来的理解，以有效检查关键管道基础设施。如果成功的话，这项开发赠款将为设计和实施网络物理人类系统提供全面的研究建议，最能利用人工和新技术的能力，以实现高生产力和安全的工作条件。该奖项反映了NSF的法定任务，并通过评估基础的智力效果和宽阔的范围来评估，并以评估为基础的评估。

项目成果

Situating Robots in the Organizational Dynamics of the Gas Energy Industry: A Collaborative Design Study

将机器人置于天然气能源行业的组织动态中：协作设计研究

• DOI: 10.1109/ro-man57019.2023.10309385
• 发表时间: 2023
• 期刊: IEEE
• 作者: Lee, Hee Rin;Tan, Xiaobo;Zhang, Wenlong;Deng, Yiming;Liu, Yongming
• 通讯作者: Liu, Yongming