I-Corps: Determining Excavator Proximity to Buried Utilities

I-Corps：确定挖掘机与埋地公用设施的接近程度

• 批准号: 1339729
• 负责人: Vineet Kamat
• 金额: $ 5万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-15 至 2014-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1339729&HistoricalAwards=false
• 关键词: Corps; Determining; Excavator; Proximity; Buried

An excavator unintentionally hits a buried utility (e.g., gas pipe, water main, electric cable, etc.) every 60 seconds in the US causing fatalities, injuries, and property damage, that together cost billions of dollars each year. It is widely documented that these accidents occur either because excavator operators do not know where utilities are buried, or because they cannot perceive where the utilities are relative to the digging excavator. The developed technology allows excavator operators to persistently see what utilities lie buried in a digging machine's vicinity, thus helping prevent accidents involving utility strikes. It also allows the monitoring of working excavator proximity to vicinal buried assets, thereby creating the capability for real time knowledge-based excavator operation and control. The technology sought to be commercialized attempts to transition fundamental knowledge from prior NSF supported research in georeferenced augmented reality visualization, equipment monitoring, and geometric proximity interpretation, and integrates them for excavator spatial awareness and operator knowledge. Commercialization of the developed technology is critical because accidents involving excavator hits to buried utilities is a long-standing and significant societal problem that disrupts daily life and commerce that can lead to fatalities, injuries, property damage, and other costs each year.This project will potentially transform excavator operation and control from a primarily skill-based activity to a knowledge-based practice, leading to significant increases in productivity and safety. This is turn will help realize enormous cost savings and reduction of potential hazards to citizens, improvement in industry competitiveness, and reduction in life cycle costs of underground infrastructure. Such benefits will also accrue in fields such as manufacturing, transportation, mining, and ship-building where the transition from skill-based to knowledge-based processes is seen to be of value.

在美国，挖掘机每 60 秒就会无意中撞到地下公用设施（例如煤气管、水管、电缆等），造成人员伤亡和财产损失，每年造成的损失总计数十亿美元。据广泛记载，这些事故的发生要么是因为挖掘机操作员不知道公用设施埋在哪里，要么是因为他们无法感知公用设施相对于挖掘机的位置。所开发的技术使挖掘机操作员能够持续查看挖掘机附近埋有哪些公用设施，从而有助于防止涉及公用设施罢工的事故。它还可以监控工作中的挖掘机与附近埋地资产的接近程度，从而创建基于知识的实时挖掘机操作和控制的能力。该技术寻求商业化，试图将之前 NSF 支持的地理参考增强现实可视化、设备监控和几何邻近解释研究中的基础知识转化为基础知识，并将它们集成到挖掘机空间意识和操作员知识中。所开发技术的商业化至关重要，因为涉及挖掘机撞击埋地公用设施的事故是一个长期存在的重大社会问题，它扰乱了日常生活和商业，每年可能导致人员伤亡、财产损失和其他损失。该项目将潜在地将挖掘机操作和控制从主要基于技能的活动转变为基于知识的实践，从而显着提高生产率和安全性。这反过来将有助于实现巨大的成本节约，减少对公民的潜在危害，提高行业竞争力，并降低地下基础设施的生命周期成本。这些好处也将在制造、运输、采矿和造船等领域产生，这些领域从基于技能的流程向基于知识的流程的转变被认为是有价值的。