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The Proactive Infrastructure Monitoring and Evaluation System (PRIME): Enabling Intelligent Earthworks Management

The Proactive Infrastructure Monitoring and Evaluation System (PRIME): Enabling Intelligent Earthworks Management
主动基础设施监测和评估系统 (PRIME):实现智能土方管理
批准号:
NE/P00914X/1
负责人:
Jonathan Chambers
金额:
$26.18万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

项目摘要

项目成果

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中文摘要
翻译
项目合作伙伴:Arup, Atkins, Canal & River Trust,环境署,Geosense, High Speed Two, Highways England, ITM Monitoring, Kier, National Grid, Network Rail, Rail Safety & Standards Board, Scottish Canals, Transport Scotland。挑战:主动基础设施监测和评估(PRIME)系统的发展是由洪水防御、交通和公用事业土方工程的失败率和严重程度不断增加所驱动的。这是由于资产老化(许多运河和铁路土方工程超过百年)和更极端的天气事件(例如2013-14年和2015-16年冬季的极端降雨)。资产失败的代价非常高昂,仅在英国每年就造成数亿英镑的损失,更不用说对人类健康的风险,以及对交通系统、公用事业和更广泛经济的破坏。岩土资产的状况评估对于具有成本效益的维护和预防危险失效事件至关重要。对恶化状况的早期识别通常可以采取低成本的预防性补救措施(故障后的干预措施通常要贵十倍),并减少灾难性故障的风险。常规的状态监测方法往往不足以预测土方工程的不稳定性。它们严重依赖于地面观测,即巡视调查或空中数据收集。这些方法无法探测到失效事件的地下前兆;相反,一旦失败开始,他们就会识别出来。基础设施资产所有者、管理人员和顾问越来越认识到,自动化监控技术有潜力通过提供持续的状态信息和故障早期预警来降低这些成本和风险。目的和目标:主要目标是提供一种新的远程状态监测和决策支持系统,用于评估安全关键岩土资产的内部状况。这将通过在最近开发的PRIME硬件平台上实施一个完全自动化的数据分析和信息传递软件工作流来实现。综合PRIME系统(即硬件和软件)将把新兴的地球物理地面成像技术与无线遥测、“大数据”处理和门户网站访问相结合。它将构成新一代智能决策支持技术的基础,能够使用医学物理学中常用的诊断成像方法,近实时地“看到”脆弱的土方工程。在本项目结束时,软件和硬件将在新的和现有的利益相关者地点演示技术准备水平(TRL) 7,准备商业化和更广泛的利益相关者社区使用。好处:PRIME对资产所有者的主要好处包括通过减少不必要的更新和提供故障事件的早期预警来节省成本,通过减少人工现场访问来节省时间,通过防止危险的土方工程故障来降低风险,并最大限度地减少人们进入潜在危险操作环境的需要。岩土监测提供商、顾问和承包商将受益于新的尖端岩土监测服务,并首次获得近实时的地下体积监测信息。主要交付成果和产出:-新软件完全自动化PRIME数据处理和信息交付-包括基于网络的决策支持仪表板。-在现有的铁路和水道试验地点,以及新的公路、输电和防洪地点示范完整的先导系统-建立TRL 7(在运作环境中示范)。-与项目合作伙伴达成一致的商业化战略,以确保技术转化为利益相关者社区。持续时间:18个月费用:183,000英镑(80% FEC)
英文摘要
Project Partners: Arup, Atkins, Canal & River Trust, Environment Agency, Geosense, High Speed Two, Highways England, ITM Monitoring, Kier, National Grid, Network Rail, Rail Safety & Standards Board, Scottish Canals, Transport Scotland.The Challenge: The development of the Proactive Infrastructure Monitoring and Evaluation (PRIME) system is driven by the increasing rate and severity of failures in flood defence, transportation, and utilities earthworks. This is due to aging assets (many canal and rail earthworks are over a hundred years old) and more extreme weather events (e.g. the extreme rainfall during winter 2013-14 & 2015-16). Asset failures are enormously expensive, costing hundreds of millions of pounds per year in the UK alone, not to mention risks to human health and disruption of transport systems, utilities and the wider economy. Assessment of the condition of geotechnical assets is essential for cost effective maintenance and prevention of hazardous failure events. Early identification of deteriorating condition generally allows low cost preventative remediation to be undertaken (post failure interventions are typically ten times more expensive) and reduces the risk of catastrophic failures. Conventional approaches to condition monitoring are often inadequate for predicting earthwork instability. They are heavily dependent on surface observations - i.e. walk-over surveys or airborne data collection. These approaches cannot detect the subsurface precursors to failure events; instead they identify failure once it has begun. There is growing recognition among infrastructure asset owners, managers, and consultants that automated monitoring technologies have the potential to reduce these costs and risks by providing continuous condition information and early warnings of failure.Aims & Objectives: The primary objective is to deliver a new remote condition monitoring and decision-support system for assessing the internal condition of safety critical geotechnical assets. This will be realised by implementing a fully automated software workflow for data analysis and information delivery, building upon the recently developed PRIME hardware platform. The integrated PRIME system (i.e. hardware & software) will combine emerging geophysical ground imaging technology with wireless telemetry, 'big data' handling, and web portal access. It will form the basis of a new generation of intelligent decision-support technology capable of 'seeing inside' vulnerable earthworks in near-real-time using diagnostic imaging methods routinely used in medical physics. By the end of this project, the software and hardware will be demonstrated to technology readiness level (TRL) 7 at new and existing stakeholder sites, ready for commercialisation and use by the wider stakeholder community.Benefits: The key benefits of PRIME to asset owners include cost savings through minimising unnecessary renewals and providing early warning of failure events, time savings associated with fewer manual site visits, and risk reduction by preventing dangerous earthworks failures, and minimising the need for people to enter potentially hazardous operational environments. Geotechnical monitoring providers, consultants & contractors will benefit through new cutting-edge geotechnical monitoring services and, for the first time, near-real-time volumetric subsurface monitoring information.Key Deliverables & Outputs:- New software to fully automate PRIME data processing and information delivery - including a web-based decision support dashboard.- Demonstration of the complete PRIME system at existing rail and waterways pilot sites, and new highways, power transmission and flood defence sites - establishing TRL 7 (demonstration in an operational environment).- A commercialisation strategy agreed with project partners to ensure technology translation to the stakeholder community.Duration: 18 monthsCost: £183,000 (at 80% FEC)
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Towards a geophysical system for the remote autonomous monitoring of the near surface
建立用于近地表远程自主监测的地球物理系统
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [Chambers JE]
通讯作者: Chambers JE
Resistivity imaging of river embankments: 3D effects due to varying water levels in tidal rivers
河堤电阻率成像:潮汐河水位变化造成的 3D 效应
DOI: 10.1002/nsg.12234
发表时间: 2022
期刊: Near Surface Geophysics
影响因子: 1.6
作者: [Ball J]
通讯作者: Ball J
DOI: 10.1190/tle41110768.1
发表时间: 2022
期刊: The Leading Edge
影响因子: --
作者: [Chambers J]
通讯作者: Chambers J
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [Chambers JE]
通讯作者: Chambers JE
10
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