Analysing GNSS network data for deformation monitoring in multi-scale, multi-temporal civil engineering applications

分析 GNSS 网络数据以进行多尺度、多时态土木工程应用中的变形监测

• 批准号: 2763649
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2763649
• 关键词: Analysing; GNSS; network; data; deformation

Deformation monitoring is a key element to develop strategies of resilience and sustainability in civil engineering infrastructure and measures against geohazards. A network of GNSS stations provides a means to monitor the motions of engineering structures and enables both localised (e.g. single points) and larger scale (e.g. national) structural movements to be detected, over time scales of seconds to years. Most of the strategies in GNSS network data analysis are based on (i) constant GNSS station velocities, (ii) modelling of GNSS data periodic signals and (iii) least squares methods to adjust measurement errors. Such strategies are deterministic approaches, where specific conditions/constraints are applied (e.g. constant velocity) to model the behaviour of the GNSS stations. Furthermore, each GNSS station is analysed individually, without examining the behaviour of other GNSS stations, both nearby and further afield, at which similar behaviour may be occurring. This research project will use to-be-developed techniques, following less deterministic approaches (e.g. artificial intelligence) in the analysis of the GNSS network data and adopting spatial analysis methods which treat the GNSS data as part of a network. It is hypothesised that these approaches could enable the extraction of more information regarding the behaviour of the GNSS data, either related locally to a GNSS-specific station or related to a region of the GNSS network. The aim of this project is to develop a methodology where the GNSS network data will be analysed in both the time and space domains and identify the behaviour of the GNSS data of the stations, as individual GNSS stations and as part of the network. This methodology will be applied to deformation monitoring scenarios from a broad range of engineering projects; (i) multi-scale projects, from small scale civil engineering structures (e.g. bridges) to larger scale including the field of geohazards (e.g. ground motion) and (ii) multi-temporal deformations, from short-term (e.g. bridge vibration) to long-term deformation (e.g. land subsidence).

变形监测是制定土木工程基础设施恢复力和可持续性战略以及防止地质灾害措施的关键要素。全球导航卫星系统台站网络提供了一种监测工程结构运动的手段，并能够在数秒至数年的时间尺度上检测局部（例如单点）和较大规模（例如全国）的结构运动。全球导航卫星系统网络数据分析中的大多数战略都是基于：全球导航卫星系统台站的恒定速度，全球导航卫星系统数据周期信号的建模，以及调整测量误差的最小二乘法。这种战略是确定性方法，其中应用特定条件/限制（例如恒定速度）来模拟全球导航卫星系统台站的行为。此外，对每个全球导航卫星系统台站进行单独分析，而不检查附近和更远的可能发生类似行为的其他全球导航卫星系统台站的行为。该研究项目将使用有待开发的技术，在分析全球导航卫星系统网络数据时采用确定性较低的方法（例如人工智能），并采用将全球导航卫星系统数据作为网络一部分处理的空间分析方法。据假设，这些方法能够提取更多关于全球导航卫星系统数据行为的信息，这些信息要么与全球导航卫星系统特定台站本地相关，要么与全球导航卫星系统网络区域相关。该项目的目的是制定一种方法，在该方法中，将在时域和空域分析全球导航卫星系统网络数据，并确定作为全球导航卫星系统各个台站和网络一部分的台站的全球导航卫星系统数据的行为。该方法将应用于各种工程项目的变形监测方案;（i）多尺度项目，从小尺度土木工程结构（如桥梁）到较大尺度，包括地质灾害（如地面运动）领域;（ii）多时间变形，从短期（如桥梁振动）到长期变形（如地面沉降）。