AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data

人工智能辅助不确定数据的概率结构健康监测

• 批准号: DP210103631
• 负责人: Prof Jun Li
• 金额: $ 25万
• 依托单位: Curtin University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP210103631
• 关键词: AI; Assisted; Probabilistic; Structural; Health

This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.

该项目旨在开发一种先进的人工智能（AI）辅助的土木工程结构概率结构健康监测方法。所开发的方法应用新颖的深度学习技术以及从不确定和复杂的环境中测量的大量数据，以进行可靠的结构状态监测和性能预测。该项目预计将在数据挖掘和解释方面做出重大改变。该项目的预期成果包括采用新颖的人工智能辅助方法来进行具有敏感特征的概率结构状况监测和未来结构性能预测。这将为基础设施资产所有者带来显着的好处，降低维护成本。