A novel physical-digital approach for the assessing a large critical asset

一种用于评估大型关键资产的新颖的物理数字方法

• 批准号: LP210200765
• 负责人: Prof Wing Chiu
• 金额: $ 26.88万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-04-28 至 2026-04-27
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP210200765
• 关键词: novel; physical; digital; approach; assessing

This project aims to deliver an artificial intelligence-enabled decision-making tool to maintain and manage the floating covers of vast lagoons that treat raw sewage. The cover harvests the biogas released from the anaerobic digestion of sewage for electric power generation that exceeds the plant’s requirement. The approach involves an innovative thermographic technique and exploits transfer learning to adapt neural networks trained on lab-scale and synthetic data to field implementation. The outcome is a machine learning framework to optimise biogas harvesting and renewable energy generation, and to avoid structural failure, that is capable of continuous improvement to take into account improved data and/or modelling capabilities.

该项目旨在提供一种人工智能决策工具，以维护和管理处理原始污水的大型泻湖的浮动覆盖物。这个盖子收集污水厌氧消化释放的沼气，用于发电，超过了工厂的要求。该方法涉及一种创新的热成像技术，并利用迁移学习来调整在实验室规模和合成数据上训练的神经网络，以适应现场实施。其结果是一个机器学习框架，以优化沼气收集和可再生能源发电，并避免结构故障，该框架能够持续改进，以考虑改进的数据和/或建模能力。