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AI-Analyst: Next Generation Advanced Pattern Recognition for Operations & Maintenance Supporting Delivery of a Low Carbon Future

AI-Analyst: Next Generation Advanced Pattern Recognition for Operations & Maintenance Supporting Delivery of a Low Carbon Future
AI-Analyst:下一代高级操作模式识别
批准号:
89639
负责人:
金额:
$41.27万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

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中文摘要
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英文摘要
Considered by many to be the holy grail of predictive maintenance, transfer learning (TL) is the ability to identify failure symptoms (ISO-13379) from one asset and apply them automatically to another. Applied across the thousands of connected plant items in the Industrial Internet of Things (IIoT), it could unleash the sector's potential adding $14.2tn to the global economy by 2030 \[Accenture\].Breakthroughs in deep learning (DL) solving Big-Data problems, such as accurate image recognition, might provide the impression that DL would enable asset failure predictions in much the same way. However asset failure data is scarce, every asset has unique data signatures, and therefore IIoT is not Big-Data \[Uniper, 2017\].This is an industrial research programme building upon a successful novel proof-of-concept technology. The AI-Analyst provides automatic modelling, early-fault detection, and diagnosis using TL, practical for O&M requirements; delivering a genuinely unique offering which can be readily commercialised and exported globally to all IIoT connected assets
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