Queen Mary-University of London Researcher Describes Recent Advances in Machine Learning (Machine Learning-Based Structural Health Monitoring Technique for Crac k Detection and Localisation Using Bluetooth Strain Gauge Sensor Network)

伦敦玛丽皇后大学的研究人员描述了机器学习的最新进展(基于机器学习的结构健康监测技术，用于使用蓝牙应变计传感器网络的Crac K检测和定位)

Robotics & Machine Learning Daily News2024，Issue(Dec.6) ：115-115.

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Queen Mary-University of London Researcher Describes Recent Advances in Machine Learning (Machine Learning-Based Structural Health Monitoring Technique for Crac k Detection and Localisation Using Bluetooth Strain Gauge Sensor Network)

伦敦玛丽皇后大学的研究人员描述了机器学习的最新进展(基于机器学习的结构健康监测技术，用于使用蓝牙应变计传感器网络的Crac K检测和定位)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布关于人工智能的新报告。根据新闻报道来自伦敦，Unit Ed Kingdom，由NewsRx记者报道，研究称，“在结构健康监测领域(SHM)，常规方法一般比较复杂，破坏性的，耗时的。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on ar tificial intelligence. According to news reportingoriginating from London, Unit ed Kingdom, by NewsRx correspondents, research stated, “Within thedomain of Str uctural Health Monitoring (SHM), conventional approaches generally are complicat ed,destructive, and time-consuming.”

Key words

Queen Mary-University of London/London/United Kingdom/Europe/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024

Robotics & Machine Learning Daily News

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