Novel Sensing Networks for Intelligent Monitoring (Newton)

用于智能监控的新型传感网络（牛顿）

• 批准号: EP/J012343/1
• 负责人: Gui Yun Tian
• 金额: $ 149.75万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FJ012343%2F1
• 关键词: Novel; Sensing; Networks; Intelligent; Monitoring

This proposal seeks funding for a four-year research programme to develop an autonomous, intelligent system to obtain a revolutionary solution for condition/structural health intelligent monitoring, with specific applications in condition monitoring of railways and in-service Non-Destructive Evaluation (NDE) for nuclear applications. This project addresses important goals: low cost and low power consumption sensor networks, sensor exploration, software architectures, autonomous data fusion and intelligent system management, spectrally efficient and reliable communications with novel approaches of radio frequency identification (RFID) based passive sensing networks, non-linear feature extraction and model based fusion, compressed sensing, cloud-based computing and decision making. The research will extend our knowledge in several complementary areas: low cost sensor technologies, wireless sensor network (WSN) for NDE and structural health monitoring (SHM), feature extraction and fusion, robust communication, and software architectures. The work will be undertaken jointly by cross-disciplinary research teams from Newcastle, Sheffield and York Universities, in collaboration with industrial strategic partners.

该提案旨在为一项为期四年的研究计划提供资金，以开发一种自主的智能系统，为状态/结构健康智能监测提供革命性的解决方案，并在铁路状态监测和核应用的在职无损评估（NDE）中得到具体应用。该项目涉及以下重要目标：低成本和低功耗传感器网络，传感器探索，软件架构，自主数据融合和智能系统管理，基于射频识别（RFID）的无源传感网络，非线性特征提取和基于模型的融合，压缩传感，基于云的计算和决策的新方法的频谱效率和可靠的通信。这项研究将扩展我们在几个互补领域的知识：低成本传感器技术，无线传感器网络（WSN）的无损检测和结构健康监测（SHM），特征提取和融合，强大的通信和软件架构。这项工作将由来自纽卡斯尔、谢菲尔德和约克大学的跨学科研究团队与工业战略合作伙伴共同开展。

项目成果

Deep Boltzmann machine for corrosion classification using eddy current pulsed thermography

• DOI: 10.1016/j.ijleo.2020.164828
• 发表时间: 2020-10
• 期刊: Optik
• 影响因子: 3.1
• 作者: Yuming Chen;F. Sohel;S. A. A. Shah-S.-A.-A.-Shah-2112405071;S. Ding

Intelligent early structural health prognosis with nonlinear system identification for RFID signal analysis

• DOI: 10.1016/j.comcom.2020.04.026
• 发表时间: 2020-05-01
• 期刊: COMPUTER COMMUNICATIONS
• 影响因子: 6
• 作者: Chen, Hanxin;Chen, Yongting;Yang, Liu
• 通讯作者: Yang, Liu

Decoupling the Influence of Permeability and Conductivity in Pulsed Eddy-Current Measurements

• DOI: 10.1109/tmag.2012.2225634
• 发表时间: 2013-03-01
• 期刊: IEEE TRANSACTIONS ON MAGNETICS
• 影响因子: 2.1
• 作者: Adewale, Ibukun Dapo;Tian, Gui Yun
• 通讯作者: Tian, Gui Yun

Investigation of Skewness Feature for Evaluation of Defects Using Eddy Current Pulsed Thermography

• DOI: 10.1109/jsen.2019.2936221
• 发表时间: 2019-12-15
• 期刊: IEEE SENSORS JOURNAL
• 影响因子: 4.3
• 作者: Chen, Xiaotian;Tian, Guiyun;Wu, Jianbo
• 通讯作者: Wu, Jianbo

Model-based method with nonlinear ultrasonic system identification for mechanical structural health assessment

• DOI: 10.1002/ett.3955
• 发表时间: 2020-03-31
• 期刊: TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
• 影响因子: 3.6
• 作者: Chen, Hanxin;Huang, Lang;Huang, Jinmin
• 通讯作者: Huang, Jinmin