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Integration of Hybrid Inspection Data into Structural Health Monitoring

Integration of Hybrid Inspection Data into Structural Health Monitoring
将混合检测数据集成到结构健康监测中
批准号:
RGPIN-2017-04356
负责人:
Arjomandi, Kaveh
金额:
$1.6万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
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英文摘要
Infrastructure around the world deteriorates as a result of aging, operational conditions, environmental loads, and sudden extreme events such as earthquakes. In Canada the civil infrastructure in poor and very poor conditions has been estimated to have a replacement cost of $141 billion. My research program concentrates on reducing the overall cost of development, maintenance, operation, and replacement of infrastructure by improving the process of health and reliability assessment of existing structures, known as Structural Health Monitoring (SHM).***I will develop structural health monitoring techniques to a level of accuracy that enables them to be applied as tools supporting strategic, tactical and operational planning decisions for maintenance, repair, and replacement of large scale public and private assets. My initial focus is on bridges, but the intent is to develop methods that also apply to buildings, transmission towers, wind mills, and dam structures.***Most previous research in SHM considers a single method as the sole monitoring technique. My program focuses on developing a holistic approach to structural health monitoring through the integration of hybrid data from various monitoring methods. The core method in my program is Operational Modal Analysis (OMA), an output-only method that has shown significant success in the SHM of bridges, buildings, wind mills, and dams. My goal is to develop methodologies for the integration of OMA with complementary approaches such as static input-output methods in order to improve the accuracy and efficiency of the monitoring process. I will focus on theoretical developments of OMA, multi-model identification, damage identification, and reliability assessment of structures using SHM data. Numerical studies, laboratory experiments, and full-scale tests will be used to verify the results. ***My research program is expected to have significant impact on the fundamental research in structural health monitoring, operational modal analysis, and structural damage models. Additionally, my program is expected to contribute to the application development of SHM and in particular the OMA method, with a focus on large-scale monitoring systems. Activities described in this Discovery Grant application will help private and public entities that are responsible for safety and operation of civil engineering infrastructure to improve the efficiency and frequency of detailed structural assessments. This will assist them to optimize the operational procedures as well as the maintenance and replacement strategies.
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Integration of Hybrid Inspection Data into Structural Health Monitoring
  • 批准号:
    RGPIN-2017-04356
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2022
  • 负责人:
    Arjomandi, Kaveh
  • 依托单位:
Integration of Hybrid Inspection Data into Structural Health Monitoring
  • 批准号:
    RGPIN-2017-04356
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2021
  • 负责人:
    Arjomandi, Kaveh
  • 依托单位:
Hybrid bridge weight in motion (BWIM) and structural health monitoring (SHM) systems
  • 批准号:
    558332-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $1.6万
  • 财政年份:
    2021
  • 负责人:
    Arjomandi, Kaveh
  • 依托单位:
Integration of Hybrid Inspection Data into Structural Health Monitoring
  • 批准号:
    RGPIN-2017-04356
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.6万
  • 财政年份:
    2020
  • 负责人:
    Arjomandi, Kaveh
  • 依托单位:
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