Collaborative Research: Health Monitoring and System Identification of Complex Mechanical Systems Using Fractional-Order Calculus Modeling

合作研究:使用分数阶微积分建模复杂机械系统的健康监测和系统识别

基本信息

  • 批准号:
    1825837
  • 负责人:
  • 金额:
    $ 27.18万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-08-15 至 2022-07-31
  • 项目状态:
    已结题

项目摘要

Inspection and maintenance are significant cost drivers to manage and preserve the quality of our nation's transportation systems and infrastructure. Current strategies are based on preventive approaches that do not consider the actual real-time status of a specific structural component. In these approaches, the systems are subject to routine inspections and replacement of components that are scheduled a priori based on a combination of empirical data and numerical predictions of the estimated life. Such approaches are sub-optimal because they may lead to replacement of fully-functional components, on the one hand, and may miss rapidly deteriorating conditions between scheduled inspections, on the other. This research will develop new methods to address both shortcomings by investigating new modeling and monitoring techniques particularly suited and applicable to modern, complex systems. To enable this condition-based monitoring approach, better theoretical and numerical models are needed to simulate the dynamic behavior of complex mechanical systems as well as to produce metrics capable of tracking their status in real-time. This award supports fundamental research to develop mathematical and computational models based on fractional calculus. The methods resulting from this research will be highly useful in application that use imaging and remote sensing in structural, geological, and biological media. The educational part of this project will feature, among its different components, the development of a new course to introduce engineering students to fractional calculus and its applications to modeling of engineering systems.This research will involve a systematic study to determine how fractional-order differential equations will enhance the state-of-the-art in system identification and monitoring. Fractional-order models are a new and useful tool for modeling of complex engineering systems, however they are not yet common in engineering. Their application to structural health monitoring will provide a substantially new approach for damage detection and diagnostics, it will introduce the system order as a new parameter for system assessment, and it will provide highly mathematically structured and concise descriptions of the dynamics of complex systems. More specifically, this work will (1) determine the effect of structural damage on the fractional order of the host system and develop methodologies to account for its impact on the underlying governing equations; (2) use fractional approaches to achieve efficient order reduction, sub-structuring, and inverse problem solutions; (3) develop fractional models for system identification based on purely experimental data; and (4) develop testbeds for experimental validation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
检查和维护是管理和保持我国交通系统和基础设施质量的重要成本驱动因素。当前的策略基于预防性方法,不考虑特定结构组件的实际实时状态。在这些方法中,系统要接受例行检查和组件更换,这些组件是根据经验数据和估计寿命的数值预测的组合预先安排的。这种方法不是最理想的,因为它们一方面可能导致更换功能齐全的组件,另一方面可能会错过定期检查之间迅速恶化的情况。这项研究将通过研究特别适合和适用于现代复杂系统的新建模和监控技术来开发新方法来解决这两个缺点。 为了实现这种基于状态的监测方法,需要更好的理论和数值模型来模拟复杂机械系统的动态行为,并生成能够实时跟踪其状态的指标。该奖项支持开发基于分数阶微积分的数学和计算模型的基础研究。这项研究产生的方法对于在结构、地质和生物介质中使用成像和遥感的应用非常有用。该项目的教育部分将在其不同组成部分中开发一门新课程,向工程学生介绍分数阶微积分及其在工程系统建模中的应用。这项研究将涉及系统研究,以确定分数阶微分如何方程将增强系统识别和监控的最先进水平。分数阶模型是复杂工程系统建模的一种新的、有用的工具,但它们在工程中尚未常见。它们在结构健康监测中的应用将为损伤检测和诊断提供一种全新的方法,它将引入系统阶数作为系统评估的新参数,并将提供复杂系统动力学的高度数学结构化和简洁的描述。 更具体地说,这项工作将(1)确定结构损伤对主系统分数阶的影响,并开发方法来解释其对基础控制方程的影响; (2)使用分数法实现高效的降阶、子结构和逆问题解决; (3) 基于纯实验数据开发用于系统辨识的分数模型; (4) 开发用于实验验证的测试平台。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(21)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A generalized fractional-order elastodynamic theory for non-local attenuating media
非局部衰减介质的广义分数阶弹性动力学理论
  • DOI:
    10.1098/rspa.2020.0200
  • 发表时间:
    2020-06-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sansit Patnaik;F. Semperlotti
  • 通讯作者:
    F. Semperlotti
Variable-order particle dynamics: formulation and application to the simulation of edge dislocations
变阶粒子动力学:刃位错模拟的公式和应用
Variable-order fracture mechanics and its application to dynamic fracture
变阶断裂力学及其在动态断裂中的应用
  • DOI:
    10.1038/s41524-021-00492-x
  • 发表时间:
    2021-02
  • 期刊:
  • 影响因子:
    9.7
  • 作者:
    Patnaik, Sansit;Semperlotti, Fabio
  • 通讯作者:
    Semperlotti, Fabio
A Ritz-based finite element method for a fractional-order boundary value problem of nonlocal elasticity
非局部弹性分数阶边值问题的基于Ritz的有限元方法
Geometrically nonlinear analysis of nonlocal plates using fractional calculus
使用分数阶微积分对非局部板块进行几何非线性分析
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Fabio Semperlotti其他文献

Acoustic scattering simulations via physics-informed neural network
通过物理信息神经网络进行声散射模拟
  • DOI:
    10.1117/12.3010166
  • 发表时间:
    2024-05-09
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Nair;Timothy F. Walsh;Greg Pickrell;Fabio Semperlotti
  • 通讯作者:
    Fabio Semperlotti
On the geometric phase and its role in the design of elastic topological materials
几何相及其在弹性拓扑材料设计中的作用
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Mohit Kumar;Fabio Semperlotti
  • 通讯作者:
    Fabio Semperlotti
Physics and geometry informed neural operator network with application to acoustic scattering
物理学和几何学神经算子网络在声学散射中的应用
  • DOI:
    10.48550/arxiv.2406.03407
  • 发表时间:
    2024-06-02
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Nair;Timothy F. Walsh;Greg Pickrell;Fabio Semperlotti
  • 通讯作者:
    Fabio Semperlotti
Nonlinear damping characteristics of shape-memory-alloy hybrid composite plates: The synergistic role of patterning and pre-straining SMA layers
形状记忆合金混合复合材料板的非线性阻尼特性:图案化和预应变 SMA 层的协同作用
Time transient Simulations via Finite Element Network Analysis: Theoretical Formulation and Numerical Validation
通过有限元网络分析进行时间瞬态模拟:理论公式和数值验证
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Jokar;S. Nair;Fabio Semperlotti
  • 通讯作者:
    Fabio Semperlotti

Fabio Semperlotti的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Fabio Semperlotti', 18)}}的其他基金

Nonlocal Elastic Metamaterials: Leveraging Intentional Nonlocality to Design Programmable Structures
非局域弹性超材料:利用有意的非局域性来设计可编程结构
  • 批准号:
    2330957
  • 财政年份:
    2024
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant
Acoustic Field Transport in Periodic and Disordered Metamaterials: a Fractional-order Continuum Approach.
周期性和无序超材料中的声场传输:分数阶连续体方法。
  • 批准号:
    1761423
  • 财政年份:
    2018
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant
CAREER: Multi-Physics Transient Holography: A Non-Intrusive Imaging Approach for the Identification of Structural Damage in Mechanical Systems
职业:多物理场瞬态全息术:一种用于识别机械系统结构损伤的非侵入式成像方法
  • 批准号:
    1453330
  • 财政年份:
    2015
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant
CAREER: Multi-Physics Transient Holography: A Non-Intrusive Imaging Approach for the Identification of Structural Damage in Mechanical Systems
职业:多物理场瞬态全息术:一种用于识别机械系统结构损伤的非侵入式成像方法
  • 批准号:
    1621909
  • 财政年份:
    2015
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant
Collaborative Research: Frequency Selective Structures for High Sensitivity/High Resolution Damage Identification via Impediographic Tomography
合作研究:通过阻抗成像技术进行高灵敏度/高分辨率损伤识别的频率选择结构
  • 批准号:
    1232423
  • 财政年份:
    2012
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant

相似国自然基金

寒地城市学区建成环境对学龄儿童心理健康的影响机制与规划干预路径研究
  • 批准号:
    52378051
  • 批准年份:
    2023
  • 资助金额:
    52 万元
  • 项目类别:
    面上项目
面向社交媒体的伪健康信息检测研究
  • 批准号:
    62306213
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
稻鱼共生系统中协调高产种稻与健康养鱼的氮素运筹策略研究
  • 批准号:
    32301374
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
数智化与主动健康联合驱动的社区老年肌少症健康教育模式的构建与实证研究
  • 批准号:
    72304080
  • 批准年份:
    2023
  • 资助金额:
    30 万元
  • 项目类别:
    青年科学基金项目
外卖平台个性化推荐对用户膳食结构与健康的影响及对策研究
  • 批准号:
    72373115
  • 批准年份:
    2023
  • 资助金额:
    40 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: Fusion of Siloed Data for Multistage Manufacturing Systems: Integrative Product Quality and Machine Health Management
协作研究:多级制造系统的孤立数据融合:集成产品质量和机器健康管理
  • 批准号:
    2323084
  • 财政年份:
    2024
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant
Collaborative Research: Behavioral Science and the Making of the Right-Reasoning Public Health Citizenry
合作研究:行为科学与正确推理的公共卫生公民的培养
  • 批准号:
    2341512
  • 财政年份:
    2024
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Continuing Grant
Collaborative Research: Fusion of Siloed Data for Multistage Manufacturing Systems: Integrative Product Quality and Machine Health Management
协作研究:多级制造系统的孤立数据融合:集成产品质量和机器健康管理
  • 批准号:
    2323082
  • 财政年份:
    2024
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant
Collaborative Research: Behavioral Science and the Making of the Right-Reasoning Public Health Citizenry
合作研究:行为科学与正确推理的公共卫生公民的培养
  • 批准号:
    2341513
  • 财政年份:
    2024
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Continuing Grant
Collaborative Research: State Health, Institutions, and Politics Survey (SHIPS)
合作研究:国家卫生、机构和政治调查 (SHIPS)
  • 批准号:
    2422182
  • 财政年份:
    2024
  • 资助金额:
    $ 27.18万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了