DDDAS - SMRP: A Framework For the Dynamic Data-Driven Fault Diagnosis of Wind Turbine Systems
DDDAS - SMRP:风力涡轮机系统动态数据驱动故障诊断框架
基本信息
- 批准号:0540132
- 负责人:
- 金额:$ 18万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2006
- 资助国家:美国
- 起止时间:2006-06-01 至 2011-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
CMS-0540132, PI: Yu Ding, Texas A&M UniversityCMS-0540278, PI: Jiong Tang, University of ConnecticutAbstractThis collaborative research (0540132, PI: Yu Ding, Texas A&M University; and 0540278, PI: Jiong Tang, University of Connecticut) will provide a dynamic data-driven framework for wind turbine diagnosis. This new methodology is fundamentally different from the current practice whose performance is limited due to the non-dynamic and non-robust nature in the modeling approaches and in the data collection and processing strategies. This framework consists of two robust data pre-processing modules for highlighting fault features and removing sensor anomaly, three interrelated, multi-level models that describe different details of the system behaviors, and one dynamic strategy for the robust local interrogation that allows for measurements to be adaptively taken according to specific physical conditions and the associated risk level. It incorporates both historical data and on-line signals into the system modeling, and enables the ability to adaptively alter data collection procedures to best capture the critical system features. Collectively, these components lead to a robust and sensitive diagnosis system for wind turbines. This research is strengthened by a close collaboration with industry that will provide abundant historical sensor data and detailed system characterization, and also offer in-field implementation opportunities. The proposed research will have strategic importance on the utilization of wind energy that is currently the most viable clean energy alternative. Today, in the vast areas that have low wind speed, wind energy cannot compete with traditional energy sources as it has a higher cost, mainly owing to its high maintenance costs and low confidence in the diagnosis technology. This dynamic and data-driven fault diagnosis will play a key role in enabling a cost-effective generation of wind electricity. Progress in the fault diagnosis of blades and gearboxes will also benefit the power generation, automobile, aerospace, and engine industries. Meanwhile, the collaborative nature of this research will provide students with a multidisciplinary training and will bring industrial perspective to the universities. This project will have a long-term impact on education through the curriculum development and will promote the public awareness of clean energy concept through outreaches to high schools.
CMS-0540132,PI:Yu Ding,Texas A M University; CMS-0540278,PI:Jiong Tang,University of Connecticut摘要这项合作研究(0540132,PI:Yu Ding,Texas A M University; 0540278,PI:Jiong Tang,University of Connecticut)将为风力涡轮机诊断提供动态数据驱动框架。 这种新的方法是从根本上不同于目前的做法,其性能是有限的,由于非动态和非鲁棒性的建模方法和数据收集和处理策略。 该框架包括两个强大的数据预处理模块,突出故障特征和消除传感器异常,三个相互关联的,多层次的模型,描述不同的细节的系统行为,和一个动态策略的强大的本地询问,允许测量自适应地采取根据特定的物理条件和相关的风险水平。 它将历史数据和在线信号结合到系统建模中,并能够自适应地改变数据收集程序,以最好地捕捉关键系统功能。 总的来说,这些组件为风力涡轮机提供了强大而灵敏的诊断系统。 这项研究通过与工业界的密切合作得到加强,这将提供丰富的历史传感器数据和详细的系统表征,并提供现场实施机会。 拟议的研究将对风能的利用具有战略意义,风能是目前最可行的清洁能源替代品。 今天,在风速较低的广大地区,风能无法与传统能源竞争,因为它具有较高的成本,主要是由于其高维护成本和对诊断技术的信心较低。 这种动态和数据驱动的故障诊断将在实现具有成本效益的风力发电方面发挥关键作用。 叶片和齿轮箱故障诊断的进展也将有利于发电,汽车,航空航天和发动机行业。同时,这项研究的合作性质将为学生提供多学科的培训,并将为大学带来工业视角。 该项目将通过课程开发对教育产生长期影响,并将通过推广到高中来提高公众对清洁能源概念的认识。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yu Ding其他文献
Numerical Study of Sulfonamide Occurrence and Transport at the Near-Shore Area of Laizhou Bay
莱州湾近岸地区磺酰胺赋存与迁移的数值研究
- DOI:
10.3390/w11102065 - 发表时间:
2019-10 - 期刊:
- 影响因子:3.4
- 作者:
Liming Xing;Haifei Liu;Wenxian Guo;Yu Ding;Zhiming Ru;Gangqin Tu;Xuerong Wu - 通讯作者:
Xuerong Wu
State Space Modeling for Size Changes
尺寸变化的状态空间建模
- DOI:
10.1007/978-3-030-72822-9_7 - 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Chiwoo Park;Yu Ding - 通讯作者:
Yu Ding
Bioactive peptides and gut microbiota: Candidates for a novel strategy for reduction and control of neurodegenerative diseases
生物活性肽和肠道微生物群:减少和控制神经退行性疾病新策略的候选者
- DOI:
10.1016/j.tifs.2020.12.019 - 发表时间:
2021-02 - 期刊:
- 影响因子:15.3
- 作者:
Shujian Wu;Alaa El-Din Ahmed Bekhit;Qingping Wu;Mengfei Chen;Xiyu Liao;Juan Wang;Yu Ding - 通讯作者:
Yu Ding
LighterFace Model for Community Face Detection and Recognition
用于社区人脸检测和识别的 LighterFace 模型
- DOI:
10.3390/info15040215 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Yuntao Shi;Hongfei Zhang;Wei Guo;Meng Zhou;Shuqin Li;Jie Li;Yu Ding - 通讯作者:
Yu Ding
The Impact of High-speed Railways on Urban Development in the Great Pearl River Delta of China
高铁对中国大珠三角城市发展的影响
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Yu Ding;Lei Zhang - 通讯作者:
Lei Zhang
Yu Ding的其他文献
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{{ truncateString('Yu Ding', 18)}}的其他基金
BIGDATA: IA: Collaborative Research: From Bytes to Watts - A Data Science Solution to Improve Wind Energy Reliability and Operation
BIGDATA:IA:协作研究:从字节到瓦特 - 提高风能可靠性和运行的数据科学解决方案
- 批准号:
1741173 - 财政年份:2017
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
CPS/Synergy/Collaborative Research: Cybernizing Mechanical Structures through Integrated Sensor-Structure Fabrication
CPS/协同/协作研究:通过集成传感器结构制造实现机械结构的网络化
- 批准号:
1545038 - 财政年份:2016
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
GOALI/Collaborative Research: A System-Level Framework for Operation and Maintenance: Synergizing Near and Long Term Cares for Wind Turbines
GOALI/协作研究:运行和维护的系统级框架:协同风力涡轮机的近期和长期维护
- 批准号:
1300560 - 财政年份:2013
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
Collaborative Research: Multi-Accuracy Bayesian Models for Improving Property Prediction of Nanotube Buckypaper Composites
合作研究:用于改进纳米管巴基纸复合材料性能预测的多精度贝叶斯模型
- 批准号:
1000088 - 财政年份:2010
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
Collaborative Research: Efficient Probabilistic Approach Using Order Reduction and Hybrid Models -- A New Paradigm for Structural Dynamic Analysis
协作研究:使用降阶和混合模型的高效概率方法——结构动态分析的新范式
- 批准号:
0926803 - 财政年份:2009
- 资助金额:
$ 18万 - 项目类别:
Continuing Grant
Collaborative Research: Fault Tolerance Analysis and Design of Clustered Sensor Networks
协作研究:集群传感器网络容错分析与设计
- 批准号:
0727305 - 财政年份:2007
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
CAREER: Collaborative Information Processing of Distributed Sensor Networks for Manufacturing Quality Improvement
职业:分布式传感器网络的协作信息处理以提高制造质量
- 批准号:
0348150 - 财政年份:2004
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
SST: Robust Wireless Piezoelectric Sensor Network for Structural Health Monitoring
SST:用于结构健康监测的强大无线压电传感器网络
- 批准号:
0427878 - 财政年份:2004
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
Collaborative Research/GOALI: Analysis and Optimization Method for Distributed Sensor Systems in Electronics Assembly Processes Systems
协作研究/GOALI:电子装配过程系统中分布式传感器系统的分析和优化方法
- 批准号:
0217481 - 财政年份:2002
- 资助金额:
$ 18万 - 项目类别:
Standard Grant
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