Sensors: Statistical Algorithm Development for Distributed Sensor Networks with Application to Structural Health Monitoring and State Assessment

传感器：分布式传感器网络统计算法开发，应用于结构健康监测和状态评估

• 批准号: 0428585
• 负责人: John Sweetman
• 金额: $ 15.65万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0428585&HistoricalAwards=false
• 关键词: Sensors; Statistical; Algorithm; Development; Distributed

ABSTRACT0428585PI: John SweetmanTexas Engineering Experiment StationNew statistical and random vibration techniques are developed and applied to interpret measured data from distributed sensor networks. The new methods build statistical distributions of selected random variables developed from the data and dynamic numerical models of the structure. The overall goal is to develop methodologies to identify relatively minor structural damage or changes in structural state prior to initiation of a major structural failure. Application within the project is marine risers on offshore oil-production structures and to structural health monitoring of onshore structures; each of these applications makes use of extensive measured data. The offshore application addresses vortex induced vibrations of marine risers, a complex problem due to irregular variations in system mass caused by fluid-structure interaction. These vibrations are a dominant design consideration for marine risers in high current, deep-water areas. The onshore application offers an improved methodology for monitoring the structural condition of various civil structures. The work is being done jointly between two campuses of Texas A&M University (College Station and Galveston). The project and its results will enhance the graduate and undergraduate engineering curricula at both campuses. The project also directly increases interaction between the two campuses, which will lead to greater future collaboration. This project is supported under the Sensors Initiative NSF 04-522.

摘要0428585 PI：约翰Sweetman得克萨斯工程实验站新的统计和随机振动技术的开发和应用，以解释测量数据从分布式传感器网络。新的方法建立统计分布的选定的随机变量开发的数据和动态数值模型的结构。 总体目标是开发方法，以确定相对较小的结构损伤或结构状态的变化之前，开始一个重大的结构故障。该项目中的应用是海上石油生产结构的海洋监测和陆上结构的结构健康监测;这些应用中的每一个都使用了大量的测量数据。 海上应用解决了海洋涡激振动，这是一个复杂的问题，由于流体-结构相互作用引起的系统质量的不规则变化。这些振动是在高水流、深水区域中的海洋锚的主要设计考虑因素。 陆上应用为监测各种土木结构的结构状况提供了一种改进的方法。 这项工作是在德克萨斯A M大学的两个校区（学院站和加尔维斯顿）之间联合进行的。 该项目及其成果将加强两个校区的研究生和本科生工程课程。 该项目还直接增加了两个校区之间的互动，这将导致未来更大的合作。 该项目得到了传感器倡议NSF 04-522的支持。