Model Construction and Physical Parameter Identification from Spectral Data

光谱数据的模型构建和物理参数识别

• 批准号: 9978786
• 负责人: Yitshak Ram
• 金额: $ 11.79万
• 依托单位: Louisiana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-01-01 至 2003-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9978786&HistoricalAwards=false
• 关键词: Model; Construction; Physical; Parameter; Identification

Yitshak M. Ram, Louisiana State University,Proposal Number: 9978786Model Construction and Physical Parameter Identification from Spectral DataProposal Abstract. The inverse problem of reconstructing a model based on spectral data is investigated, and methods for constructing low order models for vibrating systems are developed. The physical parameters of the systems are determined by the derived model. The main difficulty in addressing this problem is that vibrating structures are distributed parameter systems, whereas the descriptive analytical models are finite dimensional. The spectrum of a continuous system is inconsistent with that of the associated finite dimensional model. In order to overcome the difficulty associated with the inconsistency of the spectral data, the distributed parameter system with continuous variables is approximated by a continuous system with a finite number of physical parameters. As a result a new non-linear eigenvalue problem, with transcendental matrix elements, is introduced. The inverse problem is approached by iterative gradient and Newton's methods, and from a wave propagation standpoint. The results are validated by laboratory experiments where the density and rigidity functions of non-uniform vibrating rods are determined by using data from modal tests. The fundamental problem of identifying the physical parameters of a system from spectral data has theoretical importance and practical applications in many areas of science and engineering, e.g. dynamic system control, and sonar and radar detection. The new transcendental inverse problem introduced has the potential of bridging the gap between the infinite spectrum of distributed parameter systems and the finite spectrum of their discrete representative models. Characterization of the properties of this eigenvalue problem is thus of great theoretical and practical importance.

伊察克湾Ram，路易斯安那州立大学，提案编号：9978786从光谱数据的模型构建和物理参数识别提案摘要。研究了基于谱数据的模型重构反问题，提出了构造振动系统低阶模型的方法。系统的物理参数由导出的模型确定。解决这个问题的主要困难是，振动结构是分布参数系统，而描述性的分析模型是有限维的。连续系统的谱与相应的有限维模型的谱是不一致的。为了克服与光谱数据的不一致性相关联的困难，具有连续变量的分布参数系统被近似为具有有限数量的物理参数的连续系统。因此，一个新的非线性特征值问题，超越矩阵元素，介绍。逆问题的迭代梯度和牛顿的方法，并从波传播的观点。通过实验室试验，利用模态试验数据确定了非均匀振动杆的密度函数和刚度函数，验证了计算结果的正确性。从光谱数据识别系统的物理参数的基本问题在许多科学和工程领域具有重要的理论意义和实际应用，例如动态系统控制，声纳和雷达检测。新的超越反问题的引入，有可能弥合之间的差距差距的无限谱的分布参数系统和有限谱的离散代表模型。因此，刻画这一特征值问题的性质具有重要的理论和实际意义。