针对结构健康监测的实际需要,基于敏感性分析法和有效独立驱动点残差法来优化结构传感器配置,应用模糊模式识别法进行结构损伤状态评估,设计开发了智能结构健康监测系统软件ISHMS(intelligentstructural health monitoring system)。采...针对结构健康监测的实际需要,基于敏感性分析法和有效独立驱动点残差法来优化结构传感器配置,应用模糊模式识别法进行结构损伤状态评估,设计开发了智能结构健康监测系统软件ISHMS(intelligentstructural health monitoring system)。采用VC++和Matlab混合编程及多线程编程技术,通过调用OpenGL三维图形函数库进行结构建模并绘制出结构三维图形。通过161杆高精度空间桁架可变损伤模型振动实验,验证了该ISHMS软件的有效性。展开更多
This paper presents a new method of damage condition assessment that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness that are statistically nondescribable. In this method, ...This paper presents a new method of damage condition assessment that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness that are statistically nondescribable. In this method, healthy observations are used to construct a fury set representing sound performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed by using the state similarity matrix. Thus, an optimal group fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fitzzy pattern recognition based on an approximate principle . This method can be embedded into the system of Structural Health Monitoring （SHM） to give advice about structural maintenance and life predictio comes from Reference [ 9 ] for damage pattern recognition is presented n. Finally, a case and discussed. The study, which compared result illustrates our method is more effective and general, so it is very practical in engineering.展开更多
文摘针对结构健康监测的实际需要,基于敏感性分析法和有效独立驱动点残差法来优化结构传感器配置,应用模糊模式识别法进行结构损伤状态评估,设计开发了智能结构健康监测系统软件ISHMS(intelligentstructural health monitoring system)。采用VC++和Matlab混合编程及多线程编程技术,通过调用OpenGL三维图形函数库进行结构建模并绘制出结构三维图形。通过161杆高精度空间桁架可变损伤模型振动实验,验证了该ISHMS软件的有效性。
基金This paper is supported by the National High Technology Research and Development Program ("863" Program) of China under Grant No.2006AA04Z437
文摘This paper presents a new method of damage condition assessment that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness that are statistically nondescribable. In this method, healthy observations are used to construct a fury set representing sound performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed by using the state similarity matrix. Thus, an optimal group fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fitzzy pattern recognition based on an approximate principle . This method can be embedded into the system of Structural Health Monitoring （SHM） to give advice about structural maintenance and life predictio comes from Reference [ 9 ] for damage pattern recognition is presented n. Finally, a case and discussed. The study, which compared result illustrates our method is more effective and general, so it is very practical in engineering.
