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An Application of Data Fusion Technology in Structural Health Monitoring and Damage Identification

机译:数据融合技术在结构健康监测与损伤识别中的应用

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摘要

With the development of modernized construction industry, constructions are more and more complicated enormous, and need more sensors to obtain the structural message, so traditional health and diagnosis technology can not take on the task of damage identification and multi-sensor data fusion technology is beginning to be used in this field. Firstly, this paper simply reviews the necessity of the appearance and development of the structural health monitoring and damage identification and multi-sensor data fusion. Secondly, the framework of structural health monitoring and damage identification system is introduced. Thirdly, the three levels of multi-sensor data fusion, which are pixels-level, feature-level and decision-level fusion, are analyzed in details, and the fusion methods and their applications of each data fusion level are also discussed. Lastly, we discuss a new two-level data fusion and two-level neural network architecture model for structural damage identification. A data fusion method of neural network combined with wavelet analysis is researched in this paper.
机译:随着现代化建筑行业的发展,建筑越来越复杂,而且需要更多的传感器来获取结构信息,因此传统的健康和诊断技术无法承担损伤识别的任务,而多传感器数据融合技术正在开始用于此领域。首先,本文简单回顾了结构健康监测,损伤识别和多传感器数据融合的出现和发展的必要性。其次,介绍了结构健康监测与损伤识别系统的框架。第三,详细分析了多传感器数据融合的三个层次,分别是像素级,特征级和决策级融合,并讨论了每种数据融合级的融合方法及其应用。最后,我们讨论了用于结构损伤识别的新的两级数据融合和两级神经网络架构模型。研究了一种结合小波分析的神经网络数据融合方法。

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