KEYWORDS: Data fusion, Sensors, Neural networks, Wavelets, Structural health monitoring, Bridges, Computing systems, Data acquisition, Analytical research, Signal processing
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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.