Engineering Mechanics ›› 2009, Vol. 26 ›› Issue (增刊Ⅱ): 184-212.

• 基本方法 • Previous Articles     Next Articles

STRUCTURAL HEALTH MONITORING—INTELLIGENT INFORMATION PROCESSING AND APLLICATION

JIANG Shao-fei   

  1. (College of Civil Engineering, Fuzhou University, Fuzhou, Fujian 350108, China)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-12-25 Published:2009-12-25

Abstract: A number of large-scale complex structures have been built promoted by the development of economy, science and technology. It is an interesting issue how to monitor and manage these large structures so that the alarm will be warned before various accidents occur, thus the disaster loss can be decreased to the minimum. Numerous large long-term structural health monitoring systems have been developed and installed in China. However, another problem arise gradually how to effectively deal with the huge and abundant measured information from a structural health monitoring system, thus to asses structural condition states. In view of this, intelligent information processing, which is a process of transforming the incomplete, imprecise, inconsistent and uncertain information into complete, precise, consistent and certain information, provides an approach and technique assurance to solve the above difficulties. This paper startes from the structural health monitoring and its primary issues, and then presentes a survey and overview of the intelligent information and its application in structural health monitoring and damage diagnosis, including modern signal processing, neural network, fuzzy theory, data/ information fusion, fractal theory, rough set and evolutionary computation. Further research in the future are discussed finally. This study shows that intelligent information processing technique is one of the efficient processing tools and techniques in structural health monitoring and it also represents the effort direction in the future.

Key words: structural health monitoring, intelligent information processing, state-of-the-art, damage identification, identification accuracy

CLC Number: 

  • TP274
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