附录 Recent applications of fiber optic sensors to health monitoringin civil engineeringHong-Nan Li a, Dong-Sheng Li a, Gang-Bing Song a,bA State Key Laboratory of Coastal and Offshore Engineering, Department of Civil and Hydraulic Engineering, Dalian University of Technology,Gan jing zi district, Ling gong Road 2, Dalian 116024, China Department of Mechanical Engineering, University of Houston, Houston, TX 77204-4006, USA Received 10 January 2003; received in revised form 11 May 2004; accepted 25 May 2004AbstractAbstract This paper presents an overview of current research and development in the field of structural health monitoring with civil engineering applications. Specifically, this paper reviews fiber optical sensor health monitoring in various key civil structures,including buildings, piles, bridges, pipelines, tunnels, and dams. Three commonly used fiber optic sensors (FOSs) are briefly described. Finally, existing problems and promising research efforts in packaging and implementing FOSs in civil structural health monitoring are discussed. 2004 elsevier Ltd. All rights reserved. Keywords: Structural health monitoring Fiber optic sensor Civil health1. IntroductionStructural health monitoring has attracted much attention in both research and development in recent years. This reflects continuous deterioration conditions of important civil infrastructures, especially long-span bridges. Among them, many were built in the 1950s with a 40- to- 50-year designed life span. The collapses and failures of these deficient structures cause increasing concern about structural integrity, durability and reliability, i.e. the health of a structure throughout theWorld. Currently, there are no foot proof measures for structural safety. A structure is tested for deteriorations and damages only after signs that result from fault accumulations are severe and obvious enough. Whenthe necessity of such tests becomes obvious, damages have already exacerbated the systems reliability in many cases and some structures are even on the verge of collapse. Though routine visual inspection is mandatory for important structures in some countries, for instance, bridges in the US, its effectiveness in finding all the possible defects is questionable. A recent survey by Moore et al. 1 of the US Federal Highway Administration revealed that at most 68% of the conditionratings were correct and in-depth inspections could not find interior deficiencies considering the fact that visual examination by inspectors barely exists. Structural health monitoring (SHM) refers to the use of in-situ, continuous or regular (routine) measurement and analyses of key structural and environmental parameters under operating conditions, for the purpose of warning impending abnormal states or accidents at anearly stage to avoid casualties as well as giving maintenance and rehabilitation advice. This tentatively proposed definition of SHM complements that given by housner 2. This definition emphasizes the essence of the advance alert ability of SHM. In general, a typical SHM system includes three major components: a sensor system, a data processing system (including data acquisition, transmission and storage), and a health evaluation system (including diagnostic algorithms and information management). The sensors utilized in SHM are required to monitor not only the structural status,for instance stress,displacement,acceleration etc,but also influential environmental parameters, such as wind speed, temperature and the quality of its foundation. Since a large number of sensors will be involved in a health monitoring system, the acquisition, transmission and storage ofa large quantity of data for such continuous monitoring is a challenging task. For instance, raw data are acquired at a rate of63.46 MB per hour for the TsingMa and Kap Shui Mun Bridges and 55.87 MB per hour for TingKau Bridge 3. Therefore, many wireless 4,5, GPS 6 or GIS 7 based data acquisition,transmission methods and data archival and management architectures 8 were proposed to deal with this problem. Though it is very important to embed sensors and collect data successfully for a healthmonitoring application, the final step is to interpret correctly the data from various types of sensors to reach critical decisions regarding the load capacity, system reliability, i.e. the health status of the structure 9.At this crucial step, prognostic and diagnostic algorithms based on modal analysis, pattern recognition and time series analysis are among the most effective methods to detect the presence, location, magnitude,and extent of structural faults 10. Moreover, the information analyzed should be user friendly to improve operation and maintenance management decisions.Another crucial function of SHM is the ability to alert ongoing dangers or future accidents in advance. Though it is not a simple task to realize full