1 April 2016 Uncertainty analysis of practical structural health monitoring systems currently employed for tall buildings consisting of small number of sensors
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Abstract
Because of social background, such as repeated large earthquakes and cheating in design and construction, structural health monitoring (SHM) systems are getting strong attention. The SHM systems are in a practical phase. An SHM system consisting of small number of sensors has been introduced to 6 tall buildings in Shinjuku area. Including them, there are 2 major issues in the SHM systems consisting of small number of sensors. First, optimal system number of sensors and the location are not well-defined. In the practice, system placement is determined based on rough prediction and experience. Second, there are some uncertainties in estimation results by the SHM systems. Thus, the purpose of this research is to provide useful information for increasing reliability of SHM system and to improve estimation results based on uncertainty analysis of the SHM systems. The important damage index used here is the inter-story drift angle. The uncertainty considered here are number of sensors, earthquake motion characteristics, noise in data, error between numerical model and real building, nonlinearity of parameter. Then I have analyzed influence of each factor to estimation accuracy. The analysis conducted here will help to decide sensor system design considering valance of cost and accuracy. Because of constraint on the number of sensors, estimation results by the SHM system has tendency to provide smaller values. To overcome this problem, a compensation algorithm was discussed and presented. The usefulness of this compensation method was demonstrated for 40 story S and RC building models with nonlinear response.
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Kenta Hirai, Kenta Hirai, Akira Mita, Akira Mita, "Uncertainty analysis of practical structural health monitoring systems currently employed for tall buildings consisting of small number of sensors", Proc. SPIE 9805, Health Monitoring of Structural and Biological Systems 2016, 98050C (1 April 2016); doi: 10.1117/12.2218823; https://doi.org/10.1117/12.2218823
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