Advanced SearchSearch Tips
Development of Statistical/Probabilistic-Based Adaptive Thresholding Algorithm for Monitoring the Safety of the Structure
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Development of Statistical/Probabilistic-Based Adaptive Thresholding Algorithm for Monitoring the Safety of the Structure
Kim, Tae-Heon; Park, Ki-Tae;
  PDF(new window)
Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.
Structural health monitoring;Abnormal behavior;Vibration response;Adaptive threshold;Long-term monitoring;
 Cited by
Doebling, S. W., Farar, C. R., Prime, M. B., and Shevitz, D. W. (1998), A Review of Damage Identification Method that Examine Changes in Dynamic Properties, Shock and Vibration Digest, 30, 95-105.

Fisher, R. A., and Tippett, L. H. C. (1928), Limiting Forms of the Frequency Distributions of the Largest or Smallest Member of a Sample, Proc. Cambridge Philos. Soc. 24, 180-190. crossref(new window)

Huh, Y. C., and Kim, J. K. (2010) A Review of State of the Arts on Structural Health Monitorin g System Applied to Bridge and Building Structures, Magazine of Korean Society of Steel Construction, KSSC. Oct. 2001, 42-49(In Korean, with English abstract).

Jo, B. W., Lee, Y. S., Kim, H., and Lee, D. W. (2013), A Study on Development of the Intelligent Bridge Maintenance System using RFID, Journal of the Korean Society of Civil Engineers, 33(5), 2107-2124(In Korean, with English abstract). crossref(new window)

Kim, E. J., Cho, S. J., and Sim, S. H. (2015), A Recent Research Summary on Smart Sensors for Structural Health Monitoring, Journal of the Korea Institute for Structural Maintenance and Inspection, 19(3), 10-21(In Korean, with English abstract).

Kim, S. Y., Shin, Y. S., and Kim, G. H. (2014), Case Study on the Maintenance of a Construction Monitoring using USN-bsed Data Acquisition, The Scientific World Journal, 2014, 1-11(In Korean, with English abstract).

Lee, J. J., Park, Y. S., Yun, C. B., Koo, K. Y., and Yi, J. H. (2008), An Overview of Information Processing Techniques for Structural Health Monitoring of Bridges, Journal of Computational Structural Engineering Institute of Korea, COSEIK. 21(6). 615-632(In Korean, with English abstract).

Lee, S. C., Kim, G. S., Ju, M. K., Oh, H. H., and Park, D. H. (2010) Unified Monitoring System for Cable Supported Bridges in Korea, Journal of the Korea Institute for Structural Maintenance Inspection, Korea Institute for Structural Maintenance Inspection, 14(4), 13-22 (In Korean, with English abstract).

Sohn, H., Jung, H. J., Kong, J. S., Lee, J. J., and Sim, S. H. (2014), ICT Based Bridge Health Diagnosis and Integrated Maintenance Techniques, Magazine of the Korea institute for structural maintenance and inspection, 18(1), 1-4(In Korean, with English abstract).