Structure Health Monitoring Field Data Analysis on a Bridge


Structural Health Monitoring (SHM) has been adopted as a technique to monitor the structure performance to detect damage in bridges. Fatigue analysis is an important consideration for evaluating the health of the bridges. To estimate the remaining fatigue life more accurately, a refined evaluation load procedure is desirable. In this paper, we propose a data processing program (DPP) and a dynamic analysis program (DAG) into SHM to understand the performance of the bridges and establish fatigue life of the girders and the decks. DPP is implemented in Lab View with 6 functions: Average, Temperature Shift Elimination, FFT, Filters, Data Extraction, and Data File Splitter functions. The DAG program uses the harmonic method to analyze the effect of girders due to trucks moving across a bridge. This allows utilization of the output of DAG for input in the fatigue analysis to estimate the fatigue life. The validity of this system has been successfully demonstrated in the field monitoring of the Lindquist Bridge in Canada. However, it should be noted that complex environmental factors make damage detection of bridges a very challenging proposition.

  • Abstract
  • Introduction
  • Proposed System and Methodology
  • Implementation
  • Conclusion
  • Acknowledgement
  • References

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