Bridge Structural Health–Monitoring System Using Statistical Control Chart Analysis

Abstract

Technological advancements in sensing, computing, and networking have facilitated the application of long-term structural health-monitoring (SHM) and made it a more widely accepted tool to improve bridge management. A fiber-optic strain-based SHM system developed in cooperation with the Iowa Department of Transportation is described; the system continuously monitors bridge performance under ambient traffic loads to detect damage. Although this SHM system has broad potential application to numerous types of structural deterioration or damage, the system is presented here by using a case study associated with fatigue cracking in the web gap region. The described SHM system autonomously collects, reduces, and analyzes strain data and determines the damage occurrence in a near-real-time fashion. In this system, statistical control chart analysis is applied over the strategically defined damage indicator to determine the damage mathematically. Data preprocessing strategies were also studied to limit the impact of major non-structural factors causing strain variations. The effectiveness of the system was demonstrated with field-collected predamage data and synthetic postdamage data. Experimental research is being conducted to validate the system at the field-testing level.

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