PI: Shamim Pakzad
University: Lehigh University

Bridge structures experience significant vibrations and repeated stress cycles during their life cycles. These conditions are the bases for fatigue analysis to identify fatigue cracking, which can be used to accurately establish the remaining fatigue life of the structures (i.e. the number of stress cycles before the fatigue failure). The rain-flow counting algorithm is widely used in the analysis of fatigue data in order to reduce a spectrum of varying stress into a set of simple stress reversals, and assess the fatigue life of a structure subjected to complex loading. This procedure requires a full-field strain assessment of the structures over a typical loading period. Traditional inspection methods collect strain measurements by using strain gauges for fatigue life assessment. Large scale deployment of wired strain gauges, however, poses a fundamental limitation: they are expensive and laboriously impractical as more spatial information is desired. Addressing these limitations beg for an innovative sensing strategy where information can be integrated from inexpensive data sources.

Acceleration data can be collected relatively inexpensively by the means of mobile sensing, which is increasingly an area of interest in many fields of engineering. Mobile sensing eliminates the spatially-restrictive nature of fixed sensor networks; the spatial frequency of a mobile sensor network is a direct function of the speed and its sensors' sampling frequencies, as well as the number of mobile devices that can simultaneously collect measurements from the same structure. As a type of crowd-sensing, individual members of the public take a much more active role in data collection, thus providing more up-to-date information on a structure’s health.