Efficient infrastructure damage detection and localization using wireless sensor networks, with cluster generation for monitoring damage progression

Abstract

Structural health monitoring (SHM) involves the development of strategies to assess the condition of instrumented engineering structures. One of the most critical applications of SHM systems is civil infrastructure. For this application, it is particularly important that SHM systems be inexpensive and easy to deploy, since the maintenance of infrastructure is often inadequately funded. Wireless sensor networks (WSN) can be very useful toward this end. We present an efficient WSN-based SHM algorithm for detecting, localizing, and monitoring the progression of damage in infrastructure applications. The algorithm utilizes a novel vibration-based pattern matching technique that is very well suited for low-power WSN nodes. During a training phase, a body of reference patterns is formed from vibrations observed at sensor nodes distributed throughout the structure. During the operational phase, observed patterns are compared to the reference patterns to determine if a match exists. Through the use of an innovative distributed algorithm, a time complexity of O(logN) is achieved for the matching process. If a match does not exist, potential damage is indicated and the reference pattern closest to the observed pattern is determined using Euclidean distance. The difference between the two patterns indicates the sensor nodes at which potential damage exists. Clusters are then formed around these sensor nodes in order to monitor the progression of local damage. Simulations are performed in MATLAB for a typical bridge deployment in order to determine the degree of overlapping that occurs as clusters are generated in response to potential damage. The simulations indicate that overlapping increases gracefully as the number of nodes experiencing damage increases.