Supplemental Material for the Paper “ Deploying Wireless Sensor Networks with Fault-Tolerance for Structural Health Monitoring ” Md

Designing WSN systems for SHM is an interesting interdisciplinary topic, which is rarely combined by engineering and computer science (CS) communities deeply for their aspects. To date, most of the real SHM systems utilize wired sensor network systems to collect information about structures for SHM. While WSNs are gradually receiving attention from the engineering domains as an attractive tool, due to the WSN on-board processing, easy deployment, and relatively low capital and maintenance costs, SHM is becoming a potential application from the CS domain. During the past few years, both communities have started developing the analytical system to detect and quantify the structural health status under wireless sensor technologies [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16]. However, these approaches are generally proposed to support traditional global SHM, without much consideration to the WSN requirements and constraints. A state-of-the-art monitoring system has been deployed at the Golden Gate bridge (GGB) [10], which represents one of the first large-scale deployments of WSNs for SHM purposes. This system has a large latency, arising from the fact that the underlying SHM method (physical aspects, e.g., damage occurrence) was designed separately from the WSN (cyber aspects, e.g., communication). Distributed frameworks [7], [9], [8] are presented for damage detection, where the final decision is made at the BS. A cyber-physical system (CPS) approach has recently been suggested in [11], considering both the constraints of the underlying WSNs (the cyber components) and the SHM requirements (the physical components). In this approach, a distributed damage detection algorithm is suggested under a hierarchical WSN. Although it offers a trade-off between the computation and communication capacities, it does not reveal the details, such as connectivity or coverage, in the hierarchical architecture. A hierarchical cluster-based SHM (C-SHM for short) considers a fundamental problem in SHM: mode shape analysis in clusters [9]. In each cluster, the vibration characteristics are identified at high vibration frequencies and then are assembled together. However, a heuristic-based clustering approach is used, which may not fit a real SHM. Although the clustering in the C-SHM needs to meet extra requirements of modal analysis, the quality of SHM may be affected. This is because the modal analysis can be different at the same cluster at different times. Moreover, the system performance through the hierarchical architecture of C-SHM in terms of connectivity, communication, lifetime, etc., is not discussed. Although the approaches above are considered to be effective for monitoring, they suffer from at least two major limitations. • They require high detection latency during damage detection, and uninteresting data that are collected from a large number of sensors without a reasonable time frame. For example, GGB requires 9 hours to collect a single round of data from 64 sensors. Such systems are inadequate for identifying health status (timely or online) during an extreme event. Thus, the resulting systems may inherently suffer from high energy consumption and sensor faults/failures. • Allowing for the limitation of multi-hop transmission in WSNs, a huge amount of interesting data transmitted towards the BS may be lost. Thus, the reliability and quality of SHM is low. FTSHM attempts to mitigate the limitations of the existing algorithms and approaches to some extent.