Structural health monitoring using smart sensors

Abstract

Industrialized nations have a huge investment in the pervasive civil infrastructure on which our lives rely. To properly manage this infrastructure, its condition or serviceability should be reliably assessed. For condition or serviceability assessment, Structural Health Monitoring (SHM) has been considered to provide information on the current state of structures by measuring structural vibration responses and other physical phenomena and conditions. Civil infrastructure is typically large-scale, exhibiting a wide variety of complex behavior; estimation of a structure's state is a challenging task. While SHM has been and still is intensively researched, further efforts are required to provide efficient and effective management of civil infrastructure. Smart sensors, with their on-board computational and communication capabilities, offer new opportunities for SHM. Without the need for power or communication cables, installation cost can be brought down drastically. Smart sensors will help to make monitoring of structures with a dense array of sensors economically practical. Densely installed smart sensors are expected to be rich information sources for SHM. Efforts toward realization of SHM systems using smart sensors, however, have not resulted in full-fledged applications. All efforts to date have encountered difficulties originating from limited resources on smart sensors (e.g., small memory size, small communication throughput, limited speed of the CPU, etc.). To realize an SHM system employing smart sensors, this system needs to be designed considering both the characteristics of the smart sensor and the structures to be monitored. This research addresses issues in smart sensor usages in SHM applications and realizes, for the first time, a scalable and extensible SHM system using smart sensors. The architecture of the proposed SHM is first presented. The Intel Imote2 equipped with an accelerometer sensor board is chosen as the smart sensor platform to demonstrate the efficacy of this architecture. Middleware services such as model-based data aggregation, reliable communication, and synchronized sensing are developed. SHM Algorithms identified as promising for the usage on smart sensor systems are extended to improve practicability and implemented on Imote2s. Careful attention has been paid to integrating these software components so that the system possesses identified desirable features. The damage detection capability and autonomous operation of the developed system are then experimentally verified. The SHM system consisting of ten Imote2s are installed on a scale-model truss. The SHM system monitors the truss in a distributed manner to localize simulated damage. In summary, this report proposes and realizes a scalable and autonomous SHM system using smart sensors. The system is experimentally verified to be effective for damage detection. The autonomous nature of the system is also demonstrated. Successful completion of this research paves the way toward full-scale SHM systems employing a dense array of smart sensors.