Abstract

Structural Health Monitoring (SHM), which is one of the renowned applications of Micro-Electro-Mechanical Systems (MEMS) is an emerging field in engineering that offers potential for continuous and periodic assessment of the safety against natural hazards and vibrations and improved system reliability, improved longevity, and enhanced system performance. Based on the knowledge of the condition of the structure, certain preventive measures can be taken to prolong the service life of the structure and prevent catastrophic failure. Damage detection strategies can ultimately reduce life-cycle cost. Using traditionally wired sensors to implement such a SHM system with a dense array of sensors is quite challenging because of the difficulties in deploying and maintaining the associated wiring. Recent development of smart sensors has created the possibility of dense array of sensors in SHM. Dense arrays of low-cost smart wireless sensor networks (WSNs) have the potential to improve the quality of the SHM dramatically using their on-board computational and wireless communication capabilities. These WSNs provide rich information which SHM algorithms can utilize to detect, locate and assess structural damage caused by severe loading events and by progressive environmental deterioration as well as economical realization of the SHM system. Information from densely instrumented structures is expected to result in deeper insight into the physical state of the structural system. This study focuses on investigation of the use of MEMS and their potential applications in terms of mass, size, power and cost, where sensors capable of sensing the structural health conditions (e. g, vibration, pressure, temperature, etc.) are studied and also the development activities and recent research in the field of smart wireless sensors and application of smart sensing, monitoring and damage detection techniques for infrastructures are analyzed. Keywords—Micro-Electro-Mechanical Systems, damage detection techniques, smart sensors, structural health monitoring, wireless sensors, wireless sensor networks.

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