Development of a Wireless Bridge Monitoring System for Condition Assessment Using Hybrid Techniques

The introduction and development of wireless sensor network technology has resulted in rapid growth within the field of structural health monitoring (SHM), as the dramatic cable costs associated with instrumentation of large civil structures is potentially alleviated. Traditionally, condition assessment of bridge structures is accomplished through the use of either vibration measurements or strain sensing. One approach is through quantifying dynamic characteristics and mode shapes developed through the use of relatively dense arrays of accelerometers. Another widely utilized method of condition assessment is bridge load rating, which is enabled through the use of strain sensors. The Wireless Sensor Solution (WSS) developed specifically for diagnostic bridge monitoring provides a hybrid system that interfaces with both accelerometers and strain sensors to facilitate vibration-based bridge evaluation as well as load rating and static analysis on a universal platform. This paper presents the development and testing of a wireless bridge monitoring system designed within the Laboratory for Intelligent Infrastructure and Transportation Technologies (LIITT) at Clarkson University. The system interfaces with low-cost MEMS accelerometers using custom signal conditioning for amplification and filtering tailored to the spectrum of typical bridge vibrations, specifically from ambient excitation. Additionally, a signal conditioning and high resolution ADC interface is provided for strain gauge sensors. To permit compensation for the influence of temperature, thermistor-based temperature sensing is also enabled. In addition to the hardware description, this paper presents features of the software applications and host interface developed for flexible, userfriendly in-network control of and acquisition from the sensor nodes. The architecture of the software radio protocol is also discussed along with results of field deployments including relatively large-scale networks and throughput rates sufficient for bridge monitoring.