No abstract

Structural control technologies have attracted great interest from the earthquake engineering community over the last few decades as an effective method of reducing undesired structural responses. Traditional structural control systems employ large quantities of cables to connect structural sensors, actuators, and controllers into one integrated system. To reduce the high-costs associated with labor-intensive installations, wireless communication can serve as an alternative real-time communication link between the nodes of a control system. A prototype wireless structural sensing and control system has been physically implemented and its performance verified in large-scale shake table tests. This paper introduces the design of this prototype system and investigates the feasibility of employing decentralized and partially decentralized control strategies to mitigate the challenge of communication latencies associated with wireless sensor networks. Closed-loop feedback control algorithms are embedded within the wireless sensor prototypes allowing them to serve as controllers in the control system. To validate the embedment of control algorithms, a 3-story half-scale steel structure is employed with magnetorheological (MR) dampers installed on each floor. Both numerical simulation and experimental results show that decentralized control solutions can be very effective in attaining the optimal performance of the wireless control system.

Monitoring and economical design of alternative energy generators such as wind turbines is becoming increasingly critical; however acquisition of the dynamic output data can be a time-consuming and costly process. In recent years, low-cost wireless sensors have emerged as an enabling technology for structural monitoring applications. In this study, wireless sensor networks are installed in three operational turbines in order to demonstrate their efficacy in this unique operational environment. The objectives of the first installation are to verify that vibrational (acceleration) data can be collected and transmitted within a turbine tower and that it is comparable to data collected using a traditional tethered system. In the second instrumentation, the wireless network includes strain gauges at the base of the structure. Also, data is collected regarding the performance of the wireless communication channels within the tower. In both turbines, collected wireless sensor data is used for off-line, output-only modal analysis of the ambiently (wind) excited turbine towers. The final installation is on a turbine with embedded braking capabilities within the nacelle to generate an "impulse-like" load at the top of the tower. This ability to apply such a load improves the modal analysis results obtained in cases where ambient excitation fails to be sufficiently broad-band or white. The improved loading allows for computation of true mode shapes, a necessary precursor to many conditional monitoring techniques.

Wireless sensor networks have rapidly matured in recent years to offer data acquisition capabilities on par with those of traditional tethered data acquisition systems. Entire structural monitoring systems assembled from wireless sensors have proven to be low cost, easy to install, and accurate. However, the functionality of wireless sensors can be further extended to include actuation capabilities. Wireless sensors capable of actuating a structure could serve as building blocks of future generations of structural control systems. In this study, a wireless sensor prototype capable of data acquisition, computational analysis and actuation is proposed for use in a real‐time structural control system. The performance of a wireless control system is illustrated using a full‐scale structure controlled by a semi‐active magnetorheological (MR) damper and a network of wireless sensors. One wireless sensor designated as a controller automates the task of collecting state data, calculating control forces, and issuing commands to the MR damper, all in real time. Additional wireless sensors are installed to measure the acceleration and velocity response of each system degree of freedom. Base motion is applied to the structure to simulate seismic excitations while the wireless control system mitigates inter‐storey drift response of the structure. An optimal linear quadratic regulation solution is formulated for embedment within the computational cores of the wireless sensors. Copyright © 2007 John Wiley & Sons, Ltd.