Compressive sensing-based wireless sensors and sensor networks for structural health monitoring

Wireless sensor technology-based structural health monitoring (SHM) has been widely investigated recently. This paper presents the new developments and applications of compressive sensing (CS) for wireless sensors and sensor networks-based SHM in our research group. Frist, the group sprse optimization based compressive sensing for data sampling and recovery of wireless sensor network is introduced. Then, the lost data recovery for wireless sensors are presented. CS provides a data loss recovery technique, which can be embedded into smart wireless sensors and effectively increases wireless communication reliability without re-transmitting the data; the promise of this approach is to reduce communication and thus power savings. To embed into the smart sensor, a method called random demodulator is employed to provide memory and power efficient construction of the random sampling matrix. The program is embedded into the Imote2 smart sensor platform and tested in a series of sensing and communication experiments and field tests. Lastly, the fast moving wireless sensoing technique is presened. For the fast moving wireless data transmission, the Doppler effects are the main reason causing data packet loss. A field test on a cable-stayed bridge is performed to valid the ability of the CS-based robust wireless data transmission approach in obtaining high-quality data for the fast-moving wireless sensing technique.