Recovery of lost data for wireless sensor network used in structural health monitoring

In a wireless sensor network, data loss often occurs during the data transmission between wireless sensor nodes and the base station, which decreases the communication reliability in wireless sensor network applications. Errors caused by data loss inevitably affect the data analysis of the structure and subsequent decision making. This paper proposed an approach to recover lost data in a wireless sensor network based on the compressive sampling (CS) technique. The main idea in this approach is to project the transmitted data from x onto y, where y is the linear projection of x on a random matrix. The data vector y is permitted to lose part of the original data x in wireless transmissions between the sensor nodes and the base station. After the base station receives the imperfect data, the original data vector x can be reconstructed based on the data y using the CS method. The acceleration data collected from the vibration test of Shandong Harbin Sifangtai Bridge by wireless sensors is used to analyze the data loss recovery ability of the proposed method.