Compressive sampling and data fusion-based structural damage monitoring in wireless sensor network

Abstract

The Lamb wave phased array structural health monitoring method is effective in structural damage monitoring. In this method, the damage scattering signal can be obtained by comparing the damage structural response signal with health structural response signal, and it can be used for structural damage identification. But in the structural health monitoring based on wireless sensor networks, this method has some inevitable defects in data transmission. A large number of sampling data of damage response signal will cause huge wireless communication burden. To solve this problem, we proposed a phased array image method based on compressive sampling and data fusion for wireless structural damage monitoring. First, compressive sampling signal by compressive sampling method was collected. Then, data fusion for multi-sensor’s damage response signal was implemented in phased array. Finally, the Lamb wave phased array damage identification method based on compressive sampling and data fusion was proposed. Experimental results on carbon composite structure show that the proposed method can largely save network bandwidth and energy. This method can also realize the damage identification accurately on the aviation aluminum plate and keep the detection error within 0.82 mm.