A Method of Data Recovery Based on Compressive Sensing in Wireless Structural Health Monitoring

Sai Ji, Yajie Sun and Jian Shen

Mathematical Problems in Engineering, 2014, vol. 2014, 1-9

Abstract:

In practical structural health monitoring (SHM) process based on wireless sensor network (WSN), data loss often occurs during the data transmission between sensor nodes and the base station, which will affect the structural data analysis and subsequent decision making. In this paper, a method of recovering lost data in WSN based on compressive sensing (CS) is proposed. Compared with the existing methods, it is a simple and stable data recovery method and can obtain lower recovery data error for one-dimensional SHM’s data loss. First, response signal is measured onto the measurement data vector through inner products with random vectors. Note that is the linear projection of and is permitted to be lost in part during the transmission. Next, when the base station receives the incomplete data, the response signal can be reconstructed from the data vector using the CS method. Finally, the test of active structural damage identification on LF-21M aviation antirust aluminum plate is proposed. The response signal gathered from the aluminum plate is used to verify the data recovery ability of the proposed method.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:546478

DOI: 10.1155/2014/546478

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