Investigation of compressive sampling for structural vibration data

In structural health monitoring (SHM) of civil structures, data compression is often needed for saving the cost of data transfer and storage because of the large volumes of sensor data generated from the monitoring system. The traditional framework for data compression is to first sample the full signal, then to compress it. Recently, a new data compression method named compressive sampling (CS) has been presented, that can acquire the data directly in compressed form by using special sensors. In this paper, the potential of CS for data compression of vibration data is investigated using simulation of the CS sensor algorithm. The acceleration data collected from the SHM system of Shandong Binzhou Yellow River Highway Bridge and China National Aquatics Center are used to analyse the data compression ability of CS. For comparison, the wavelet transform based and Huffman coding methods are also employed to compress the data. The results show that CS is useful for compression of vibration data in SHM of civil structures and that CS works better for narrowband signals such as the Shandong Binzhou Yellow River Highway Bridge vibration signal than wideband signals such as the vibration signal from the National Aquatics Center. Finally, a design of analog-to-digital converter (ADC) based on CS technique (CSADC) is proposed in this paper and a simulation with analog signal is carried out to illustrate the ability of CSADC for acquiring data directly with compressed form.