A Wavelet-Based Data Compression Algorithm for Bridge Vibration

To solve the existing problems of the traditional bridge vibration (BV) data compression methods, on the basis of deep analysis for the wavelet transform (WT), a method of wavelet transform combined with LZW coding is proposed in this paper. In accordance with the characteristics of the bridge vibration data and the properties of wavelet transform-based multi-resolution analysis, Donoho threshold compression algorithm is adopted to quantify the high-frequency decomposed components. Then the bridge vibration data are compressed with the improved LZW coding. To justify the proposed method, several groups of actual sampling data are simulated. The results indicate that the data compression based on the combination of LZW and WT can effectively improve the compression ratio. The energy recovery proportion is higher than 0.9999, and the compression ratio is better than 10.8.