Analysis of Noise Reduction Effect of Drainage Asphalt Pavement Based on Transform Domain and Noise Estimation

Abstract

Drainage asphalt pavement originated in Europe, and has been popularized and applied all over the world because of its characteristics of improving driving safety and reducing traffic noise. However, it is found that the gaps of single-layer drainage pavement are easily blocked by dust and gravel, which leads to a sharp decline in its excellent performance. This paper mainly studies the noise reduction performance of drainage asphalt pavement. Based on the theoretical analysis of structural layer design of noise reduction and drainage asphalt pavement, this paper evaluates and compares the pavement noise performance of five asphalt pavement surface mixtures, such as dense gradation AC, SMA and open gradation OGFC, by using wavelet transform theory, discrete Curvelet transform and methods based on transform domain and noise estimation. The results show that the transform domain and noise estimation used in this paper improve the signal-to-noise ratio of the collected signals, and the processing results have high fidelity after denoising the noise of the drainage asphalt pavement. This method is a noise reduction technology with obvious technical advantages and broad application prospects for special noises with great random variation.