Wavelet Denoising of TSD Deflection Slope Measurements for Improved Pavement Structural Evaluation

Abstract Continuous deflection devices (CDDs) can safely measure pavement deflection (or other related properties) while traveling at highway speed, which reduces traffic disruption. CDD measurements are contaminated with relatively high noise levels compared to stop‐and‐go devices such as the Falling Weight Deflectometer. In this article, we use wavelet transform denoising to remove the noise and estimate the true deflection slope measurements obtained from the Traffic Speed Deflectometer. Results show that failure to denoise deflection slope measurements can lead to calculated Effective Structural Number values that are highly variable (unstable). Attempting to filter these highly variable measurements can lead to erroneous results. We also use wavelet transform denoising to identify localized weak spots such as those that are caused by pavement reflection cracking. Identifying weak spots with wavelets is possible because wavelets are spatially adaptive to local features. In contrast, a linear filter is not capable of adapting to local features.