Dynamic Coplanar Capacitance Imaging Optimization of Hidden Damages in Asphalt Mixtures
Coplanar array capacitance imaging technology acquires the permittivity distribution of tested objects by detecting variations in capacitance,providing a reliable,non-destructive method for detecting and identifying hidden damages in asphalt pavements.In this paper,a set of sensitivity field optimization strategies are proposed for obtaining a high imaging accuracy,approximate real,and uniform-sensitivity field distribution.This optimized sensitivity field is used for reconstructing the distribution images of hidden damages in asphalt mixtures.Firstly,the multi-layer sensitivity fields are fused using the wavelet transform to obtain the fused sensitivity field.Secondly,according to the measured dynamic coplanar capacitance distributions,the threshold optimization method is used to extract the feature sensitivity fields of different scanning steps,and then the real sensitive fields are obtained.Finally,based on non-local mean filtering,the sharp areas of the real sensitivity fields are smoothed to obtain homogenized sensitive fields.The hidden damages in asphalt mixtures is imaged based on the fusion,feature,and homogenized sensitivity fields.The fused sensitivity field distribution with clear contours is obtained by wavelet transform;the real sensitivity field,which can reflect the distribution of hidden damages is obtained based on the feature sensitivity field extracted by capacitance contribution;and the homogenized sensitivity field with uniform local distribution is obtained based on non-homogeneous mean filtering.The results show that the stability of the edges of the damages in the reconstructed images based on the fused sensitivity field is significantly improved;the artifacts around the damages in the reconstructed images based on the feature sensitivity field are basically eliminated;and the internal distribution of damages in the reconstructed images based on the homogenized sensitivity field is more uniform.From high to low,the degree of imaging quality improvement based on different sensitive field optimization methods isas follows feature sensitivity field＞homogenized sensitivity field＞fused sensitivity field.
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