Sparse representation-based underground hidden crack filler identification method

Abstract

The invention discloses a sparse representation-based underground hidden crack filler identification method. In combination with the feature extraction advantages of empirical mode decomposition (EMD) and wavelet decomposition, firstly, the EMD on the echo signals of different underground crack fillers is conducted to obtain an optimal empirical mode component. Secondly, the original echo signals are subjected to wavelet decomposition to obtain an optimal wavelet decomposition coefficient. Finally, the optimal empirical mode component and the optimal wavelet decomposition coefficient are subjected to correlation analysis, and then the optimal wavelet decomposition coefficient largest in correlation with the optimal empirical mode is adopted as a base of a novel over-complete dictionary. After the over-complete dictionary is obtained, a to-be-identified signal is processed based on the same method described as above. In this way, the optimal feature component of the signal can be obtained. At last, the over-complete dictionary and the to-be-identified optimal component are substituted into the compressed-sensing reconstructing algorithm, so that the signal is reconstructed and identified. The method has the advantages of smaller sampled data volume and higher precision.

Description

technical field [0001] The invention belongs to the field of ultra-wideband ground-penetrating radar weak and small target detection, and in particular relates to a method for identifying underground hidden crack fillers based on sparse representation. Background technique [0002] The advantages of UWB GPR, such as strong anti-interference and high resolution, have important development and application prospects in the crack detection of roads and bridges. The detection of constants and geometric structures is a very difficult problem, which is the focus and difficulty of research at home and abroad. Aiming at hidden cracking hazards in roads and bridges, a large number of detection studies on asphalt pavement cracks by conventional GPR equipment show that ground penetrating radar can detect the position of the crack surface, but the crack filler plays an important role. If the coal around the story is filled If the materials have nearly the same dielectric constant, crack...

AI Technical Summary

Problems solved by technology

Aiming at hidden cracking hazards in roads and bridges, a large number of detection studies on asphalt pavement cracks by conventional GPR equipment show that ground penetrating radar can detect the position of the crack surface, but the crack filler plays an important role. If the coal around the story is filled have nearly the same dielectric constant, crack detection becomes difficult

Coupled with the high-resolution requirements of the bottom-penetrating radar, the amount of collected data needs to increase sharply, which brings difficulties to data processing and real-time display. The problem of identifying underground hidden crack fillings has not yet been effectively solved.

Images