Invisible disease detection method of pavement structure layer

Abstract

The invention relates to an invisible disease detection method of a pavement structure layer, which comprises the steps of detecting a pavement with a road ground penetrating radar and an excitation pavement acoustic generator, obtaining a modulus of resilience of the pavement structure layer according to detected data, analyzing a strength characteristic of the pavement structure layer of a detected road section according to the modulus of resilience, and exactly detecting positions and sizes of invisible diseases such as cavities and looseness in the pavement. The method can quickly, accurately and continuously detect the invisible diseases such as the looseness, the cavities, interlayer discontinuity and poor strength in the structure layer of the pavement of forms such as highways of various grades, urban roads and airfield runways, provides complete data for evaluating the detected pavement, provides bases for implementing road prevention and maintenance, provides data support for maintenance decisions within the service life of the road, reduces interference with traffic, is nondestructive, reduces secondary damages to the pavement, saves cost, reduces energy consumption, increases social benefits, and can evaluate structural conditions of the pavement more completely and reasonably.

Description

technical field [0001] The invention relates to a method for detecting pavement structural layers, in particular to a method for detecting invisible diseases of pavement structural layers. Background technique [0002] At present, whether it is the traditional manual maintenance inspection or the modern multi-functional road pavement inspection vehicle with advanced technology and complete technology, the statistics are mainly based on the surface diseases that appear on the road surface. It is difficult to find hidden dangers in the subgrade and pavement; the traditional detection method represented by drilling cores randomly selects points and drills samples according to specifications, analyzes and processes, and obtains road quality parameters. Due to the random selection of measuring points in these conventional methods, the randomness of the detection results is large, and the detection depth is limited, and the drilling core generally adopts wet drilling, so it is dif...

AI Technical Summary

Problems solved by technology

For the invisible diseases mentioned above, due to the lack of effective detection means, the distribution and severity of the hidden dangers of the surface layer, base layer or roadbed in the pavement structure layer cannot be discovered and ascertained in advance, so it is difficult to monitor and evaluate the road Quality status, unable to formulate targeted treatment measures, can only "cure the head for...

Images