Subgrade compaction automatic stratification and automatic layer thickness detection method based on paver trajectory

Abstract

The invention provides a subgrade compaction automatic stratification and automatic layer thickness detection method based on paver trajectory, comprising the following steps: (1) vehicle modeling; (2), invalid data filtering; (3), surface elevation calculation and linear interpolation of discontinuous data; (4), trajectory calculation of the paver and stratification accord to the paver trajectory; (5): data correction and the layer thickness calculation according to the correction result. The invention is based on the Beidou satellite positioning, the calculation accuracy fully meets the market demand, improves the automatic program of the operation, and provides important data guarantee for the pressure implementation quality monitoring management.

Description

technical field [0001] The invention relates to the field of roadbed compaction automatic layering algorithms based on paver tracks, in particular to a roadbed compaction automatic layering and layer thickness automatic detection method based on paver tracks. Background technique [0002] In the construction of large-scale infrastructure projects such as airports, railways, and highways, it is necessary to fill in layers and compact them in layers to achieve sufficient compactness. The compaction thickness has a significant effect on the compaction effect. During subgrade construction, automatic layering and layer thickness automatic calculation of construction data of construction machinery and equipment such as road rollers and paver are the key technologies in digital construction. Layering and layer thickness data are important basic data for later construction quality monitoring. . [0003] At present, the existing digital construction products on the market still hav...

AI Technical Summary

Problems solved by technology

[0003] At present, the existing digital construction products on the market still have disadvantages such as complex configuration, inconvenient use, low accuracy rate of results, and many manual interventions for the automatic layering of subgrade compaction and automatic detection of layer thickness.

And the layering and layer thickness detection methods in the current digital construction products are not perfect, and have not substantially reduced the user's work intensity, improved work efficiency, and increased the degree of automation and intelligence

Images