An early warning system and method for asphalt pavement rainy season minor repairs

Abstract

The invention discloses a bituminous pavement rainy season minor repair early warning system and a bituminous pavement rainy season minor repair early warning method. The method includes the following steps that: bituminous pavement diseases are recognized and are put into statistics, so that a pavement disease database can be formed; big data collection is carried out, so that a rainy season pothole repair rate prediction model is established; a rainy season minor repair (pothole repair) early-warning system is established; and a bituminous pavement rainy season minor repair index is issued through a mobile terminal before the rainy season comes, so that rainy season minor repair work of a highway management unit can be guided. According to the bituminous pavement rainy season minor repair early warning method adopting big data analysis, data collection and analysis are carried out for formation reasons of bituminous pavement potholes in the rainy season; the rainy season pothole repair rate prediction model according with engineering practical experiences is established; the bituminous pavement rainy season minor repair index is issued through the rainy season minor repair early warning system before the rainy season comes; and therefore, prediction and early warning can be carried out for the rainy season minor repair work of the highway management unit, and a platform basis is provided for pre-event management.

Description

Technical field [0001] The invention relates to the engineering application of road detection data, in particular to an early warning system and method for minor repairs of asphalt pavement in rainy season. Background technique [0002] Automated rapid detection of road conditions has been widely used in the maintenance and management inspection of national trunk roads ("National Inspection") and the maintenance management work of highway managers in various provinces. The detection data is mainly used for road network-level performance evaluation. It provides a technical reference for road managers to make scientific decisions on maintenance. However, in general, there are still the following shortcomings in the application of road condition automation and rapid detection data: data collection and analysis costs are high, but data mining is not deep enough, and the main form of data results is more extensive road condition evaluation data; The application target is single, whic...

AI Technical Summary

Problems solved by technology

But in general, there are still the following shortcomings in the application of automatic and rapid road condition detection data: data collection and analysis costs are relatively high, but the data mining is not deep enough, and the data results are mainly in the form of relatively extensive road condition evaluation data; The application object is single, which is helpful to road managers at the road network level, but has little effect on front-line road maintenance units

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