An ultra-thin asphalt intelligent production management method and system

Abstract

The present application relates to the field of intelligent production management and control of road engineering, in particular to an intelligent production management method and system based on ultra-thin asphalt, comprising: separating the real-time data of the production line into a core process field and a background interference field. Through the process knowledge graph, discrete data is constructed into a process state network, and periodic disturbance vectors of weather and equipment vibration are extracted. The two are antagonistically fused to form a comprehensive state representation, driving the digital mirror image to deduce the future quality control point prediction trajectory cluster. Analyze the fluctuation extreme value and frequency, compare the process tolerance to identify risks, trace the abnormal factors, and generate control strategies for aggregate supply, asphalt heating, mixing timing, and paving speed. The present application can fully reflect the process correlation, accurately quantify external disturbances, predict quality fluctuations in advance, and improve the accuracy of production control.

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