In the context of rapid social and economic development, the transportation industry is under increasing pressure, and the requirements of vehicles on roads are increasing. People are paying more and more attention to the quality of asphalt pavement. However, due to the threat of excessive diseases, the pavement is prone to water damage and cracks. Therefore, it is particularly important to strengthen the quality control of asphalt pavement construction and disease prevention. Based on this, this article conducts an in-depth study on asphalt pavement disease and construction quality control under the background of big data. Based on the big data mining technology, this paper realizes the research on the relationship between pavement disease problems and influencing factors such as air temperature, surface porosity and traffic load, summarizes and analyzes several problems in the construction process, and proposes common disease prevention measures. Research shows that to improve construction quality management, it is necessary to establish a construction information database based on scientific statistical methods, monitor key indicators in the construction process in real time, and control and manage the entire construction process. Once problems are found, effective measures must be taken Solve it in time to ensure that the construction can be carried out smoothly, thereby effectively improving the level of pavement construction.
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