基于深度学习的地铁隧道施工工程质量自动评价系统

Automatic Evaluation System of Subway Tunnel Construction Quality Based on Deep Learning

为提高施工工程质量评价精度,提出基于深度学习的地铁隧道施工工程质量自动评价系统研究。利用STM32F407核心处理器来与相关数据采集设备连接,并进行数据处理。对采集到的数据进行特征量统计并取值,利用模糊综合法建立工程质量评价模糊矩阵,基于深度学习对工程质量评价模糊矩阵进行训练,完成系统设计。实验表明系统在实现自动评价的基础上,评价误差系数在规定范围内,评价速度更快,实用性更强。

In order to improve the accuracy of construction quality evaluation, an automatic evaluation system of subway tunnel construction quality based on deep learning is proposed. STM32F407 core processor is used to connect with the relevant data acquisition equipment and process the data. The collected data are counted and taken value, the fuzzy comprehensive method is used to establish the fuzzy matrix of engineering quality evaluation, and the fuzzy matrix of engineering quality evaluation is trained based on deep learning to complete the design of the system. The experimental show that the evaluation error coefficient of the design system is within the specified range on the basis of automatic evaluation, evaluation speed is faster, more practical.