Research on Intelligent Compaction Technology of Subgrade Based on Regression Analysis

Hou, Ziyi and Dang, Xiao and Yuan, Yezhen and Tian, Bo and Li, Sili and Yao, Yongsheng (2021) Research on Intelligent Compaction Technology of Subgrade Based on Regression Analysis. Advances in Materials Science and Engineering, 2021. pp. 1-9. ISSN 1687-8434

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Abstract

A remote monitoring system with the intelligent compaction index CMV as the core is designed and developed to address the shortcomings of traditional subgrade compaction quality evaluation methods. Based on the actual project, the correlation between the CMV and conventional compaction indexes of compaction degree K and dynamic resilient modulus E is investigated by applying the one-dimensional linear regression equation for three types of subgrade fillers, clayey gravel, pulverized gravel, and soil-rock mixed fill, and the scheme of fitting CMV to the mean value of conventional indexes is adopted, which is compared with the scheme of fitting CMV to the single point of conventional indexes in the existing specification. The test results show that the correlation between the CMV and conventional indexes of clayey gravel and pulverized gravel is much stronger than that of soil-rock mixed subgrades, and the correlation coefficient can be significantly improved by fitting CMV to the mean of conventional indexes compared with single-point fitting, which can be considered as a new method for intelligent rolling correlation verification.

Item Type: Article
Subjects: AP Academic Press > Engineering
Depositing User: Unnamed user with email support@apacademicpress.com
Date Deposited: 17 Jan 2023 10:27
Last Modified: 21 May 2024 12:12
URI: http://info.openarchivespress.com/id/eprint/25

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