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.
Highlights
Subgrade soil settlement beneath pavements is a major concern for engineers [1]
Compaction plays an important role in improving the strength of the subgrade and pavement [2], and in long-term engineering practice, a variety of compaction quality evaluation indexes have been formed at home and abroad, mainly including two categories of physical testing indexes represented by compaction degree and mechanical indexes represented by elastic modulus [3, 4], the testing methods and principles of these evaluation indexes are different, but most of them have low testing efficiency, poor representation, lagging results, and other disadvantages
With the continuous development of the engineering industry, there is an urgent need for a device that can test compaction with the vehicle, which can display the compaction test results in real time and guide the operator to operate reasonably. e corresponding detection systems have been developed in Sweden, Germany, USA, Japan, and China, and various compaction control indicators based on the harmonic method have been proposed, such as CMV [5,6,7] in Sweden and CCV [8,9,10] in Japan
Summary
Subgrade soil settlement beneath pavements is a major concern for engineers [1]. Compaction plays an important role in improving the strength of the subgrade and pavement [2], and in long-term engineering practice, a variety of compaction quality evaluation indexes have been formed at home and abroad, mainly including two categories of physical testing indexes represented by compaction degree and mechanical indexes represented by elastic modulus [3, 4], the testing methods and principles of these evaluation indexes are different, but most of them have low testing efficiency, poor representation, lagging results, and other disadvantages. Intelligent compaction technology can continuously and comprehensively reflect the compaction information of the subgrade, and when using the intelligent compaction system to quantitatively evaluate the compaction quality, the correlation between CMV and conventional indicators needs to be established, but this relationship is not fixed because CMV indicators are affected by multiple factors such as roller type, vibration frequency, and soil type It is stipulated in JT/T 1127-2017 [11] that, before carrying out intelligent compaction control, the one-dimensional linear regression equation between the intelligent compaction index and the conventional index is established by point-to-point coordinate correspondence, and the correlation coefficient must be ensured to be above 0.7. Because the conventional fitting method does not consider the influence of the two testing methods in the roller wheel width direction on the correlation coefficient, this paper proposes an improved scheme for fitting CMV with the average value of conventional indicators along the wheel width direction, and relying on the Nanning ShajingWuxu Expressway project, three filler types of subgrades are selected to fit the relationship between CMV and conventional quality control indexes of compaction K and dynamic resilient modulus E [15,16,17], respectively
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