GeoCongress 2006 2006
DOI: 10.1061/40803(187)41
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Compaction Monitoring Using Intelligent Soil Compactors

Abstract: The nonlinear vibrations of dynamic soil compactors are taken as the basis for feedback control systems for intelligent compaction. According to the achieved compaction, the parameters of the soil compactor are continuously changed. The vibratory roller measures permanently the stiffness of the subgrade. In conjunction with GPS-data, this measurement can be used as a QA/QC tool. The stiffness data are directly correlated to plate bearing test. In practice, the intelligent compaction ensures that the compaction… Show more

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Cited by 42 publications
(31 citation statements)
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“…In order to perform the spectrum analysis and obtain the SCV, the original acoustic signal for each pass of compaction was processed in the following steps: firstly, the signals of the start and stop rolling regions were removed, and zero drift was eliminated; then the remaining acoustic signals were divided into six blocks, and each block was about 4 m in length (Figure 12, Strip 4); subsequently, the effective acoustic signals of each block was transformed by FFT, respectively, and the corresponding frequency spectrum was obtained; next, the magnitude of the spectrum data was converted by log 10 , and the SHA of each acoustic signal block was obtained, respectively; finally, the SCV was determined using Equation (16). To illustrate the problem, the frequency spectrum of signal collected from Block 1 in Strip 1 was analyzed (Figure 14).…”
Section: Spectrum Analysis Of Detection Resultsmentioning
confidence: 99%
“…In order to perform the spectrum analysis and obtain the SCV, the original acoustic signal for each pass of compaction was processed in the following steps: firstly, the signals of the start and stop rolling regions were removed, and zero drift was eliminated; then the remaining acoustic signals were divided into six blocks, and each block was about 4 m in length (Figure 12, Strip 4); subsequently, the effective acoustic signals of each block was transformed by FFT, respectively, and the corresponding frequency spectrum was obtained; next, the magnitude of the spectrum data was converted by log 10 , and the SHA of each acoustic signal block was obtained, respectively; finally, the SCV was determined using Equation (16). To illustrate the problem, the frequency spectrum of signal collected from Block 1 in Strip 1 was analyzed (Figure 14).…”
Section: Spectrum Analysis Of Detection Resultsmentioning
confidence: 99%
“…Recently, several scholars paid attention to the automatic quality control method of compaction monitoring [17][18][19][20][21]. Intelligent compaction monitoring systems were developed and applied to road or earthmoving construction [22][23][24][25][26].…”
Section: Introductionmentioning
confidence: 99%
“…With the construction scale enlarging, the construction technic and the mechanization level enhancing, this artificial quality control method was difficult to meet the safety and quality demand of modern rockfill dam construction, so a comprehensive, efficient, real-time and automated quality control system was urgent to improve the quality control measures, namely to ensure project quality. Foreign research is concentrated in the fields of traffic engineering and geotechnical engineering [4][5][6][7][8] , which has certain reference for domestic research on construction quality monitoring of rockfill dam. Monitor system for quality of concrete face rockfill dam applied in Shuibuya Hydropower Station [9] is a beneficial exploration in the quality control methods of large-scale rockfill dam.…”
Section: Introductionmentioning
confidence: 99%