About the research
This project involved an extensive field program carried out to identify the relationships between soil engineering properties, as measured by various in situ devices, and the results of machine compaction monitoring using prototype compaction monitoring technology developed by Caterpillar Inc. Primary research tasks for this study include the following: (1) experimental testing and statistical analyses to evaluate machine power in terms of the engineering properties of the compacted soil (e.g., density, strength, stiffness) and (2) recommendations for using the compaction monitoring technology in practice. The compaction monitoring technology includes sensors that monitor the power consumption used to move the compaction machine, an on-board computer and display screen, and a GPS system to map the spatial location of the machine. In situ soil density, strength, and stiffness data characterized the soil at various stages of compaction. For each test strip or test area, in situ soil properties were compared directly to machine power values to establish statistical relationships. Statistical models were developed to predict soil density, strength, and stiffness from the machine power values. Field data for multiple test strips were evaluated. The R2 correlation coefficient was generally used to assess the quality of the regressions. Strong correlations were observed between averaged machine power and field measurement data. The relationships are based on the compaction model derived from laboratory data. Correlation coefficients (R2) were consistently higher for thicker lifts than for thin lifts, indicating that the depth influencing machine power response exceeds the representative lift thickness encountered under field conditions. Caterpillar Inc. compaction monitoring technology also identified localized areas of an earthwork project with weak or poorly compacted soil. The soil properties at these locations were verified using in situ test devices. This report also documents the steps required to implement the compaction monitoring technology evaluated.
About the research
This Phase I report describes a preliminary evaluation of a new compaction monitoring system developed by Caterpillar, Inc. (CAT), for use as a quality control and quality assurance (QC/QA) tool during earthwork construction operations. The CAT compaction monitoring system consists of an instrumented roller with sensors to monitor machine power output in response to changes in soilmachine interaction and is fitted with a global positioning system (GPS) to monitor roller location in real time.
Three pilot tests were conducted using CAT?s compaction monitoring technology. Two of the sites were located in Peoria, Illinois, at the Caterpillar facilities. The third project was an actual earthwork grading project in West Des Moines, Iowa. Typical construction operations for all tests included the following steps: (1) aerate/till existing soil; (2) moisture condition soil with water truck (if too dry); (3) remix; (4) blade to level surface; and (5) compact soil using the CAT CP-533E roller instrumented with the compaction monitoring sensors and display screen. Test strips varied in loose lift thickness, water content, and length.
The results of the study show that it is possible to evaluate soil compaction with relatively good accuracy using machine energy as an indicator, with the advantage of 100% coverage with results in real time. Additional field trials are necessary, however, to expand the range of correlations to other soil types, different roller configurations, roller speeds, lift thicknesses, and water contents. Further, with increased use of this technology, new QC/QA guidelines will need to be developed with a framework in statistical analysis.
Results from Phase I revealed that the CAT compaction monitoring method has a high level of promise for use as a QC/QA tool but that additional testing is necessary in order to prove its validity under a wide range of field conditions. The Phase II work plan involves establishing a Technical Advisor Committee, developing a better understanding of the algorithms used, performing further testing in a controlled environment, testing on project sites in the Midwest, and developing QC/QA procedures.