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Development of soil compaction analysis software (SCAN) integrating a low cost GPS receiver and compactometer.

Hwang J, Yun H, Kim J, Suh Y, Hong S, Lee D - Sensors (Basel) (2012)

Bottom Line: The SCAN is distinguished from other previous software for intelligent compaction (IC) in that it can use the results from various types of GPS positioning methods, and it also has an optimal structure for remotely managing the large amounts of data gathered from numerous rollers.For this, several methods were developed: (1) improving the accuracy of low cost GPS receiver's positioning results; (2) modeling the trajectory of a moving roller using a GPS receiver's results and linking it with the data from the compactometer; and (3) extracting the information regarding the compaction states of the ground from the modeled trajectory, using spatial analysis methods.The SCAN was verified throughout various field compaction tests, and it has been confirmed that it can be a very effective tool in evaluating field compaction states.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil, Architectural & Environmental Engineering, Sungkyunkwan University, Suwon 440-746, Korea. gpsboy@skku.edu

ABSTRACT
A software for soil compaction analysis (SCAN) has been developed for evaluating the compaction states using the data from the GPS as well as a compactometer attached on the roller. The SCAN is distinguished from other previous software for intelligent compaction (IC) in that it can use the results from various types of GPS positioning methods, and it also has an optimal structure for remotely managing the large amounts of data gathered from numerous rollers. For this, several methods were developed: (1) improving the accuracy of low cost GPS receiver's positioning results; (2) modeling the trajectory of a moving roller using a GPS receiver's results and linking it with the data from the compactometer; and (3) extracting the information regarding the compaction states of the ground from the modeled trajectory, using spatial analysis methods. The SCAN was verified throughout various field compaction tests, and it has been confirmed that it can be a very effective tool in evaluating field compaction states.

No MeSH data available.


Comparison of positioning accuracy based on RTK results. (a) Positioning differences between RTK and raw SPP results (dashed line), RTK and SPP with GVKF results (full line); (b) Positioning differences between RTK and raw SBAS results (dashed line), RTK and SBAS with GVKF results (full line).
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f12-sensors-12-02351: Comparison of positioning accuracy based on RTK results. (a) Positioning differences between RTK and raw SPP results (dashed line), RTK and SPP with GVKF results (full line); (b) Positioning differences between RTK and raw SBAS results (dashed line), RTK and SBAS with GVKF results (full line).

Mentions: As shown in Figure 11(a,b), there were many gross errors in the raw SBAS and SPP results (full lines) in which many positions were placed outside of the road. After being filtered by GVKF, most positions were placed inside the road, so it was logical that the accuracy of filtered results was improved considerably by GVKF. In order to analyze the improvement of accuracy more clearly, we compared and summarized all results (raw, GVKF and RTK) according to the positioning methods as shown in Figure 12 and Table 4.


Development of soil compaction analysis software (SCAN) integrating a low cost GPS receiver and compactometer.

Hwang J, Yun H, Kim J, Suh Y, Hong S, Lee D - Sensors (Basel) (2012)

Comparison of positioning accuracy based on RTK results. (a) Positioning differences between RTK and raw SPP results (dashed line), RTK and SPP with GVKF results (full line); (b) Positioning differences between RTK and raw SBAS results (dashed line), RTK and SBAS with GVKF results (full line).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376573&req=5

f12-sensors-12-02351: Comparison of positioning accuracy based on RTK results. (a) Positioning differences between RTK and raw SPP results (dashed line), RTK and SPP with GVKF results (full line); (b) Positioning differences between RTK and raw SBAS results (dashed line), RTK and SBAS with GVKF results (full line).
Mentions: As shown in Figure 11(a,b), there were many gross errors in the raw SBAS and SPP results (full lines) in which many positions were placed outside of the road. After being filtered by GVKF, most positions were placed inside the road, so it was logical that the accuracy of filtered results was improved considerably by GVKF. In order to analyze the improvement of accuracy more clearly, we compared and summarized all results (raw, GVKF and RTK) according to the positioning methods as shown in Figure 12 and Table 4.

Bottom Line: The SCAN is distinguished from other previous software for intelligent compaction (IC) in that it can use the results from various types of GPS positioning methods, and it also has an optimal structure for remotely managing the large amounts of data gathered from numerous rollers.For this, several methods were developed: (1) improving the accuracy of low cost GPS receiver's positioning results; (2) modeling the trajectory of a moving roller using a GPS receiver's results and linking it with the data from the compactometer; and (3) extracting the information regarding the compaction states of the ground from the modeled trajectory, using spatial analysis methods.The SCAN was verified throughout various field compaction tests, and it has been confirmed that it can be a very effective tool in evaluating field compaction states.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil, Architectural & Environmental Engineering, Sungkyunkwan University, Suwon 440-746, Korea. gpsboy@skku.edu

ABSTRACT
A software for soil compaction analysis (SCAN) has been developed for evaluating the compaction states using the data from the GPS as well as a compactometer attached on the roller. The SCAN is distinguished from other previous software for intelligent compaction (IC) in that it can use the results from various types of GPS positioning methods, and it also has an optimal structure for remotely managing the large amounts of data gathered from numerous rollers. For this, several methods were developed: (1) improving the accuracy of low cost GPS receiver's positioning results; (2) modeling the trajectory of a moving roller using a GPS receiver's results and linking it with the data from the compactometer; and (3) extracting the information regarding the compaction states of the ground from the modeled trajectory, using spatial analysis methods. The SCAN was verified throughout various field compaction tests, and it has been confirmed that it can be a very effective tool in evaluating field compaction states.

No MeSH data available.