Development of algorithms for asphalt pavement compaction monitoring utilizing ground penetrating radar

The density of asphalt mixture plays an important role in the performance of asphalt pavement. Compaction is critical for achieving the desired density during the construction of asphalt pavement. To ensure successful compaction, the density of asphalt pavement should be monitored in a timely manner, and the information should be fed back to the compactor operator to avoid under-compaction or over-compaction. This study proposes a technique based on ground penetrating radar (GPR) for monitoring the density of asphalt pavement during compaction continuously, non-destructively, and in real time. The utmost challenge in developing this technique is to eliminate the effect of surface moisture, sprayed by the compactor during compaction, on GPR data. The increase of asphalt pavement density and surface moisture content can cause an increase in the amplitude of the reflection pulse in the GPR signals in time domain. To extract density information without the effect of surface moisture, numerical simulation, laboratory experiments, and field tests were conducted. First, the difference between the effect of surface moisture variation and the effect of density variation on GPR signal was investigated. Numerical simulation was performed using the finite-difference time-domain (FDTD) method to study the propagation of GPR wave within pavement structure. Both simulation results and laboratory experimental results revealed the fundamental difference between the two effects: In frequency domain, the high frequency components of the GPR pulse is sensitive to density variation and variation of surface moisture content, and the low frequency components are only sensitive to the density variation. The difference between the two effects is referred to as the “frequency-selective effect” in this dissertation. Second, based on the findings of the “frequency-selective effect”, a “correction algorithm” was developed based on the “reference scan approach” to eliminate the effect of surface moisture and to extract density information. To develop and validate the algorithm, a full-scale test site was constructed with compaction pass number from 0 to 10, and a large amount of GPR data was collected from the pavement with different surface moisture contents. A total of 22 cores were taken for validation purposes. After applying the algorithm, it was found that the average density prediction error was reduced from 3.1% to 0.9%, thus indicating the effectiveness of the algorithm. The GPR system was tested in a field construction site. The system successfully monitored the density change after each roller pass during compaction. The density estimation results obtained from GPR after the final compaction had higher accuracy than the density results obtained from the nuclear density gauge.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Civil Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Shangguan, Pengcheng

Contributors dc:contributor

• Tutumluer, Erol
• Ozer, Hasan
• Al-Qadi, Imad L.
• Jin, Jianming
• Harvey, John

• Asphalt Compaction
• Ground Penetrating Radar (GPR)
• Compaction Monitoring

Statement dc:rights

• Copyright 2014 Pengcheng Shangguan

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/73067

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/73067