Intelligent Compaction and Quality Assurance of Roller Measurement Values utilizing Backfitting and Multiresolution Scale Space Analysis

TL;DR

This paper presents a novel approach combining backfitting and multiresolution scale space analysis to improve intelligent compaction quality assurance using roller measurement data.

Contribution

It introduces a new statistical framework integrating spatial mixed-effects modeling with multiresolution analysis for better assessment of compaction quality.

Findings

Enhanced detection of compaction inconsistencies

Improved spatial modeling of roller measurement data

Potential for real-time quality assurance

Abstract

Modern earthwork compaction rollers collect location and compaction information as they traverse a compaction site. These roller measurement values present a challenging spatio-temporal statistical problem that requires careful implementation of a proper stochastic model and estimation procedure. Heersink and Furrer (2013) proposed a sequential, spatial mixed-effects model and a sequential, spatial backfitting routine for estimation of the modeling terms for such data. The estimated fields produced from this backfitting procedure are analyzed using a multiresolution scale space analysis developed by Holmstrom et al. (2011). This image analysis is proposed as a viable solution to improved intelligent compaction and quality assurance of the compaction process.