Vibratory Compactor Density Analysis via Neural Network
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Solution Overview
Problem
Current methods for monitoring compacted density of asphalt mats during the paving process are cumbersome, time-consuming, and lack precision, often requiring only a few density readings per lane mile, which can lead to costly remedial measures due to failure to meet target density specifications.
Innovation Solution
A vibratory compactor equipped with sensors and a compaction analyzer featuring a feature extraction module, neural network module, and analyzer module that generates real-time density signals by analyzing vibratory response signals, allowing for adjustments to machine parameters to achieve uniform compaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional density measurement methods (core sampling) are used, then measurement precision can be achieved, but the process is cumbersome and time-consuming
Solution Approach 1:
The patent replaces the mechanical core sampling method with a vibratory response-based measurement system. Accelerometers detect vibrations from the compactor, and a neural network analyzes these vibrations to predict density, eliminating the need for physical core extraction and laboratory testing while maintaining measurement accuracy.
Solution Approach 2:
The patent creates a virtual model of the compaction process by using vibratory response signals as proxies for actual density measurements. The neural network model replicates the relationship between vibrations and density, allowing continuous monitoring without physical intervention to extract samples.
2Loss of time
If only a few density readings are taken per lane mile, then measurement time is reduced, but the risk of failure to meet target density increases
Solution Approach 1:
The patent enables continuous density monitoring throughout the entire compaction process. The system operates continuously as the compactor moves along the roadway, providing uninterrupted density data without requiring discrete sampling points, thus maintaining high reliability while minimizing time loss.
Solution Approach 2:
The system provides real-time feedback on compaction density through the neural network analysis of vibratory signals. This continuous feedback allows immediate detection of density deviations from target specifications, enabling timely adjustments to compaction parameters and ensuring compliance without requiring multiple discrete readings.
3Measurement precision
If density measurements are taken at a large number of points in a grid fashion, then measurement precision improves, but cost and complexity increase
Solution Approach 1:
The patent replaces complex grid-based spatial sampling with a single-point continuous measurement system. By using vibratory response analysis, the system achieves comprehensive density assessment without requiring multiple measurement locations, significantly reducing system complexity while maintaining or improving precision.
Solution Approach 2:
The patent makes the measurement system universal by using the compactor's own vibratory response as the measurement signal. The same compaction process that compacts the material also provides the measurement data, eliminating the need for separate measurement equipment and multiple sampling points.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time, continuous measurement of asphalt pavement density, reducing the need for costly core sampling and ensuring uniform compaction, thereby preventing under- or over-compaction and improving construction efficiency.
Implementation Method 1
gathering responsive vibratory signals of the roller
Data Source
AI summary
A method of compacting a roadway section includes entering initial input parameters into a compaction analyzer. A plurality of passes is made with a roller over a portion of the roadway section and vibratory energy is applied thereto. Responsive vibration signals are gathered and the compaction analyzer generates estimated density signals. Actual density measurements are taken and the estimated densities are compared thereto. Selected ones of the initial input parameters are adjusted so that an adjusted density output signal which represents the actual density of a roadway section is generated.