Thermal Segregation Detection in Asphalt Paving
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Solution Overview
Problem
Existing quality control systems in asphalt laying processes rely heavily on manual temperature measurements and lack the ability to accurately identify the root cause of temperature deviations and thermal segregation in paving materials, leading to suboptimal paving conditions.
Innovation Solution
A method and apparatus that utilize thermal profiling and artificial intelligence to analyze temperature data from a paving area, detect segregated spots in the paving material, and determine the quality of the material by identifying specific analysis parameters and assigning corresponding quality parameters, thereby providing actionable insights for improving paving conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual temperature measurements are used for quality control, then the system complexity is reduced, but the measurement precision and reliability of temperature monitoring deteriorates
Solution Approach 1:
The patent replaces manual mechanical temperature measurement systems with an automated optical/thermal imaging system. The thermal camera captures temperature distributions across the paving material surface, and computer vision algorithms automatically analyze the thermal profiles to detect segregation and quality issues, eliminating the need for manual contact measurements while improving precision and continuity.
Solution Approach 2:
The system performs self-monitoring and self-diagnosis by automatically analyzing thermal profiles to detect quality parameters. The computer vision system independently identifies temperature deviations, segregation patterns, and paving quality issues without requiring manual intervention, enabling the system to monitor and control its own process quality.
2Measurement precision
If thermal profiling with AI analysis is implemented, then the detection precision of thermal segregation improves, but the device complexity increases
Solution Approach 1:
The patent segments the thermal analysis process into distinct functional components: thermal image acquisition, thermal profile extraction, pattern recognition, quality parameter determination, and causal analysis. Each segment handles a specific aspect of the detection task, making the complex system modular and manageable while improving overall detection precision through specialized processing at each stage.
Solution Approach 2:
The patent introduces an intermediary computer vision system that acts as a mediator between the thermal camera and the final quality assessment. This intermediary layer processes raw thermal images into meaningful thermal profiles and patterns, translating physical temperature data into actionable quality insights through algorithmic analysis.
3Productivity
If real-time thermal monitoring is implemented, then the productivity and quality control efficiency improve, but the energy consumption increases
Solution Approach 1:
The system employs periodic thermal profiling at strategic points during the paving process rather than continuous monitoring. The thermal camera captures images at intervals when the paver is in position to detect segregation patterns, balancing real-time quality control with energy efficiency by activating the thermal monitoring function only when needed for quality assessment.
Solution Approach 2:
The patent replaces energy-intensive continuous active heating or monitoring systems with passive thermal imaging that captures existing thermal patterns in the paving material. The thermal camera detects temperature distributions without requiring active energy input to heat or continuously process the material, reducing overall energy consumption while maintaining real-time quality control capability.
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
The system enables real-time monitoring and analysis of thermal data, allowing for the automatic detection of thermal segregation and the provision of precise recommendations to operators, thereby enhancing the quality and consistency of the paving process.
Implementation Method 1
a first thermal profile of a portion (49) of a paving area (47) in which the paving material (15) is distributed
Data Source
AI summary
Method for detecting a quality of paving material distributed along a paving area using a paver, including: receiving a first thermal profile of a portion of the paving area where the paving material is distributed, the first thermal profile having a plurality of temperature values assigned to respective measurement points; the portion including a first subportion; analyzing the first thermal profile to detect segregated spots of paving material within the portion enabling to determine a quality of the paving material, including: determining a first zone of the measuring points arranged adjacent to each other and having temperature values within a predetermined range, the first zone corresponding to the first subportion and being at least partially surrounded by measurement points having temperature values out of the predetermined range; determining a first analysis parameter for the first zone; and determining a first quality parameter for the subportion to assign the first quality parameter to the first analysis parameter.