Wood Treatability Prediction Using Sensor Groups
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Solution Overview
Problem
The variability in wood properties leads to inconsistent chemical uptake and extended treatment cycles during wood treatment, resulting in unnecessary costs due to uncertainty about the treatability of individual wood pieces in batch processes.
Innovation Solution
A method using single and/or multiple sensor groups to provide qualitative and quantitative estimates of chemical uptake and penetration in wood products, employing classification algorithms and various sensor technologies like near-infrared spectroscopy and acousto-ultrasonic properties to predict treatability, allowing for more precise treatment cycles and manufacturing decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If batch treating process is used for wood products, then treatment coverage is improved, but chemical uptake consistency deteriorates due to natural variability in wood properties
Solution Approach 1:
The system performs preliminary measurement of wood product properties (density, moisture content, species identification) before the treating process to predict chemical uptake and penetration characteristics. This advance knowledge allows for optimized treatment parameters to be applied, ensuring consistent results across the batch while maintaining high productivity.
Solution Approach 2:
The system uses measured wood properties and predicted treatability to adjust treatment parameters during the batch process. By incorporating feedback from initial measurements, the system can modify pressure, vacuum, and chemical concentration parameters to compensate for natural wood variability, achieving consistent chemical uptake across diverse wood pieces.
2Reliability
If extended treatment cycles are used to ensure adequate treatment, then treatment effectiveness is improved, but production time increases
Solution Approach 1:
The system performs preliminary assessment of wood treatability using sensor measurements and classification algorithms before treatment. This advance evaluation identifies the specific treatment cycle duration needed for each wood product, eliminating the need for extended cycles while ensuring adequate treatment effectiveness.
Solution Approach 2:
The system changes treatment parameters (pressure, vacuum, chemical concentration, cycle duration) based on measured wood properties and predicted treatability. By adapting parameters to match the specific characteristics of each wood product, the system achieves effective treatment in optimized time, avoiding unnecessary extension of treatment cycles.
3Ease of manufacture
If uniform treatment parameters are applied to all wood pieces, then process simplicity is maintained, but chemical waste increases due to over-treatment of highly absorbent pieces
Solution Approach 1:
The system changes treatment parameters based on measured wood properties such as density, moisture content, and species type. By adjusting chemical concentration, pressure, and cycle duration to match the specific treatability of each wood product, the system prevents over-treatment and chemical waste while maintaining process simplicity through automated parameter selection.
Solution Approach 2:
The system performs preliminary measurement and classification of wood products to predict chemical uptake characteristics before treatment. This advance knowledge enables optimized parameter selection that matches the actual treatability of each piece, preventing chemical waste from over-treatment while keeping the process simple through automated decision-making.
4Measurement precision
If multiple sensor groups are used to improve measurement accuracy, then treatability prediction precision is improved, but device complexity increases
Solution Approach 1:
The system uses multiple sensor groups that perform multiple functions: identifying wood species, measuring density, determining moisture content, and predicting treatability. By making the sensor system multi-functional, the patent achieves high measurement precision without proportionally increasing complexity, as the same sensors serve several measurement purposes simultaneously.
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
This approach enables accurate classification of wood products into treatability groups, optimizing chemical uptake and penetration, reducing unnecessary chemical application and treatment time, thereby lowering costs and improving efficiency in wood treatment processes.
Implementation Method 1
employing classification algorithms and various sensor technologies like near-infrared spectroscopy
Implementation Method 2
employing classification algorithms and various sensor technologies like acousto-ultrasonic properties
Data Source
AI summary
A method for determining potential uptake and/or potential penetration of a liquid and/or chemical within a wood product is provided. The methods involve the use of single and/or multiple sensor group systems to provide qualitative and/or quantitative estimates of uptake and/or penetration. Properties measured and/or detected by the sensor groups are inputted to an algorithm for determining treatability of the wood product.