Log End Imaging for Fast Strength-Based Timber Sorting
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Solution Overview
Problem
Existing methods for determining the stiffness and strength of logs are time-consuming, prone to human error, and inaccurate, especially for logs with high moisture content or recently harvested logs, leading to inefficient merchandising and potential misuse of logs in wood products.
Innovation Solution
A system utilizing imaging technology and computer processing to automatically identify growth characteristics such as growth rings, pith location, and other features on log ends, enabling precise determination of mechanical properties regardless of moisture content or time since harvest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used to determine log stiffness and strength, then human judgment can be applied, but the process is time-consuming and prone to human error
Solution Approach 1:
The patent replaces manual visual inspection with an automated imaging system that captures images of log ends and uses image processing algorithms to identify growth characteristics. This substitution of mechanical/manual processes with automated optical and computational systems resolves the contradiction by providing both high accuracy through consistent algorithmic analysis and high speed through automated image processing, eliminating human error and time-consuming manual evaluation.
Solution Approach 2:
The system enables logs to be automatically evaluated without human intervention by using image processing to self-identify growth characteristics such as growth rings, latewood/earlywood patterns, and pith location. The automated categorization process allows the system to serve itself by making independent determinations of log quality and directing logs to appropriate processing paths without requiring time-consuming manual inspection.
2Measurement precision
If traditional methods are used to determine stiffness and strength, then existing equipment can be utilized, but the determination is inaccurate for logs with high moisture content or recently harvested logs
Solution Approach 1:
The patent changes the measurement parameters from direct mechanical property measurement (which is affected by moisture content) to growth characteristic analysis through imaging. By measuring growth rings, latewood/earlywood ratios, and other visual characteristics that are independent of moisture content, the system achieves consistent measurement precision across all log conditions including recently harvested logs with high moisture content, thereby resolving the contradiction between precision and adaptability.
3Productivity
If logs are sorted based on external characteristics only, then sorting can be performed quickly, but the internal quality and mechanical properties cannot be accurately assessed
Solution Approach 1:
The patent transitions from one-dimensional external visual inspection to analyzing two-dimensional cross-sectional characteristics of log ends. By examining the internal growth patterns, ring structures, and wood density variations visible in end-grain images, the system achieves accurate assessment of mechanical properties while maintaining high sorting speed through automated image processing, resolving the contradiction between productivity and measurement precision.
Data Source
AI summary
Methods and systems of categorizing logs based on growth characteristics of the logs are disclosed. An exemplary method includes obtaining an image of an end surface of a log that includes growth rings, identifying one of more growth characteristics of the log based on the growth rings, and providing instructions to categorize the log based on the identified growth characteristics. The growth characteristics can include log age, diameter, rings per inch, and pith eccentricity. In some embodiments, images of both end surfaces of the log are obtained to identify other characteristics, such as an end-to-end diameter, which is used to provide further instructions to categorize the log.