3D Granular Size Distribution Measurement via Laser Scanning
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Solution Overview
Problem
Existing methods for measuring the size distribution of granular matter, such as wood chips, are limited in accuracy and cannot effectively handle random orientations of granules, leading to inconsistent pulp quality and energy consumption in industrial processes.
Innovation Solution
A method and apparatus using three-dimensional image processing to scan and segment granular bulk matter, applying geometric corrections to size-related parameters to compensate for random orientations, and statistically estimating size distribution, enabling more accurate online measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sifting methods are used to measure granular matter size distribution, then the measurement process is simple and inexpensive, but the measurement precision is limited and cannot accurately represent the true size distribution
Solution Approach 1:
The patent replaces mechanical sifting methods with optical scanning and image processing technology. A laser scanner captures three-dimensional profile images of granular matter, and computer algorithms automatically analyze the images to determine size distribution, eliminating the need for physical sifting trays and manual measurement
Solution Approach 2:
The patent transitions from two-dimensional projection measurements to three-dimensional profile imaging. By capturing depth information and analyzing the actual three-dimensional shapes of granules, the system achieves more accurate size measurements that account for random orientations, rather than relying on flat projections that can be misleading
2Productivity
If online computerized grain size measurement using image processing is used, then productivity is improved compared to offline classification, but measurement precision is limited due to inability to compensate for random orientation
Solution Approach 1:
The patent changes the measurement parameters from simple two-dimensional area measurements to three-dimensional profile analysis. By capturing depth information and calculating actual granule dimensions in three-dimensional space, the system maintains high measurement speed while significantly improving accuracy for randomly oriented granules
Solution Approach 2:
The patent performs preliminary three-dimensional scanning and segmentation of granular matter before statistical analysis. By pre-processing the image data to identify individual granule boundaries and extract three-dimensional profiles, the system prepares accurate measurement data in advance, enabling both high productivity and precision in the final size distribution calculation
3Measurement precision
If offline chip classification using Williams classifier is used, then measurement precision can be obtained through physical separation, but loss of time occurs due to offline measurement not suitable for process control
Solution Approach 1:
The patent replaces the mechanical sifting process with optical scanning and digital image analysis. The laser scanner rapidly captures three-dimensional images of chips in their natural random orientation, and computer algorithms instantly process the data to determine size distribution, eliminating the time-consuming mechanical separation process while maintaining or improving measurement accuracy
Data Source
AI summary
A method and apparatus for measuring size distribution of bulk matter consisted of randomly orientated granules, such as wood chips, make use of scanning the exposed surface of the granular matter to generate three-dimensional profile image data defined with respect to a three-coordinate reference system, The image data is segmented to reveal regions associated with distinct granules, and values of the size-related parameter for the revealed regions are estimated. Then, a geometric correction to each ones of estimated size-related parameter values is applied, to compensate for the random orientation of corresponding distinct granules. Finally, the size distribution of bulk matter is statistically estimated from the corrected size-related parameter values.