Rolling Food Grading via Laser Triangulation
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Solution Overview
Problem
Existing methods for grading fruit and vegetables based on size and shape are inadequate, as they fail to accurately distinguish between different shapes and sizes due to variations in density and orientation, leading to inconsistent quality assessment.
Innovation Solution
A method involving the use of a feed path where products roll and rotate, allowing continuous detection of their surface structure using techniques like laser triangulation and 'time of flight' to reconstruct a three-dimensional representation, enabling accurate grading of size, shape, and texture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If weight-based selection is used, then grading speed is improved, but size measurement precision deteriorates due to density variations
Solution Approach 1:
The patent replaces mechanical weight-based selection with an optical measurement system using laser triangulation. Instead of using scales and weight-based sorting, the system uses light projection and detection to directly measure the three-dimensional geometry of fruits, eliminating the indirect inference from weight to size that causes precision errors due to density variations.
Solution Approach 2:
The patent creates a digital three-dimensional copy of the fruit's surface geometry through laser scanning. This optical copy allows for precise measurement of size, shape, and surface characteristics without physical contact, enabling accurate size determination independent of the fruit's density or weight.
2Manufacturing precision
If hole-based size selection is used, then size grading is improved, but measurement precision deteriorates due to orientation dependency
Solution Approach 1:
The patent transitions from two-dimensional hole-based size selection to three-dimensional optical scanning. By capturing the fruit's geometry in three dimensions through laser triangulation, the system can determine size characteristics (height, equatorial diameter, volume) independent of the fruit's orientation during measurement, eliminating the orientation dependency inherent in hole-based methods.
Solution Approach 2:
The patent changes the measurement parameter from simple dimensional fitting through holes to comprehensive three-dimensional geometric analysis. The system measures multiple parameters simultaneously (height, diameter, surface area, volume, shape factors) and uses these combined parameters for accurate size grading, making the measurement robust against orientation variations.
3Measurement precision
If multiple detection points are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines the laser projector and camera into a single integrated detection unit. Instead of using separate devices for light projection and image capture, the system merges these functions into one compact unit, reducing device complexity while maintaining the capability to perform triangulation measurements from multiple effective points through the coordinated operation of the integrated components.
Solution Approach 2:
The patent uses the natural rolling motion of fruits on the conveyor belt to dynamically present different surface portions to the fixed detection point. This dynamic approach allows a single stationary detection unit to effectively scan the entire surface of rolling fruits, achieving comprehensive surface coverage without requiring multiple fixed detection points or complex multi-angle sensor arrays.
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 method allows for precise grading of fruit and vegetables based on size, shape, and texture, ensuring consistent quality assessment without interrupting the production line and with relatively low implementation costs.
Implementation Method 1
detecting the relative surface structure of each food product at one or more surface portions by projecting a laser beam on the surface of the food product and detecting the deformed laser beam
Implementation Method 2
The deformed two-dimensional image is compared with a non-deformed two-dimensional image for a selection of preset colour and/or luminous intensity points of the pattern. A depth coordinate is calculated for each point of the pattern from the projection of the point on the surface.
Data Source
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AI summary
A method for grading substantially rigid food products able to roll on their outer surface, such as fruit and vegetables, comprises the operating steps of: feeding each food product (1) and making it roll on its outer surface; detecting the relative surface structure of the food product (1) at one or more of its surface portions (2); repeating the detection step a plurality of times, for detecting at least once the relative surface structure of at least most of the surface of the food product (1); combining the relative surface structures detected to reconstruct an overall surface structure of the food product (1); and grading each food product (1) according to the overall surface structure detected.