Virtual Color Sensor for Container Sorting
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Solution Overview
Problem
Current color sensor systems in the beverage production industry are expensive, inflexible, and inefficient for recognizing multiple container colors, leading to suboptimal throughput and resource utilization, especially when dealing with mixed containers and complex visual elements.
Innovation Solution
A method utilizing an image recording device to capture spatially resolved color images of multiple containers, analyzing these images to identify individual containers, and using machine learning algorithms, specifically neural networks, to determine characteristic color information and assign unique identification to each container, enabling flexible and accurate sorting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional color sensors are used to recognize container colors, then color recognition can be performed, but the system becomes expensive and inflexible with limited multi-color recognition capability
Solution Approach 1:
The patent uses image recording devices to capture visual information of containers and creates virtual color sensors through image analysis. Instead of using multiple physical color sensors, the system copies color information by analyzing images, thereby reducing hardware costs and increasing flexibility while maintaining accurate color recognition capability
Solution Approach 2:
A single image recording device can recognize multiple colors and identify different container types simultaneously. The image analysis system serves multiple functions including color recognition, container identification, and sorting guidance, replacing the need for multiple specialized sensors and enabling versatile operation across different container types
2Area of stationary object
If multiple color sensors are installed to cover larger regions, then more containers can be monitored, but the device complexity and cost increase
Solution Approach 1:
The patent combines the functions of multiple color sensors into a single image recording device. By merging color detection, container identification, and visual inspection into one device, the system achieves broader monitoring coverage without increasing the number of separate sensors, thereby reducing device complexity and cost
3Adaptability or versatility
If sequential transport of different beverage types is used, then production flexibility is maintained, but buffers and transport capacities are not optimally utilized
Solution Approach 1:
The image recording device captures visual information of containers in advance during transport, and the analysis system identifies container types and colors before they reach the sorting point. This preliminary identification allows for optimized transport capacity utilization by preparing sorting instructions ahead of time, enabling more efficient buffer management and reducing the need for sequential transport of single types
4Productivity
If order picking of mixed containers is implemented, then throughput increases, but temporary storage requirements and technical outlay increase
Solution Approach 1:
The image analysis system provides real-time feedback on container identification and color recognition during transport. This feedback enables dynamic sorting decisions without requiring large temporary storage buffers, as the system can guide containers directly to their designated destinations based on real-time visual analysis, thereby reducing infrastructure requirements while maintaining high throughput
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 enhances the reliability and cost-effectiveness of the sorting process by allowing for the recognition of multiple container types and colors, improving throughput and reducing resource inefficiencies, while enabling accurate order-specific packaging and storage.
Implementation Method 1
the light reflected from the target object, i.e., the container, is then detected with a receiver
Data Source
AI summary
A method for sorting and/or treating containers includes the steps of:recording at least one image and/or a video of a plurality of containers by an image recording device, which is configured for recording spatially resolved color images;analyzing the at least one recorded image;identifying the individual containers;assigning an identification information and at least one portion of the recorded image to each of the identified containers; andascertaining a color information, which is characteristic of an identified container, from the portion of the recorded image.