Particle Sorting Device Bubble Detection via Image Brightness
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Solution Overview
Problem
Existing particle sorting devices require a bubble detector, increasing costs and limiting structural freedom, and there is a need to detect bubbles, foreign substances, and other contaminants in droplets effectively.
Innovation Solution
A particle sorting device that uses imaging units to capture and compare reference and captured images of droplets, allowing for the detection of bubbles and foreign substances by analyzing changes in brightness and pixel distribution, thereby stopping the sorting process and maintaining reliability without the need for additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a bubble detector is connected to the flow channel to detect bubbles, then bubble detection capability is improved, but device complexity and cost increase
Solution Approach 1:
The imaging device originally intended for particle observation is made to serve dual purposes: both particle analysis and bubble/foreign substance detection. By processing images through specific algorithms that analyze brightness distribution and pixel density, the system detects contaminants without requiring dedicated detection hardware, thus eliminating the need for separate bubble detectors and reducing overall device complexity
Solution Approach 2:
Instead of using a physical bubble detector that directly contacts the flow channel, the system creates an optical copy (image) of the droplet contents and analyzes it digitally. The imaging device captures light transmission patterns, and software algorithms identify bubbles and foreign substances based on abnormal brightness distributions, replacing physical detection mechanisms with optical-digital counterparts
2Reliability
If a bubble detector is connected to the flow channel to detect bubbles, then bubble detection capability is improved, but manufacturing cost increases
Solution Approach 1:
The imaging device originally intended for particle observation is made to serve dual purposes: both particle analysis and bubble/foreign substance detection. By processing images through specific algorithms that analyze brightness distribution and pixel density, the system detects contaminants without requiring dedicated detection hardware, thus eliminating the need for separate bubble detectors and reducing overall device complexity
Solution Approach 2:
Instead of using a physical bubble detector that directly contacts the flow channel, the system creates an optical copy (image) of the droplet contents and analyzes it digitally. The imaging device captures light transmission patterns, and software algorithms identify bubbles and foreign substances based on abnormal brightness distributions, replacing physical detection mechanisms with optical-digital counterparts
3Device complexity
If imaging units are used to detect bubbles and foreign substances by analyzing image brightness, then device complexity is reduced, but measurement precision may be affected
Solution Approach 1:
The system replaces physical detection mechanisms (mechanical bubble detectors) with optical-digital analysis. Imaging devices capture light transmission patterns, and software algorithms process the visual data to identify bubbles and foreign substances based on abnormal brightness distributions, substituting mechanical detection with optical-digital methods
Solution Approach 2:
The system changes the detection parameter from physical presence (mechanical detection) to optical property analysis (brightness distribution). By analyzing pixel density, average brightness, and brightness standard deviations in different droplet regions, the system transforms the detection task into a quantitative image processing problem, enabling accurate contaminant identification through parameter analysis rather than direct physical measurement
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 simple and accurate detection of bubbles and foreign substances, improving the stability and reliability of the sorting process while reducing costs by eliminating the need for separate bubble detection sensors, and providing greater structural freedom.
Implementation Method 1
an imaging device which images a droplet containing the microparticles which is discharged from an orifice provided on an edge portion of the flow path
Data Source
Figure 1
Figure 2
Figure 3A~3B
AI summary
Disclosed herein are a particle sorting device capable of simply detecting bubbles, foreign substances, or the like in droplets, a method for analyzing particles, a program, and a particle sorting system. The particle sorting device includes a judgment unit, and the judgment unit judges whether or not captured image information including captured droplet image information about a brightness of an image of particle-containing droplets captured after discharge from an orifice has changed with respect to previously-set reference image information including reference droplet image information about a brightness of an image of droplets captured after discharge from the orifice.