Yarn Spindle Image Counting for Trolley Exit Detection
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Solution Overview
Problem
The manual sampling detection method for yarn spindles during transportation has inefficiencies and a high missed detection rate, which can affect subsequent packaging processes.
Innovation Solution
A detection method and apparatus using image acquisition and a target detection model to count yarn spindles in entering and leaving images, generating detection information based on quantity differences, thereby automating and enhancing detection efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual sampling detection is used to check yarn spindles on the trolley, then the detection process is simple to implement, but the detection efficiency is low and the missed detection rate is high
Solution Approach 1:
The patent replaces manual mechanical detection with an automated image-based detection system. Image acquisition devices capture images of the trolley and yarn spindles, and a detection model automatically identifies and counts the yarn spindles, eliminating manual sampling and significantly improving both detection efficiency and accuracy.
Solution Approach 2:
The patent creates visual copies (images) of the actual yarn spindles on the trolley. By capturing multiple images from different angles and using image processing to reconstruct the three-dimensional arrangement of yarn spindles, the system can accurately count them without physical contact or manual handling.
2Loss of time
If manual sampling detection is performed on the trolley leaving the designated area, then the detection process is straightforward, but it requires significant time and labor resources
Solution Approach 1:
The patent implements continuous automated detection as the trolley moves through the designated area. Image acquisition devices continuously capture images of the trolley and yarn spindles, and the detection model processes these images in real-time, eliminating the need for manual sampling and significantly reducing detection time.
Solution Approach 2:
The detection system is self-serve in the sense that it automatically performs image acquisition, processing, and analysis without requiring manual intervention. The system independently completes the entire detection process, from capturing images to generating detection results, thereby reducing both time consumption and labor requirements.
Data Source
AI summary
Provided is a detection method, an electronic device and a storage medium. The method includes: obtaining an entering image and a leaving image when detecting that a trolley leaves an area; where the entering image is obtained by performing image acquisition on the trolley after the trolley enters the area, and the leaving image is obtained by performing image acquisition on the trolley after the trolley leaves the area; inputting the entering image into a target detection model to obtain a first quantity of yarn spindles contained in the entering image, and inputting the leaving image into the target detection model to obtain a second quantity of yarn spindles contained in the leaving image; and generating detection information for the trolley based on the first quantity of yarn spindles contained in the entering image and the second quantity of yarn spindles contained in the leaving image.