Abstract:
Objective A visual-detection-based peeling device for a green onion processing machine was designed to address the problems of tender and fragile white stalk tissue of green onions, marked variation in stem diameter, uneven adhesion of the outer dry skin, and difficulty in rapidly identifying the peeling status during postharvest green onion peeling.
Method According to the morphological parameters of green onion plants, a peeling device integrating an iris flexible clamping mechanism, a planetary-gear clamping and rotating mechanism, and a high-pressure airflow peeling assembly was designed, and its operating performance was analyzed. A visual detection algorithm for green onion dry skin based on HSV color threshold segmentation was developed. Visual detection tests and prototype verification tests were then carried out.
Result The recognition accuracies for images of unsatisfactory and satisfactory peeling, respectively, were 97.2% and 98.9%, respectively. The overall recognition accuracy was 98.1%, and the average processing time was 0.0292s. The average normalized area errors for images of unsatisfactory and satisfactory peeling, respectively, were 1.589% and 0.149%, respectively. The prototype verification test showed that when the leaf feeding length was 60 mm, the clamping rotation speed was 45 r/min, and the blowing time was 9 s, the peeling success rate was 93.33%, and the green onion damage rate was 6.67%.
Conclusion The peeling device for the green onion processing machine based on HSV threshold segmentation can rapidly identify the presence of residual dry skin on green onions and enable flexible clamping, low-speed rotation, and airflow peeling of the white stalk sections of green onions, providing a reference for mechanized postharvest green onion peeling and vision-based control.
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