Optimization and testing of key parameters of peppercorn fresh fruit peeling machines
Year: 2025
Type: article
Abstract: ABSTRACT Lack of research on the key parameters of pepper peeling machines is the main reason for the low peeling efficiency and high damage rate of peppercorn peeling machines. Accordingly, to address the existing problems, the Box-Behnken response surface experimental design method was adopted to select the isometric push winch speed, tooth-type striking winch speed, and operation time as the influencing factors, and the peeling rate and damage rate were used as the evaluation indices to conduct the experiments. The experimental data were then collected, and mathematical regression models of the influencing factors and evaluation indicators were established. An analysis of the impact of the influencing factors on the evaluation indices revealed that the factors affecting the peeling rate and damage rate were in the following order: toothed strike winch speed > operating time > isometric push winch speed. Then, multiobjective models of the peeling rate and damage rate were constructed, and the parameters of the multiobjective model were optimized via the improved multiobjective seagull optimization algorithm. The optimal parameter combinations for maximizing the peeling rate were determined to be 800 r min-1 for the tooth striking winch, 204 r min-1 for the isometric pushing winch, and 4.9 min for the operation time; under these optimal solution conditions, the peeling rate was 94.27% and the damage rate was 6.03%. The parameters were validated by practical tests with 10 batches of peppercorn peeling operations. The results showed that under the optimized parameter combination, the processing effect was superior, and the quality requirement of peppercorn peeling was achieved.
Authors: Dezhan Shen, Yuan Zhang, Zhenhua Zhao, Lijiao Wei
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $34
OpenAlex ID: W4413214475
