Journal of Northeastern University(Natural Science) ›› 2021, Vol. 42 ›› Issue (9): 1290-1298.DOI: 10.12068/j.issn.1005-3026.2021.09.011

• Mechanical Engineering • Previous Articles     Next Articles

Blade Power Consumption Optimization of Straw Crushing Machines Using the Improved Genetic Algorithm

YE Cui-li, WANG Na, PANG Shuo, YAN Hang   

  1. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China.
  • Revised:2021-01-29 Accepted:2021-01-29 Published:2021-09-16
  • Contact: WANG Na
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Abstract: To reduce the power consumption of straw crushing machines, the blade of straw crushing machines was taken as the research object to optimize its structure and motion parameters. A mathematical model of blade power consumption was established by analyzing the blade force, and the correctness of the model was verified by field experiments. An advanced genetic algorithm was proposed, and its feasibility and superiority were verified by using standard test functions. The mathematical model was optimized by using the advanced genetic algorithm, and the structural static analysis of the blades before and after optimization was carried out by using the ANSYS Workbench platform. The optimization results showed that the power consumption is reduced by 6.4% compared with that before optimization, from 19.3kW to 18.06kW. The results of structural static analysis showed that the optimized structure is reasonable and feasible.

Key words: straw crushing machine; blade power consumption; mathematical model; advanced genetic algorithm; blade optimization

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