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Article type: Research Article
Authors: Luo, Zhengmaoa | Dong, Dachongb; * | Cai, Ziranc | Wan, Yid
Affiliations: [a] Zhejiang College of Security Technology, Wenzhou, Zhejiang, China | [b] Wenzhou Polytechnic, Wenzhou, Zhejiang, China | [c] Wenzhou Business School, Wenzhou, Zhejiang, China | [d] Department of Computer Science and Engineering, Shaoxing University, Shaoxing, Zhejiang, China
Correspondence: [*] Corresponding author: Dachong Dong, Wenzhou Polytechnic, Wenzhou, Zhejiang 325035, China. E-mail: 67944877@qq.com.
Abstract: In the research, an agricultural machinery reliability analysis method based on fusion algorithm is proposed, a optimal radial basis function neural network and M-C statistical test method are mixed to obtain an agricultural machinery reliability. This mixed model is used to reliability design and calculation of a cotton picker, the simulation model of reliability control and calculation for a cotton picker based on the mixed algorithm is set up, and reliability of the level spindle of a cotton picker is computed through the mixed method, and the effect of important factors on the cotton picker is predicted. The level spindle is critical force-bearing parts of a cotton picker and breakdown occurs frequently, their reliability control and optimization are key problems that need to be solved urgently, this study builds an innovative approach for the reliability optimization and design of agricultural equipments.
Keywords: A radial basis function neural network, reliability control and calculation, M-C numerical simulation, agricultural equipments
DOI: 10.3233/JCM-226885
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 5, pp. 2635-2643, 2023
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