Machine-Vision-Based Algorithm for Blockage Recognition of Jittering Sieve in Corn Harvester

文献类型： 外文期刊

第一作者： Fu, Jun

作者： Fu, Jun;Yuan, Haikuo;Zhao, Rongqiang;Ren, Luquan;Fu, Jun;Yuan, Haikuo;Zhao, Rongqiang;Chen, Zhi;Ren, Luquan;Fu, Jun;Chen, Zhi;Wang, Jin;Tang, Xinlong

作者机构：

关键词： corn harvest; jittering sieve; machine vision; blockage recognition

期刊名称：APPLIED SCIENCES-BASEL （ 影响因子：2.679； 五年影响因子：2.736 ）

ISSN：

年卷期： 2020 年 10 卷 18 期

页码：

收录情况： SCI

摘要： Jittering sieve is a significant component of corn harvester, and it is used to separate kernels from impurities. The sieves may be blocked by kernels during the separating process, leading to the reduction of working performance. Unfortunately, the automatic recognition of blockage has not been studied yet. To address this issue, in this study we develop machine-vision-based algorithms to divide the jittering sieve into sub-sieves and to recognize kernel blockages. Additionally, we propose the metric to evaluate blocking level of each sub-sieve, aiming to provide the basis for automatic blockage clearing. The performance of the proposed algorithm is verified through simulation experiments on real images. The success ratio of edge determination reaches 100%. The mean cross-correlation coefficient of the blockage levels and the actual numbers of blocked kernels for all test scenes is 0.932. The results demonstrate the proposed algorithm can be used for accurate blockage recognition, and the proposed metric is appropriate for evaluating the blockage level.

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