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Design of a deviation information detection mechanism for sugar beet harvesters based on agricultural machinery and agronomy integration.

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Title: Design of a deviation information detection mechanism for sugar beet harvesters based on agricultural machinery and agronomy integration.
Authors: Wang, Shenying1,2 wangshenying@caas.cn, Pan, Jinbo1,2 2157977186@qq.com, Xiao, Qiang3 327531828@qq.com, You, Zhaoyan1 1275306672@qq.com, Li, Jianmei4 lxdjz666@163.com, Gao, Xuemei1 gaoxuemei@caas.cn, Xie, Shengshi5 xieshengshi@163.com
Source: International Journal of Agricultural & Biological Engineering. Feb2026, Vol. 19 Issue 1, p120-131. 12p.
Subjects: Agricultural equipment, Sugar beets, Farm mechanization, Geometric modeling, Detection algorithms
Abstract: To address large geometric shape differences, poor ridge distribution straightness, and the uncertain spatial distribution of beet roots during the harvesting period, as well as damage caused by the inaccurate row correction detection mechanisms of combine harvesters, this study conducts a design analysis and performance tests of deviation information detection mechanisms based on the integration of agricultural machinery and agronomy. The agronomic process of mechanized sugar beet production was analyzed, the geometric dimensions of root tubers under typical planting patterns of typical varieties in main sugar beet production areas were measured, and a three-dimensional geometric model of beet root tubers was established. A device for measuring ridge shape and root tuber distribution was designed, and agronomic parameters during the harvesting period, such as plant spacing, ridge height, unearthed height, and deviation distance of beet root tubers, were measured and analyzed. A spatial model of ridge shape and beet root tuber growth distribution on the ridge during harvesting was established. The overall structure of the deviation information detection mechanism was analyzed and designed, and the structural forms and key parameters of key mechanisms, such as left-right swing detection and up-down floating profiling, were designed on the basis of agronomic parameter analysis. Using the missed detection rate as the evaluation index, field performance tests of the deviation information detection mechanism were conducted. The results revealed that when the average forward speed of the harvester was 0.84 m/s, the average missed detection rate of the deviation information detection mechanism was 0.56%. This method has high adaptability and detection accuracy and achieves a high level of integration for agricultural machinery (detection spatial region of the detection mechanism) and agronomy (beet root distribution spatial region). This study provides a technical basis and methodological reference for improving the quality and efficiency of automatic row correction combined with harvesting operations for crops such as sugar beets. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:To address large geometric shape differences, poor ridge distribution straightness, and the uncertain spatial distribution of beet roots during the harvesting period, as well as damage caused by the inaccurate row correction detection mechanisms of combine harvesters, this study conducts a design analysis and performance tests of deviation information detection mechanisms based on the integration of agricultural machinery and agronomy. The agronomic process of mechanized sugar beet production was analyzed, the geometric dimensions of root tubers under typical planting patterns of typical varieties in main sugar beet production areas were measured, and a three-dimensional geometric model of beet root tubers was established. A device for measuring ridge shape and root tuber distribution was designed, and agronomic parameters during the harvesting period, such as plant spacing, ridge height, unearthed height, and deviation distance of beet root tubers, were measured and analyzed. A spatial model of ridge shape and beet root tuber growth distribution on the ridge during harvesting was established. The overall structure of the deviation information detection mechanism was analyzed and designed, and the structural forms and key parameters of key mechanisms, such as left-right swing detection and up-down floating profiling, were designed on the basis of agronomic parameter analysis. Using the missed detection rate as the evaluation index, field performance tests of the deviation information detection mechanism were conducted. The results revealed that when the average forward speed of the harvester was 0.84 m/s, the average missed detection rate of the deviation information detection mechanism was 0.56%. This method has high adaptability and detection accuracy and achieves a high level of integration for agricultural machinery (detection spatial region of the detection mechanism) and agronomy (beet root distribution spatial region). This study provides a technical basis and methodological reference for improving the quality and efficiency of automatic row correction combined with harvesting operations for crops such as sugar beets. [ABSTRACT FROM AUTHOR]
ISSN:19346344
DOI:10.25165/j.ijabe.20261901.10135