Evidence map›Paper›PMID 37798399›Full record

ArticleScientific reports2023

Height detection of crop divider toes of sugarcane harvester based on Kalman adaptive adjustment.

Chunming Wen, Yunzhi Yan, Wanling Wu, Jianheng Li, Bingxu Hou, Wenxuan Cui, Youzong Huang, Kaihua Li, Xiaozhu Long, Hongliang Nong

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Chunming WenGuangxi Key Laboratory of Intelligent Unmanned System and Intelligent Equipment, Nanning, China. wenchunming@gxmzu.edu.cn.
Yunzhi YanCollege of Electronic Information, Guangxi Minzu University, Nanning, China.
Wanling WuCollege of Electronic Information, Guangxi Minzu University, Nanning, China.
Jianheng LiCollege of Electronic Information, Guangxi Minzu University, Nanning, China.
Bingxu HouCollege of Electronic Information, Guangxi Minzu University, Nanning, China.
Wenxuan CuiCollege of Electronic Information, Guangxi Minzu University, Nanning, China.
Youzong HuangState Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, Nanning, China.
Kaihua LiGuangxi Key Laboratory of Intelligent Unmanned System and Intelligent Equipment, Nanning, China.
Xiaozhu LongNanning Taiyin Technology Co., Ltd, Nanning, China.
Hongliang NongGuangxi Agricultural Machinery Research Institute, Nanning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crop divider toes are an essential device of sugarcane harvester. Moving forward against the ground is a critical way to improve the harvesting rate of lodged sugarcane. Height detection is the basis for precise control of crop divider toes moving forward against the ground. Due to the current problem of operating difficulties in manually adjusting the height of crop divider, a height detection system based on a millimeter wave radar sensor was designed to detect the height of crop divider toes from the ground. This paper proposed a height detection method of crop divider toes for sugarcane harvester based on Kalman adaptive adjustment. The data measured by the sensor was pretreated to determine whether the height had changed. Reset the Kalman filter and adjust the parameters when changes occur to improve the filter response speed and ranging accuracy. To adapt to the scenario of quickly adjusting the height of crop divider during the traveling process of sugarcane harvester. A one-way ANOVA test and a two-way ANOVA test were conducted on a simulated test platform. The results of the one-way ANOVA test showed that both forward speed and vegetation cover thickness had a significant effect on height detection accuracy. The results of the two-way ANOVA test showed that the interaction of forward speed and vegetation cover thickness did not have a significant effect on ranging accuracy. It was verified through experiments that both the ranging accuracy and the response speed of height change were significantly improved after the processing of the method in this paper. The mean square error after processing was lower than 2.5 cm. The feasibility of the height detection system was verified by field trials. The results of this study will provide a reference for the design of automatic elevation of crop divider.

Indexed as

SaccharumEdible GrainRadarToes

Identifiers

PMID37798399
PMCPMC10556070

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.