Traveling control method adapted to different paddy ground conditions with feedforward compensation for crawler combine harvester based on online tracking error prediction

He, Yongqiang; Zhou, Jun; Sun, Jingwei; Jia, Hongbo; Gemechu, Tamiru Tesfaye

doi:10.1016/j.compag.2024.108853

Computers and Electronics in Agriculture

2024

DOI: 10.1016/j.compag.2024.108853

|View full text |Cite

Traveling control method adapted to different paddy ground conditions with feedforward compensation for crawler combine harvester based on online tracking error prediction

Yongqiang He,

Jun Zhou,

Jingwei Sun

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article4

Relationship

Self Cite0

Independent4

Authors

Journals

Cited by 4 publications

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Detection of rice panicle density for unmanned harvesters via RP-YOLO

Sun,

Zhou,

et al. 2024

Computers and Electronics in Agriculture

View full text Add to dashboard Cite

Detection of rice panicle density for unmanned harvesters via RP-YOLO

Sun,

Zhou,

et al. 2024

Computers and Electronics in Agriculture

View full text Add to dashboard Cite

A meta transfer learning-driven few-shot fault diagnosis method for combine harvester gearboxes

She,

Yang,

Duan

et al. 2024

Computers and Electronics in Agriculture

View full text Add to dashboard Cite

Design for Copying Grouser and Bionic Convex Hull Patterns on Track Surfaces of Crawler Combine Harvesters

Yuan,

Tang,

Liu

et al. 2024

Agriculture

View full text Add to dashboard Cite

In the rainy season, which often has uncertain rainfall, crawler combine harvesters have difficulty traversing wet and soft rice fields. A large amount of clay is often accumulated on the track surfaces, resulting in frequent slipping and sinking, which greatly affects the operational performance and harvesting efficiency of crawler combine harvesters. To address this issue, this paper proposes a high-traction track grouser based on the structure of an ostrich’s foot sole. First, a traction force mathematical model is constructed to analyze the interaction between a track grouser and wet and soft rice fields, and parameter optimization is conducted. Then, the bionic information of a dung beetle’s non-smooth body surface is extracted, and the surface of the track is designed with biomimetic convex hull patterns based on the geometric similarity principle and adhesive experiments. Finally, the analysis results indicate that the optimized track grouser significantly improved the traction of the track in wet and soft rice fields. For the track plate with a bionic desorption convex hull pattern, a convex hull diameter of 6 mm, convex hull spacing of 8.25 mm, and convex hull height of 3 mm led to good adhesion reduction and desorption effects in wet and soft soil.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Traveling control method adapted to different paddy ground conditions with feedforward compensation for crawler combine harvester based on online tracking error prediction

Cited by 4 publications

References 21 publications

Detection of rice panicle density for unmanned harvesters via RP-YOLO

Detection of rice panicle density for unmanned harvesters via RP-YOLO

A meta transfer learning-driven few-shot fault diagnosis method for combine harvester gearboxes

Design for Copying Grouser and Bionic Convex Hull Patterns on Track Surfaces of Crawler Combine Harvesters

Contact Info

Product

Resources

About