Integrated operational monitoring and fault early warning system for wheat combine harvesters based on CAN bus.
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| Title: | Integrated operational monitoring and fault early warning system for wheat combine harvesters based on CAN bus. |
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| Authors: | Zhang, Weipeng1 zhangwellp@163.com, Guo, Hongze1 johnguohz@163.com, Zhao, Bo1 zhaoboshi@126.com, Liu, Suchun1 suchun1804@163.com, Zhou, Liming1 haibo1129@163.com, Wang, Fengzhu1 wangfengzhu1@126.com, Li, Zongbin1 1307791409@qq.com, Liu, Yangchun1 lyc215@163.com |
| Source: | International Journal of Agricultural & Biological Engineering. Feb2026, Vol. 19 Issue 1, p170-178. 9p. |
| Subjects: | Combines (Agricultural machinery), Controller area network (Computer network), Precision farming, Process control systems, Multisensor data fusion, Fault diagnosis |
| Abstract: | The core objective of this study is to address critical challenges in the operational monitoring and fault early warning of wheat combine harvesters. To this end, this study designed a field-oriented multi-parameter detection system for wheat combine harvesters, which utilizes the CAN bus and virtual instrumentation. Key challenges in this field include three aspects: first, manual inspection is inefficient and lacks automated detection methods, making it difficult to meet the real-time requirements of large-scale operations; second, fault early warning accuracy is low, as single-parameter evaluation is prone to false positives and false negatives; third, monitoring parameters function in isolation, leading to significant data inconsistencies that hinder the early detection of potential faults. To address these issues, this study focuses on three key tasks: establishing a multi-parameter collaborative monitoring framework, optimizing hardware and communication protocols, and developing data processing methods for fault detection and warning. Specifically, sensors for fuel consumption, Hall-effect rotational speed, and strain-gauge torque are deployed at critical components of the harvester. The system then efficiently transmits operational status data via the CAN bus to a processing module, enabling remote real-time monitoring of the harvester's comprehensive operational conditions. For the designed fault warning algorithm, it dynamically adjusts warning thresholds by comparing characteristic parameters with historical data, thereby achieving accurate fault identification and timely warning responses. This study innovatively transmitted multi-source sensor data through the high-anti-interference CAN bus and developed a fault warning algorithm incorporating feature recognition and dynamic thresholds. In simulated experiments, the measurement errors of both instantaneous and cumulative fuel consumption were ≤5%, while the system achieved a warning accuracy of 97.3% and a response time of ≤180 ms. This represents a 15.3-percentage-point improvement in accuracy compared to traditional single-parameter warning systems. Overall, this study addresses the challenge of multi-parameter integrated monitoring for wheat combine harvesters and provides a scalable technical solution for hardware integration and comprehensive data analysis. It also offers a reference for the intelligent upgrading of Chinese harvesters, which is expected to accelerate the transformation of agricultural mechanization toward precision and informatization. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Agricultural & Biological Engineering is the property of International Journal of Agricultural & Biological Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 192721067 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Integrated operational monitoring and fault early warning system for wheat combine harvesters based on CAN bus. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Weipeng%22">Zhang, Weipeng</searchLink><relatesTo>1</relatesTo><i> zhangwellp@163.com</i><br /><searchLink fieldCode="AR" term="%22Guo%2C+Hongze%22">Guo, Hongze</searchLink><relatesTo>1</relatesTo><i> johnguohz@163.com</i><br /><searchLink fieldCode="AR" term="%22Zhao%2C+Bo%22">Zhao, Bo</searchLink><relatesTo>1</relatesTo><i> zhaoboshi@126.com</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Suchun%22">Liu, Suchun</searchLink><relatesTo>1</relatesTo><i> suchun1804@163.com</i><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Liming%22">Zhou, Liming</searchLink><relatesTo>1</relatesTo><i> haibo1129@163.com</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Fengzhu%22">Wang, Fengzhu</searchLink><relatesTo>1</relatesTo><i> wangfengzhu1@126.com</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Zongbin%22">Li, Zongbin</searchLink><relatesTo>1</relatesTo><i> 1307791409@qq.com</i><br /><searchLink fieldCode="AR" term="%22Liu%2C+Yangchun%22">Liu, Yangchun</searchLink><relatesTo>1</relatesTo><i> lyc215@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Agricultural+%26+Biological+Engineering%22">International Journal of Agricultural & Biological Engineering</searchLink>. Feb2026, Vol. 19 Issue 1, p170-178. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Combines+%28Agricultural+machinery%29%22">Combines (Agricultural machinery)</searchLink><br /><searchLink fieldCode="DE" term="%22Controller+area+network+%28Computer+network%29%22">Controller area network (Computer network)</searchLink><br /><searchLink fieldCode="DE" term="%22Precision+farming%22">Precision farming</searchLink><br /><searchLink fieldCode="DE" term="%22Process+control+systems%22">Process control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Multisensor+data+fusion%22">Multisensor data fusion</searchLink><br /><searchLink fieldCode="DE" term="%22Fault+diagnosis%22">Fault diagnosis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The core objective of this study is to address critical challenges in the operational monitoring and fault early warning of wheat combine harvesters. To this end, this study designed a field-oriented multi-parameter detection system for wheat combine harvesters, which utilizes the CAN bus and virtual instrumentation. Key challenges in this field include three aspects: first, manual inspection is inefficient and lacks automated detection methods, making it difficult to meet the real-time requirements of large-scale operations; second, fault early warning accuracy is low, as single-parameter evaluation is prone to false positives and false negatives; third, monitoring parameters function in isolation, leading to significant data inconsistencies that hinder the early detection of potential faults. To address these issues, this study focuses on three key tasks: establishing a multi-parameter collaborative monitoring framework, optimizing hardware and communication protocols, and developing data processing methods for fault detection and warning. Specifically, sensors for fuel consumption, Hall-effect rotational speed, and strain-gauge torque are deployed at critical components of the harvester. The system then efficiently transmits operational status data via the CAN bus to a processing module, enabling remote real-time monitoring of the harvester's comprehensive operational conditions. For the designed fault warning algorithm, it dynamically adjusts warning thresholds by comparing characteristic parameters with historical data, thereby achieving accurate fault identification and timely warning responses. This study innovatively transmitted multi-source sensor data through the high-anti-interference CAN bus and developed a fault warning algorithm incorporating feature recognition and dynamic thresholds. In simulated experiments, the measurement errors of both instantaneous and cumulative fuel consumption were ≤5%, while the system achieved a warning accuracy of 97.3% and a response time of ≤180 ms. This represents a 15.3-percentage-point improvement in accuracy compared to traditional single-parameter warning systems. Overall, this study addresses the challenge of multi-parameter integrated monitoring for wheat combine harvesters and provides a scalable technical solution for hardware integration and comprehensive data analysis. It also offers a reference for the intelligent upgrading of Chinese harvesters, which is expected to accelerate the transformation of agricultural mechanization toward precision and informatization. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Agricultural & Biological Engineering is the property of International Journal of Agricultural & Biological Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.25165/j.ijabe.20261901.8941 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 170 Subjects: – SubjectFull: Combines (Agricultural machinery) Type: general – SubjectFull: Controller area network (Computer network) Type: general – SubjectFull: Precision farming Type: general – SubjectFull: Process control systems Type: general – SubjectFull: Multisensor data fusion Type: general – SubjectFull: Fault diagnosis Type: general Titles: – TitleFull: Integrated operational monitoring and fault early warning system for wheat combine harvesters based on CAN bus. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhang, Weipeng – PersonEntity: Name: NameFull: Guo, Hongze – PersonEntity: Name: NameFull: Zhao, Bo – PersonEntity: Name: NameFull: Liu, Suchun – PersonEntity: Name: NameFull: Zhou, Liming – PersonEntity: Name: NameFull: Wang, Fengzhu – PersonEntity: Name: NameFull: Li, Zongbin – PersonEntity: Name: NameFull: Liu, Yangchun IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19346344 Numbering: – Type: volume Value: 19 – Type: issue Value: 1 Titles: – TitleFull: International Journal of Agricultural & Biological Engineering Type: main |
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