Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM
In order to detect the assembly quality of the combine harvester accurately and effectively, a method for the assembly quality inspection of the combine harvester based on the improved whale algorithm (IWOA) to optimize the least square support vector machine is proposed. Aiming at the characteristi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2022/5181360 |
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| _version_ | 1832556678677004288 |
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| author | Sixia Zhao Yizhen Ma Mengnan Liu Xiaoliang Chen Liyou Xu |
| author_facet | Sixia Zhao Yizhen Ma Mengnan Liu Xiaoliang Chen Liyou Xu |
| author_sort | Sixia Zhao |
| collection | DOAJ |
| description | In order to detect the assembly quality of the combine harvester accurately and effectively, a method for the assembly quality inspection of the combine harvester based on the improved whale algorithm (IWOA) to optimize the least square support vector machine is proposed. Aiming at the characteristics of whale optimization algorithm’s weak search ability and easy maturity, this paper introduces the cosine control factor and the sine time-varying adaptive weight to improve it and uses the benchmark function to verify the general adaptability of the algorithm. Combined with the local mean decomposition (LMD), the assembly quality inspection model of the combine harvester was established and applied to the Dongfanghong 4LZ-9A2 combine harvester for experimental verification. The experimental results show that the IWOA proposed in this paper has better optimization ability and adaptability. The average accuracy of the IWOA model proposed in this paper reaches 90.5%, which is 4% higher than that of the WOA model, and the standard deviation of the average accuracy is reduced by 0.15%, which indicates that the IWOA model has better stability. |
| format | Article |
| id | doaj-art-6d46eddad2cc493ab8a58337f529c06b |
| institution | Kabale University |
| issn | 1875-9203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-6d46eddad2cc493ab8a58337f529c06b2025-02-03T05:44:39ZengWileyShock and Vibration1875-92032022-01-01202210.1155/2022/5181360Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVMSixia Zhao0Yizhen Ma1Mengnan Liu2Xiaoliang Chen3Liyou Xu4College of Vehicle and Traffic EngineeringCollege of Vehicle and Traffic EngineeringState Key Laboratory of Power System of TractorCollege of Vehicle and Traffic EngineeringCollege of Vehicle and Traffic EngineeringIn order to detect the assembly quality of the combine harvester accurately and effectively, a method for the assembly quality inspection of the combine harvester based on the improved whale algorithm (IWOA) to optimize the least square support vector machine is proposed. Aiming at the characteristics of whale optimization algorithm’s weak search ability and easy maturity, this paper introduces the cosine control factor and the sine time-varying adaptive weight to improve it and uses the benchmark function to verify the general adaptability of the algorithm. Combined with the local mean decomposition (LMD), the assembly quality inspection model of the combine harvester was established and applied to the Dongfanghong 4LZ-9A2 combine harvester for experimental verification. The experimental results show that the IWOA proposed in this paper has better optimization ability and adaptability. The average accuracy of the IWOA model proposed in this paper reaches 90.5%, which is 4% higher than that of the WOA model, and the standard deviation of the average accuracy is reduced by 0.15%, which indicates that the IWOA model has better stability.http://dx.doi.org/10.1155/2022/5181360 |
| spellingShingle | Sixia Zhao Yizhen Ma Mengnan Liu Xiaoliang Chen Liyou Xu Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM Shock and Vibration |
| title | Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM |
| title_full | Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM |
| title_fullStr | Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM |
| title_full_unstemmed | Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM |
| title_short | Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM |
| title_sort | assembly quality inspection of combine harvester based on whale algorithm optimization lssvm |
| url | http://dx.doi.org/10.1155/2022/5181360 |
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