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Prediction Method of Tractor Ploughing Resistance Based on Multi-source Heterogeneous Sensor Data
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Xiaoxu SUN, Yue SONG, Kai ZHANG, Zheng WANG, Zhixiong LU
Transactions of the Chinese Society for Agricultural Machinery | 2025, 56(12) : 131 - 139
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Transactions of the Chinese Society for Agricultural Machinery | 2025, 56(12): 131-139
• Special Column of Key Technologies for Intelligent Agricultural Power Equipment •
Prediction Method of Tractor Ploughing Resistance Based on Multi-source Heterogeneous Sensor Data
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Xiaoxu SUN, Yue SONG, Kai ZHANG, Zheng WANG, Zhixiong LU
Affiliations
  • College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Published: 2025-12-25 doi: 10.6041/j.issn.1000-1298.2025.12.011
Outline
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In order to realize the precise control of ploughing resistance and improve the traction efficiency of tractor in ploughing operation, a prediction method of ploughing resistance was proposed. A plowing resistance perception model based on the upper pull rod force was proposed, and the experimental verification was carried out. In view of the problem that the measurement results were unstable by only sensing the ploughing resistance through the upper pull rod force in the actual field operation, a ploughing operation parameter test platform was built, and the multi-source heterogeneous sensor data based on tillage depth, upper pull rod force, vehicle speed and wheel speed were obtained and the prediction samples were constructed. The wavelet threshold denoising (WTD) and sparrow search algorithm (SSA) were introduced into the least squares support vector machine (LSSVM), and the combined prediction model of ploughing resistance based on WTD-SSA-LSSVM was established and the model performance was verified. The results showed that the model prediction method had higher accuracy than that of the upper pull rod force. In addition, different prediction methods were compared. The R2, MAE, RMSE and MAPE of the test set obtained by the combined prediction model method were 0.97, 118.1 N, 151.4 N and 2.2%, respectively. Compared with prediction models of LSSVM and SSA-LSSVM, R2 was increased by 8.9% and 5.4%, respectively. MAE was decreased by 49.7% and 42.2%, respectively. RMSE was decreased by 46.7% and 39.1%, respectively. MAPE was decreased by 56.8% and 48.8%, respectively. Therefore, the method proposed had better prediction performance and was more suitable for the prediction of tractor plough resistance.

tractor  /  ploughing resistance  /  model prediction  /  least squares support vector machine  /  multi-source heterogeneous sensor data
孙晓旭, 宋悦, 张凯, 王峥, 鲁植雄. 基于多源异构传感器数据的拖拉机犁耕阻力预测方法. 农业机械学报, 2025 , 56 (12) : 131 -139 . DOI: 10.6041/j.issn.1000-1298.2025.12.011
Xiaoxu SUN, Yue SONG, Kai ZHANG, Zheng WANG, Zhixiong LU. Prediction Method of Tractor Ploughing Resistance Based on Multi-source Heterogeneous Sensor Data[J]. Transactions of the Chinese Society for Agricultural Machinery, 2025 , 56 (12) : 131 -139 . DOI: 10.6041/j.issn.1000-1298.2025.12.011
Year 2025 volume 56 Issue 12
210
92
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doi: 10.6041/j.issn.1000-1298.2025.12.011
  • Receive Date:2025-05-23
  • Online Date:2026-09-30
  • Published:2025-12-25
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  • Received:2025-05-23
  • Revised:2025-07-01
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    College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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