{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T23:07:35Z","timestamp":1773270455297,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T00:00:00Z","timestamp":1727654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Key Research and Development Plan Project of Heilongjiang Province","award":["2022ZX05B02"],"award-info":[{"award-number":["2022ZX05B02"]}]},{"name":"The Key Research and Development Plan Project of Heilongjiang Province","award":["52275246"],"award-info":[{"award-number":["52275246"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022ZX05B02"],"award-info":[{"award-number":["2022ZX05B02"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52275246"],"award-info":[{"award-number":["52275246"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>High-speed precision planters are subject to high-speed (12~16 km\/h) operation due to terrain undulation caused by mechanical vibration and sensor measurement errors caused by the sowing depth monitoring system\u2019s accuracy reduction problems. Thus, this study investigates multi-sensor data fusion technology based on the sowing depth monitoring systems of high-speed precision planters. Firstly, a sowing depth monitoring model comprising laser, ultrasonic, and angle sensors as the multi-sensor monitoring unit is established. Secondly, these three single sensors are filtered using the Kalman filter. Finally, a multi-sensor data fusion algorithm for optimising four key parameters in the extended Kalman filter (EKF) using an improved sparrow search algorithm (ISSA) is proposed. Subsequently, the filtered data from the three single sensors are integrated to address the issues of mechanical vibration interference and sensor measurement errors. In order to ascertain the superiority of the ISSA-EKF, the ISSA-EKF and SSA-EKF are simulated, and their values are compared with the original monitoring value of the sensor and the filtered sowing depth value. The simulation test demonstrates that the ISSA-EKF-based sowing depth monitoring algorithm for high-speed precision planters, with a mean absolute error (MAE) of 0.083 cm, root mean square error (RMSE) of 0.103 cm, and correlation coefficient (R) of 0.979 achieves high-precision monitoring. This is evidenced by a significant improvement in accuracy when compared with the original monitoring value of the sensor, the filtered value, and the SSA-EKF. The results of a field test demonstrate that the ISSA-EKF-based sowing depth monitoring system for high-speed precision planters enhances the precision and reliability of the monitoring system when compared with the three single-sensor monitoring values. The average MAE and RMSE are reduced by 0.071 cm and 0.075 cm, respectively, while the average R is improved by 0.036. This study offers a theoretical foundation for the advancement of sowing depth monitoring systems for high-speed precision planters.<\/jats:p>","DOI":"10.3390\/s24196331","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T07:19:37Z","timestamp":1727680777000},"page":"6331","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Sowing Depth Monitoring System for High-Speed Precision Planters Based on Multi-Sensor Data Fusion"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9177-501X","authenticated-orcid":false,"given":"Song","family":"Wang","sequence":"first","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1708-0839","authenticated-orcid":false,"given":"Shujuan","family":"Yi","sequence":"additional","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"}]},{"given":"Bin","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"},{"name":"Provincial Key Laboratory of Intelligent Agricultural Machinery Equipment, Daqing 163319, China"}]},{"given":"Yifei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"},{"name":"College of Engineering, Northeast Agricultural University, Harbin 150030, China"}]},{"given":"Shuaifei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"}]},{"given":"Guixiang","family":"Tao","sequence":"additional","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"}]},{"given":"Xin","family":"Mao","sequence":"additional","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"}]},{"given":"Wensheng","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yadav, N., Khanduri, V.P., Singh, B., Dhanai, C.S., Riyal, M.K., Rawat, D., Ahmad, T., and Kumar, M. 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