耕作机具耕深在线测量装置设计与试验OA

Tillage depth is a critical parameter for evaluating the performance of agricultural tillage equipment.To overcome the limitations of manual measurement methods,including high error rates,low efficiency,and the lack of real-time monitoring,a universal online tillage depth measurement system was presented.The system integrated a laser distance sensor with a nine-axis attitude sensor to dynamically capture operational data from tillage tools.Utilizing Gaussian and Kalman filtering algorithms,the system effectively reduced noise and fuses data,enabling real-time calculation of tillage depth.The results were transmitted wirelessly via LoRa to an operator terminal for display,storage,and analysis.Comprehensive soil bin experiments were conducted to validate the system's performance.In static tests,the weighted fusion data demonstrated a maximum error of 0.43 cm,an average error of 0.26 cm,and a root mean square error of 0.24 cm when compared with results of manual measurements.Dynamic tests with target depths of 8 cm,12 cm,and 15 cm yielded maximum deviations of 1.63 cm,1.80 cm,and 1.18 cm,respectively,with corresponding depth variation coefficients of 6.37%,5.28%,and 2.68%.These results confirmed the system's ability to significantly enhance the efficiency,accuracy,and digitalization of agricultural machinery testing.The proposed system provided a reliable,real-time monitoring solution for precision agriculture,reducing reliance on manual methods and improving operational transparency.Its adaptability to various tillage conditions and high measurement reliability make it a valuable tool for advancing agricultural mechanization and smart farming practices.