A fuzzy decision-making algorithm-based header height measurement system for combine harvester

Header height is a critical parameter during the operation of the harvester. Accurately and consistently measuring header height is challenging due to adverse factors such as uneven farmland topography, irregular ground surfaces, weeds, and crop stubble. This study proposes an intelligent calculation algorithm based on the fusion of the Kalman filter and fuzzy decision-making (KFF) to achieve accurate, stable, reliable and real-time header height measurement and a header height online measurement system (HMS) for combine harvester is developed. The algorithm first calculates the initial header height according to the trajectory of the header. The Kalman filter algorithm then predicts the header height for the subsequent state. Finally, the accurate header height is calculated after fuzzy decision-making. The algorithm effectively addresses the interference caused by complex working conditions on header height measurement. A band-pass filter is designed and a signal transmitter based on an STM32 embedded microcontroller is developed to counter the interference characteristics of header bumps and vibration on the height detection signal. Furthermore, the header height online measurement system (HMS) software for combine harvesters was developed. This system handles sensor data collection, conducts header height fusion calculations, and facilitates human-machine interaction. This study carries out field tests under varying combine harvester operating speeds and initial static header heights (ISHH). Results showed that the measurement error is mainly distributed in the range of- 0.5 to 0.5 cm. The mean relative error (MRE) of the absolute header height measurement error was 0.9 %, 1.0 %, 1.0 %, and 1.0 % at velocities of 2, 3, 4, and 5 km/h, respectively. The average MRE was 0.975 %. Furthermore, the MRE of the measurement results was 1.6 %, 1.0 %, 0.8 % and 0.6 % for different ISHH of 10, 15, 20 and 25 cm, respectively. The mean MRE was 1 %. ANOVA results showed that different speeds and ISHH do not significantly impact the measurement results of the HMS. The HMS developed in this study exhibited a high degree of precision and stability, providing critical support for the continuous regulation of header height.