A novel approach for describing and classifying the unevenness of the bottom layer of paddy fields

In recent years, increasing attention has been paid to the unevenness of farmlands since uneven land could reduce the working quality and service life of agricultural machinery. Due to the special constitution of paddy fields, the prevalent road profilers, such as laser range finders or 3D cameras, are unable to profile the bottom layer on which tractor wheels travel. Based on the concept that the acceleration of a working tractor is a direct response to an uneven path, a novel acquisition platform consisting of a real time kinematic global satellite system (RTK-GNSS), an attitude and heading reference system (AHRS) and a rice-transplanter was developed. Then, the corresponding data processing method was proposed in order to describe the unevenness in terms of the displacement power spectral density (DPSD), and the characteristic parameter G(d)(n(0)) was determined in order to classify the unevenness. Experiments on a cement path, a gravel path and a paddy field path were carried out to validate the proposed methodology, and the results showed the following. (1) The travelling speed of the transplanter had little effect on the unevenness classification. (2) The unevenness classifications for the tested cement, gravel, and paddy field paths were class A, B and C, respectively, in terms of the ISO 8608 standard, which was in accordance with the driver's perception. (3) For all the applied paths, the calculated omega values of the PSD were greater than 2, which indicated that long waves were prevalent in the spatial frequency range of interest. In summary, the proposed approach is an efficient and effective way to acquire, describe and classify the unevenness of the bottom layer of paddy fields. This work can serve as a basis for future studies of soil structure monitoring, components' reliability design and adaptive controller development for intelligent farm machinery.