PERIODICITY AND STOCHASTIC HIERARCHICAL ORDERS OF SOIL CUTTING FORCE DATA DETECTED BY AN “AUTO-REGRESSIVE ERROR DISTRIBUTION FUNCTION” (AREF)

Abstract

In this article, we describe a methodology to estimate typical soil properties such as moisture content andcompactness using soil cutting force fluctuation information obtained by a conventional chisel. The data were obtained ina Yolo loam field under four different soil conditions: tilled dry (TD), tilled wet (TW), untilled dry (UD), and untilled wet (UW).In order to quantify the complexity of fluctuating patterns of soil cutting force and soil physical properties, we introduce anew time-series analysis technique, the auto-regressive error function (AREF). We found that the frequency distributionpattern of the modified time-series data with the time lag showed a very clear shift with change in the time lag. The AREFwas developed to detect this pattern shift. The soil cutting force time-series data obtained using an instrumented chisel wereanalyzed using power spectrum and AREF techniques. The spatial power spectrum analysis detected periodicity under drysoil conditions. On the other hand, the AREF showed a very clear hierarchical order, which was caused by the existence ofself-similarity in the fluctuating patterns of soil cutting forces under all four tested soil conditions. Two AREF parameterswere found to be related to soil moisture content and cone index, but not bulk density.