Predicting 3D forces of disc tool and soil disturbance area using fuzzy logic model under sensor based soil-bin

A knowledge-based fuzzy logic model was developed on experimental data and used to predict the draft,side and vertical forces and soil disturbance area by disc tillage tool operation.The laboratory research work was conducted to evaluate the performance of the disc tool at three working speeds(1.25 m/s,1.98 m/s and 2.47 m/s,respectively)and depths(0-5 cm,5-10 cm and 10-15 cm,respectively)on paddy soil under soil-bin environment.Further,draft(Fx),side(Fz)and vertical(Fy)forces of disc and soil disturbance area were assessed and predicted towards working speeds and depths.A fuzzy prediction model with two input variables(speed and depth)and four output variables was developed and the Mamdani inference approach was used.Draft,side and vertical forces of disc and soil disturbance area were positively responded 0.97,0.95 and 0.84 and 0.99,respectively.The prediction results showed a close relationship between measured and predicted data.Similarly,the measured and predicted results revealed that the draft,side,vertical forces,and soil disturbance area slightly increased,while increasing the speed and depth of the disc tool.Furthermore,disc forces and soil disturbed area were highly significant(p<0.05)for higher speed towards depth.It was concluded that the fuzzy model may be introduced for predicting the disc forces and soil disturbance area during the disc tillage tool operation with high accuracy.

Investigating spatial and temporal variations of soil moisture content in an arid mining area using an improved thermal inertia model

Mining operations can usually lead to environmental deteriorations. Underground mining activities could cause an extensive decrease in groundwater level and thus a dramatic variation in soil moisture content（SMC）. In this study, the spatial and temporal variations of SMC from 2001 to 2015 at two spatial scales（i.e., the Shendong coal mining area and the Daliuta Coal Mine） were analyzed using an improved thermal inertia model with a long-term series of Landsat TM/OLI（TM=Thematic Mapper and OLI=Operational Land Imager） data. Our results show that at large spatial scale（the Shendong coal mining area）, underground mining activities had insignificant negative impacts on SMC and that at small spatial scale（the Daliuta Coal Mine）, underground mining activities had significant negative impacts on SMC. Trend analysis of SMC demonstrated that areas with decreasing trend of SMC were mainly distributed in the mined area, indicating that underground mining is a primary cause for the drying trend in the mining region in this arid environment.