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 c...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.展开更多
Robot-assisted minimally invasive surgery(RMIS)has attracted notable attention because of its numerous advantages over traditional surgery.Nevertheless,the lack of real-time force feedback in RMIS can result in surgic...Robot-assisted minimally invasive surgery(RMIS)has attracted notable attention because of its numerous advantages over traditional surgery.Nevertheless,the lack of real-time force feedback in RMIS can result in surgical errors and damage to delicate tissues.The stringent requirements for the sensitivity and volume of force sensors in RMIS make the design and fabrication of such sensors a considerable challenge.Herein,we present a high-sensitivity three-dimensional(3D)force sensing module consisting of a micro-electro-mechanical piezoresistive sensor chip and a polydimethylsiloxane cap with pyramidal microstructures for force transmission.The sensor chip incorporates four cantilevers with a circular microhole at their fixed ends to concentrate stress in piezoresistive areas;the shape of the microhole was optimized to ensure an appropriate trade-off between high sensitivity and reliability.The proposed 3D force sensor showed more than twice higher sensitivity in the X-,Y-,and Z-axis directions than the sensor based on traditional cantilevers.Furthermore,the proposed sensor exhibited little hysteresis(<1.91%),good stability,and fast response(~30 ms).An artificial neural network was adopted for 3D force decoupling;this network accurately converted resistance changes into 3D forces,showing a prediction error of<2%.Furthermore,the proposed sensor was integrated into a robot to perform various clamping tasks,exhibiting good application potential for RMIS.展开更多
基金This work is financially supported by the National Key Research of Development Program of China(Grant No.2016YFD0702004)the National Natural Science Foundation of China(Grant No.51605196)+3 种基金the Jiangsu Key Research and Development Program of China(Grant No.BE2016356)the Natural Science Foundation of Jiangsu Province of China(Grant No.BK20160532)the National Science Foundation for Post-doctoral Scientists of China(Grant No.2016M591788)Natural Science Foundation of the Higher Education Institutions of Jiangsu Province,China(Grant No.17KJB416003).
文摘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.
基金supported by the National Natural Science Foundation of China(Grant No.62401385)the Natural Science Foundation of Jiangsu Province(Grant No.BK20240803)+1 种基金the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.24KJB460025)the Open Fund of State Key Laboratory of Precision Measurement Technology and Instruments(Grant No.Pilab2413)。
文摘Robot-assisted minimally invasive surgery(RMIS)has attracted notable attention because of its numerous advantages over traditional surgery.Nevertheless,the lack of real-time force feedback in RMIS can result in surgical errors and damage to delicate tissues.The stringent requirements for the sensitivity and volume of force sensors in RMIS make the design and fabrication of such sensors a considerable challenge.Herein,we present a high-sensitivity three-dimensional(3D)force sensing module consisting of a micro-electro-mechanical piezoresistive sensor chip and a polydimethylsiloxane cap with pyramidal microstructures for force transmission.The sensor chip incorporates four cantilevers with a circular microhole at their fixed ends to concentrate stress in piezoresistive areas;the shape of the microhole was optimized to ensure an appropriate trade-off between high sensitivity and reliability.The proposed 3D force sensor showed more than twice higher sensitivity in the X-,Y-,and Z-axis directions than the sensor based on traditional cantilevers.Furthermore,the proposed sensor exhibited little hysteresis(<1.91%),good stability,and fast response(~30 ms).An artificial neural network was adopted for 3D force decoupling;this network accurately converted resistance changes into 3D forces,showing a prediction error of<2%.Furthermore,the proposed sensor was integrated into a robot to perform various clamping tasks,exhibiting good application potential for RMIS.
