A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency a...A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency and section-forming quality of mine roadways and engineering tunnels.In order to improve the drilling-positioning accuracy of a three-boom drilling jumbo,we established a kinematics model of the multi-degree-of-freedom(multi-DOF)multi-boom system,using the improved Denavit-Hartenberg(D-H)method,and obtained the mapping relationship between the end position and the amount of motion of each joint.The error of the inverse kinematics calculation for the drilling boom is estimated by an analytical method and a global search algorithm based on particle swarm optimization(PSO)for a straight blasting hole and an inclined blasting hole.On this basis,we propose a back-propagation(BP)neural network optimized by an improved sparrow search algorithm(ISSA)to predict the positioning error of the drilling booms of a three-boom drilling jumbo.In order to verify the accuracy of the proposed error compensation model,we built an automatic-control test platform for the boom,and carried out a positioning error compensation test on the boom.The results show that the average drilling-positioning error was reduced from 9.79 to 5.92 cm,and the error was reduced by 39.5%.Therefore,the proposed method effectively reduces the positioning error of the drilling boom,and improves the accuracy and efficiency of rock drilling.展开更多
Considering energy shortage, large molecules in corn cob and easy separation of solid catalysts, nano oxides are used to transform corn cob into useful chemicals. Because of the microcrystals, nano oxides offer enough...Considering energy shortage, large molecules in corn cob and easy separation of solid catalysts, nano oxides are used to transform corn cob into useful chemicals. Because of the microcrystals, nano oxides offer enough accessible sites for cellulose, hemicellulose and monosaccharide from corn cob hydrolysis and oxidant. Chemical conversion of corn cob to organic acids is investigated over nano ceria, alumina, titania and zirconia under various atmospheres. Liquid products are mainly formic and acetic acids. A small amount of other compounds, such as D-xylose,D-glucose, arabinose and xylitol are also detected simultaneously. The yield of organic acids reaches 25%–29% over the nano oxide of ceria,zirconia and alumina with 3 h reaction time under 453 K and 1.2 MPa O2. The unique and fast conversion of corn cob is directly approached over the nano oxides. The results are comparative to those of biofermentation and offer an alternative method in chemically catalytic conversion of corn cob to useful chemicals in a one-pot chemical process.展开更多
基金National Natural Science Foundation of China(No.12472038)Natural Science Foundation of Jiangsu Province(No.BK20230688)+2 种基金Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.22KJB440004)Key Research and Development Program of Xuzhou(No.KC22404)Research Fund for Doctoral Degree Teachers of Jiangsu Normal University of China(No.22XFRS011).
文摘A rock-drilling jumbo is the main piece of tunneling equipment used in the energy and infrastructure industries in various countries.The positioning accuracy of its drilling boom greatly affects tunneling efficiency and section-forming quality of mine roadways and engineering tunnels.In order to improve the drilling-positioning accuracy of a three-boom drilling jumbo,we established a kinematics model of the multi-degree-of-freedom(multi-DOF)multi-boom system,using the improved Denavit-Hartenberg(D-H)method,and obtained the mapping relationship between the end position and the amount of motion of each joint.The error of the inverse kinematics calculation for the drilling boom is estimated by an analytical method and a global search algorithm based on particle swarm optimization(PSO)for a straight blasting hole and an inclined blasting hole.On this basis,we propose a back-propagation(BP)neural network optimized by an improved sparrow search algorithm(ISSA)to predict the positioning error of the drilling booms of a three-boom drilling jumbo.In order to verify the accuracy of the proposed error compensation model,we built an automatic-control test platform for the boom,and carried out a positioning error compensation test on the boom.The results show that the average drilling-positioning error was reduced from 9.79 to 5.92 cm,and the error was reduced by 39.5%.Therefore,the proposed method effectively reduces the positioning error of the drilling boom,and improves the accuracy and efficiency of rock drilling.
基金supported by the Doctoral Fund of the Ministry of Education of China(Grant No.20100091120035)NSF of China(21103087)
文摘Considering energy shortage, large molecules in corn cob and easy separation of solid catalysts, nano oxides are used to transform corn cob into useful chemicals. Because of the microcrystals, nano oxides offer enough accessible sites for cellulose, hemicellulose and monosaccharide from corn cob hydrolysis and oxidant. Chemical conversion of corn cob to organic acids is investigated over nano ceria, alumina, titania and zirconia under various atmospheres. Liquid products are mainly formic and acetic acids. A small amount of other compounds, such as D-xylose,D-glucose, arabinose and xylitol are also detected simultaneously. The yield of organic acids reaches 25%–29% over the nano oxide of ceria,zirconia and alumina with 3 h reaction time under 453 K and 1.2 MPa O2. The unique and fast conversion of corn cob is directly approached over the nano oxides. The results are comparative to those of biofermentation and offer an alternative method in chemically catalytic conversion of corn cob to useful chemicals in a one-pot chemical process.
