To evaluate the operation comfortability in the master-slave robotic minimally invasive surgery(MIS), an optimal function was built with two operation comfortability decided indices, i.e., the center distance and volu...To evaluate the operation comfortability in the master-slave robotic minimally invasive surgery(MIS), an optimal function was built with two operation comfortability decided indices, i.e., the center distance and volume contact ratio. Two verifying experiments on Phantom Desktop and Micro Hand S were conducted. Experimental results show that the operation effect at the optimal relative location is better than that at the random location, which means that the optimal function constructed in this paper is effective in optimizing the operation comfortability.展开更多
This work aims at selecting optimal operating variables to obtain the minimum specific energy(SE) in sawing of rocks.A particular granite was sampled and sawn by a fully automated circular diamond sawblades.The periph...This work aims at selecting optimal operating variables to obtain the minimum specific energy(SE) in sawing of rocks.A particular granite was sampled and sawn by a fully automated circular diamond sawblades.The peripheral speed,the traverse speed,the cut depth and the flow rate of cooling fluid were selected as the operating variables.Taguchi approach was adopted as a statistical design of experimental technique for optimization studies.The results were evaluated based on the analysis of variance and signal-to-noise ratio(S/N ratio).Statistically significant operating variables and their percentage contribution to the process were also determined.Additionally,a statistical model was developed to demonstrate the relationship between SE and operating variables using regression analysis and the model was then verified.It was found that the optimal combination of operating variables for minimum SE is the peripheral speed of 25 m/s,the traverse speed of 70 cm/min,the cut depth of 2 cm and the flow rate of cooling fluid of 100 mL/s.The cut depth and traverse speed were statistically determined as the significant operating variables affecting the SE,respectively.Furthermore,the regression model results reveal that the predictive model has a high applicability for practical applications.展开更多
Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimization of furnaces could not only help to improve product quality but also benefit to reduce energy consum...Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimization of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control(CMPC)strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The controllers connected with two kinds of communication networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reasonable CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.展开更多
基金Supported by the National High Technology Research and Development Program of China("863" Program,No.2012AA02A606)the Research Project of State Key Laboratory of Mechanical System and Vibration(MSV201412)
文摘To evaluate the operation comfortability in the master-slave robotic minimally invasive surgery(MIS), an optimal function was built with two operation comfortability decided indices, i.e., the center distance and volume contact ratio. Two verifying experiments on Phantom Desktop and Micro Hand S were conducted. Experimental results show that the operation effect at the optimal relative location is better than that at the random location, which means that the optimal function constructed in this paper is effective in optimizing the operation comfortability.
文摘This work aims at selecting optimal operating variables to obtain the minimum specific energy(SE) in sawing of rocks.A particular granite was sampled and sawn by a fully automated circular diamond sawblades.The peripheral speed,the traverse speed,the cut depth and the flow rate of cooling fluid were selected as the operating variables.Taguchi approach was adopted as a statistical design of experimental technique for optimization studies.The results were evaluated based on the analysis of variance and signal-to-noise ratio(S/N ratio).Statistically significant operating variables and their percentage contribution to the process were also determined.Additionally,a statistical model was developed to demonstrate the relationship between SE and operating variables using regression analysis and the model was then verified.It was found that the optimal combination of operating variables for minimum SE is the peripheral speed of 25 m/s,the traverse speed of 70 cm/min,the cut depth of 2 cm and the flow rate of cooling fluid of 100 mL/s.The cut depth and traverse speed were statistically determined as the significant operating variables affecting the SE,respectively.Furthermore,the regression model results reveal that the predictive model has a high applicability for practical applications.
文摘Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimization of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control(CMPC)strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The controllers connected with two kinds of communication networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reasonable CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.