Ni-W-P composite coatings reinforced by Ce O2 and Si O2 nano-particles on the surface of common carbon steels, were prepared by double pulse electrodeposition. The crystallization course was characterized by phase str...Ni-W-P composite coatings reinforced by Ce O2 and Si O2 nano-particles on the surface of common carbon steels, were prepared by double pulse electrodeposition. The crystallization course was characterized by phase structures, crystallinity, grain sizes and microstructures. The results indicate that as-deposited composite coating is amorphous. Whereas it turns into the crystalline structure with 98.25% crystallinity, and Ni3 P, Ni2 P and Ni5P2 alloy phases precipitate from structures at 400 °C. Thereafter, Ni2 P and Ni5P2 metastable alloy phases turn into Ni3 P stable alloy phase at 500 °C. The crystallization course of the composite coating has finished when being heat-treated at 700 °C. The average sizes of Ni grains increase with the rise of heat treatment temperature from400 °C to 700 °C. Ce O2 and Si O2 nano-particles deposited into Ni-W-P alloys can delay the crystallization course and habit the growth of alloy phases.展开更多
The hot-dip galvanizing line(HDGL) is a typical order-driven discrete-event process in steelmaking. It has some complicated dynamic characteristics such as a large time-varying delay, strong nonlinearity, and unmeasur...The hot-dip galvanizing line(HDGL) is a typical order-driven discrete-event process in steelmaking. It has some complicated dynamic characteristics such as a large time-varying delay, strong nonlinearity, and unmeasured disturbance, all of which lead to the difficulty of an online coating weight controller design. We propose a novel neural network based control system to solve these problems. The proposed method has been successfully applied to a real production line at Va Lin LY Steel Co., Loudi, China. The industrial application results show the effectiveness and efficiency of the proposed method, including significant reductions in the variance of the coating weight and the transition time.展开更多
基金Project(20806035)supported by the National Natural Science Foundation of ChinaProject(2009CI026)supported by the Back-up Personnel Foundation of Academic and Technology Leaders of Yunnan Province,ChinaProject(KKZ6200927001)supported by the Opening Fund of Key Laboratory of Inorganic Coating Materials,Chinese Academy of Sciences
文摘Ni-W-P composite coatings reinforced by Ce O2 and Si O2 nano-particles on the surface of common carbon steels, were prepared by double pulse electrodeposition. The crystallization course was characterized by phase structures, crystallinity, grain sizes and microstructures. The results indicate that as-deposited composite coating is amorphous. Whereas it turns into the crystalline structure with 98.25% crystallinity, and Ni3 P, Ni2 P and Ni5P2 alloy phases precipitate from structures at 400 °C. Thereafter, Ni2 P and Ni5P2 metastable alloy phases turn into Ni3 P stable alloy phase at 500 °C. The crystallization course of the composite coating has finished when being heat-treated at 700 °C. The average sizes of Ni grains increase with the rise of heat treatment temperature from400 °C to 700 °C. Ce O2 and Si O2 nano-particles deposited into Ni-W-P alloys can delay the crystallization course and habit the growth of alloy phases.
文摘The hot-dip galvanizing line(HDGL) is a typical order-driven discrete-event process in steelmaking. It has some complicated dynamic characteristics such as a large time-varying delay, strong nonlinearity, and unmeasured disturbance, all of which lead to the difficulty of an online coating weight controller design. We propose a novel neural network based control system to solve these problems. The proposed method has been successfully applied to a real production line at Va Lin LY Steel Co., Loudi, China. The industrial application results show the effectiveness and efficiency of the proposed method, including significant reductions in the variance of the coating weight and the transition time.
