A model is developed for predicting the correlation between processing parameters and the technical target of double glow by applying artificial neural network (ANN). The input parameters of the neural network (NN) ar...A model is developed for predicting the correlation between processing parameters and the technical target of double glow by applying artificial neural network (ANN). The input parameters of the neural network (NN) are source voltage, workplace voltage, working pressure and distance between source electrode and workpiece. The output of the NN model is three important technical targets, namely the gross element content, the thickness of surface alloying layer and the absorption rate (the ratio of the mass loss of source materials to the increasing mass of workpiece) in the processing of double glow plasma surface alloying. The processing parameters and technical target are then used as a training set for an artificial neural network. The model is based on multiplayer feedforward neural network. A very good performance of the neural network is achieved and the calculated results are in good agreement with the experimental ones.展开更多
The Ni-Cr-Mo-Cu multi-element surface alloying with the electric brushplating Ni interlayer on the low carbon steel substrate has been investigated. By theelectrochemical method in 3.5 percent (mass fraction) NaCl sol...The Ni-Cr-Mo-Cu multi-element surface alloying with the electric brushplating Ni interlayer on the low carbon steel substrate has been investigated. By theelectrochemical method in 3.5 percent (mass fraction) NaCl solution, the corrosion resistance of thecomposite alloying layer and single alloying layer is determined. The experimental results showthat the corrosion resistance of the composite alloying layer is obviously better than that of thesingle alloying layer. The structure and composition of passive films formed on the two kinds ofalloyed layers after electrochemical tests in 3.5 percent NaCl solution have been studied usingX-ray photoelectron spectroscopy (XPS). It is concluded that the double glow plasma surface alloyingof low carbon steel with the electric brush plating Ni interlayer is an appropriate technique toenhance the corrosion resistance compared with the single double glow surface alloying.展开更多
文摘A model is developed for predicting the correlation between processing parameters and the technical target of double glow by applying artificial neural network (ANN). The input parameters of the neural network (NN) are source voltage, workplace voltage, working pressure and distance between source electrode and workpiece. The output of the NN model is three important technical targets, namely the gross element content, the thickness of surface alloying layer and the absorption rate (the ratio of the mass loss of source materials to the increasing mass of workpiece) in the processing of double glow plasma surface alloying. The processing parameters and technical target are then used as a training set for an artificial neural network. The model is based on multiplayer feedforward neural network. A very good performance of the neural network is achieved and the calculated results are in good agreement with the experimental ones.
文摘The Ni-Cr-Mo-Cu multi-element surface alloying with the electric brushplating Ni interlayer on the low carbon steel substrate has been investigated. By theelectrochemical method in 3.5 percent (mass fraction) NaCl solution, the corrosion resistance of thecomposite alloying layer and single alloying layer is determined. The experimental results showthat the corrosion resistance of the composite alloying layer is obviously better than that of thesingle alloying layer. The structure and composition of passive films formed on the two kinds ofalloyed layers after electrochemical tests in 3.5 percent NaCl solution have been studied usingX-ray photoelectron spectroscopy (XPS). It is concluded that the double glow plasma surface alloyingof low carbon steel with the electric brush plating Ni interlayer is an appropriate technique toenhance the corrosion resistance compared with the single double glow surface alloying.
