Research On Laser Surface Hardening Of Automobile Cylinder Sleeve

Laser surface hardening is one of a number of surface treatments, which can improve the surface hardness of workpieces and materials, increase wear resistance, reduce friction coefficient, thin grain and microstructure, improve the surface mechanical properties of materials, and also have unique advantages of small or almost no deformation.Laser surface hardening on automobile engine HT150 cylinder sleeve is studied principally in this paper. Firstly, Artificial Neural Network (ANN) technology as one of the artificial intelligence is applied to the prediction of laser surface hardening. Based on the data obtained from the experiment of laser surface hardening on HT150 cylinder liner materials, a neural network forecast model of laser surface hardening index about HT150 Cylinder liner is established by using BP neural network based on MATLAB neural network toolbox, and the correctness of the prediction model is verified through comparing the predicted values with the experimental data.The user-friendly interface of the hardened index predicting system of laser surface hardening on HT150 cylinder liner is compiled by using the MATLAB software.The developed predicting system uses the source code program of the laser surface hardening index prediction model of MATLAB-based BP neural network as a background algorithm. The main function of the forecasting system is that when the materials and the selected process parameters are known, the depth and surface hardness of the hardening layer after the laser surface hardening can be forecast, and when operating the predicting system, user only needs to input three known values of process parameters including laser power, scanning speed and spot diameter, the forecast system is able to predict the hardened indicators under the condition of certain parameters (the surface hardness value and the layer depth value) before the trial; Secondly, the approach of the neural network prediction system with a combination of orthogonal test method is used to determine the best process parameters. Specifically, in order to avoid taking experimental data blindly and randomizedly and reducing the times of the experiment. First, we use cross-cousin to arrange a pilot program, designing some groups of process parameters, and then we use the developed prediction system of laser surface hardening to predict the surface hardness and the layer depth values for each group of these sets of data, instead of specific experiment. Followingly, we have an orthogonal analysis of laser surface hardening (including the orthogonal analysis of the surface hardness and that of the layer depth) for these sets of data and predict the results, obtaining a set of optimum process parameters (P, V, D) values,and in the end,we conduct an additional set of laser surface hardening experiment followed by this group of optimal parameters (P, V, D), validating the accuracy of the prediction system further by comparing the experimental values with the predicted values; Moreover, based on these sets of data and the hardened results obtained above,we study the rule that the single laser processing parameters (laser power P, scanning speed V, spot diameter D) respectively has an effect on the harded index (the surface hardness and the hardened depth). Besides,a combined effect factor P/(DV) value is put forward,and we study the rule that the combined effect factor P/(DV) value has an effect on the harded index (the surface hardness and the hardened depth).Finally, taking the automobile engine block restoration of Zhengzhou Mechanical Institute for a specific example,the front of experimental and theoretical research results of the automobile cylinder liner are applied to the recovery and restoration of the automotive engine block.