Research on controlling method for different classifications of laser surface strengthening process by using artificial neural network

Experiments show that metal surface properties can be more or less modified by laser surface strengthening treatment. In this paper four different strengthening classifications of structure and characteristic of phase layer: non-transformation hardening, transformation hardening, shallow melting and melting were analyzed and the relationship between the four strengthening classifications and laser processing parameters: laser power (P), laser processing beam diameter (D), laser scanning velocity (v) were established by using BP neural network. HT300, as a kind of main high strength cast iron, was widely used for making gears, camshafts, chain wheel, etc. The study results, using HT300 as experimental material, show that laser processing parameters can be chosen conveniently and material surface quality is controlled effectively.