Application Study Of Rail Remoulding Cutting Parmeters Optimization Based On BP-GA Methods

The material of railroad rail is the U71Mn High Manganese Steel (HMS) with high hard hardness and cutting difficulty. Due to long term wheel-rail relationship, the railroad rail emerges various damage. It is very difficult to cut the used rail with strain hardening, the used rail is a typical difficult machining materials.At present, the selection of the HMS cutting parameters usually depends on experience it does not make sense that the selection of cutting parameters is by experience. alsoit is the main cause that leads to wear and damage of the tool and low efficiency.Based on the analytical research of HMS characteristics, firstly, we discuss that tool material and cutter geometrical angles effect on the cutting. Secondly, we analyze and summarize the cutting force and cutting temperature in the machining process. Lastly, we get the tool life empirical formula of the milling HMS by means of multi-factors orthogonal experiment design, the formula is as a constraint condition in the BP-GA optimization modelWe establish the mathematical model of optimization parameter, through analyzing the each factor which affects the cutting results in the process, it has obtained that the constraint conditions and optimization function. Ultimately, We work out the practical problem by means of BP Neural Network and Genetic Algorithms(BP-GA). The mathematical model of machining the High Manganese Steel and the Genetic Algorithm in this paper is useful to production, which make the theoretical basis and application guidance for machining High Manganese Steel.