Turning parameter prediction method for machining TC4 titanium alloy workpiece

A prediction method, titanium alloy technology, applied in metal processing machinery parts, metal processing equipment, manufacturing tools, etc., can solve the problems of slow convergence speed, weakened stability, and low convergence accuracy in the later stage.

Pending Publication Date: 2019-10-15
XUZHOU NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

Although the basic particle swarm optimization method has many advantages, its low convergence accuracy, slow convergence speed in the later per

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  • Turning parameter prediction method for machining TC4 titanium alloy workpiece
  • Turning parameter prediction method for machining TC4 titanium alloy workpiece
  • Turning parameter prediction method for machining TC4 titanium alloy workpiece

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Embodiment Construction

[0057] This embodiment provides a method for predicting the A sound level based on the physical quantity of the workpiece, such as figure 1 As shown, the method specifically includes the following steps:

[0058] (1) Take the turning speed, feed rate, and back cutting amount as the turning parameters to be predicted for processing TC4 titanium alloy workpieces, aiming at the lowest turning temperature, the smallest surface roughness of the workpiece, and the largest material removal rate, and satisfying the turning parameters Under the condition of the lower limit, a prediction model for turning parameters is constructed.

[0059] Among them, the constructed turning parameter prediction model is specifically:

[0060] Minimum turning temperature objective function: t=46.11n 0.6084 f 0.0939 a p 0.0043

[0061] Minimum workpiece surface roughness objective function: R a =2.85n -0.2836 f 0.6141 a p 0.5181

[0062] Maximum material removal rate objective function: Q=10...

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Abstract

The invention discloses a turning parameter prediction method for machining a TC4 titanium alloy workpiece. The method comprises the steps that (1) taking the turning rotating speed, the feeding amount and the back cutting depth as to-be-predicted turning parameters for machining the TC4 titanium alloy workpiece, taking the minimum turning temperature, the minimum workpiece surface roughness and the maximum material removal rate as targets, and constructing a turning parameter prediction model under the condition that the upper limit and the lower limit of the turning parameters are met; (2) changing the turning parameter prediction model into a coding optimization model; and (3) setting upper and lower limits of turning parameters of a to-be-predicted machining workpiece, inputting the upper and lower limits into the coding optimization model established in the step (2), and solving the coding optimization model by using an adaptive random simplified particle swarm optimization algorithm to obtain optimal configuration of the turning speed, the feeding amount and the back cutting depth. According to the method, the turning parameters of the TC4 titanium alloy workpiece can be rapidly predicted.

Description

technical field [0001] The invention relates to machining data prediction, in particular to a turning parameter prediction method for processing TC4 titanium alloy workpieces. Background technique [0002] Turning, milling, planing and grinding are the four methods of modern mechanical processing, and their level determines the country's industrial level to a certain extent. Turning, as one of the important methods, is a current research hotspot. [0003] Other scholars have made a lot of valuable work on the optimization of turning parameters. Miodragovic [Document: Miodragovic G.R, Dordevic V, Bulatovic R.R, et al. Optimization of multi-passturning and multi-pass face milling using subpopulation firefly algorithm [J]. The institution of mechanical engineers part C-journal of mechanical engineering science, 2 233(5):1520-1540.] etc. Considering the minimum processing cost, the shortest processing time and the maximum profit, the improved firefly algorithm is used to optim...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N3/00B23Q17/09
CPCG06N3/006B23Q17/0904G06F2119/06G06F30/20
Inventor 张鑫邹德旋喻秋
Owner XUZHOU NORMAL UNIVERSITY
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