Straightening method based on support vector machine for workpiece deformation

A support vector machine and workpiece technology, applied in the field of workpiece correction, can solve problems affecting the accuracy of deformation correction, difficult to do, lack of learning, etc., to achieve remote operation monitoring, save test funds and time, and improve efficiency and accuracy Effect

Inactive Publication Date: 2012-07-25
SHANGHAI MARITIME UNIVERSITY
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  • Abstract
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  • Claims
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Problems solved by technology

[0006] In practice, using neural network and other methods to determine the correction process parameters and determine the correction effect, it is necessary to provide a large and reliable training data to build a calculation mod

Method used

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  • Straightening method based on support vector machine for workpiece deformation
  • Straightening method based on support vector machine for workpiece deformation
  • Straightening method based on support vector machine for workpiece deformation

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Example Embodiment

[0017] Hereinafter, preferred embodiments of the present invention are given in conjunction with the drawings to illustrate the technical solutions of the present invention in detail. figure 1 It is a specific flow chart of the workpiece intelligent correction method based on the support vector machine algorithm of the present invention. The present invention includes the following steps:

[0018] (1). Collect work piece deformation correction data: Carry out work piece correction tests under different materials, different sizes, different deformation positions, and different degrees of deformation, and collect correction force position and size data. If the conditions are not met, past experience data can be collected.

[0019] (2). Create a training sample set

[0020] Sort out the workpiece deformation correction test data obtained in step 1, and construct a training sample set. The input parameters include workpiece material parameters, shape dimensions, deformation position, ...

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Abstract

The invention relates to a straightening method based on a support vector machine for workpiece deformation. The method includes steps of (1) collecting test data of workpiece deformation straightening; (2) building up a training sample set; (3) building up a straightening parameter predicting model based on computing method of the support vector machine; and (4) performing workpiece straightening process: inputting actual workpiece deformation data into the predicting model, automatically calculating straightening position and straightening force parameters, and inputting the calculated data into a straightening device to perform automatic workpiece straightening. By the aid of a small amount of workpiece straightening test data, the straightening method is capable of realizing intelligent predicting of the straightening parameter, and accordingly, a large amount of test cost and time is saved, and efficiency and precision of the workpiece straightening are enhanced.

Description

Technical field [0001] The invention relates to the technical field of workpiece correction, in particular to a method for correcting workpiece deformation based on a support vector machine. Background technique [0002] During the processing of metal workpieces such as casting, forging, heat treatment, etc., due to uneven stress, uneven heating and cooling, transportation and stacking, etc., residual stresses are usually generated inside, resulting in varying degrees of residual deformation. These deformations seriously affect the performance of the workpiece and must be corrected. [0003] At present, most of the domestic workpiece correction equipment is a manually operated machine with a simple structure. It mainly depends on the experience of workers to determine the correction process parameters. It can realize automatic operation according to different correction requirements. It has disadvantages such as low work efficiency and poor stability, and it is difficult to meet la...

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Application Information

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IPC IPC(8): B21D1/00B21D3/00
Inventor 刘龙董达善
Owner SHANGHAI MARITIME UNIVERSITY
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