Online prediction method for crossbeam loading speed of large-sized die forging press based on Taylor expansion

A technology of die forging press and prediction method, applied in the field of forging

Inactive Publication Date: 2016-07-27
CENT SOUTH UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide an online prediction method for the upper beam speed of a large die forging press based on Taylor e

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  • Online prediction method for crossbeam loading speed of large-sized die forging press based on Taylor expansion
  • Online prediction method for crossbeam loading speed of large-sized die forging press based on Taylor expansion
  • Online prediction method for crossbeam loading speed of large-sized die forging press based on Taylor expansion

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Embodiment Construction

[0061]The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0062] The present invention is an online prediction method of beam speed on a large die forging press, the flow chart of which is as follows figure 1 shown. Taking the forging process of an aluminum alloy (Al-1100) forging as an example, the implementation details of the online prediction of the beam speed on the large-scale die forging press related to the present invention are introduced in detail. The method includes:

[0063] Step 1: Predict the speed of the upper beam at the next moment based on the online perception of the load of the large die forging press (system input) and the speed of the upper beam (system output) during the forging process;

[0064] A forging test was carried out on an aluminum alloy (Al-1100) forging, and the load of a large die forging press during the forging process (such as figure 2 shown) and the upper b...

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Abstract

The invention provides an online prediction method for a crossbeam loading speed of a large-sized die forging press based on Taylor expansion. The method comprises the following steps: (1) predicting a next-moment crossbeam loading speed by sensing a load (system input) and the crossbeam loading speed (system output) of the large-sized die forging press in a forging process on line; (2) popularizing and defining similar continuous conductive conditions according to a Taylor expansion condition, judging intermittent points of a system by introducing a continuous conductive index, and determining a number of continuous points and an order of a model; and (3) performing parameter identification by using a multiple regression method according the system input and the system output of online sensing, and implementing online detection of the crossbeam loading speed of the large-sized die forging press through model matching. Through adoption of the method, the crossbeam loading speed of the large-sized die forging press can be predicted on line rapidly and accurately, and a theoretical basis and technical support are provided for effective control of the large-size die forging press.

Description

Technical field: [0001] The invention belongs to the technical field of forging, and relates to an online prediction method for the velocity of an upper beam of a large die forging press based on Taylor expansion. Background technique: [0002] Due to the time-varying load, nonlinear hydraulic drive and other factors in the actual forging process, the entire forging process is very complicated, which poses a challenge to accurately and quickly predict the dynamic behavior of large die forging presses. [0003] At present, the prediction methods in engineering mainly include mathematical modeling prediction methods based on physical mechanisms and data-driven online modeling prediction methods. Due to the strong nonlinear and time-varying characteristics of the forging process, it is difficult to establish an accurate mathematical model based on the physical mechanism. Furthermore, data-driven online modeling methods are increasingly used in complex forging systems due to th...

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Application Information

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IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 蔺永诚谌东东陈明松
Owner CENT SOUTH UNIV
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