Blade machining process error prediction method based on extended error flow

A technology for processing and error prediction, applied in special data processing applications, instruments, electrical digital data processing, etc.

Inactive Publication Date: 2013-12-11
NORTHWESTERN POLYTECHNICAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] In order to overcome the limitations of the existing error flow technology that only considers the geometric error source in the multi-process process of rigid body par

Method used

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  • Blade machining process error prediction method based on extended error flow
  • Blade machining process error prediction method based on extended error flow
  • Blade machining process error prediction method based on extended error flow

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Embodiment Construction

[0178] Reference Figure 1-7 . Taking a certain kind of blade (material titanium alloy TC4) parts processed by an aero engine manufacturer as an example, the error analysis and prediction of the blade processing process is carried out according to the steps. The present invention is described in detail to verify the predictive effect of the present invention on the error of a certain type of blade multi-process machining process.

[0179] Discrete the cross-section lines of the blade parts with equal precision to obtain the micro-element coordinate points, simplify the blade parts into thin-plate parts, and map the corresponding micro-element coordinate points to the simplified blade model to obtain the progress of the thin plate and the blade parts. After the discrete processing, the points correspond, and these corresponding points on the thin plate are used to approximate the corresponding points on the blade.

[0180] In the simplified model, ps 1 To ps 4 For the micro elemen...

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Abstract

The invention discloses a blade machining process error prediction method based on extended error flow. The method is used for solving the technical problem that only geometric error sources are considered when multi-procedure rigid body part assembling or machining processes are adopted as the study object according to an existing error flow method. According to the technical scheme, the method comprises the steps that a model drive is adopted for conducting process monitoring, errors generated by a geometric positioning error source and errors generated by a force-carrying deformation error source are timely predicted, an error coupling and a transmission mechanism are studied, and a machining process error coupling modeling scheme is designed; infinitesimal division is conducted on a blade part through a grid division thought, and deformation analyses are converted to coordinate transformation of an infinitesimal coordinate system; a multi-source and multi-procedure error coupling model based on the extended error flow is built, and a composition error prediction model based on the error coupling model is given on this basis. According to the blade machining process error prediction method based on the extended error flow, working personnel can be helped to timely find manufacturing defects of the blade and correct and adjust the blade, reworking times are reduced and machining quality and efficiency are improved.

Description

Technical field [0001] The invention relates to an error prediction method for blade processing, in particular to an error prediction method for blade processing based on an extended error flow. Background technique [0002] Due to the particularity of blade parts, its forming process is essentially different from that of traditional high-rigidity parts. It is more sensitive to fluctuations of various error sources, and the interaction phenomena such as error transmission and accumulation between processes are more complicated. Therefore, studying the coupling and propagation of errors in the process of blade parts processing, analyzing the coupling and transmission forms of errors, and establishing the corresponding relationship between error sources and errors is the key and prerequisite for quality monitoring, traceability and adjustment of the processing process, and the quality improvement of blade parts Is of great significance. [0003] Literature Liu J., Jin J. and Shi J. ...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 李山王佩杨青龙任静波
Owner NORTHWESTERN POLYTECHNICAL UNIV
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