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Blade Profile Error Evaluation Method Based on k-Nearest Neighbor Iterative Closest Grid Algorithm

A blade profile and evaluation method technology, applied in calculation, image analysis, program control, etc., can solve the problems of low calculation efficiency, inability to accurately reflect the real profile error of the workpiece surface, high memory requirements, etc., to achieve high precision and improve calculation Accuracy and efficiency, the effect of improving acquisition efficiency

Active Publication Date: 2021-08-10
INST OF MACHINERY MFG TECH CHINA ACAD OF ENG PHYSICS
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is: the existing contour error evaluation method uses the distance between the measured point cloud and the ideal point cloud as the optimization target, but this index cannot accurately reflect the real contour error of the workpiece surface; these methods The point cloud is used to describe the CAD model. A sufficiently dense point cloud is required to ensure the accuracy of the distance from the calculated point to the ideal surface. The memory requirements are high and the calculation efficiency is low.

Method used

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  • Blade Profile Error Evaluation Method Based on k-Nearest Neighbor Iterative Closest Grid Algorithm
  • Blade Profile Error Evaluation Method Based on k-Nearest Neighbor Iterative Closest Grid Algorithm
  • Blade Profile Error Evaluation Method Based on k-Nearest Neighbor Iterative Closest Grid Algorithm

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Experimental program
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Effect test

Embodiment 1

[0084] Such as figure 1 As shown, a blade surface profile error evaluation method based on the K-nearest neighbor iterative nearest grid algorithm includes the following steps:

[0085] S1. Set the machining tolerance of the workpiece as τ, and triangulate the CAD surface of the blade with the discrete precision of ω·τ (0 Where t represents the identification number of each part of the blade, Indicates the number of discrete points of this part of the profile.

[0086] S2: if image 3 As shown, the REVO five-axis measurement system is used to obtain the measurement points of the entire blade surface, and the measurement point cloud data set is recorded as no t Indicates the number of measuring points in this part, N=∑ t no t . k represents the number of iterations, the initial situation k=0, i=1...n t .

[0087] S3: Calculate the positions of all current measurement points for each part of the blade to the nearest point on the triangular patch and the correspo...

specific Embodiment approach

[0129] The specific implementation of the blade contour error evaluation method based on the K-nearest neighbor iterative nearest grid algorithm comprises the following steps:

[0130] Step 1. Mark the four parts CC, CV, LE, and TE of the blade CAD surface of the compressor as t=1, 2, 3, 4 respectively, and the machining tolerance of the workpiece τ=0.01mm, take ω=0.1, and The discrete precision of 0.1τ triangulates the CAD surface of the blade, and the discrete point cloud set that constitutes the triangular surface is The amount of discrete point cloud data in each part is A total of 154966. The discrete point cloud that will make up the triangular patch Stored according to the k-d tree structure, the set of triangular faces of each part is The quantity is m 1 =69531, m 2 =75043, m 3 =59688, m 4 =102331, a total of 306593 pieces. The REVO five-axis measurement system is used to obtain the measurement points of the entire blade surface, and the measurement point c...

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Abstract

The invention discloses a blade profile error evaluation method based on the K-nearest neighbor iterative nearest grid algorithm. In the blade surface profile error evaluation method, a five-axis measurement system is used to obtain the measurement point cloud of the entire blade surface, so as to measure the point cloud to an ideal profile. The maximum and minimum distance of the triangular surface is used as the objective function, and the KNN-ICM algorithm is used to match and analyze the measurement point cloud and the triangulated CAD model. Compared with the traditional error evaluation method, this method improves the measurement point to the ideal type. The calculation accuracy and efficiency of the surface distance can more accurately reflect the contour error of the workpiece and reduce the memory consumption during calculation; this method solves the problem of incomplete analysis of the key section method, and completely reflects the blade surface as a whole and each part deviation distribution.

Description

technical field [0001] The invention relates to the technical fields of computer-aided manufacturing and numerical control machining, in particular to a blade profile error evaluation method based on the K-nearest neighbor iterative nearest grid algorithm. Background technique [0002] As a high-failure component in the power plant, the blade parts seriously affect the working performance and service life of the whole machine. The shape error of the blade profile has a great influence on the secondary flow loss, directly affects the energy conversion rate of the compressor and thus affects the working efficiency, and plays a decisive role in the performance of the engine. Therefore, the processing and profile quality of blade parts The detection is of great significance in the detection of engine parts. [0003] With the continuous development and improvement of measurement technology, there are more and more techniques and means for blade surface profile analysis. The key...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/13
CPCG05B19/4086G05B2219/35356G06T7/0004G06T2207/10028G06T2207/30164G06T7/13
Inventor 樊炜闵康刘晓卓张云飞周涛黄文
Owner INST OF MACHINERY MFG TECH CHINA ACAD OF ENG PHYSICS