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A step-by-step stacking method for the initial unbalance of multi-level parts of large-scale high-speed rotary equipment based on convolutional neural network

A technology of convolutional neural network and balance, which is applied in the field of step-by-step stacking of initial unbalance of multi-level components of large-scale high-speed rotary equipment, can solve problems such as large vibration, poor assembly quality, and large unbalance of aero-engine rotors, and achieve improved The effect of efficiency and precision

Active Publication Date: 2021-10-29
HARBIN INST OF TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Aiming at the deficiencies of the above-mentioned existing technologies, a method of stacking the initial unbalance of multi-level components of large-scale high-speed rotary equipment based on the minimization of centroid and mass center is proposed to solve the problem of large initial unbalance of aero-engine rotor assembly. Poor assembly quality and large vibration problems, improve the performance of the engine rotor

Method used

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  • A step-by-step stacking method for the initial unbalance of multi-level parts of large-scale high-speed rotary equipment based on convolutional neural network
  • A step-by-step stacking method for the initial unbalance of multi-level parts of large-scale high-speed rotary equipment based on convolutional neural network
  • A step-by-step stacking method for the initial unbalance of multi-level parts of large-scale high-speed rotary equipment based on convolutional neural network

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Experimental program
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Effect test

Embodiment 1

[0031] Based on the minimization of centroid and mass center, the method of stacking the initial unbalance of multi-level parts of large-scale high-speed rotary equipment step by step, such as figure 1 As shown, the method includes

[0032] Step 1. During the assembly of the multi-stage rotor of the aero-engine, the positioning error of the single-stage rotor will be transmitted and accumulated, which will affect the accumulated eccentricity error of the assembled multi-stage rotor. Determine the eccentricity error transfer matrix caused by the positioning error of the rotors at each stage after the n-stage rotor is assembled, and the eccentricity error transfer matrix is:

[0033]

[0034] Among them, p i is the ideal position vector of the center of the radial measuring surface of the i-th rotor; dp iis the machining error vector of the center position of the radial measuring surface of the i-th rotor; S ri Rotate θ around the Z axis for the i-th stage rotor ri Rotati...

Embodiment 2

[0051] A step-by-step stacking device for the initial unbalance of multi-level parts of large-scale high-speed rotary equipment based on the minimization of centroid and mass center, such as figure 2 As shown, the device includes a base 1, an air bearing shafting 2, a centering and tilting workbench 3, precision force sensors 4a, 4b, 4c, a static balance measuring platform 5, a column 6, and a lower transverse measuring rod 7 , the lower telescopic inductive sensor 8, the upper horizontal measuring rod 9 and the upper lever inductive sensor 10; the air bearing shaft system 2 is nested in the center of the base 1, and the self-aligning and tilting workbench 3 is arranged on the air bearing shaft At the center of the system 2, three precision force sensors 4a, 4b, 4c are evenly arranged on the centering and tilting workbench 3; the static balance measurement platform 5 is on the three precision force sensors 4a, 4b, 4c; the column 6 is distributed on The left side of the air be...

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Abstract

The invention proposes a step-by-step stacking method and device for initial unbalanced quantities of multi-level components of large-scale high-speed rotary equipment based on convolutional neural networks, and belongs to the technical field of mechanical assembly. The method comprises the steps of first obtaining respectively the eccentricity error transfer matrix caused by the positioning errors of the rotors of each level after n-level rotors are assembled, the unbalance amount of the nth-level rotors caused by the positioning errors of the rotors of all levels after assembly, and the The eccentricity error transfer matrix caused by the rotor orientation error and the unbalance of the nth stage rotor caused by the orientation error of each stage of rotor after assembly, and then, the unbalance of any stage of the multi-stage rotor after assembly is obtained by vector addition, and according to The unbalanced quantity builds an optimization model. The device includes: a base, an air bearing shafting system, a self-aligning and tilting workbench, respectively a precision force sensor, a static balance measuring platform, a column, a lower transverse measuring rod, a lower telescopic inductive sensor, an upper transverse measuring rod and an upper Lever type inductive sensor.

Description

technical field [0001] The invention relates to a step-by-step stacking method and device for initial unbalanced quantities of multi-level components of large-scale high-speed rotary equipment based on a convolutional neural network, and belongs to the technical field of mechanical assembly. Background technique [0002] The aero engine is the core component of the aircraft. In order to ensure the safety of the aircraft, it needs to work safely and reliably for a long time. The vibration of the rotor seriously affects the safety, efficiency and life of the engine, and the unbalance of the rotor is an important factor determining the vibration response of the engine rotor. The engine rotor is assembled by a plurality of discs, and the unbalanced amount of the discs at each level forms the unbalanced amount of the rotor through a certain combination. Although the unbalance of each stage disc is strictly limited during the design process, if the assembly is improper, the unbal...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/12G01M1/16
Inventor 刘永猛孙传智谭久彬胡明
Owner HARBIN INST OF TECH
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