Self-adaptive main shaft performance degradation identification method based on S test piece

A recognition method and self-adaptive technology, applied in the recognition of patterns in signals, character and pattern recognition, testing of mechanical parts, etc., can solve the problems of white noise can not be completely neutralized, noise residual, etc., to achieve reasonable preventive maintenance , the effect of rationally arranging production

Pending Publication Date: 2020-03-24
BEIJING INFORMATION SCI & TECH UNIV
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  • Abstract
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  • Application Information

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Problems solved by technology

Although modal aliasing is suppressed to a certain extent, the added white noise cannot be completely neutralized, and there is a noise residual problem

Method used

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  • Self-adaptive main shaft performance degradation identification method based on S test piece
  • Self-adaptive main shaft performance degradation identification method based on S test piece
  • Self-adaptive main shaft performance degradation identification method based on S test piece

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0093] Different degrees of wear on the cutting edge of the tool are used to simulate different degrees of failure of the spindle. A total of three tool working conditions are set. When milling the S specimen under each working condition, the same processing technology and cutting conditions are used to collect the vibration signals in the radial direction of the spindle, as shown in image 3 shown.

[0094] The material of the S test piece is aviation aluminum 7075-T7451, and it is clamped on the workbench with countersunk screws. The processing tool is a φ20mm three-blade end mill. The first working condition is that two cutting edges have crater wear, the second working condition is that one cutting edge has crater wear, and the third working condition is a brand new milling cutter. The three working conditions respectively simulate the electric spindle bearing with two balls worn out, one ball worn out, and the bearing has no faults.

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Abstract

The invention relates to a self-adaptive main shaft performance degradation identification method based on an S test piece. The method comprises the steps: collecting and storing radial vibration signals of a main shaft while the S test piece is machined; segmenting the radial vibration signals according to time, and performing adaptive noise complete set empirical mode decomposition on each segment of radial vibration signals to obtain IMF components; extracting intrinsic mode component characteristic parameters of the decomposed signals for signal reconstruction, and calculating the information entropy of a reconstructed signal power spectrum and the gravity center frequency of a marginal spectrum; after the S test piece is machined, judging whether a measurement result of the S test piece is qualified or not, and obtaining characteristics of a normal state and characteristics of an abnormal state of the machine tool spindle; comparing the PSE value and the SCF value of each sectionof vibration signal obtained after calculation of the radial vibration signals collected in the process of machining the new S test piece with the characteristics of the normal state and the abnormalstate of the main shaft respectively, and judging the health condition of the main shaft; and constructing power spectrum entropy curves of different machining stages of the machined S test piece to classify the degradation degree of the main shaft.

Description

technical field [0001] The invention relates to a method for identifying the state of a main shaft, in particular to a method for identifying performance degradation of an adaptive main shaft based on an S test piece. Background technique [0002] With the urgent requirements for high-speed, high-efficiency and high-precision in major fields such as aviation, aerospace and transportation, higher requirements are put forward for the stability of high-end CNC equipment and the reliability of the system. The spindle unit is a key component that determines the high speed and high precision of the machine tool. Carry out regular inspections on the spindle, grasp its performance degradation trend, arrange production in a planned way and implement preventive repair and maintenance. High-speed spindles include rotating components such as rotors, motors, bearings, and sleeves. The coordination between the various sub-components affects the dynamic characteristics and rotation accura...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G01M13/045
CPCG01M13/045G06F2218/22G06F2218/08
Inventor 王红军韩风霞籍永健谷玉海
Owner BEIJING INFORMATION SCI & TECH UNIV
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