Manufacturing equipment main shaft bearing health assessment method based on probability description and spectral analysis

A spindle bearing and health assessment technology, applied in probabilistic CAD, special data processing applications, instruments, etc., can solve problems such as insensitivity, data over-reliance on early failures, etc., and achieve the effect of overcoming over-dependence

Pending Publication Date: 2021-01-05
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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  • Application Information

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Problems solved by technology

[0007] In view of this, the present invention provides a health assessment method for manufacturing equipment spindle bearings based on probabilistic description and spectral analysis to solve the problem that the degradation model proposed in the background technology is overly depe

Method used

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  • Manufacturing equipment main shaft bearing health assessment method based on probability description and spectral analysis
  • Manufacturing equipment main shaft bearing health assessment method based on probability description and spectral analysis
  • Manufacturing equipment main shaft bearing health assessment method based on probability description and spectral analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0078] The whole life cycle data set in Example 1 contains a total of 984 files, the experimental sampling frequency is 20kHz, the shaft rotation frequency is 33.33Hz, and the data is collected every 10 minutes. At the end of the experiment, it is found that the outer ring of the main shaft bearing has a serious failure. The bearing outer ring theory The characteristic frequency is about 236Hz.

[0079] Such as figure 1 Shown is a step-by-step flowchart of a method for evaluating the health of spindle bearings in manufacturing equipment based on probability description and spectral analysis, including the following steps:

[0080] (1) Feature extraction

[0081] According to the sampling frequency and the spindle speed, the sampling points for each rotation of the spindle are about 600 points, and the data of each file is intercepted by 1200 points and 16 segmented signals;

[0082] After 4-layer WPT decomposition of the segmented signal, the last layer of node signal is rec...

Embodiment 2

[0109] The full life cycle data set of Example 2 contains 161 files in total, the experimental sampling frequency is 25.6kHz, the shaft rotation frequency is 35Hz, and the data is collected every 1 minute. At the end of the experiment, it is found that the outer ring of the main shaft bearing has a serious failure. The outer ring of the main shaft bearing The theoretical characteristic frequency is about 108Hz.

[0110] (1) Feature extraction

[0111] According to the sampling frequency and the spindle speed, the sampling points for each rotation of the spindle are about 731 points, and the data of each file is divided into 1462 points to intercept 16 segmented signals;

[0112] After 4-layer WPT decomposition of the segmented signal, the last layer of node signal is reconstructed to obtain 16-segment signal components;

[0113] Demodulate each segmented signal and the reconstructed signal of the last WPT node to obtain 17 envelope signals, and calculate the ESGI index of the...

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Abstract

The invention discloses a manufacturing equipment main shaft bearing health assessment method based on probability description and spectral analysis, which relates to the technical field of high-precision mechanical equipment reliability analysis.According to the features of a vibration signal in the process of main shaft bearing performance degradation, an ESGI index is proposed to extract features as an input value to perform GHMM model training and OLL likelihood probability output, the OLL probability is controlled by using EWMA to obtain an HEPI index to describe a performance degradationcurve to perform main shaft bearing degradation evaluation, and an HCPLLI index is constructed to assist in identifying early faults of a main shaft bearing. The fault position of the main shaft bearing is determined through lifting power spectrum analysis after the early fault occurs. According to the method, the problems that a degradation model excessively depends on historical full-life-cycledata, and the degradation evaluation process is insensitive to early faults are solved, and early fault recognition, performance degradation evaluation and fault position determination of the manufacturing equipment main shaft bearing are achieved.

Description

technical field [0001] The invention relates to the technical field of reliability analysis of high-precision mechanical equipment, and more specifically relates to a method for evaluating the health of a main shaft bearing of manufacturing equipment based on probability description and spectrum analysis. Background technique [0002] In recent decades, safe production and the high-speed, efficient and sustainable development of the national economy have put forward higher requirements for the production process. Bearings are the most commonly used and core components in manufacturing equipment. , Aerospace, military products, etc. have a wide range of applications. Statistics show that about 70% of mechanical failures are vibration failures, and nearly 30% of vibration failures are caused by bearing failures. Therefore, it is necessary to monitor and evaluate the health status of spindle bearings in manufacturing equipment, and this topic has also attracted extensive atten...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06F111/08G06F119/02G06F119/04
CPCG06F30/20G06F2111/08G06F2119/02G06F2119/04
Inventor 杨文安胡旭辉绳远远郭宇
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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