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Rolling bearing fault mode identification method based on combination of SPA map and ResBet

A technology for rolling bearings and fault identification, applied in character and pattern recognition, neural learning methods, testing of machine/structural components, etc., can solve problems such as large gradients, gradient explosions, explosions, etc.

Active Publication Date: 2021-03-30
SOUTHWEST JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although CNN has a better ability to extract image features, and as the number of network layers deepens, the network can extract deeper feature information and obtain good generalization ability, but when the number of network layers deepens, the network will change. It is becoming more and more difficult to train, because in a network with a deeper number of layers, when the gradient information is transmitted from the last layer to the first layer of the network, there will be a phenomenon that the gradient is close to zero or the gradient is very large, which is called gradient dispersion or Gradient explosion, the deeper the number of layers in the network, the more serious the phenomenon of gradient dispersion or gradient explosion will be, which will make it more difficult to extract deep-level features

Method used

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  • Rolling bearing fault mode identification method based on combination of SPA map and ResBet
  • Rolling bearing fault mode identification method based on combination of SPA map and ResBet
  • Rolling bearing fault mode identification method based on combination of SPA map and ResBet

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Experimental program
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Effect test

Embodiment

[0081] The experimental data used in this embodiment is the 6205-2RS JME SKF deep groove ball bearing data set (SMITH W, RANDALL R. Rolling element bearing diagnostics using case western reserve university data: a benchmarkstudy[J].Mechanical Systems and Signal Processing,2015,64-65(3):100-131), the fault types are divided into inner ring faults, rolling element faults and outer ring faults, each of which has The single-point fault is introduced by the EDM method, the fault diameter is 0.007 inches, and the loads on each fault are 0, 1HP, 2HP and 3HP, and the normal bearings are used to construct the comparison data under the same situation, as shown in Table 1 .

[0082] Table 1 16 working conditions under normal and 0.007 failure

[0083]

[0084]

[0085] When dividing the data, first divide the data into training set, verification set and test set according to the general principle of dividing the training set, verification set and test set. The ratio of the trainin...

Embodiment 2

[0211] In order to further observe the classification situation of the fault location by the rolling bearing fault identification method provided by the present invention, in addition, the data with damage degrees of 0.014 inches and 0.021 inches were selected to carry out 2 groups of 16 classification experiments according to the method given in Example 1 (specifically, each Working conditions are shown in Table 4). First the data is divided into training set, verification set and test set, then utilize the data in the training set and verification set to train the ResNet network model (same structure as in Example 1) according to steps A1-A6, then utilize the data in the test set The data is tested on the trained ResNet network model according to steps S1-S4, and the experimental results and the experimental results under 0.007 inches are recorded in Table 3. It can be seen from Table 3 that the accuracy rates under the three damage levels are all above 99%, indicating that ...

Embodiment 3

[0215] In order to further observe the performance of the rolling bearing fault identification method provided by the present invention in the classification of the fault degree, select all normal data and all damage degrees of the inner ring, outer ring (6 o'clock direction) and rolling elements under all loads, 16 kinds of data in each group Three sets of experiments were carried out, in which the working conditions of the inner ring are shown in Table 4, and the working conditions of the outer ring (6 o'clock direction) and rolling elements are similar to those in Table 4. First the data is divided into training set, verification set and test set, then utilize the data in the training set and verification set to train the ResNet network model (same structure as in Example 1) according to steps A1-A6, then utilize the data in the test set The data is tested on the trained ResNet network model according to steps S1-S4, and the experimental results are recorded in Table 5.

[...

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Abstract

The invention discloses a rolling bearing fault identification method based on the combination of an SPA map and ResNet, and the method comprises the steps: firstly decomposing an original signal intoa trend term and a detrend term which are greatly different through an SPA method, converting the obtained trend term and detrend term into a color map through the combination of the original signalterm, and finally achieving the fault type identification through a ResNet network model, under the condition that bearing fault information is extracted as much as possible, component items being greatly reduced, and meanwhile, extracting deep bearing fault information through deep ResNet, so that the rolling bearing fault recognition efficiency and accuracy are improved.

Description

technical field [0001] The invention belongs to the technical field of fault identification of rotating machinery, and relates to fault identification of rolling bearings, in particular to a fault identification method of rolling bearings based on the combination of SPA-atlas and ResNet. Background technique [0002] Rolling bearings are one of the most commonly used components in mechanical systems. They play an extremely important role in maintaining the stability of mechanical systems, but they are also one of the most vulnerable parts. According to the statistics of mechanical system failures, the proportion of rolling bearing failures exceeds 40%. When the bearing is damaged, it will lead to abnormal operation of the mechanical system, and serious accidents will cause economic losses and casualties. Therefore, accurate bearing fault diagnosis is very important to ensure the normal operation of the mechanical system. Since rolling bearings mostly work under complex work...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/045G06K9/00G06N3/04G06N3/08
CPCG01M13/045G06N3/08G06N3/045G06F2218/12
Inventor 张敏李贤均程文明
Owner SOUTHWEST JIAOTONG UNIV
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