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Fault diagnosis method of rolling bearing under variable working conditions

A rolling bearing and fault diagnosis technology, applied in the direction of mechanical bearing testing, etc., can solve the problems of failure judgment accuracy and decline, and achieve the effect of improving judgment accuracy, judgment speed and good stability

Inactive Publication Date: 2013-04-17
BEIHANG UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the defect that the commonly used rolling bearing fault diagnosis method usually fails or its judgment accuracy is greatly reduced when the working condition changes

Method used

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  • Fault diagnosis method of rolling bearing under variable working conditions
  • Fault diagnosis method of rolling bearing under variable working conditions
  • Fault diagnosis method of rolling bearing under variable working conditions

Examples

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Embodiment

[0077] This example uses the experimental data of 6205-2RS deep groove ball bearings for verification. The outer diameter of the bearing is 39.04mm, the thickness is 12mm, the pitch diameter is 28.5mm, the diameter of the rolling elements is 7.94mm, and the number of rolling elements is 9. The angle is 0°. The bearing test consists of a motor with a power of 1.5kW, a torque sensor / encoder, a dynamometer and an electrical control device. The motor drives the input shaft, and the output shaft drives the load.

[0078] The sample signals collected during the normal state of the rolling bearing, the inner ring fault, the outer ring fault, and the rolling element fault are respectively used to detect and verify the rolling bearing fault diagnosis method based on the Hilbert-Huang transformation and singular value decomposition of the present invention under variable working conditions. The specific steps are as follows :

[0079] Step 1. In the running state of the rolling bearing...

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Abstract

The invention relates to a fault diagnosis method of a rolling bearing under variable working conditions. The method comprises the steps of: extracting a characteristic vector of a signal by means of Hilbert-Huang conversion, carrying out EMD (Empirical Mode Decomposition) to a signal to obtain a plurality of IMFs (Intrinsic Mode Function), and selecting useful IMFs to carry out Hilbert conversion respectively to obtain analytic signals Hi(t) and taking envelopes respectively to form a characteristic vector w; then, carrying out singular value decomposition for w by a singular value decomposition method, and using a singular value matrix as the final fault characteristic vector; using the singular value matrixes in four modes of the rolling bearing as input and four matrixes corresponding to the four modes as output to train an Elman neural network. When the rolling bearing fails, whether the rolling bearing is faulted or not can be judged and direction of faults can be accurately positioned through analysis and judgment of a signal at t moment by the trained Elman neural network. According to the invention, classification of fault modes of the rolling bearing under variable working conditions can be effectively finished, and higher precision is maintained.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of rolling bearings, and in particular relates to a fault diagnosis method of rolling bearings under variable working conditions based on Hilbert-Huang transformation and singular value decomposition. Background technique [0002] The role of rolling bearings is to support the rotating shaft and the parts on the shaft, and maintain the normal working position and rotation accuracy of the shaft. It is characterized by convenient use and maintenance, reliable operation, good starting performance, and high bearing capacity at medium speeds. Rolling bearings are key components commonly used in mechanical equipment. Whether their working status is normal or not is directly related to the production quality and safety of the entire unit and even the entire production line. Compared with other mechanical parts, rolling bearings have a prominent feature: their life span is highly discrete, that is...

Claims

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Application Information

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IPC IPC(8): G01M13/04
Inventor 刘红梅王轩吕琛刘大伟王靖
Owner BEIHANG UNIV
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