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Method for detecting early fault of bearing through secondary phase coupling and improved bi-spectrum algorithm

A technology of secondary phase and detection method, applied in the direction of mechanical bearing testing, etc., can solve the problems of difficult fault characteristics, nonlinearity, low signal-to-noise ratio, etc., achieve stable and reliable detection ability, avoid bearing accidents, and have a wide range of applications.

Inactive Publication Date: 2018-06-05
胡文扬
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most of the methods currently developed are more effective when the bearing fault is more obvious
[0004] In the early stage of bearing faults, on the one hand, the vibration signals obtained due to load fluctuations are mostly non-stationary signals, and conventional analysis methods are difficult to effectively analyze the fault characteristics; on the other hand, due to the noisy external environment and electromagnetic interference, the obtained signals Contains a lot of noise and interference components, and the signal-to-noise ratio is low. It is difficult to find the fault symptoms of rolling bearings in time by conventional analysis methods
Furthermore, the local damage faults of inner and outer ring pitting account for about 90% of the total number of bearing faults, and their vibration signals often show typical nonlinear and non-stationary characteristics, and it is difficult to extract effective fault features by conventional methods

Method used

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  • Method for detecting early fault of bearing through secondary phase coupling and improved bi-spectrum algorithm
  • Method for detecting early fault of bearing through secondary phase coupling and improved bi-spectrum algorithm
  • Method for detecting early fault of bearing through secondary phase coupling and improved bi-spectrum algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0090] Example 1: Early fault detection of inner ring of 6205-2RS JEM SKF deep groove ball bearing

[0091] Bearing structure parameters: roller diameter D B =7.94mm; Bearing pitch diameter D P =39.04mm; Number of rollers N B =9. The diameter of a single defect in the inner ring of the bearing is 0.1778mm, and the depth of the defect is 0.2794mm.

[0092] Bearing operating environment: motor load 2HP, speed 1748r / min (29.1333Hz).

[0093] Data acquisition parameters: rotational speed and sampling frequency F of the vibration accelerometer signal on the bearing seat s =12000Hz, acquisition length N=122136.

[0094] According to these parameters and the structural parameters of the bearing, the theoretically calculated characteristic frequency of the inner ring defect of the bearing is F IRF =157.7628Hz, in the improved bispectral model algorithm of secondary phase coupling detection, the length of FFT analysis data is taken as 4096, and the frequency resolution is df=F s...

Embodiment 2

[0098] Example 2: Early fault detection of 6205-2RS JEM SKF deep groove ball bearing outer ring

[0099] Bearing structure parameters: roller diameter D B =7.94mm; Bearing pitch diameter D P =39.04mm; Number of rollers N B =9. The diameter of a single-point defect on the outer ring of the bearing is about 0.1778mm, and the depth of the defect is about 0.2794mm.

[0100] Bearing operating environment: motor load 2HP, speed 1750r / min (29.1667Hz).

[0101] Data acquisition parameters: rotational speed and sampling frequency F of the vibration accelerometer signal on the bearing seat s =12000Hz, acquisition length N=122136.

[0102] Based on these parameters and the structural parameters of the bearing, the theoretically calculated characteristic frequency of the bearing outer ring defect is F ORF =104.5567Hz, in the improved bispectral model algorithm of secondary phase coupling detection, the length of FFT analysis data is taken as 4096, and the frequency resolution is df=...

Embodiment 3

[0106] Example 3: MB ER-10K Bearing Roller Fault Detection

[0107] Bearing structure parameters: roller diameter D B =7.9248mm; bearing pitch diameter D P =33.4772mm; Number of rollers N B =8.

[0108] Bearing operating environment: speed 1807r / min (30.12Hz).

[0109] Data acquisition parameters: rotational speed and sampling frequency F of the vibration accelerometer signal on the bearing seat s =25600Hz, acquisition length N=472000.

[0110] According to these parameters and the structural parameters of the bearing, the theoretically calculated characteristic frequency of the bearing roller defect is F BF =119.9981Hz, in the improved bispectral model algorithm of secondary phase coupling detection, the length of FFT analysis data is taken as 4096, and the frequency resolution is df=F s / 4096=25600 / 4096=6.25Hz, the frequency resolution is too large, but the characteristic frequency of the bearing roller defect visible in the actual analysis is F RBF =floor(F BF / df)×...

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Abstract

The invention discloses a method for detecting an early fault of a bearing through a through secondary phase coupling and improved bi-spectrum algorithm, and the method comprises the following steps:obtaining a resampling signal sequence; calculating the resampling signal sequence through an improved bi-spectrum model of secondary phase coupling detection; and carrying out the detection analysisof the early faint defect feature component of the bearing. The method starts from the coupling effect between a fault behavior and a dynamic behavior of a system, combines with the advanced signal processing theory and method for the exploration of a detection method for the early fault features of a rolling bearing, and aims at recognizing a bearing fault at an early stage through a vibration signal, the nonlinear coupling effect with consideration to the fault impact, and improved higher-order statistical analysis. The method has the stable and reliable detection capability for the detection of the early faint fault of the bearing, enables a bearing fault to be timely found, and avoids a bearing accident. The method is wide in application range, and can be used for the detection and tracking of early faults of bearings in various types of transmission systems.

Description

technical field [0001] The invention belongs to the technical field of state monitoring and fault diagnosis, and relates to bearing dynamics, high-order statistical analysis in signal processing, nonlinear coupling mechanism and feature extraction of weak fault detection, and specifically relates to a secondary phase coupling and improvement Bearing early fault detection method based on bispectrum algorithm. Background technique [0002] Rolling bearings are known as the joints of mechanical equipment, and as a crucial moving part, they are widely used in rotating machinery in various industrial fields. Bearing failure is also a relatively common failure in rotating machinery. According to incomplete statistics, 30% of rotating machinery failures are caused by bearing failures. Specifically in the field of motor applications, almost half of motor failures originate from bearing failures. Once the bearing fails, it may trigger a chain reaction and cause the entire system to...

Claims

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Application Information

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IPC IPC(8): G01M13/04
Inventor 胡文扬胡文轩
Owner 胡文扬
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