Improved keyless phase fault feature order extraction method

A technology of fault features and extraction methods, applied in the testing of mechanical components, testing of machine/structural components, measuring devices, etc., can solve the problem of difficulty in accurately guiding the resampling of the original signal, inaccurate order of equipment fault features, and eliminating noise. Interference lack of research and other problems, to avoid the cycle truncation error defect, improve operation safety monitoring, and enhance the effect of fault characteristics

Active Publication Date: 2018-11-23
XI AN JIAOTONG UNIV
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Problems solved by technology

There are two difficulties in using this method to track the order of the keyless phase: 1) directly integrating the obtained instantaneous frequency will lead to deviations in the instantaneous phase information, making it difficult to accurately guide the resampling of the original signal; 2) There is noise interference in the original signal. When the signal is re-sampled in the angle domain, the noise interference will also enter the angle domain. The commonly used keyless phase order technology lacks research in eliminating noise interference. Therefore, the extracted equipment fault characteristic order times inaccurate

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  • Improved keyless phase fault feature order extraction method

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Embodiment 1

[0104] In order to illustrate the superiority of the present invention, a fault vibration simulation signal of the outer ring of the bearing under the condition of variable speed is selected, and its waveform diagram is as follows figure 1 shown. The expression of the simulated signal is: The sampling time is 5s, and the sampling frequency is 20kHz. It can be seen from its expression that it consists of three parts. The first part is the impact signal s(t)=e-300tsin(2π·2000t) caused by the bearing fault, and the second part is the harmonic signal, which consists of three harmonic signals B 1 cos(2πnf(t)+β 1 )=0.005cos(2πn·(300+1000·sin(2π·0.1·t) / 60)+π / 6), B 2 cos(2πnf(t)+β 2 )=0.007cos(2πn·(300+1000·sin(2π·0.1·t) / 60)-π / 3) and B 3 cos(2πnf(t)+β 3 )=0.006cos(2πn·(300+1000·sin(2π·0.1·t) / 60)+π / 2), the third part is white noise with a signal-to-noise ratio of -3dB.

[0105] figure 2 is the instantaneous phase estimation diagram of the simulated signal. During the instant...

Embodiment 2

[0110] The vibration signal of the fault vibration signal of the outer ring of the bearing collected under the actual variable speed condition, the waveform diagram is as follows Figure 5 shown.

[0111] Figure 6 In order to perform integral correction on the instantaneous frequency with optimal harmonic component energy through the peak search algorithm after the time-frequency processing of the bearing signal, the limit error is set to ε≤1.0×10- 6 , so as to obtain the instantaneous phase estimation map, from Figure 6 It can be seen that the corrected instantaneous phase has a high degree of coincidence with the instantaneous phase obtained by the keyed phase method, and the instantaneous phase information is accurately estimated. Then, through the mapping relationship between the time domain and the angle domain, according to the estimated instantaneous phase information, the time domain signal is resampled in the angle domain with a constant angle increment, and the h...

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Abstract

The invention discloses an improved keyless phase fault feature order extraction method comprising the following steps: 1, using a vibration acceleration sensor to obtain equipment state information,and using a time frequency analysis method to preprocess the obtained state information so as to obtain an instant frequency; 2, carrying out normal integral operation for the estimated instant frequency so as to obtain a roughly estimated instant phase, and using a Romberg integral rule to correct the roughly estimated instant phase, thus finally obtaining an accurately estimated instant phase; 3, using the accurately estimated instant phase information to resample an angle domain of the original signal according to a mapping relation between the time domain and the angle domain; 4, using a flexible angle domain synchronous averaging method to denoise the resampled signal of the angle domain, and carrying out order spectral analysis for the denoised angle domain resampled signals, thus extracting the equipment fault feature order. The method can accurately extract the equipment fault feature order under a keyless phase change rotating speed condition.

Description

technical field [0001] The invention belongs to the field of fault feature extraction of mechanical vibration signals and variable speed working conditions of mechanical equipment, and relates to an improved keyless phase fault feature order extraction method. Background technique [0002] Mechanical fault diagnosis is usually based on the assumption that the machinery is running smoothly, but in fact many mechanical equipments have working conditions where the speed changes. The operating characteristics of variable speed conditions cause the fault characteristics of traditional diagnostic methods to appear blurred, dynamically changed, or even annihilated. At the same time, due to the continuous existence of noise, the signal-to-noise ratio is reduced, which increases the difficulty of extracting fault characteristics. Existing diagnostic methods for stable working conditions often rely on the acquisition of frequency modulation information. In the absence of frequency mod...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/00
CPCG01M13/00
Inventor 訾艳阳武杰陈景龙王宇周子桐朱国威
Owner XI AN JIAOTONG UNIV
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