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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
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Abstract: In order to solve the difficulty in extracting fault features of rolling bearing of belt conveyor under the condition of variable load and variable speed, a rolling bearing fault feature extraction method based on second-order transient extraction transform was proposed. First, the second-order frequency-varying model was constructed according to the impact component frequency feature of fault bearing vibration signal; the spectral smearing phenomenon that existed when the traditional timevarying model dealt with short-term and broadband impact components was eliminated. Then based on the short time Fourier transform (STFT), the time frequency feature representation with high energy aggregation was realized by two-dimensional group delay time frequency rearrangement algorithm, thus the influence of background noise and non-impact components in vibration signal was reduced. Finally, according to the distribution of instantaneous frequency and instantaneous amplitude, the repetitive frequency of the impact component in the resonance frequency band was used as the basis to identify the type of bearing fault. Using simulation data and actual engineering data of belt conveyors, the effectiveness of the proposed method is verified. The research results show that comparing with the traditional time frequency analysis method, the proposed method can more accurately diagnose bearing faults under variable load and variable speed conditions, accurately identify the fault characteristic frequency of 53.32Hz and 106.9Hz in the actual vibration signal with noise interference, and has certain engineering application value.
Key words: belt conveyor; rolling bearing; fault diagnosis; second-order transient extraction transform(STET); time frequency representation; short time Fourier transform(STFT)
PENG Cheng-cheng.Fault feature extraction method for rolling bearing based on STET[J].Journal of Mechanical & Electrical Engineering,2021,38(10):1246-1252.