Rolling bearing diagnosis based on an unbiased-autocorrelation morphological filter method

Measurement ◽  
2021 ◽  
pp. 110617
Author(s):  
Mingjun Tang ◽  
Yuhe Liao ◽  
Dan He ◽  
Rongkai Duan ◽  
Xining Zhang
Keyword(s):  
Rolling Bearing ◽  
Filter Method ◽  
Morphological Filter

Application of Morphological Filtering Technology in Underwater Acoustic Signal Preprocessing

2015 ◽  
Vol 719-720 ◽  
pp. 1019-1022
Author(s):  
Lei Lei Deng
Keyword(s):  
Data Processing ◽  
Acoustic Signal ◽  
Original Data ◽  
Acoustic Signals ◽  
Filter Method ◽  
Morphological Filter ◽  
Pulse Interference ◽  
Underwater Acoustic ◽  
Morphological Filtering ◽  
Underwater Acoustic Signal

In order to extract useful information of underwater acoustic signals from noise, preprocessing steps are unavoidable. In view of trend and transient pulse interference exited in the original data inevitability, morphological filter method is applied and analyzed in this paper. Data processing results show that the morphological filter method is superior to the traditional filter method.

Simulation Research on Rolling Element Bearing Feature Extraction Based on Recursive Least-Squares Lattice-Ladder Algorithms

2014 ◽  
Vol 548-549 ◽  
pp. 481-486
Author(s):  
Jie Ping Zhu ◽  
Yong Xiang Zhang ◽  
Shuai Zhang ◽  
Xiao Lin Wang
Keyword(s):  
Feature Extraction ◽  
Least Squares ◽  
Vibration Signal ◽  
Rolling Bearing ◽  
Rolling Element Bearing ◽  
Recursive Least Squares ◽  
Filter Method ◽  
Feature Extraction Method ◽  
Rolling Element ◽  
Element Bearing

In order to extract the weak fault information from complicated vibration signal of rolling element bearing, the Recursive Least-Squares (RLS) Lattice-Ladder Algorithms is introduced into the field of rolling bearing feature extraction. An adaptive feature extraction method is proposed. The RLS Lattice-Ladder algorithms and its adaptive filter property in the process of feature extraction were discussed. The rolling bearing vibration signal was refined by the RLS Lattice-Ladder filter method, and the refined vibration signal was demodulated by square envelope, then the rolling bearing’s characteristic fault frequency was identified by enveloped normalized amplitude-frequency spectrum. Simulation results show that compared with the LMS filter method, this method can identify fault frequency more quickly and more effectively.

Discussion on “Rolling bearing applications” at the Manchester Section of the Institution

1948 ◽  
Vol 27 (8) ◽  
pp. 416
Author(s):  
Morton ◽  
Allan ◽  
Hayton ◽  
Gejji ◽  
Murphy ◽  
...  
Keyword(s):  
Rolling Bearing

Efficiency of application of the phase-chronometric method and neurodiagnostics for monitoring the degradation of rolling bearings during operation

2020 ◽  
pp. 43-50
Author(s):  
A.S. Komshin ◽  
K.G. Potapov ◽  
V.I. Pronyakin ◽  
A.B. Syritskii
Keyword(s):  
Life Cycle ◽  
Wavelet Analysis ◽  
Metrological Support ◽  
Rolling Bearing ◽  
Technical Condition ◽  
Measurement Information ◽  
Rolling Bearings ◽  
Vibration Diagnostics ◽  
Bearing Life ◽  
Alternative Approach

The paper presents an alternative approach to metrological support and assessment of the technical condition of rolling bearings in operation. The analysis of existing approaches, including methods of vibration diagnostics, envelope analysis, wavelet analysis, etc. Considers the possibility of applying a phase-chronometric method for support on the basis of neurodiagnostics bearing life cycle on the basis of the unified format of measurement information. The possibility of diagnosing a rolling bearing when analyzing measurement information from the shaft and separator was evaluated.

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