Planetary Gearbox Fault Diagnosis Based on ICEEMD-Time-Frequency Information Entropy and VPMCD
Autor: | Hongmei Liu, Xin Gao, Yihan Wang, Zhonghui Fan |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Computer science
VPMCD Fault (power engineering) lcsh:Technology Hilbert–Huang transform lcsh:Chemistry Control theory Entropy (information theory) General Materials Science Instrumentation lcsh:QH301-705.5 Fluid Flow and Transfer Processes time-frequency information entropy ICEEMD Noise (signal processing) lcsh:T Process Chemistry and Technology General Engineering Mode (statistics) fault diagnosis lcsh:QC1-999 Computer Science Applications Time–frequency analysis planetary gearbox Vibration Nonlinear system lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 lcsh:Engineering (General). Civil engineering (General) lcsh:Physics |
Zdroj: | Applied Sciences Volume 10 Issue 18 Applied Sciences, Vol 10, Iss 6376, p 6376 (2020) |
ISSN: | 2076-3417 |
DOI: | 10.3390/app10186376 |
Popis: | Planetary gearboxes are more and more widely used in large and complex construction machinery such as those used in aviation, aerospace fields, and so on. However, the movement of the gear is a typical complex motion and is often under variable conditions in real environments, which may make vibration signals of planetary gearboxes nonlinear and nonstationary. It is more difficult and complex to achieve fault diagnosis than to fix the axis gearboxes effectively. A fault diagnosis method for planetary gearboxes based on improved complementary ensemble empirical mode decomposition (ICEEMD)-time-frequency information entropy and variable predictive model-based class discriminate (VPMCD) is proposed in this paper. First, the vibration signal of planetary gearboxes is decomposed into several intrinsic mode functions (IMFs) by using the ICEEMD algorithm, which is used to determine the noise component by using the magnitude of the entropy and to remove the noise components. Then, the time-frequency information entropy of intrinsic modal function under the new decomposition is calculated and regarded as the characteristic matrix. Finally, the fault mode is classified by the VPMCD method. The experimental results demonstrate that the method proposed in this paper can not only solve the fault diagnosis of planetary gearboxes under different operation conditions, but can also be used for fault diagnosis under variable operation conditions. Simultaneously, the proposed method is superior to the wavelet entropy method and variational mode decomposition (VMD)-time-frequency information entropy. |
Databáze: | OpenAIRE |
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