A Weak Signal Detection Method for Bearing Based on QGA and Stochastic Resonance
Aiming at the problems that the vibration signal is weak and the SNR is low in its early failure stage of rolling bearing, a weak signal detection method combining Quantum Genetic Algorithm (QGA) and Stochastic Resonance is proposed, which improves SNR and identifies fault location. Firstly, the lar...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2020-06-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1780 |
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| Summary: | Aiming at the problems that the vibration signal is weak and the SNR is low in its early failure stage of rolling bearing, a weak signal detection method combining Quantum Genetic Algorithm (QGA) and Stochastic Resonance is proposed, which improves SNR and identifies fault location. Firstly, the large parameter signal is scale transformed and the noise intensity is estimated according to the input signal to realize the initialization of the parameters. Secondly, the output SNR is selected as the objective function, and the two parameter are dealt with adaptive optimization through the QGA; Finally, the SNR of weak signal is improved by stochastic resonance system. Simulation and experimental results show that the method fully considers the interaction between system parameters, and can effectively improve SNR, and achieve early detection of weak signal in failure stage. |
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| ISSN: | 1007-2683 |