Fault Diagnosis of Rotation Machinery Based on Support Vector Machine Optimized by Quantum Genetic Algorithm
Considering the disadvantages of conventional fault diagnosis methods for rotating machinery, such as low efficiency and low accuracy, we propose a fault diagnosis method based on support vector machine (SVM) optimized by quantum genetic algorithm (QGA). First, the SVM parameters are optimized by QG...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8260909/ |