Research on Aero-Engine Vibration Fault Based on Neural Network and Information Fusion Technology |
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| Wu Yahui, Zhang Dazhi |
- Abstract:
- It is an important means for determining the conditions and making fault analysis of the aero-engine by measuring its vibration. Because the different features give different analysis results for vibration fault, in order to integration these information, the results of the different Back Propagation (BP) neural networks were fused by applying the Dempster-Shafer (D-S) evidential theory of the information fusion and the basic belief assignment function was established according to the statistical parameters of the networks. The analysis results from the aero-engine vibration signals show that the information fusion method can improve the reliability of the diagnosis and decrease the uncertainty.
- Keywords:
- D-S evidence theory, vibration, BP neural network, Aero-engine
- Download:
- IMEKO-TC22-2017-017.pdf
- DOI:
- -
- Event details
- IMEKO TC:
- TC22
- Event name:
- TC22 Conference 2017 - Measurement facing new challenges!
- Title:
4th Conference on Vibration Measurement (together with 23rd TC3 Conference on the Measurement of Force, Mass and Torque and 13th TC5 Conference on the Measurement of Hardness)
- Place:
- Helsinki, FINLAND
- Time:
- 30 May 2017 - 01 June 2017