Abstract
The fault prediction of weapon equipments is getting more difficult for its complex structure, unique operating environment and multi-source faults. Currently although the main fault prediction methods have achieved certain success in practical application, they all fall short in some aspects. Based on the grey prediction modeling theory and with an analysis of the shortages of GM(1, 1) model, an adaptive multivariable grey prediction model is proposed, which reconstructs whitening background values and initial conditions in view of the relationship among many related reduction feature informations. The datas of a certain aeroengine are taken as an example for prediction and analysis, and the results show that the model is high practicability and precision.
Original language | English |
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Pages (from-to) | 1801-1808 |
Number of pages | 8 |
Journal | Journal of Information and Computational Science |
Volume | 8 |
Issue number | 10 |
State | Published - Oct 2011 |
Keywords
- Adaptive algorithm
- Fault prediction
- GM(1, 1) model
- Particle swarm algorithm