Fault Prediction Method of the Marine Gas Turbine Based on Neural Network-Markov

Jian Guo Cui; Long Zhang; Gui Hua Wang; Bo Cui; Li Ying Jiang

doi:10.4028/www.scientific.net/AMM.538.171

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 538Fault Prediction Method of the Marine Gas Turbine...

Fault Prediction Method of the Marine Gas Turbine Based on Neural Network-Markov

Abstract:

Since the fault of marine gas turbine is difficult to predict accurately, making the rolling bearing as the specific object, a fault prediction model of the marine gas turbine based on Neural Network and Markov method is built through the data analysis, preprocessing and feature extraction for the rolling bearing history test data. First, it uses the neural network method to realize the health state recognition of the marine gas turbine. Then, the fault of the marine gas turbine is predicted by taking advantage of the fault prediction which is based on the Markov model. The results show that the efficiency of fault prediction for the marine gas turbine can be realized better through the fault prediction model constructed in view of the Neural Network and Markov. And it also has a significant practical value in project item.

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Periodical:

Applied Mechanics and Materials (Volume 538)

Pages:

171-174

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.538.171

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Online since:

April 2014

Authors:

Jian Guo Cui*, Long Zhang, Gui Hua Wang, Bo Cui, Li Ying Jiang

Keywords:

Faults Prediction, Marine Gas Turbine, Markov Model, Neural Network (NN), State Recognition

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* - Corresponding Author

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