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Transient Fault Diagnosis Algorithm based on Feature Classification and Its Application in High-Power Laser facility

Qiang Ren  Hang Gao  Hailei Ren  Baoran An  Tianyou Yun  Xiaoli Wang  
【摘要】:High-power laser facility plays an import role both in scientific research and military application,and the occurred faults are usually transient.In this paper,a transient fault diagnosis algorithm based on feature classification is proposed,and the algorithm has been applied in the high-power laser facility.The method extracts the features of input data with an autoencoder network.And based on the extracted features,a multi-layer full connection neural network is adopted for fault diagnosis.By comparing the results with those obtained by traditional fault diagnosis methods,the performance of the algorithm has been verified.

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