Entry-Exit Water Perception and Damage Monitoring of Rotors for Cross-Media Vehicle

Bo Fusen; Pan Deng; Fang Ziyi; Fu Bowei; Li Hanyang; Liu Zhihai

doi:10.11993/j.issn.2096-3920.2026-0045

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Bo Fusen, Pan Deng, Fang Ziyi, Fu Bowei, Li Hanyang, Liu Zhihai. Entry-Exit Water Perception and Damage Monitoring of Rotors for Cross-Media Vehicle[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2026-0045

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Bo Fusen, Pan Deng, Fang Ziyi, Fu Bowei, Li Hanyang, Liu Zhihai. Entry-Exit Water Perception and Damage Monitoring of Rotors for Cross-Media Vehicle[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2026-0045

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Entry-Exit Water Perception and Damage Monitoring of Rotors for Cross-Media Vehicle

doi: 10.11993/j.issn.2096-3920.2026-0045

College of Physics and Optoelectronic Engineering, Harbin Engineering University, Harbin 150001, China

Received Date: 2026-03-05
Accepted Date: 2026-04-14
Rev Recd Date: 2026-04-05

Available Online: 2026-09-02

Abstract

Abstract

In the process of medium conversion, the rotor of cross-medium vehicle faces complex instantaneous strain problems due to the sudden change of medium physical parameters. Long-term alternating load can easily lead to the initiation, propagation and even fracture of blade microcracks, which seriously threatens the operational reliability and task continuity of the vehicle. In order to solve the core problems of rotor inlet and outlet water state perception and damage monitoring, this paper constructs a complete technical system of ' signal acquisition-processing-feature extraction-model training-state perception ': The experimental device controls the inlet and outlet water of the rotor drive structure through the guide rail, and uses the fiber grating demodulator to collect the whole process signal of the rotor inlet and outlet water in real time. The singular point elimination method is selected to identify and eliminate the abnormal data points, and the characteristics of the signal entering water, water and outlet water are completely retained. The timestamp and amplitude information of the time series are retained by image conversion, and the time correlation characteristics are enhanced and the redundancy is eliminated. Then the feature signal and the converted image are used for model training. The results show that the training model realizes the accurate identification and real-time damage warning of the rotor inlet and outlet water state of the cross-media vehicle, provides decision support for the route adjustment of the vehicle, effectively improves its intelligent perception and penetration ability, and promotes the in-depth application of optical monitoring technology in the field of new weapon equipment and national defense.
- rotor of cross-media vehicle,
- fiber bragg grating,
- unsteady disturbance,
- signal processing,
- state perception,
- damage monitoring

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References(28)

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