Dual-Window-Based Method for Detecting Behavioral Attitudes of Storage,Transportation and Launch Containers
The storage,transportation and launch container,serving as the carrying equipment for rocket projectiles,holds significant importance in monitoring its attitude and assessing its safety status during transit.To accurately identify the motion changes of the storage,transportation and launch con-tainer during transit,a dual-window-based method for detecting its behavioral attitudes is designed.Three-axis motion data of the container is obtained through attitude sensors;the first window is used for time segmentation and feature extraction of the time-series data,combined with the Temporal Convolu-tional Network(TCN)to identify the phase in which the container is located;the second window is uti-lized to assess potential hazardous behaviors of the container;and the results from both windows are inte-grated to complete the recognition of the container's behavioral attitudes.The experimental results demon-strate that this method can accurately identify hazardous behaviors of the storage,transportation and launch container at different stages during transit,providing a methodological reference for the future de-velopment of intelligent storage,transportation and launch containers and possessing certain engineering application value.
storage,transportation and launch containersbehavioral attitudesdual windowsTemporal Convolutional Network(TCN)
NETL
NSTL
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