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Updated: May 20, 2025

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基于CNN-LSTM-SA神经网络的薄墙的动态负载识别

Jun Wang1, Shaowei Song1,2, Chang Liu1

  • 1National Key Laboratory of Aerospace Liquid Propulsion, Xi'an Aerospace Propulsion Institute, Xi'an 710100, China.

Materials (Basel, Switzerland)
|March 27, 2025
PubMed
概括

精确的航天器载荷识别对于结构安全至关重要. 一种新的CNN-LSTM-SA神经网络方法提高了薄壁航天器结构的负载采集精度和稳定性.

关键词:
美国有线电视新闻网-LSTM-SA负载识别 负载识别薄壁的隔间是薄壁的隔间.时间序列映射时间序列映射

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