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Updated: Feb 18, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

2.2K

風力タービンのベアリングの故障分類の識別は,最適化された変数モード分解とコンボリュアルニューラルネットワーク-双方向ゲートリキュアントユニット-注意に基づく

Minan Tang1, Zhanglong Tao1, Changyou Wang2

  • 1College of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou, China.

Science progress
|February 16, 2026
PubMed
まとめ

この研究では,最適化変数モード分解 (VMD) とCNN-BiGRU-Attentionモデルを組み合わせて,精密な風力タービンのギアボックスローリングベアリングの故障分類を行い,発電機の信頼性を向上させるための最適化変数モード分解 (VMD) が導入されています.

キーワード:
CNN バイグルー 注目モデルIGRIME-VMD アルゴリズムによる風力タービンの風力タービンは,ベアリングの故障診断複合的な多次元斜面エントロピーである.

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