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ハイブリッドメカニズムデータに基づくCNC機械のデジタルツインの構築方法
Ruiqi Zhao1, Hua Huang2, Le Mei1
1School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou, 730050, China.
Scientific reports
|September 1, 2025
まとめ
この研究は,CNC機械工具の給餌システムのためのハイブリッドデジタルツイン (DT) フレームワークを導入します. シミュレーションの精度とリアルタイムの同期を大幅に改善し,精度の高い製造を可能にします.
科学分野:
- 製造エンジニアリング
- 制御システム
- デジタルツイン技術
背景:
- 従来のCNC機械工具供給システムのモデルは,シミュレーションの精度が低く,一般化が限られている.
- 単純化されたプロセスの複製と厳格な最適化方法は,パフォーマンスを妨げます.
- 既存のモデルはリアルタイムの 適応パラメータ更新に苦戦しています
研究 の 目的:
- 新しいハイブリッドメカニズムデータ駆動デジタルツイン (DT) モデリングフレームワークを提案する.
- 精度とCNC機械ツールフィードシステムのシミュレーションの汎用性を向上させる.
- 精密製造のためのリアルタイムDT同期を実現します.
主な方法:
- 非線形コップリングの特徴化方法を開発し,フージ比例積分 (PI) コントロールと機械システムダイナミクスを組み合わせた.
- メカニズムモデル補償のためのWOA-CNN-LSTM-Attentionアルゴリズムを構築しました.
- パラメータ収束のための忘却因子を持つ再帰最小二乗を用いたオンライン認識システムを実装しました.
主要な成果:
- 曖昧なPI制御法を使用した従来のモデルと比較して最大エラーが32.79%減少しました.
- WOA-CNN-LSTM-Attentionアルゴリズムで最大実験誤差を0.0576mmから0.0121mmに減らした.
- リアルタイムDT同期のために,素早いパラメータ収束 (0.005s単純な,0.01s複雑なケース) を達成した.
結論:
- 提案されたハイブリッドDTフレームワークは,安定した効率的なDTシステムを構築するための体系的な解決策を提供します.
- データベースのアプローチと高度なアルゴリズムを統合することで,シミュレーションの精度が著しく向上します.
- このフレームワークは,高度な精密製造アプリケーションに不可欠なリアルタイム同期を可能にします.
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