August 15, 2025

The prospective prediction of thermal error of NC machine tools based on neural network algorithm

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Analysis reveals thermal error compensation in CNC tools improves prediction accuracy, indicating neural networks can enhance precision.

Higher prediction accuracy results from the LSTM neural network, achieving lower error metrics compared to traditional methods.
Residual mean square error was measured at 0.945, confirming the effectiveness of the LSTM algorithm in thermal error prediction.
Neural networks like LSTM address challenges like hysteresis in thermal error compensation for CNC machine tools.
Investigation highlights the urgent need for effective solutions to thermal issues affecting numerical control accuracy.

Xin Hao (2025) studied this question.

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