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<p>To compensate for machine tool system error, engineers manually correct the adjustment parameters based on experience and repeatedly measure the tooth surface error. This method is not only inefficient but also costly. This study addresses tooth surface error evaluation and compensation in spiral bevel gear machining by proposing an innovative method that integrates mathematical modeling with machine learning. The method combines mathematical modeling of tooth surface generation with a BP neural network-based error compensation strategy, enabling automated prediction and correction of machining errors. Experimental results show a significant reduction in mean square error from 1446.9 to 490.7, confirming the effectiveness of the proposed method. This research overcomes the limitations of traditional techniques and provides an efficient and automated solution for spiral bevel gear machining, with important theoretical and practical implications for the field of gear manufacturing.</p>

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Tooth surface error evaluation and compensation of spiral bevel gear based on machine learning

  • 期刊论文

  • 发表日期：

    2025年10月3日

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  • Geng Li,
  • Peng Wang,
  • Kan Xing,
  • Jiahao Wu

摘要

To compensate for machine tool system error, engineers manually correct the adjustment parameters based on experience and repeatedly measure the tooth surface error. This method is not only inefficient but also costly. This study addresses tooth surface error evaluation and compensation in spiral bevel gear machining by proposing an innovative method that integrates mathematical modeling with machine learning. The method combines mathematical modeling of tooth surface generation with a BP neural network-based error compensation strategy, enabling automated prediction and correction of machining errors. Experimental results show a significant reduction in mean square error from 1446.9 to 490.7, confirming the effectiveness of the proposed method. This research overcomes the limitations of traditional techniques and provides an efficient and automated solution for spiral bevel gear machining, with important theoretical and practical implications for the field of gear manufacturing.