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Abstract <p>The fractal representation of the formation of the surface layer and the self-similarity of the formation of roughness on it during metal cutting are considered. A criterion for assessing the self-similarity of roughness is proposed—the error of self-similarity. The diagnostic parameter of surface-layer quality control in automated production based on fractal dimension <i>D</i><sub><i>F</i></sub> of vibroacoustic emission signals in real time is substantiated. A neural-network model for controlling the shaping of the surface layer for CNC machines is proposed.</p>

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Development of the Scientific Foundations of the Formation of the Surface Layer of Workpieces during Cutting Based on Nonlinear Dynamics, Fractal Analysis, and Neural Network Modeling

  • 期刊论文

  • 发表日期：

    2026年4月1日

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  • Yu. G. Kabaldin

摘要

Abstract

The fractal representation of the formation of the surface layer and the self-similarity of the formation of roughness on it during metal cutting are considered. A criterion for assessing the self-similarity of roughness is proposed—the error of self-similarity. The diagnostic parameter of surface-layer quality control in automated production based on fractal dimension DF of vibroacoustic emission signals in real time is substantiated. A neural-network model for controlling the shaping of the surface layer for CNC machines is proposed.