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  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2026, Vol. 62 ›› Issue (13): 309-321.doi: 10.3901/JME.260303

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Characterizing and Tracing of Motion Error in CNC Machine Tools Based on Chaotic Attractors

DU Liuqing, CUI Kaihua, YU Yongwei   

  1. College of Mechanical Engineering, Chongqing University of Technology, Chongqing 400054
  • Received:2025-07-09 Revised:2025-12-02 Published:2026-08-28

Abstract: The variation of motion error in CNC machine tools is a nonlinear evolution process with chaotic characteristics. The intrinsic structural state of CNC machine tools determines the nonlinear dynamical evolution trajectory of motion accuracy, namely the chaotic attractor, which opens up a new approach for characterizing and tracing the causes of motion error in CNC machine tools. Therefore, from the perspective of the nonlinear dynamic behavior of the precision evolution of CNC machine tools, a method for essential characteristics and further characterization of motion error evolution based on chaotic attractors is proposed. Firstly, a motion error model is established using the circular motion trajectory of CNC machine tools. The time-series characteristics of motion error are verified through chaotic theory, demonstrating that the evolution of motion error exhibits chaotic characteristics. Then, chaotic attractors of motion error caused by different error factors are reconstructed in phase space, and a mapping model between these chaotic attractors and motion error of CNC machine tools is established. A method for characterizing the motion error of CNC machine tools based on chaotic attractors is proposed. Furthermore, the discrete wavelet transform based on sparrow search algorithm is introduced for time series denoising, addressing the problem that noise interference obscures the phase diagram of chaotic attractors. Finally, the original laws and essential characteristics of the dynamic system are extracted and recovered from the chaotic sequence of motion error. The evolution trajectory of motion accuracy is reconstructed in high-dimensional phase space, and the factors affecting the accuracy variation of CNC machine tools are traced based on the characteristics of chaotic attractors. Experimental results show that the geometric structure of the reconstructed chaotic attractor is relatively clear, and multi-source motion error factors of CNC machine tools can be identified with distinct features and strong adaptability.

Key words: motion error, phase space reconstruction, chaotic attractor, sparrow search, discrete wavelet transform

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