Symmetry in Intelligent Spindle Modelling and Vibration Analysis

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Engineering and Materials".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 324

Special Issue Editors


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Guest Editor
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Interests: rotor dynamics; fault diagnosis; chatter detection; vibration analysis
School of Mechanical Engineering, Southeast University, Nanjing 211189, China
Interests: multi-axis printing; multi-axis machining; computer-aided manufacturing; pinn-based path planning
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
Interests: vibration control; compliant mechanisms; robotics

Special Issue Information

Dear Colleagues,

Intelligent spindle modelling and vibration analysis have become key focusses for advancing modern manufacturing. Spindles are central to machining processes, and their dynamic behaviour directly influences productivity, precision, and tool life. One of the long-standing challenges has been to develop models that accurately represent the complex interactions of stiffness, damping, and cutting forces, which often lead to chatter and other vibration instabilities. Recent trends highlight the growing role of artificial intelligence and data-driven diagnostics; however, physics-based modelling and dynamic characterisation remain essential. In particular, leveraging symmetry in spindle structures and vibration modes offers additional insight into dynamic responses, enabling more reliable vibration analysis and robust system control. Intelligent approaches that combine physical models with advanced signal processing and machine learning now provide the foundation for real-time monitoring and predictive maintenance.

The integration of these techniques is raising expectations for high-speed machining, where spindles must operate under increasingly complex conditions with greater stability and precision. Research in this field is therefore moving toward hybrid modelling, intelligent fault detection algorithms, and adaptive monitoring systems. By bridging raw vibration data with actionable insights, intelligent spindle modelling plays a pivotal role in achieving more resilient, adaptive, and high-performance manufacturing systems.

Dr. Jianghai Shi
Dr. Dong He
Dr. Wenshuo Ma
Guest Editors

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Keywords

  • intelligent spindle modelling
  • vibration analysis
  • chatter detection
  • symmetry in dynamics
  • high-performance manufacturing

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Published Papers (1 paper)

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Research

16 pages, 1598 KB  
Article
Sliding Mode Control of Symmetric Permanent Magnet Synchronous Motor Based on Novel Adaptive Reaching Law and Combining Improved Terminal Fast Sliding Mode Disturbance Observer
by Mingyuan Hu, Changning Wei, Lei Zhang, Ping Wang, Dongjun Zhang and Tongwei Xie
Symmetry 2025, 17(12), 2057; https://doi.org/10.3390/sym17122057 - 2 Dec 2025
Viewed by 207
Abstract
Permanent Magnet Synchronous Motors (PMSMs) exhibit inherent symmetry in their electromagnetic structure yet behave as nonlinear and strongly coupled systems that are susceptible to internal parameter perturbations and external disturbances, posing challenges to effective control under dynamic operating conditions. To address these issues, [...] Read more.
Permanent Magnet Synchronous Motors (PMSMs) exhibit inherent symmetry in their electromagnetic structure yet behave as nonlinear and strongly coupled systems that are susceptible to internal parameter perturbations and external disturbances, posing challenges to effective control under dynamic operating conditions. To address these issues, this paper proposes a sliding mode control strategy for PMSMs that integrates a Novel Adaptive Reaching Law (NARL) and an Improved Terminal Fuzzy Sliding Mode Disturbance Observer (IFTSMDO), denoted as SMC-NARL-IFTSMDO. The NARL is designed with a state-dependent dynamic gain adjustment mechanism and terminal attractive factor characteristics: it increases the gain to ensure fast convergence when the system state is far from the sliding mode surface, and adaptively attenuates the gain to suppress chattering when approaching the sliding mode surface, thereby balancing the contradiction between convergence speed and chattering in traditional sliding mode control. The IFTSMDO constructs a composite sliding mode surface incorporating error derivatives, terminal power terms, and saturation functions, which enhances the sensitivity of disturbance estimation in the small-error stage, avoids high-frequency chattering caused by sign functions, and provides accurate feedforward compensation for the speed loop controller to improve the system’s anti-disturbance capability. Additionally, the asymptotic stability of the proposed control strategy is strictly proven using the Lyapunov stability theory, laying a solid theoretical foundation for its application. Experiments are conducted on a TMS320F28379D DSP-based platform, and quantitative results show that compared with the traditional sliding mode control (SMC-TRL), the proposed strategy reduces the no-load startup response time by 60%, the steady-state speed fluctuation by 60%, and the speed fluctuation under load disturbance by 81.5%, fully demonstrating its superiority in dynamic response and anti-disturbance performance. Full article
(This article belongs to the Special Issue Symmetry in Intelligent Spindle Modelling and Vibration Analysis)
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