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Flutter Monitoring of Screw Milling Based on RF‑LSSVM
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Xingwei SUN1, 2, Jia LI1, 2, Heran YANG1, 2, Weifeng ZHANG1, 2, Zhixu DONG1, 2, Yin LIU1, 2
Journal of Vibration,Measurement and Diagnosis | 2025, 45(5) : 885 - 892
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Journal of Vibration,Measurement and Diagnosis | 2025, 45(5): 885-892
• PAPER •
Flutter Monitoring of Screw Milling Based on RF‑LSSVM
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Xingwei SUN1, 2, Jia LI1, 2, Heran YANG1, 2, Weifeng ZHANG1, 2, Zhixu DONG1, 2, Yin LIU1, 2
Affiliations
  • 1.College of Mechanical Engineering，Shenyang University of Technology　Shenyang，110870，China
  • 2.Key Laboratory of Numerical Control Manufacturing Technology for Complex Surfaces of Liaoning Province　Shenyang，110870，China
Published: 2025-10-01 doi: 10.16450/j.cnki.issn.1004-6801.2025.05.004
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Aiming at the chatter problem in the process of milling screw rotors，a chatter monitoring method based on RelifF algorithm to the least square support vector machine （RF-LSSVM） is proposed. Firstly，the vibration signals in the milling process of the screw rotor are decomposed，and feature extraction and selection are performed using the variational modal （VMD） and the RelifF algorithm. Secondly，the penalty factor，kernel parameter，the number of near neighbor samples of RelifF algorithm and the length of dimension reduction feature of LSSVM are iteratively optimized using the enhanced whale optimization algorithm （E-WOA）. Finally，a flutter identification model is established by inputting the reduced-dimensional flutter eigenvector matrix and outputting the flutter occurrence state. The experimental results show that the proposed VMD-RF-LSSVM model has a higher recognition accuracy than the unoptimized variational modal decomposition-support vector machine （VMD-SVM） model，reaching 99.5% accuracy. The proposed method can effectively monitor the chatter problem in the screw milling process，provides a thought for the optimization of the screw milling processing.

variational modal decomposition  /  least square support vector machine  /  machining chatter  /  feature dimension reduction
Xingwei SUN, Jia LI, Heran YANG, Weifeng ZHANG, Zhixu DONG, Yin LIU. Flutter Monitoring of Screw Milling Based on RF‑LSSVM[J]. Journal of Vibration,Measurement and Diagnosis, 2025 , 45 (5) : 885 -892 . DOI: 10.16450/j.cnki.issn.1004-6801.2025.05.004
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Article Info
doi: 10.16450/j.cnki.issn.1004-6801.2025.05.004
  • Receive Date：2023-11-30
  • Online Date：2026-03-27
  • Published：2025-10-01
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  • Received：2023-11-30
  • Revised：2024-07-11
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Affiliations
    1.College of Mechanical Engineering，Shenyang University of Technology　Shenyang，110870，China
    2.Key Laboratory of Numerical Control Manufacturing Technology for Complex Surfaces of Liaoning Province　Shenyang，110870，China
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表12种不同金属材料的力学参数
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Number of
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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