@article{MTMT:34232416,
	title = {An alternative approach to model the dynamics of a milling tool},
	url = {https://m2.mtmt.hu/api/publication/34232416},
	author = {Chen, Kaidong and Zhang, He and van de Wouw, Nathan and Detournay, Emmanuel},
	doi = {10.1016/j.jsv.2023.117940},
	journal-iso = {J SOUND VIB},
	journal = {JOURNAL OF SOUND AND VIBRATION},
	volume = {569},
	unique-id = {34232416},
	issn = {0022-460X},
	abstract = {Mathematical models play an increasing role in understanding and predicting machining processes, in particular milling. However, despite the considerable efforts that have been dedicated to this problem, a majority of milling models still rely on simplifying assumptions to calculate the chip thickness. In this paper, the chip thickness is determined without these simplifications, based on a surface function that describes the milled surface and on information about the workpiece boundary. By combining the partial differential equation (PDE) governing the evolution of this surface function with the ordinary differential equations (ODE) governing the tool/machine dynamics, a mixed PDE-ODE formulation is proposed to describe the dynamics of the milling process. The coupled system of differential equations is solved using an algorithm that combines finite difference (ODE) and finite volume (PDE) methods. A case study is presented to compare the proposed approach with the classical delay differential equations (DDE) model formulation for milling processes based on a simplified chip thickness model. The PDE-ODE formulation represents an explicit mathematical model for milling process dynamics; it yields a theoretically exact chip thickness and offers a means to assess the validity of models based on DDE formulation. Moreover, the proposed formulation is capable of simulating transient tool behaviors when the tool is milling the outer region of the workpiece, which is in general neglected by the DDE-based models.},
	keywords = {Milling; Chip thickness; Modeling and numerical simulation; Tool/machine dynamics; PDE-ODE formulation},
	year = {2024},
	eissn = {1095-8568},
	orcid-numbers = {Detournay, Emmanuel/0000-0003-3698-7575}
}

@article{MTMT:34724268,
	title = {A novel chatter detection method in micro-milling process using wavelet packet entropy},
	url = {https://m2.mtmt.hu/api/publication/34724268},
	author = {Jing, Xiubing and Yang, He and Song, Xiaofei and Chen, Yun and Li, Huaizhong},
	doi = {10.1007/s00170-024-13325-0},
	journal-iso = {INT J ADV MANUFACT TECHNOL},
	journal = {INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY},
	volume = {online first},
	unique-id = {34724268},
	issn = {0268-3768},
	year = {2024},
	eissn = {1433-3015},
	pages = {1},
	orcid-numbers = {Jing, Xiubing/0000-0002-7649-2262}
}

@article{MTMT:34207865,
	title = {Predicting saddle-node bifurcations using transient dynamics: a model-free approach},
	url = {https://m2.mtmt.hu/api/publication/34207865},
	author = {Habib, Giuseppe},
	doi = {10.1007/s11071-023-08941-6},
	journal-iso = {NONLINEAR DYNAM},
	journal = {NONLINEAR DYNAMICS},
	volume = {111},
	unique-id = {34207865},
	issn = {0924-090X},
	abstract = {This paper proposes a novel method for predicting the presence of saddle-node bifurcations in dynamical systems. The method exploits the effect that saddle-node bifurcations have on transient dynamics in the surrounding phase space and parameter space, and does not require any information about the steady-state solutions associated with the bifurcation. Specifically, trajectories of a system obtained for parameters close to the saddle-node bifurcation present local minima of the logarithmic decrement trend in the vicinity of the bifurcation. By tracking the logarithmic decrement for these trajectories, the saddle-node bifurcation can be accurately predicted. The method does not strictly require any mathematical model of the system, but only a few time series, making it directly implementable for gray- and black-box models and experimental apparatus. The proposed algorithm is tested on various systems of different natures, including a single-degree-of-freedom system with nonlinear damping, the mass-on-moving-belt, a time-delayed inverted pendulum, and a pitch-and-plunge wing profile. Benefits, limitations, and future perspectives of the method are also discussed. The proposed method has potential applications in various fields, such as engineering, physics, and biology, where the identification of saddle-node bifurcations is crucial for understanding and controlling complex systems.},
	year = {2023},
	eissn = {1573-269X},
	pages = {20579-20596},
	orcid-numbers = {Habib, Giuseppe/0000-0003-3323-6901}
}

@article{MTMT:34362493,
	title = {Revealing the interaction mechanism of pulsed laser processing with the application of acoustic emission},
	url = {https://m2.mtmt.hu/api/publication/34362493},
	author = {Liu, Weinan and Rong, Youmin and Yang, Ranwu and Wu, Congyi and Zhang, Guojun and Huang, Yu},
	doi = {10.1007/s12200-023-00070-7},
	journal-iso = {FRONTIERS OF OPTOELECTRONICS},
	journal = {FRONTIERS OF OPTOELECTRONICS},
	volume = {16},
	unique-id = {34362493},
	issn = {2095-2759},
	abstract = {The mechanisms of interaction between pulsed laser and materials are complex and indistinct, severely influencing the stability and quality of laser processing. This paper proposes an intelligent method based on the acoustic emission (AE) technique to monitor laser processing and explore the interaction mechanisms. The validation experiment is designed to perform nanosecond laser dotting on float glass. Processing parameters are set differently to generate various outcomes: ablated pits and irregular-shaped cracks. In the signal processing stage, we divide the AE signals into two bands, main and tail bands, according to the laser processing duration, to study the laser ablation and crack behavior, respectively. Characteristic parameters extracted by a method that combines framework and frame energy calculation of AE signals can effectively reveal the mechanisms of pulsed laser processing. The main band features evaluate the degree of laser ablation from the time and intensity scales, and the tail band characteristics demonstrate that the cracks occur after laser dotting. In addition, from the analysis of the parameters of the tail band very large cracks can be efficiently distinguished. The intelligent AE monitoring method was successfully applied in exploring the interaction mechanism of nanosecond laser dotting float glass and can be used in other pulsed laser processing fields.},
	keywords = {MONITORING; Laser ablation; CRACKS; Acoustic emission; Laser dotting},
	year = {2023},
	eissn = {2095-2767}
}

@article{MTMT:33848897,
	title = {Chatter detection in milling processes-a review on signal processing and condition classification},
	url = {https://m2.mtmt.hu/api/publication/33848897},
	author = {Navarro-Devia, John Henry and Chen, Yun and Dao, Dzung Viet and Li, Huaizhong},
	doi = {10.1007/s00170-023-10969-2},
	journal-iso = {INT J ADV MANUFACT TECHNOL},
	journal = {INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY},
	unique-id = {33848897},
	issn = {0268-3768},
	abstract = {Among the diverse challenges in machining processes, chatter has a significant detrimental effect on surface quality and tool life, and it is a major limitation factor in achieving higher material removal rate. Early detection of chatter occurrence is considered a key element in the milling process automation. Online detection of chatter onset has been continually investigated over several decades, along with the development of new signal processing and machining condition classification approaches. This paper presents a review of the literature on chatter detection in milling, providing a comprehensive analysis of the reported methods for sensing and testing parameter design, signal processing and various features proposed as chatter indicators. It discusses data-driven approaches, including the use of different techniques in the time-frequency domain, feature extraction, and machining condition classification. The review outlines the potential of using multiple sensors and information fusion with machine learning. To conclude, research trends, challenges and future perspectives are presented, with the recommendation to study the tool wear effects, and chatter detection at dissimilar milling conditions, while utilization of considerable large datasets-Big Data-under the Industry 4.0 framework and the development of machining Digital Twin capable of real-time chatter detection are considered as key enabling technologies for intelligent manufacturing.},
	keywords = {STABILITY; Feature extraction; Signal processing; Milling; VIBRATION; Tool condition monitoring; Machining dynamics; Chatter detection},
	year = {2023},
	eissn = {1433-3015},
	orcid-numbers = {Li, Huaizhong/0000-0002-5617-702X}
}

@article{MTMT:34307458,
	title = {Auto-identification of dominant modal parameters from multi-batch signals based on weighted SSA to suppress milling vibration},
	url = {https://m2.mtmt.hu/api/publication/34307458},
	author = {Peng, Yili and Chen, Xubing and Jiang, Xuchu and Huang, Kuntao and Fu, Zhongtao},
	doi = {10.1007/s00170-023-12156-9},
	journal-iso = {INT J ADV MANUFACT TECHNOL},
	journal = {INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY},
	unique-id = {34307458},
	issn = {0268-3768},
	abstract = {The modal parameters identified from on-site cutting signals can more truly reflect the dynamics of the machine tool in the operating state. However, due to the spindle rotation and position change of movable parts in the cutting process, modal identification based on on-site cutting vibration signals is interfered with the harmonic frequencies, structural time-varying, artificial analysis, and other uncertain factors. The current modal parameter identification methods cannot realize the auto-identification of machine tool structures simultaneously considering the above factors. Therefore, to realize the auto-identification of structural dominant modal parameters eliminating the interference of harmonic, structural time-varying, and artificial analysis, a new weighted SSA (singular spectrum analysis) method is proposed in this paper. First, multi-batch on-site vibration signals are decomposed to extract the eigenvalue and eigen matrix through singular value decomposition (SVD). Then, based on the variance filtering of principal component analysis, a half principal component analysis is proposed to extract the weighted vector of the eigen matrix. After that, the clustering algorithm is adopted to average the sample set, and the power spectrum curve is modified and reconstructed according to the cluster center. The dominant modal parameters are auto-identified with the reconstructed curve and optimized through the genetic algorithm. Finally, cutting tests are conducted to verify the feasibility and effectiveness of the auto-identification and optimization method.},
	keywords = {cluster algorithm; Auto-identification of modal parameter; Suppression of cutting vibration; Weighted SSA},
	year = {2023},
	eissn = {1433-3015}
}

@article{MTMT:33154441,
	title = {Investigation on an in-process chatter detection strategy for micro-milling titanium alloy thin-walled parts and its implementation perspectives},
	url = {https://m2.mtmt.hu/api/publication/33154441},
	author = {Wang, Peng and Bai, Qingshun and Cheng, Kai and Zhang, Yabo and Zhao, Liang and Ding, Hui},
	doi = {10.1016/j.ymssp.2022.109617},
	journal-iso = {MECH SYST SIGNAL PR},
	journal = {MECHANICAL SYSTEMS AND SIGNAL PROCESSING},
	volume = {183},
	unique-id = {33154441},
	issn = {0888-3270},
	year = {2023},
	eissn = {1096-1216},
	orcid-numbers = {Wang, Peng/0000-0002-2653-5367}
}

@article{MTMT:34504731,
	title = {A Novel Method for Updating Time-Varying Information of Milling Thin-Walled Components Based on Digital Twin Model},
	url = {https://m2.mtmt.hu/api/publication/34504731},
	author = {Wang, Zhaodong and Liu, Shujie and Li, Hongkun and Ou, Jiayu and Peng, Defeng and Li, Zhi},
	doi = {10.1109/JSEN.2023.3342025},
	journal-iso = {IEEE SENS J},
	journal = {IEEE SENSORS JOURNAL},
	volume = {1},
	unique-id = {34504731},
	issn = {1530-437X},
	year = {2023},
	eissn = {1558-1748},
	pages = {1-1},
	orcid-numbers = {Li, Hongkun/0000-0003-1979-4763; Ou, Jiayu/0000-0002-5448-3496}
}

@article{MTMT:33154471,
	title = {Investigation of robotic milling chatter stability prediction under different cutter orientations by an updated full-discretization method},
	url = {https://m2.mtmt.hu/api/publication/33154471},
	author = {Ji, Yongjian and Wang, Liyong and Song, Yue and Wang, Hongjun and Liu, Zhibing},
	doi = {10.1016/j.jsv.2022.117150},
	journal-iso = {J SOUND VIB},
	journal = {JOURNAL OF SOUND AND VIBRATION},
	volume = {536},
	unique-id = {33154471},
	issn = {0022-460X},
	year = {2022},
	eissn = {1095-8568}
}

@mastersthesis{MTMT:34504856,
	title = {On the effect of machine tool dynamics on surface quality and stability},
	url = {https://m2.mtmt.hu/api/publication/34504856},
	author = {Kiss, Ádám},
	publisher = {Budapest University of Technology and Economics},
	unique-id = {34504856},
	year = {2022},
	orcid-numbers = {Kiss, Ádám/0000-0002-7074-4553}
}