An improved semi-analytical approach for modeling of process damping in orthogonal cutting considering cutting edge radius

Cao, Chang; Zhang, Xiaoming; Huang, Tao; Ding, Han

doi:10.1177/0954405419863605

Cited by 8 publications

(3 citation statements)

References 37 publications

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“…Based on Chiou and Liang's model 25 , they also deduced the equivalent process damping coefficient of the tool with the tool wear belt. Cao et al 28 proposed a semi-analytical method to calculate the extruded volume in cutting with honed tools. To predict the stability of dynamic machining systems, there are severe methods for simulation, such as single frequency method, 29 multi-frequency method, 30,31 semidiscretization method, [32][33][34] etc.…”

Section: Introductionmentioning

confidence: 99%

Study on the process damping in milling of thin-walled Ti-6Al-4V workpiece: Modeling, analysis, and prediction

Zhao

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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Due to limited stiffness and wall thickness, chatter usually occurs in the milling of thin-walled components, which reduces the surface quality and machining productivity. It is well acknowledged that process damping, which results from the interference between the flank face and the machined surface, can improve the chatter stability. This paper analyzes the influence of process damping on the milling system of thin-walled Ti-6Al-4V alloy based on the Nyquist criterion and the Routh criterion. Meanwhile, a detailed and improved calculation model of the interference area is presented to promote the prediction accuracy of process damping. The comparison of computational results and experimental findings verifies the accuracy of the proposed model. The decrease of spindle speed increases the interference area as well as the total damping of the milling system. When the spindle speed is 1000 rpm, the ultimate stable axial depth of cut increases from 1.2 mm to 2.7 mm by utilizing the special designed end mills based on the presented model.

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Section: Introductionmentioning

confidence: 99%

Study on the process damping in milling of thin-walled Ti-6Al-4V workpiece: Modeling, analysis, and prediction

Zhao

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Since the time varying dynamic cutting force coefficient matrix can be approximated by its Fourier series component, the ZOA method allows a rapid calculation of SLD compared with time domain method. This method has been extended to variable-pitch cutters, 4 honed tools 5 and so on.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling and stability prediction in milling process of thin-walled workpiece with multiple structural modes

Zhang

Luo

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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Regenerative chatter can easily occur in the milling process of thin-walled workpiece due to the inherently low stiffness. This article aims to predict the stability of thin-walled workpiece in the milling process with a complete dynamic model. First, multiple structural modes of thin-walled workpiece are taken into consideration, and a complete dynamic model of thin-walled workpiece milling system is developed. Then, a numerical integration method is used to achieve the stability lobe diagrams of the milling system and identify the chatter frequency. Besides, the major structural mode, which is responsible for the occurrence of thin-walled workpiece chatter in the milling process, is predicted. A series of milling tests concerning a general cantilever plate are conducted, and the test results agree well with the predicted results, which shows the effectiveness of the proposed method. Finally, the effects of milling tool and structural modes on milling stability are discussed separately, which could provide theoretical basis for the dynamic modeling of thin-walled workpiece in milling process.

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“…1,2 In thin-wall milling process, the time-varying dynamics of the workpiece makes it difficult to build the cutting system model accurately, such that the cutting parameters may be unsuitable by using the analytic methods. 3–7 Paralleled by the development of sensor technology, the signal produced in the milling process is widely used to identify chatter. Hence, a sensor-based method is essential to identify and suppress chatter, which can enhance the surface finish and guarantee the stable cutting process.…”

Section: Introductionmentioning

confidence: 99%

Chatter identification in thin-wall milling using an adaptive variational mode decomposition method combined with the decision tree model

Wang

Niu

Sun

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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Chatter is prone to occur in thin-wall part milling process due to the low stiffness and damping of the workpiece. It roughens the machining surface, shortens the tool life, and thus should be detected and prevented. However, the multimode and time-varying dynamics of thin-wall parts produces nonstationary and multicomponent cutting signals, which makes it challenging to accurately identify the chatter occurrence. In this article, an effective chatter identification method based on adaptive variational mode decomposition and decision tree is presented to tackle this problem. The adaptive variational mode decomposition is used to adaptively decompose the raw acoustic signal into several subsignals, and the decision tree is used to automatically determine the chatter threshold. First, the convergence of multicenter-frequency signal processing is analyzed and is proved to be closely related to the accuracy of variational mode decomposition. Afterward, a criterion is set up to initialize the center frequencies of variational mode decomposition, on the basis of which an adaptive energy ratio-based method with good computational efficiency is presented to extract the frequencies of the main components from the raw signal. The initial center frequencies and the number of modes of variational mode decomposition are simultaneously obtained. As a result, the raw signal is adaptively decomposed into several subsignals, which contain its principal components. Then, the normalized energy and sample entropy of the subsignals are selected to establish the decision tree model for automatic chatter identification. Several milling tests on a thin-wall plate are carried out to verify the proposed method. The results show that chatter can be identified accurately and efficiently using the proposed method.

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An improved semi-analytical approach for modeling of process damping in orthogonal cutting considering cutting edge radius

Cited by 8 publications

References 37 publications

Study on the process damping in milling of thin-walled Ti-6Al-4V workpiece: Modeling, analysis, and prediction

Study on the process damping in milling of thin-walled Ti-6Al-4V workpiece: Modeling, analysis, and prediction

Dynamic modeling and stability prediction in milling process of thin-walled workpiece with multiple structural modes

Chatter identification in thin-wall milling using an adaptive variational mode decomposition method combined with the decision tree model

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