A novel precise integration-based updated numerical integration method for milling stability prediction

Stability lobe diagrams (SLDs) can be employed to determine the stability behavior of a milling process. Hence, SLD recognition is an important issue for an effective stable machining monitoring system. Various methods have been developed for prediction of milling stability. However, the main shortc...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology Vol. 124; no. 7-8; pp. 2109 - 2126
Main Authors: Liu, WeiChao, Yang, Wen-An, Chen, YuXin, You, YouPeng
Format: Journal Article
Language:English
Published: London Springer London 01.02.2023
Springer Nature B.V
Subjects:
Accuracy
Advanced manufacturing technologies
Algorithms
CAE) and Design
Computer-Aided Engineering (CAD
Efficiency
Engineering
Experimental methods
Hermite polynomials
Industrial and Production Engineering
Interpolation
Mechanical Engineering
Media Management
Milling (machining)
Numerical analysis
Numerical integration
Original Article
Research methodology
Simulation
Stability lobes
Submerging
Vibration
Stability lobe diagrams
Precise integration
Milling stability prediction
Hermite interpolation
Updated numerical integration method
ISSN:0268-3768, 1433-3015
Online Access:Get full text
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Summary:Stability lobe diagrams (SLDs) can be employed to determine the stability behavior of a milling process. Hence, SLD recognition is an important issue for an effective stable machining monitoring system. Various methods have been developed for prediction of milling stability. However, the main shortcoming of such methods is that they cannot accurately and efficiently predict milling stability. This study proposes a novel precise integration-based updated numerical integration method (PI-UNIM) that can be both accurate and efficient in milling stability prediction. The fifth-order Hermite interpolation polynomial for numerical integration formula derivation is addressed in this work. Transition matrix is obtained with the precise integration algorithm. The numerical results obtained using extensive simulation indicate that the proposed method can effectively recognize SLDs for not only low immersion milling situation but also high immersion milling situation. Empirical comparisons show that the proposed method performs better than existing methods in terms of computation accuracy and computation efficiency. A demonstrative example is provided to illustrate the usage of the proposed method.
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-022-10372-3