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Research Papers

RCSA-Based Method for Tool Frequency Response Function Identification Under Operational Conditions Without Using Noncontact Sensor

[+] Author and Article Information
Rong Yan

National NC System Engineering
Research Center,
Huazhong University of
Science and Technology,
Wuhan 430074, China
e-mail: yanrong@hust.edu.cn

Xiaowei Tang

National NC System Engineering
Research Center,
Huazhong University of
Science and Technology,
Wuhan 430074, China
e-mail: txwysxf@126.com

Fangyu Peng

National NC System Engineering
Research Center,
Huazhong University of
Science and Technology,
Wuhan 430074, China;
State Key Laboratory of Digital Manufacturing
Equipment and Technology,
Huazhong University of
Science and Technology,
Wuhan 430074, China
e-mail: zwm8917@263.net

Yuting Li

National NC System Engineering
Research Center,
Huazhong University of
Science and Technology,
Wuhan 430074, China
e-mail: lytwhut@163.com

Hua Li

National NC System Engineering
Research Center,
Huazhong University of
Science and Technology,
Wuhan 430074, China
e-mail: M201570333@hust.edu.cn

1Corresponding author.

Manuscript received August 29, 2016; final manuscript received December 1, 2016; published online January 30, 2017. Editor: Y. Lawrence Yao.

J. Manuf. Sci. Eng 139(6), 061009 (Jan 30, 2017) (11 pages) Paper No: MANU-16-1470; doi: 10.1115/1.4035418 History: Received August 29, 2016; Revised December 01, 2016

The stability lobe diagrams predicted using the tool frequency response function (FRF) at the idle state usually have discrepancies compared with the actual stability cutting boundary. These discrepancies can be attributed to the effect of spindle rotating on the tool FRFs which are difficult to measure at the rotating state. This paper proposes a new tool FRF identification method without using noncontact sensor for the rotating state of the spindle. In this method, the FRFs with impact applied on smooth rotating tool and vibration response tested on spindle head are measured for two tools of different lengths clamped in spindle–holder assembly. Based on those FRFs, an inverse receptance coupling substructure analysis (RCSA) algorithm is developed to identify the FRFs of spindle–holder–partial tool assembly. A finite-element modeling (FEM) simulation is performed to verify the validity of inverse RCSA algorithm. The tool point FRFs at the spindle rotating state are obtained by coupling the FRFs of the spindle–holder–partial tool and the other partial tool. The effects of spindle rotational speed on tool point FRFs are investigated. The cutting experiment demonstrates that this method can accurately identify the tool point FRFs and predict cutting stability region under spindle rotating state.

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References

Figures

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Fig. 1

Two tools of different lengths clamped in spindle–holder assembly and substructures

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Fig. 3

FRFs obtained by ansys harmonic analysis and inverse RCSA calculation

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Fig. 4

Impact testing for different tool overhang

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Fig. 5

Comparison of FRF measured under different tool overhang: (a) tool overhang length is 105 mm, (b) tool overhang length is 95 mm, (c) tool overhang length is 85 mm, and (d) tool overhang length is 75 mm

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Fig. 6

Impact experiments under spindle rotating state

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Fig. 7

FRFs tested by model impact

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Fig. 8

Comparison of tool point FRF in x and y directions obtained using impact testing with that identified by the proposed method: (a) tool overhang length is 75 mm and (b) tool overhang length is 70 mm

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Fig. 9

Identified tool point FRFs under different spindle rotating speeds

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Fig. 10

Cutting experiment

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Fig. 11

(a) Stability diagrams obtained for idle state and 4000 rpm spindle speed and (b) stability diagrams obtained for idle state and 5000 rpm spindle speed. The symbols are follows: (1)○is a stable case and (2) * is an unstable cutting case.

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Fig. 12

Cutting force spectrum of Fx at different parameter points: (a) point A (chatter), (b) point B (stable), (c) point C (chatter), and (d) point D (stable)

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