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Research Papers

A Statistical Model of Equivalent Grinding Heat Source Based on Random Distributed Grains

[+] Author and Article Information
Zhenguo Nie

Beijing Key Lab of Precision/Ultra-Precision
Manufacturing Equipments and Control,
Tsinghua University,
Beijing 100084, China;
George W. Woodruff School
of Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332-0405
e-mails: zhenguo.nie@me.gatech.edu;
zhenguonie@gmail.com

Gang Wang

Beijing Key Lab of Precision/Ultra-Precision
Manufacturing Equipments and Control,
Tsinghua University,
Beijing 100084, China;
Department of Mechanical Engineering,
Tsinghua University,
Beijing 100084, China
e-mail: gwang@tsinghua.edu.cn

Dehao Liu

Beijing Key Lab of Precision/Ultra-Precision
Manufacturing Equipments and Control,
Tsinghua University,
Beijing 100084, China;
George W. Woodruff School
of Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332-0405

Yiming (Kevin) Rong

Beijing Key Lab of Precision/Ultra-Precision
Manufacturing Equipments and Control,
Tsinghua University,
Beijing 100084, China;
Department of Mechanical
and Energy Engineering,
South University of Science and
Technology of China,
Shenzhen 518055, China

1Corresponding author.

Manuscript received September 13, 2017; final manuscript received December 4, 2017; published online March 7, 2018. Assoc. Editor: Y. B. Guo.

J. Manuf. Sci. Eng 140(5), 051016 (Mar 07, 2018) (13 pages) Paper No: MANU-17-1572; doi: 10.1115/1.4038729 History: Received September 13, 2017; Revised December 04, 2017

Accurate information about the evolution of the temperature field is a theoretical prerequisite for investigating grinding burn and optimizing the process parameters of grinding process. This paper proposed a new statistical model of equivalent grinding heat source with consideration of the random distribution of grains. Based on the definition of the Riemann integral, the summation limit of the discrete point heat sources was transformed into the integral of a continuous function. A finite element method (FEM) simulation was conducted to predict the grinding temperature field with the embedded net heat flux equation. The grinding temperature was measured with a specially designed in situ infrared system and was formulated by time–space processing. The reliability and correctness of the statistical heat source model were validated by both experimental temperature–time curves and the maximum grinding temperature, with a relative error of less than 20%. Finally, through the FEM-based inversed calculation, an empirical equation was proposed to describe the heat transfer coefficient (HTC) changes in the grinding contact zone for both conventional grinding and creep feed grinding.

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Figures

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Fig. 1

Grinding burn on the surface of turbine blade fir-tree root after creep feed grinding

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Fig. 2

Development history of temperature measurement in machining: calorimetry [9], thermocouple [10], spectral radiance [11], infrared imaging [12], infrared optical fiber [13], PVD [14], and micro resistance [15]

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Fig. 3

Flow directions of the grinding heat

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Fig. 4

Schematic diagram of the statistical modeling method of the grinding temperature field

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Fig. 5

Schematic diagram of single grain grinding

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Fig. 6

Penetration depth of a single grain

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Fig. 7

Surface microtopography of an alumina abrasive wheel

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Fig. 8

Specific heat of 2Cr12Ni4Mo3VNbN steel

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Fig. 9

Schematic and appliance of single grain cutting

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Fig. 10

Tangential forces of single grain cutting

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Fig. 11

Heat flux distributions along the grinding contact arc. ap=100 μm, vs=20 m/s and vw=300 mm/min.

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Fig. 12

Thermal boundary conditions

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Fig. 13

Temperature fields computed by FEM (unit: °C). ap=100 μm, vs=20 m/s and vw=300 mm/min, dry grinding (a), wet grinding (b).

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Fig. 14

SEM micrograph of tempered 2Cr12Ni4Mo3VNbN steel

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Fig. 15

Schematic sketch of the infrared measurement system

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Fig. 16

The infrared measurement system placed on a grinding machine table

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Fig. 17

Grinding temperature variation curves

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Fig. 18

Experimentally measured grinding temperature field (unit: °C)

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Fig. 19

Maximum grinding temperature of the workpiece

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Fig. 20

Comparison of the simulated and experimental temperature–time curves. vs=20 m/s, vw=300 mm/min, dry grinding.

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Fig. 21

Comparison of the simulated and experimental maximum temperature. vs=20 m/s, vw=300mm/min.

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Fig. 22

HTC of the grinding contact zone during normal grinding and creep feed grinding. vw=300 mm/min, wet grinding.

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Fig. 23

HTC fitting results. vw=300 mm/min, wet grinding.

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