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Prediction model for surface generation mechanism and roughness in face gear grinding

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Abstract

Owing to the complexity of the movement and contact relationships between grinding wheel and face gear, the previous surface prediction models for cylindrical, flat, and internal grinding are not able to reveal the surface generation mechanism in face gear generating grinding. In this work, according to the contact conditions between face gear and grinding wheel, grinding width and contact arc length were calculated. Based on the mapping relationship between face gear and wheel grain derived from theory of gearing, generation mechanism of face gear was revealed based on material removal of one step, single path, and entire surface of face gear. From this study, it is concluded that (1) swing angle increment of grinding wheel affects the grinding overlapping width and is the most significant factor affecting the tooth surface roughness. (2) The axial profile of grinding wheel geometry is the basic reason of uneven tooth surface topography. After optimizing the swing angle increment in different regions of face gear, an overall uniform morphology can be obtained efficiently. Experimental results show reasonable consistency with numerical simulations that validate the proposed model. This work provided a novel prediction model for surface generation mechanism and roughness for face gear grinding and can be utilized to optimize the process parameters to obtain higher tooth surface integrity.

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Data availability

We confirm that data is open and transparent.

Code availability

The codes generated during the current study are available from the corresponding author on reasonable request.

Abbreviations

a n :

Normal cutting depth of grains

a n,k :

Normal cutting depth of grain k at point d

\({a}_{n,k,{q}_{m}}\) :

The corrected value for an,k

\({a}_{n,k,q}\) :

Normal cutting depth of grain k when j = q

a p :

Cutting depth

b 1, b 2 :

Boundary points of the grinding width of grain k

\({b}_{k,o},{b}_{k,i}\) :

The maximum gap width of grain k when j = qm

d :

One point on contact line

d alo :

Grinding allowance of the face gear

\(\Delta d\) :

Meshing spacing

h c,k :

Protrusion height of the grain at the position of c and k on the wheel surface

h max :

The maximum protrusion height of the grains

h k :

Protrusion height of grain k

h x , k , q :

Protrusion heights of grain k in the xs0 direction when j = q

h z , k , q :

Protrusion heights of grain k in the zs0 direction when j = q

i, j :

Grid indices in the axial and involute profile direction of pinion

i f :

Transmission ratio of face gear pair

\({i}_{k,o},\ {i}_{k,i}\)  :

The index values of i for \({b}_{k,o}\) and \({b}_{k,i}\)

\({j}_{k,o},\ {j}_{k,i}\)  :

The index values of j for \({b}_{k,o}\) and \({b}_{k,i}\)

k :

Curvature of wheel profile

l 1,l 2 :

Overlapping width and non-overlapping width of the n-th grinding path

L :

Arc length between adjacent grains

M :

Grain size number

\({\mathbf{M}}_{2s}\) :

Transformation matrix from \({S}_{s}\) to \({S}_{2}\)

\({\mathbf{M}}_{2p}\) :

Transformation matrix from \({S}_{p}\) to \({S}_{2}\)

\({\mathbf{M}}_{pm}\) :

Transformation matrix from \({S}_{m}\) to \({S}_{p}\)

\({\mathbf{M}}_{ms}\) :

Transformation matrix from \({S}_{s}\) to \({S}_{2}\)

\({\mathbf{M}}_{s0,s}\) :

Transformation matrix for obtaining the involute profile of grinding wheel

\({\mathbf{M}}_{t0,s0}\) :

Transformation matrix for obtaining wheel profile in coordinate system St

\({\mathbf{M}}_{t,t0}\) :

Transformation matrix for obtaining the overall profile of grinding wheel

N g :

Normal vector of the wheel profile at point p

n :

Rotation speed of grinding wheel

\(\left({n}_{gx,q},{n}_{gz,q}\right)\) :

Normal vector coordinates when j = q

\(\left({n}_{gx,k},{n}_{gz,k}\right)\) :

Normal vector coordinates when j = b

P in :

Approach point

P out :

Recess point

P ha :

Addendum interference point

P hf :

Final point of transition curve

p :

The center of the bottom surface of grain k

p k + 1 :

The center of the bottom surface of (k + 1)-th grain

q m :

The corrected value for q

R k :

Rotation radius of grain k

R 2 :

\({\phi }_{\mathrm{sin}}\)’S corresponding radius

S p (x p, y p, z p):

Coordinate rigidly connected to the pinion

S m (x m, y m, z m):

Coordinate rigidly connected to the face gear

S s (x s, y s, z s):

Follow-up coordinate systems of pinion

S 2 (x 2, y 2, z 2):

Follow-up coordinate systems of face gear

S t (x t, y t, z t):

Coordinate system of grinding wheel

\({t}_{qm}\) :

The movement time when j = qm

\({u}_{s}\) :

Tooth width parameter of pinion

\({v}_{s,k}\) :

Cutting speed of grain k

v w :

Feed rate of the face gear

(x k , p, z k , p):

Coordinates of point p / coordinates when j = b

\(\left({x}_{k+1,p1},{z}_{k+1,p1}\right)\) :

Coordinates of point pk+1

\(\left({x}_{q},{z}_{q}\right)\) :

Coordinates when j = q

(x i, z i), (i = 1, 2) :

Coordinates of b1 and b2

z s :

Teeth number of pinion

\({\phi }_{s \mathrm{min}}\) :

Rotation angle of pinion

\(\Delta {\phi }_{s}\) :

Swing angle increments of grinding wheel

\({\phi }_{s\ \mathrm{max}}\)  :

Upper limit of the angle \({\phi }_{s}\)

\({\phi }_{s\ \mathrm{min}}\)  :

Lower limit of the angle \({\phi }_{s}\)

\({\phi }_{2}\) :

Rotation angle of face gear

\({\phi }_{\mathrm{sin}}\) :

Limiting angle of point Pin

\({\phi }_{sha}\) :

Limiting angle of point Pha

\({\phi }_{out}\) :

Limiting angle of point Pout

\({\phi }_{shf}\) :

Limiting angle of point Phf

\({\theta }_{s}\) :

Roll angle of involute

\({\theta }_{sha}\) :

Roll angle corresponding to the dedendum of pinion

\({\theta }_{s\ \mathrm{max}}\)  :

Roll angle corresponding to the addendum of pinion

θ i :

Roll angle of (k + 1)-th grain

\({\theta }_{k,i}\) :

Angle between the normal vectors of the profile point (xi, yi) and (xk,p, zk,p)

\({\theta }_{u},{\theta }_{d}\) :

Roll angles corresponding to b1 and b2

μ :

Mean value of grain diameter distribution

σ :

Standard deviation of grain diameter distribution

References

  1. Lewicki DG, Heath GF (2016) Advanced face gear surface durability evaluations. NASA/TM-2016–218943. https://ntrs.nasa.gov/citations/20160003580

  2. Xia CJ, Wang SL, Ma C, Wang SB, Xiao YL (2019) Crucial geometric error compensation towards gear grinding accuracy enhancement based on simplified actual inverse kinematic model. Int J Mech Sci 169:105319. https://doi.org/10.1016/j.ijmecsci.2019.105319

    Article  Google Scholar 

  3. Tang JY, Yin F, Chen XM (2013) The principle of profile modified face-gear grinding based on disk wheel. Mech Mach Theory 70:1–15. https://doi.org/10.1016/j.mechmachtheory.2013.06.013

    Article  Google Scholar 

  4. Guo H, Peng XQ, Zhao N, Zhang SY (2015) A CNC grinding method and envelope residual model for face gear. Int J Adv Manuf Tech 79:1689–1698. https://doi.org/10.1007/s00170-015-6915-7

    Article  Google Scholar 

  5. Wang YZ, Lan Z, Hou LW, Zhao HP, Zhong Y (2015) A precision generating grinding method for face gear using CBN wheel. Int J Adv Manuf Tech 79:1839–1848. https://doi.org/10.1007/s00170-015-6962-0

    Article  Google Scholar 

  6. Yin YL, Yu HL, Wang HM, Song ZY, Zhang Z, Ji XC, Cui TH, Wei M, Zhang W (2020) Friction and wear behaviors of steel/bronze tribopairs lubricated by oil with serpentine natural mineral additive. Wear 456:203387. https://doi.org/10.1016/j.wear.2020.203387

    Article  Google Scholar 

  7. Xu X, Outeiro J, Zhang J, Zhang J, Xu BB, Zhao WH, Astakhov V (2021) Machining simulation of Ti6Al4V using coupled Eulerian-Lagrangian approach and a constitutive model considering the state of stress. Simul Model Pract Theory 110:102312. https://doi.org/10.1016/j.simpat.2021.102312

    Article  Google Scholar 

  8. Bove R, Lunghi P, Sammes NM (2005) SOFC mathematic model for systems simulations–Part 2: definition of an analytical model. Int J Hydrog 30(2):189–200. https://doi.org/10.1016/j.ijhydene.2004.04.018

    Article  Google Scholar 

  9. Komanduri R, Lucca DA, Tani Y (1997) Technological advances in fine abrasive processes. CIRP Ann 46(2):545–596. https://doi.org/10.1016/S0007-8506(07)60880-4

    Article  Google Scholar 

  10. Agarwal S, Khare SK, Pandey VP, Patel M (2017) An analytical chip thickness model for performance assessment in silicon carbide grinding. Procedia Manuf 10:298–306. https://doi.org/10.1016/j.promfg.2017.07.060

    Article  Google Scholar 

  11. Wu CJ, Dong WJ, Zhu LJ, Zhang J, Xu LJ, Liang SY (2020) Modeling of grinding chip thickness distribution based on material removal mode in grinding of SiC ceramics. J Adv Mech Des Syst Manuf 14(1):JAMDSM0018. https://doi.org/10.1299/jamdsm.2020jamdsm0018

  12. Liu ZM, Tang Q, Zhang YF, Liu N (2019) An analytical method for surface roughness prediction in precision grinding of screw rotors. Int J Adv Manuf Technol 103(5–8):2665–2676. https://doi.org/10.1007/s00170-019-03598-1

    Article  Google Scholar 

  13. Jiang JL, Ge PQ, Hong J (2013) Study on micro-interacting mechanism modeling in grinding process and ground surface roughness prediction. Int J Adv Manuf Technol 67(5–8):1035–1052. https://doi.org/10.1007/s00170-012-4546-9

    Article  Google Scholar 

  14. Liu YM, Warkentin A, Bauer R, Gong YD (2013) Investigation of different grain shapes and dressing to predict surface roughness in grinding using kinematic simulations. Precis Eng 37(3):758–764. https://doi.org/10.1016/j.precisioneng.2013.02.009

    Article  Google Scholar 

  15. Nguyen TA, Butler DL (2005) Simulation of precision grinding process, part 1: generation of the grinding wheel surface. Int J Mach Tools Manuf 45(11):1321–1328. https://doi.org/10.1016/j.ijmachtools.2005.01.005

    Article  Google Scholar 

  16. Chen DX, Tian YL (2010) Modeling and simulation methodology of the machined surface in ultra – precision grinding. Chin J Mech Eng 46(13):186–191. https://en.cnki.com.cn/Article_en/CJFDTotal-JXXB201013028.htm

  17. Rabiey M, Wei JLZ (2018) Simulation of workpiece surface roughness after flat grinding by electroplated wheel. Procedia Cirp 77:303–306. https://doi.org/10.1016/j.procir.2018.09.021

    Article  Google Scholar 

  18. Wang YZ, Liu Y, Chu XM, He YM, Zhang W (2017) Calculation model for surface roughness of face gears by disc wheel grinding. Int J Mach Tools Manuf 123:76–88. https://doi.org/10.1016/j.ijmachtools.2017.08.002

    Article  Google Scholar 

  19. Zhou RC, Zhao N, Li W, Li R, Guo GD, Guo H (2019) A grinding method of face gear mating with a conical spur involute pinion. Mech Mach Theory 141:226–244. https://doi.org/10.1016/j.mechmachtheory.2019.07.013

    Article  Google Scholar 

  20. Zhou WH, Tang JY, Shao W (2020) Study on surface generation mechanism and roughness distribution in gear profile grinding. Int J Mech Sci 187:105921. https://doi.org/10.1016/j.ijmecsci.2020.105921

    Article  Google Scholar 

  21. Chen HF, Tang JY, Zhou W (2013) Modeling and predicting of surface roughness for generating grinding gear. J Mater Process Technol 213(5):717–721. https://doi.org/10.1016/j.jmatprotec.2012.11.017

    Article  Google Scholar 

  22. Baidakova NV, Orlova TN (2017) Usage of abrasive grains with controllable shapes as means of grinding wheels operation stabilization. Procedia Eng 206:188–193. https://doi.org/10.1016/j.proeng.2017.10.458

    Article  Google Scholar 

  23. Doman DA, Warkentin A, Bauer R (2006) A survey of recent grinding wheel topography models. Int J Mach Tools Manuf 46(3):343–352. https://doi.org/10.1016/j.ijmachtools.2005.05.013

    Article  Google Scholar 

  24. Cai ZQ, Lin C (2020) Research on the discrete algorithm of tooth surface for a curve-face gear. J Mech Des 142(5):053301. https://doi.org/10.1115/1.4044434

    Article  Google Scholar 

  25. Wang YZ, Hou LW, Lan Z, Zhong Y, Chu XM (2015) CNC technology of wheel dressing for precision grinding face gear. J Sichuan Univ (Eng Sci Ed) 47(4):186–191. https://en.cnki.com.cn/Article_en/CJFDTOTAL-SCLH201504028.htm

  26. Zhu WL, Yang Y, Li HN, Axinte D, Beaucamp A (2019) Theoretical and experimental investigation of material removal mechanism in compliant shape adaptive grinding process. Int J Mach Tools Manuf 142:76–97. https://doi.org/10.1016/j.ijmachtools.2019.04.011

    Article  Google Scholar 

  27. Gao T, Zhang XP, Li CH, Zhang YB, Yang M, Jia DZ, Ji HJ, Zhao YG, Li RZ, Yao P, Zhu LD (2020) Surface morphology evaluation of multi-angle 2D ultrasonic vibration integrated with nanofluid minimum quantity lubrication grinding. J Manuf Process 51:44–61. https://doi.org/10.1016/j.jmapro.2020.01.024

    Article  Google Scholar 

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Funding

This work was funded by the National Natural Science Foundation of China (No: 51905459), State Key Laboratory of Mechanical Transmission, Chongqing University (No. SKLMT-MSKFKT-202003), and Aero Engine Corporation of China’s 2019 Industry-University-Research Cooperation Project (No: HFZL2019CXY025).

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Xiaofan Ma: Methodology, data curation, formal analysis, validation, and writing–original draft and editing. Zhiqin Cai: Funding acquisition, writing (review), and revision. Bin Yao: Funding acquisition, resource supervision, and project administration. Guanfeng Chen: Conceptualization. Sijie Cai: Resources. Wanshan Liu: Investigation and software.

Corresponding author

Correspondence to Zhiqin Cai.

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Ma, X., Cai, Z., Yao, B. et al. Prediction model for surface generation mechanism and roughness in face gear grinding. Int J Adv Manuf Technol 120, 4423–4442 (2022). https://doi.org/10.1007/s00170-022-09035-0

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