CN107480317A - A kind of method for improving gear hobbing process precision - Google Patents

A kind of method for improving gear hobbing process precision Download PDF

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CN107480317A
CN107480317A CN201710437560.7A CN201710437560A CN107480317A CN 107480317 A CN107480317 A CN 107480317A CN 201710437560 A CN201710437560 A CN 201710437560A CN 107480317 A CN107480317 A CN 107480317A
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gear
hobbing
flank
profile error
msub
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韩江
夏链
袁彬
朱永刚
吴路路
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Hefei University of Technology
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    • B23F—MAKING GEARS OR TOOTHED RACKS
    • B23F5/00—Making straight gear teeth involving moving a tool relatively to a workpiece with a rolling-off or an enveloping motion with respect to the gear teeth to be made
    • B23F5/20—Making straight gear teeth involving moving a tool relatively to a workpiece with a rolling-off or an enveloping motion with respect to the gear teeth to be made by milling
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Abstract

The present invention relates to the method for improving gear hobbing process precision.Operating procedure is as follows：1. the hobbing processes for being processed gear, extraction influence the hobbing processes parameter of Gear Processing precision, hobbing processes parameter combination is designed, carries out gear hobbing process experiment, obtains the flank profile error criterion for being processed gear；2. flank profile error mathematic model is built by response surface design the non linear fit method according to the flank profile error criterion of hobbing processes parameter combination and processed gear；3. based on the expection machining accuracy value corresponding to each flank profile error criterion, apply weight ratio, structure flank of tooth synthesis profile error mathematic model to each flank profile error model；4. being based on genetic algorithm, optimize hobbing processes parameter, obtain optimizing hobbing processes parameter.The present invention improves the machining accuracy of gear hobbing, and theoretical foundation is provided for the selection of actual hobbing processes parameter and the accuracy of gear.

Description

A kind of method for improving gear hobbing process precision
Technical field
The invention belongs to mechanical processing technique technical field, and in particular to a kind of method for improving gear hobbing process precision.
Background technology
In the gear hobbing process of reality, the motion between hobboing cutter and workpiece gear can develop into a pair of crossed helical gears Between transmission, but because each cutting edge of hobboing cutter relative to workpiece gear for interruption open flume type cutting, digital control system interpolation cycle it is big It is small differ, the presence of machine motor rigidity, machine vibration, the factor such as thermal deformation, it is not smooth gradually to open to cause workpiece gear Face, can form certain ripple, and height, the trend of ripple have conclusive influence to workpiece items flank profile error.Reason The flank of tooth wave height of opinion, trend etc. can be according to the installations of every precision index of lathe, the interpolation cycle of digital control system, fixture Precision, every geometric accuracy index of cutter, the theory of engagement are derived and calculated.Because theoretical wave height, trend are every The formative factor of profile errors, theoretical wave height, slope etc. can be referred to as to every theoretical flank profile error sometimes, but it is real In the processing of border, obtained every flank profile error detecting value is far longer than theoretical value.Flank profile error is as Gear Processing The engagement such as the important measurement index of precision, its vibration to gear product, noise, fatigue resistance, contact stress, wearability property There can be very big influence.Currently in order to obtaining more accurate flank profile error prediction model, and reduce lot of experiments The cost that number is brought, existing scholar have scholar based on Central Composite experimental design to carry out the arrangement of technological parameter, but in Technological parameter set by heart composite experiment design can exceed the scope done and arranged, easily cause the damage of lathe, also scholar Analysis and modeling is carried out to individual index multi-factor problem based on Response Surface Method, because response surface design experimental design is limited only to seek The quantitative relationship looked between independent experiment index and each factor, it is impossible to comprehensive modeling is carried out to multi objective problem, thus it is unpredictable Flank profile error simultaneously selects optimal cutting tooth process parameter combination.
The content of the invention
In view of in place of the shortcomings of the prior art, the present invention provides a kind of method for improving gear hobbing process precision, passes through Gear Processing precision weight matches and genetic algorithm, and hobbing processes parameter is optimized, to reach optimal gear hobbing process essence Degree.
A kind of operating procedure of raising gear hobbing process precision is as follows：
(1) is directed to the gear hobbing process technique for being processed gear, and extraction influences the hobbing processes parameter of Gear Processing precision, Hobbing processes parameter combination is designed, carries out gear hobbing process experiment, obtains the flank profile error criterion for being processed gear；
(2) is non-by response surface design according to the flank profile error criterion of hobbing processes parameter combination and processed gear Linear fitting builds flank profile error mathematic model；
(3) is based on the expection machining accuracy value corresponding to each flank profile error criterion, to each flank profile error model Apply weight ratio, structure flank of tooth synthesis profile error mathematic model；
(4) is based on genetic algorithm, and hobbing processes parameter is optimized, and obtains optimizing hobbing processes parameter.
The technical scheme further limited is as follows：
In step (1), the modulus m of the processed gearnFor 1<mn<5th, number N of teeth 15<N<100th, helixangleβ is -50 ° <β<50°；The hobbing processes parameter is hobboing cutter rotating speed SS, rolling cut depth hd, axial feed velocity fz；
The gear hobbing process experiment, designs hobbing test scheme using Box-Behnken test design methods, obtains the flank of tooth Profile errors index is gear-profile total deviation Fα, the Gear Helix total deviation Fβ, tooth pitch add up total deviation Fp。
In step (2), the flank profile error mathematic model is as follows：
Y (x)=β0+β1x1+β2x2+β3x3+β11x1 2+β22x2 2+β33x3 2+β12x1x2+β13x1x3+β23x2x3+ε
In above formula, y (x) is flank profile error criterion, x1、x2、x3Three kinds of hobbing processes parameters are represented respectively, and ε is additional Constant, β0、β1、β2、β3、β11、β22、β33、β12、β13、β23The interaction work of respectively each hobbing processes parameter and each technological parameter With corresponding influence coefficient.
In step (3), the flank of tooth synthesis profile error prediction model FallFor：
In above formula, Fa0、Fβ0、FP0For according to standard ISO1328-1：Gear Processing precision index determined by 1995 is expected Value, Fα、Fβ、FpGear-profile total deviation, the Gear Helix total deviation and the tooth pitch respectively established add up total deviation mathematical modulo Type, FallFor the flank of tooth established according to said gear machining accuracy index desired value and every flank profile error mathematic model Comprehensive profile error prediction model.
In step (4), it is described hobbing processes parameter is optimized during, based on genetic algorithm, according to specific Hobbing processes parameter combination and the flank of tooth synthesis profile error prediction model established, determine optimization process parameter.
The advantageous effects of the present invention embody in the following areas：
1. the present invention can quickly determine hobbing processes parameter and the flank of tooth wheel of processed gear by gear hobbing process experiment Relation between wide index, reduce the modeling cost of flank profile error model.
2. the present invention is by the weight proportion of reasonable distribution items flank profile error criterion, the flank of tooth integral wheel established Wide error model has greatly improved than the effect of optimization for the flank of tooth synthesis profile error model that the single addition method is established, and makes each Item flank profile error at least reduces 11.01%.
3. the present invention combines genetic algorithm so that the solving speed of multiple target nonlinear multivariable optimization aim is compared with conventional numeric Method for solving is faster.
Brief description of the drawings
Fig. 1 is the method flow diagram of present invention prediction gear hobbing process precision.
Fig. 2 is the Box-Behnken experimental design schematic diagrames of plan design of the present invention.
Fig. 3 a are the comparison figures of gear-profile total deviation predicted value of the present invention and actual value.
Fig. 3 b are the comparison figures of the Gear Helix total deviation predicted value of the present invention and actual value.
Fig. 3 c are the comparison figures that tooth pitch of the present invention adds up total deviation predicted value and actual value.
Fig. 4 a are that the present invention works as rolling cut depth hdHobboing cutter rotating speed and axial feed velocity are to gear-profile total deviation during=2mm Response surface design.
Fig. 4 b are that the present invention works as axial feed velocity fzRolling cut depth and hobboing cutter rotating speed are to gear-profile during=10mm/min The response surface design of total deviation.
Fig. 4 c are that the present invention works as hobboing cutter rotating speed SsRolling cut depth and axial feed velocity are to gear-profile during=1000r/min The response surface design of total deviation.
Fig. 5 a are that the present invention works as rolling cut depth hdHobboing cutter rotating speed and axial feed velocity are always inclined to the Gear Helix during=2mm The response surface design of difference.
Fig. 5 b are that the present invention works as axial feed velocity fzRolling cut depth and hobboing cutter rotating speed are to gear spiral during=10mm/min The response surface design of line total deviation.
Fig. 5 c are that the present invention works as hobboing cutter rotating speed SsRolling cut depth and axial feed velocity are to gear spiral during=1000r/min The response surface design of line total deviation.
Fig. 6 a are that the present invention works as rolling cut depth hdHobboing cutter rotating speed adds up total deviation with axial feed velocity to tooth pitch during=2mm Response surface design.
Fig. 6 b are that the present invention works as axial feed velocity fzRolling cut depth adds up with hobboing cutter rotating speed to tooth pitch during=10mm/min The response surface design of total deviation.
Fig. 6 c are that the present invention works as hobboing cutter rotating speed SsRolling cut depth adds up with axial feed velocity to tooth pitch during=1000r/min The response surface design of total deviation.
Fig. 7 is the process that the present invention is iterated optimization based on genetic algorithm to the synthesis flank profile error established Figure.
Embodiment
Below in conjunction with the accompanying drawings, the present invention is further described by embodiment.
Embodiment 1
So that 40Cr is processed gear as an example, using YGS3110B chain digital control gear hobbing machines.The basic parameter of gear is：Modulus mn= 2, number of teeth z=6, gear helical angle β=30 °, pressure angle α=20 °.The basic parameter of hobboing cutter is：Modulus mn=2, head number z=1, Hobboing cutter lead angle β=4.25 °, pressure angle α=20 °.Every flank profile error is carried out with JD45 types gear measuring center Detection.
Referring to Fig. 1, a kind of operating procedure of raising gear hobbing process precision is as follows：
Step (1), the gear hobbing process technique for being processed gear, extraction influence the hobbing processes ginseng of Gear Processing precision Number, hobbing processes parameter combination is designed, carry out gear hobbing process experiment, obtain the flank profile error criterion for being processed gear.
Present invention is generally directed to gear hobbing process, three hobbing processes factors are respectively hobboing cutter rotating speed SS, rolling cut depth hd, axle To feed speed fz, Box-Behnken experimental designs belong to two horizontal total divisor experimental designs, be usually used in solving factor of influence with Nonlinear problem between response results, and utilize statistical method predicated response model.
Four influence factors are included for gear gear hobbing input parameter, design four factor Box-Behnken experimental designs, such as Shown in Fig. 2, it is 12 according to four factor Box-Behnken testing sites, is 3 plus replica test number, overall test can be tried to achieve Number N=15.
The Box-Behnken experimental factors of table 1 are horizontal
The Box-Behnken of table 2
Testing program and result of the test
Table 1 is the test level table that is done according to Box-Behnken test codes, according to the technique listed by test level table Parameter, gear hobbing process G code is worked out, gear hobbing process experiment is carried out on YGS3610B chain digital control gear hobbing machines, and experimental result is remembered Record show Box-Behnken testing programs and its measurement result in response results column, table 2.
Step (2), it is bent by responding according to the flank profile error criterion of hobbing processes parameter combination and processed gear Face the non linear fit method structure flank profile error mathematic model.
Response surface design nonlinear fitting solution is carried out according to the test index result recorded in previous step (1), it is contemplated that Gear hobbing process technological parameter is to the non-linear effects of every flank profile error, by each hobbing processes parameter tried to achieve and each Influence coefficient, three kinds of hobbing processes parameters, additional constant corresponding to the reciprocation of technological parameter bring general flank of tooth wheel into Wide error mathematic model
Y (x)=β0+β1x1+β2x2+β3x3+β11x1 2+β11x1 2+β22x2 2+β33x3 2+β12x1x2+β12x1x2+β13x1x3+β23x2x3In+ε, in formula, y (x) is flank profile error criterion, x1、x2、x3Three kinds of hobbing processes parameters are represented respectively, and ε is additional Constant, β0、β1、β2、β3、β11、β22、β33、β12、β13、β23The interaction work of respectively each hobbing processes parameter and each technological parameter With corresponding influence coefficient, the mathematical modeling for trying to achieve every flank profile error of the present embodiment is：
Fα=26.142-0.030 × Ss-0.20×fz-1.77×hd-7.500×10-5×Ss×fz+1.000×10-3× Ss×hd-0.030×fz×hd+1.260×10-5×Ss 2+0.024×fz 2+0.479×hd 2
Fβ=30.921-0.030 × Ss-0.332 × fz-2.796 × hd+2.500 × 10-5×Ss×fz+7.500× 10-4×Ss×hd+5.000×10-3×fz×hd+1.33×10-5×Ss2+0.026×fz2+0.633×hd2
Fp=28.321-0.017 × Ss+0.208 × fz+1.129 × hd-3.250000 × 10-4×Ss×fz-1.25× 10-3×Ss×hd-0.035×fz×hd+8.33×10-6×Ss2+0.016×fz2+0.333×hd2
P value corresponding to three kinds of flank profile errors is much smaller than 0.05, illustrates that model is meaningful, true detected value Relativity figure with predicted value is as shown in Fig. 3 a, Fig. 3 b, Fig. 3 c, from Fig. 3 a, Fig. 3 b and Fig. 3 c, each true detected value The both sides of predicted value are evenly distributed on, therefore, the degree of fitting of each flank profile error model is preferable, in given test parameters model In enclosing, each flank profile error can be predicted exactly.
Step (3), based on the expection machining accuracy value corresponding to each flank profile error criterion, to each flank profile error Model applies weight ratio, structure flank of tooth synthesis profile error mathematic model；
General flank of tooth synthesis profile error prediction model FallFor：
In above formula, Fa0、Fβ0、FP0For according to standard ISO1328-1：Gear Processing precision index determined by 1995 is expected Value, Fα、Fβ、FpGear-profile total deviation, the Gear Helix total deviation and the tooth pitch respectively established add up total deviation mathematical modulo Type, FallFor the flank of tooth established according to said gear machining accuracy index desired value and every flank profile error mathematic model Comprehensive profile error prediction model.
The flank of tooth synthesis profile error prediction model F of this exampleallFor：
If add up the response mathematical modeling of total deviation to gear-profile total deviation, the Gear Helix total deviation and tooth pitch respectively Optimize, then what may be drawn is different machined parameters preferred values, because same group of machined parameters make three while reached The probability very little of minimum value, it is therefore desirable to establish one can Comprehensive Assessment this three errors overall target Fall, can establishing When synthetically expressing the model of every flank profile error criterion, because each error criterion is in required precision corresponding to national standard, Its every error index value it is not of uniform size, it is comprehensive when carrying out hobbing processes optimization if being simply added three error criterions The value that closing error is reduced can not be uniformly distributed according to respective accuracy value, at this point it is possible to using additional weight ratio Method carry out the size of balance error, be F according to the error amount of gear standard in 7 class precisiona=9 (μm), Fβ=14 (μ m)、Fp=23 (μm).
According to F value sizes corresponding to each hobbing processes parameter, each hobbing processes parameter can be obtained to each flank profile error The size of influence degree, i.e. gear-profile total deviation Fα(fz>hd>Ss), the Gear Helix total deviation Fβ(hd>fz>Ss), tooth pitch tires out Count total deviation Fp(Ss>hd>fz)。
For gear-profile total deviation FαFor, the F values of the every Gearmaking Technology parameter obtained by regression analysis Respectively 52.18,55.9,74.26, therefore, every cutting tooth process parameter is to the influence degree sequencing of tooth profile total deviation (hd>fz>Ss), from the response surface figure of gear-profile total deviation also it can be gathered that this rule, the specifying information of response surface figure is such as Under：Take hdFor zero level value 2mm when, Ss、fzTo FαResponse surface design figure respectively as shown in fig. 4 a, SsDuring increase, gear The trend reduced is presented in tooth profile total deviation, and the severe degree changed will be less than fz；Take fzFor zero level value 10mm/min when, Ss、 hdTo FαThe response surface design figure come is distinguished as shown in Figure 4 b, hdDuring increase, becoming for increase is presented in gear-profile total deviation Gesture, and mean change severe degree is slightly larger than Ss；Take SsFor zero level value 1000r/min when, fz、hdTo FαThe response surface design figure come Respectively as illustrated in fig. 4 c, with hdIncrease, increased trend is presented in gear-profile total deviation, and changes severe degree compared with fzWill Greatly；In general, it is (h to the influence degree sequencing of the Gear Helix total deviation also to embody every cutting tooth process parameterd >fz>Ss)。
For the Gear Helix total deviation FβFor, the F of the every Gearmaking Technology parameter obtained by regression analysis Value is respectively 7.91,79.65,17.40, and therefore, every cutting tooth process parameter is first to the influence degree of the Gear Helix total deviation Order is (f afterwardsz>hd>Ss), from the response surface figure of the Gear Helix total deviation also it can be gathered that this rule, the tool of response surface figure Body information is as follows：Take hdFor zero level value 2mm when, Ss、fzTo FαResponse surface design figure respectively as shown in Figure 5 a, SsThe process of increase In, the trend reduced is presented in the Gear Helix total deviation, and the severe degree changed is less than fz；Take fzFor zero level value 10mm/ During min, Ss、hdTo FαThe response surface design figure come is distinguished as shown in Figure 5 b, hdDuring increase, the Gear Helix total deviation is in The trend now increased, and mean change severe degree is slightly larger than Ss；Take SsFor zero level value 1000r/min when, fz、hdTo FαCome Response surface design figure is distinguished as shown in Figure 5 c, with hdIncrease, the Gear Helix total deviation present first reduce after increased trend, And change severe degree is slightly smaller than fz；In general, every cutting tooth process parameter is also embodied to the Gear Helix total deviation Influence degree sequencing is (fz>hd>Ss)。
Add up total deviation F for tooth pitchpFor, the F values of the every Gearmaking Technology parameter obtained by regression analysis Respectively 106.12,35.37,53.70, therefore, every cutting tooth process parameter adds up the influence degree of total deviation to tooth pitch successively Order is (Ss>hd>fz), add up the response surface figure of total deviation also from tooth pitch it can be gathered that this rule, the specific letter of response surface figure Breath is as follows：Take hdFor zero level value 2mm when, Ss、fzTo FαResponse surface design figure respectively as shown in Figure 6 a, SsDuring increase, Tooth pitch, which adds up total deviation presentation, first reduces the trend increased afterwards, and the severe degree changed is greater than fz；Take fzFor zero level value During 10mm/min, Ss、hdTo FαThe response surface design figure come is distinguished as shown in Figure 6 b, hdDuring increase, tooth pitch adds up total deviation The trend of increase is presented, and mean change severe degree is less than Ss；Take SsFor zero level value 1000r/min when, fz、hdTo FαCome Response surface design figure is distinguished as fig. 6 c, with hdIncrease, tooth pitch add up total deviation present first reduce after increased trend, and Change severe degree is less than fz, in general, also embody the influence journey that every cutting tooth process parameter adds up total deviation to tooth pitch Degree sequencing is (Ss>hd>fz)。
Step (4), based on genetic algorithm, hobbing processes parameter is optimized, obtain optimizing hobbing processes parameter.
Based on genetic algorithm, it is 40 to take population number, iterations 500, and Fig. 7 show multi-objective genetic algorithm evolution Tendency chart, it can be obtained by Fig. 7, when iteration is more than 50 times, lines tend towards stability, resulting optimal hobbing processes parameter combination For：Speed of mainshaft Ss=1147.3r/min；Axial feed velocity fz=6.28r/min；Back engagement of the cutting edge hd=1.1mm, now tooth Face synthesis profile errors tend towards stability as 2.47 (um), gear profile total deviation Fα=7.15 (um), the Gear Helix total deviation Fβ =11.80 (um), tooth pitch add up total deviation Fp=19.20 (um).The hobbing processes parameter main shaft chosen according to practical experience turns Fast Ss=1200r/min；Axial feed velocity fz=10r/min；Back engagement of the cutting edge hd=2mm, the average gear profile of gained are always inclined Poor Fα=8.69 (um), average the Gear Helix total deviation Fβ=13.26 (um), average tooth pitch add up total deviation Fp=23.87 (um), according to the gear profile total deviation F of gained after optimizationαThan reducing 17.72% obtained by practical experience, the Gear Helix is total Deviation FβThan reducing 11.01% obtained by practical experience, tooth pitch adds up total deviation FpThan reducing 19.56% obtained by practical experience.
Embodiment 2
1. workpiece parameter
The idiographic flow of the present invention is as shown in Figure 1.So that 40Cr is processed gear as an example, using YGS3110B numerical control gear hobbings Machine.The basic parameter of gear is：Modulus mn=1.25, number of teeth z=43, gear helical angle β=24 °, pressure angle α=20 °.Hobboing cutter Basic parameter be：Modulus mn=1.25, head number z=1, hobboing cutter lead angle β=2.33 °, pressure angle α=20 °.Feeding mode For axial-radial continuous feed.Every flank profile error is detected with JD45 types gear measuring center.
2. technological parameter
The scope of four hobbing processes factors is respectively：
Hobboing cutter rotating speed 800<SS<2000th, rolling cut depth 0.5<hd<2nd, axial feed velocity 5<fz<15。
3. the operating procedure of gear hobbing process precision is improved with embodiment 1.
4. result.
It is by the optimal hobbing processes parameter combination obtained by this method：Hobboing cutter rotating speed SS=1420 (r/min)；Rolling Cutting depth hd=0.75 (mm)；Axial feed velocity fz=5.5 (mm/min), now the flank of tooth synthesis profile errors tend towards stability for 0.6181 (um), gear profile total deviation Fα=4.6 (um), the Gear Helix total deviation Fβ=6.1 (um), tooth pitch are accumulative total inclined Poor Fp=14.7 (um).The hobboing cutter rotating speed S chosen according to practical experienceS=1500 (r/min)；Rolling cut depth hd=1 (mm)；Axle To feed speed fz=10 (mm/min), the average gear profile total deviation F of gainedα=6.5 (um), average the Gear Helix are total Deviation Fβ=8.2 (um), average tooth pitch add up total deviation Fp=17.6 (um), according to the gear profile total deviation of gained after optimization FαThan reducing 29.23% obtained by practical experience, the Gear Helix total deviation FβThan reducing 25.61% obtained by practical experience, tooth Away from accumulative total deviation FpThan reducing 16.48% obtained by practical experience, i.e., every flank profile error criterion minimum reduces 16.48%.

Claims (5)

  1. A kind of 1. method for improving gear hobbing process precision, it is characterised in that operating procedure is as follows：
    (1) is directed to the gear hobbing process technique for being processed gear, and extraction influences the hobbing processes parameter of Gear Processing precision, design Hobbing processes parameter combination, gear hobbing process experiment is carried out, obtain the flank profile error criterion for being processed gear；
    (2) is non-linear by response surface design according to the flank profile error criterion of hobbing processes parameter combination and processed gear Fitting process builds flank profile error mathematic model；
    (3) is applied based on the expection machining accuracy value corresponding to each flank profile error criterion to each flank profile error model Weight ratio, structure flank of tooth synthesis profile error mathematic model；
    (4) is based on genetic algorithm, and hobbing processes parameter is optimized, and obtains optimizing hobbing processes parameter.
  2. A kind of 2. method for improving gear hobbing process precision according to claim 1, it is characterised in that：
    In step (1), the modulus m of the processed gearnFor 1<mn<5th, number N of teeth 15<N<100th, helixangleβ is -50 °<β<+ 50°；The hobbing processes parameter is hobboing cutter rotating speed SS, rolling cut depth hd, axial feed velocity fz；
    The gear hobbing process experiment, designs gear hobbing process testing program using Box-Behnken test design methods, obtains the flank of tooth Profile errors index is gear-profile total deviation Fα, the Gear Helix total deviation Fβ, tooth pitch add up total deviation Fp。
  3. A kind of 3. method for improving gear hobbing process precision according to claim 1, it is characterised in that：
    In step (2), the flank profile error mathematic model is as follows：
    Y (x)=β0+β1x1+β2x2+β3x3+β11x1 2+β22x2 2+β33x3 2+β12x1x2+β13x1x3+β23x2x3+ε
    In above formula, y (x) is flank profile error criterion, x1、x2、x3Three kinds of hobbing processes parameters are represented respectively, and ε is additional normal Amount, β0、β1、β2、β3、β11、β22、β33、β12、β13、β23The reciprocation of respectively each hobbing processes parameter and each technological parameter Corresponding influence coefficient.
  4. A kind of 4. method for improving gear hobbing process precision according to claim 1, it is characterised in that：
    In step (3), the flank of tooth synthesis profile error prediction model FallFor：
    <mrow> <msub> <mi>F</mi> <mrow> <mi>a</mi> <mi>l</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <msub> <mi>F</mi> <mrow> <mi>a</mi> <mn>0</mn> </mrow> </msub> </mfrac> <msub> <mi>F</mi> <mi>a</mi> </msub> <mo>+</mo> <mfrac> <mn>1</mn> <msub> <mi>F</mi> <mrow> <mi>&amp;beta;</mi> <mn>0</mn> </mrow> </msub> </mfrac> <msub> <mi>F</mi> <mi>&amp;beta;</mi> </msub> <mo>+</mo> <mfrac> <mn>1</mn> <msub> <mi>F</mi> <mrow> <mi>P</mi> <mn>0</mn> </mrow> </msub> </mfrac> <msub> <mi>F</mi> <mi>p</mi> </msub> </mrow>
    In above formula, Fa0、Fβ0、FP0For according to standard ISO1328-1：Gear Processing precision index desired value, F determined by 1995α、 Fβ、FpGear-profile total deviation, the Gear Helix total deviation and the tooth pitch respectively established add up total deviation mathematical modeling, Fall For the flank of tooth integral wheel established according to said gear machining accuracy index desired value and every flank profile error mathematic model Wide error prediction model.
  5. A kind of 5. method for improving gear hobbing process precision according to claim 1, it is characterised in that：
    In step (4), it is described hobbing processes parameter is optimized during, based on genetic algorithm, according to specific gear hobbing Combination of process parameters and the flank of tooth synthesis profile error prediction model established, determine optimization process parameter.
CN201710437560.7A 2017-06-09 2017-06-09 A kind of method for improving gear hobbing process precision Pending CN107480317A (en)

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CN108628254A (en) * 2018-03-30 2018-10-09 重庆大学 Power causes error lower rolling tooth to process tooth surface parameters acquisition methods
CN109128390A (en) * 2018-09-28 2019-01-04 厦门理工学院 A kind of straight bevel gear planing operation flank profil three-dimensional modeling method and computer readable storage medium
CN109933940A (en) * 2019-03-22 2019-06-25 重庆大学 Hobbing processes parameter optimization method based on hobboing cutter spindle vibration response model
CN109977579A (en) * 2019-04-03 2019-07-05 合肥工业大学 Improve the Machine-settings optimization method of hypoid gear meshing quality
CN111666645A (en) * 2020-06-24 2020-09-15 中国航发中传机械有限公司 Modeling method, system and medium for spiral bevel gear based on discrete point data
CN113102838A (en) * 2021-05-18 2021-07-13 山东大学 Method for solving working angle of cutter in gear hobbing process
CN113127986A (en) * 2021-03-30 2021-07-16 南京工业大学 Method for analyzing influence of cutter error on tooth profile of machined gear

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108628254A (en) * 2018-03-30 2018-10-09 重庆大学 Power causes error lower rolling tooth to process tooth surface parameters acquisition methods
CN109128390A (en) * 2018-09-28 2019-01-04 厦门理工学院 A kind of straight bevel gear planing operation flank profil three-dimensional modeling method and computer readable storage medium
CN109128390B (en) * 2018-09-28 2019-10-25 厦门理工学院 A kind of straight bevel gear planing operation flank profil three-dimensional modeling method and computer readable storage medium
CN109933940A (en) * 2019-03-22 2019-06-25 重庆大学 Hobbing processes parameter optimization method based on hobboing cutter spindle vibration response model
CN109933940B (en) * 2019-03-22 2023-01-06 重庆大学 Hobbing process parameter optimization method based on hob spindle vibration response model
CN109977579A (en) * 2019-04-03 2019-07-05 合肥工业大学 Improve the Machine-settings optimization method of hypoid gear meshing quality
CN109977579B (en) * 2019-04-03 2022-09-13 合肥工业大学 Machine tool machining parameter optimization method for improving hypoid gear meshing quality
CN111666645A (en) * 2020-06-24 2020-09-15 中国航发中传机械有限公司 Modeling method, system and medium for spiral bevel gear based on discrete point data
CN113127986A (en) * 2021-03-30 2021-07-16 南京工业大学 Method for analyzing influence of cutter error on tooth profile of machined gear
CN113102838A (en) * 2021-05-18 2021-07-13 山东大学 Method for solving working angle of cutter in gear hobbing process

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