CN108356364B - A kind of herringbone bear processing unit (plant) and its turning and method for milling - Google Patents

A kind of herringbone bear processing unit (plant) and its turning and method for milling Download PDF

Info

Publication number
CN108356364B
CN108356364B CN201810454630.4A CN201810454630A CN108356364B CN 108356364 B CN108356364 B CN 108356364B CN 201810454630 A CN201810454630 A CN 201810454630A CN 108356364 B CN108356364 B CN 108356364B
Authority
CN
China
Prior art keywords
turning
milling
workbench
plant
processing unit
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810454630.4A
Other languages
Chinese (zh)
Other versions
CN108356364A (en
Inventor
刘天寅
赵福长
赵新
刘明
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
BAOJI XINFUQUAN MACHINERY TECHNOLOGY Co.,Ltd.
Original Assignee
Baoji Scientific And Technological Development Co Ltd Of New Fuquan Machinery
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Baoji Scientific And Technological Development Co Ltd Of New Fuquan Machinery filed Critical Baoji Scientific And Technological Development Co Ltd Of New Fuquan Machinery
Priority to CN201810454630.4A priority Critical patent/CN108356364B/en
Publication of CN108356364A publication Critical patent/CN108356364A/en
Application granted granted Critical
Publication of CN108356364B publication Critical patent/CN108356364B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B23MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23FMAKING GEARS OR TOOTHED RACKS
    • B23F7/00Making herringbone gear teeth

Abstract

The present invention discloses a kind of herringbone bear processing unit (plant), comprising: main lathe bed, mill teeth column, milling-teeth blade, by milling slide along the mill teeth column it is axially slidable be arranged on the mill teeth column;Workbench is rotatably disposed in the main lathe bed axial direction other side;Vertical lathe body, vertical stay and turning insert, through turning head along the axially slidable hollow structure that the vertical stay is arranged in of the vertical stay, turning and the public rotary table of milling can process double helical tooth in high precision.The present invention discloses a kind of method for turning of herringbone bear processing unit (plant), and turning revolving speed, feed distance and turning time, turning accuracy based on BP neural network control workpiece are higher.Invention additionally discloses a kind of method for milling of herringbone bear processing unit (plant), can accurately control the revolving speed of workbench and the axial movement speed of milling-teeth blade and workbench positive and negative rotation time, improve the machining accuracy of double helical tooth.

Description

A kind of herringbone bear processing unit (plant) and its turning and method for milling
Technical field
The present invention relates to gear machining technology fields, and more particularly, the present invention relates to a kind of herringbone bear processing unit (plant)s And its turning and method for milling.
Background technique
Herringbone bear has many advantages, such as small smooth running, noise, large carrying capacity, does not have axial force, in petroleum machinery, work The industries extensive applications such as journey machinery, mining machinery, ship, it is high-precision with the fast development and technology upgrading of these industries The demand of degree herringbone bear increasingly increases, and more stringent requirements are proposed with processing efficiency for this precision to herringbone bear.
Traditional herringbone bear processing technology, usually by gear blank elder generation clamping on lathe, turning goes out herringbone bear Outer circle, inner hole and end face, then refill and clip on special double helical gear milling machine, mill out herringbone bear tooth socket.It is this Traditional herringbone bear processing method needs to complete the vehicle of herringbone bear by two lathe, double helical tooth tooth milling machine lathes It cuts and Milling Process, due to needing secondary clamping, there are secondary clamping error, affects Gear Processing precision, also, gear turns Fortune and secondary installing need to consume a large amount of time, cause herringbone bear processing non-cutting time excessive, efficiency is very low.Therefore, it passes The equipment that the herringbone bear processing of system needs is more, and occupied ground is big, manpower is more, the time of consumption is more, and secondary clamping is brought again Clamping error.It is generally speaking exactly at high cost, low efficiency, low precision.
Summary of the invention
It is an object of the invention to design and develop a kind of herringbone bear processing unit (plant), turning and the public revolution of milling Workbench can process double helical tooth in high precision.
Another object of the present invention is to design and develop a kind of method for turning of herringbone bear processing unit (plant), based on BP nerve The turning revolving speed of network-control workpiece, feed distance and turning time, turning accuracy are higher.
The present invention also develops a kind of method for milling of herringbone bear processing unit (plant), can accurately control the revolving speed of workbench with And axial movement speed and the workbench positive and negative rotation time of milling-teeth blade, improve the machining accuracy of double helical tooth.
Technical solution provided by the invention are as follows:
A kind of herringbone bear processing unit (plant) characterized by comprising
Main lathe bed, and
Mill teeth column is arranged in the main lathe bed axial direction side and can be axially moved along the lathe bed;
Milling-teeth blade, by milling slide along the mill teeth column it is axially slidable be arranged on the mill teeth column;
Workbench is rotatably disposed in the main lathe bed axial direction other side;
Vertical lathe body, is radially arranged on the main lathe bed on rear side of the workbench along the main lathe bed;
Vertical stay is radially slidably arranged in the vertical lathe, the vertical stay along the vertical lathe body For hollow structure;
Turning insert is arranged in the vertical stay by turning head along the vertical stay is axially slidable In hollow structure.
Preferably, further includes:
First straight line guide rail is arranged in the main lathe bed axial direction side, and the mill teeth column passes through first ball screw Slidably it is arranged on the first straight line guide rail;
Second straight line guide rail is axially disposed on the mill teeth column inner face, the mill teeth along the mill teeth column Knife rest is slidably arranged on the second straight line guide rail by the second ball-screw;
Third linear guide is radially arranged in the vertical lathe body, the vertical stay along the vertical lathe body Slidably it is arranged in the third linear guide by third ball-screw;
4th linear guide is axially disposed in the vertical stay hollow structure, the vehicle along the vertical stay Sharpener frame is slidably arranged in the 4th linear guide by the 4th ball-screw;
Power mechanism, respectively with the first ball screw, the second ball-screw, third ball-screw, the 4th ball Lead screw is connected with workbench, for driving the first ball screw, the second ball-screw, third ball-screw, the 4th ball Lead screw and workbench work.
Preferably, further includes:
Infrared sensor is separately positioned on the bench top center of circle, milling slide and turning head, for examining Survey the horizontal distance and vertical distance and the turning head and bench top of the milling slide and the bench top center of circle The horizontal distance and vertical distance in the face center of circle;
Velocity sensor is arranged at the workbench axle center, for detecting the angular velocity of rotation of the workbench;
Controller is connect with the infrared sensor, speed probe and power mechanism, for receiving the infrared biography The detection data of sensor and speed probe simultaneously controls the power mechanism work.
Correspondingly, the present invention also provides a kind of method for turning of herringbone bear processing unit (plant), when carrying out turning, are based on BP Vertical distance and turning head and workbench of the neural network to the revolving speed of workbench, turning head and the bench top center of circle The horizontal distance in the top surface center of circle is controlled, and is included the following steps:
Step 1: input turning type, turning specification, the hardness of turning insert hardness and turner;
Step 2: determining the input layer vector x={ x of three layers of BP neural network1,x2,x3,x4};Wherein, x1For vehicle Cut type, x2For turning specification, x3For the hardness of turning insert, x4For the hardness of turner, the input neuronWherein, A is size, and B is turning inner hole, and C is turning end, the input neuronWherein, D is size radius, and E is turning inner hole radius, and F is turning end thickness;
Step 3: the input layer DUAL PROBLEMS OF VECTOR MAPPING to middle layer, the middle layer vector y={ y1,y2,…,ym}; M is middle layer node number;
Step 4: obtaining output layer neuron vector o={ o1,o2,o3,o4};Wherein, o1For the revolving speed of workbench, o2For vehicle The vertical distance of sharpener frame and the bench top center of circle, o3For the horizontal distance of turning head and the bench top center of circle, o4For vehicle Cut the time.
Preferably, the middle layer node number m meets:Wherein n is input layer Number, p are output layer node number.
Preferably, the turning time meets:
Wherein, ω is the angular velocity of rotation of workbench.
Preferably, the excitation function of the middle layer and the output layer is all made of S type function fj(x)=1/ (1+e-x)。
Correspondingly, the present invention also provides a kind of method for milling of herringbone bear processing unit (plant), after workpiece completes turning, control Device processed controls milling-teeth blade horizontal feed, controls the horizontal distance of milling slide and the bench top center of circle are as follows:
Wherein, L0For the horizontal distance of milling slide and the bench top center of circle, r is excircle of workpiece radius, and l is double helical tooth Depth,For the length for stretching out milling-teeth blade from milling slide end face;
The vertical feed of milling slide is controlled, so that milling-teeth blade is contacted with the workpiece top surface;
Workbench is controlled to rotate forward, so that the angular speed of worktable rotary meets:
Wherein, ω is the angular velocity of rotation of workbench, and ξ is correction coefficient, and e is the truth of a matter of natural logrithm, and ε is milling-teeth blade Hardness, ζ be workpiece hardness, r0For inner hole of workpiece radius, D is the distance at double helical tooth both ends, and n is the speed of milling-teeth blade rotation Degree, x are the distance that double helical tooth outer end face is a little arrived in the roller seating space of double helical tooth;
Speed of the control milling slide along mill teeth column axial downward movement while workbench rotates forward are as follows:
Wherein, υ is speed of the milling slide along mill teeth column axial downward movement, and θ is the angle of double helical tooth;
Workbench rotates forward after a certain period of time, and control workbench is inverted with identical angular velocity of rotation, and withdrawing after same time is complete At the milling of a double helical tooth.
Preferably, the time t that the workbench rotates forward1Are as follows:
Preferably, after withdrawing, workbench is controlled with ω angular velocity of rotation and rotates t2After time,
Wherein, d is the distance of adjacent double helical tooth;
Method for milling described in claim 8 or 9 is repeated, until completing the milling of workpiece circumferential direction double helical tooth.
It is of the present invention the utility model has the advantages that
(1) herringbone bear processing unit (plant) of the present invention, being capable of clamped one time, so that it may expeditiously complete high-precision Turning, the Milling Process for spending herringbone bear solve traditional high-accuracy herringbone gear processing and need smooth turning lathe, high-precision The processing technology that two lathes of tooth milling machine could be completed, and occupied area is small, use cost high-efficient, that reduce lathe and The processing cost of herringbone bear.It can reach 6 grades of national standard or more Gear Processing precision.
(2) method for turning of herringbone bear processing unit (plant) of the present invention, the vehicle based on BP neural network control workpiece It is higher to cut revolving speed, feed distance and turning time, turning accuracy.
(3) method for milling of herringbone bear processing unit (plant) of the present invention, can accurately control the revolving speed of workbench with And axial movement speed and the workbench positive and negative rotation time of milling-teeth blade, improve the machining accuracy of double helical tooth.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of herringbone bear processing unit (plant) of the present invention.
Specific embodiment
Present invention will be described in further detail below with reference to the accompanying drawings, to enable those skilled in the art referring to specification text Word can be implemented accordingly.
As shown in Figure 1, the present invention provides a kind of herringbone bear processing unit (plant), including main lathe bed 101, it is characterized in that: described The upper surface left part of main lathe bed 101 is equipped with by first straight line guide rail 102, first ball screw 103 along X-axis side-to-side movement Mill teeth column 104, the right front of the main lathe bed 101 are equipped with turning and the public workbench 105 of milling around the revolution of C axis, institute The right back for stating main lathe bed 101 is fixed with vertical lathe body 106;It is led on the inner face of the mill teeth column 104 by second straight line Rail 107, the second ball-screw 108 are equipped with the milling slide 109 to move up and down along Z axis, horizontal peace on the milling slide 109 Equipped with the mill teeth electro spindle 110 turned round around S axis, by C axis, X-axis, three axis moving interpolation of Z axis, herringbone bear is completed by S axis Milling;It is equipped with by third linear guide 111, third ball-screw 112 along U axis on the inner face of the vertical lathe body 106 The vertical stay 113 moved left and right is pacified by the 4th linear guide 114, the 4th ball-screw 115 on the vertical stay 113 Equipped with the vertical tool holder 116 moved up and down along W axis, is turned round on workbench 105 around C axis by workpiece, found stay 113 along U Axis radial feed founds tool holder 116 along W axis axial direction feed, and the lathe tool by being fixed on vertical 116 lower end of tool holder completes workpiece Outer circle, inner hole and the turning of end face.
Linear axis of the present invention selects high-precision high rigidity roller line slideway, ball-screw, cooperates high-precision planetary reduction gear Device realizes Inertia Matching, so that the positioning of linear axis and repetitive positioning accuracy reach 0.002um.Milling selects high-precision high-strength Spend form cutter, cooperate high-power high-accuracy milling spindle, guarantee form cutter can quick accurate clamping, the axis of milling spindle To and circular runout control in 0.002um.Rotary table reaches P2A grades of high-precision rigid composite table top bearing knots using precision Structure, axial, circular runout precision reach 0.003mm, and axial carrying capacity is up to 10 tons.Workbench uses high power large torque torque Electric-machine directly-driven cooperates high accuracy circular grating, realizes the transmission of high-precision zero clearance, the positioning of workbench and repetitive positioning accuracy reach 3, there is unrivaled advantage compared with traditional turntable.
The public rotary table of turning and milling of the present invention.When progress herringbone bear outer circle, inner hole, facing When, lathe high-precision rotary working-table C axis revolution, the vertical stay U axis radial feed in the upper right corner founds tool holder W axis and axially walks Knife completes turning function by lathe tool;When carrying out the milling of herringbone bear tooth socket, high-precision rotary working-table C axis, the left side Mill teeth column X-axis, milling slide Z axis, three axis moving interpolations are completed the Milling Function of herringbone bear by mill teeth main shaft S axis.
Herringbone bear processing unit (plant) of the present invention, being capable of clamped one time, so that it may expeditiously complete high-precision people The turning of word gear, Milling Process solve traditional high-accuracy herringbone gear processing and need smooth turning lathe, high-precision mill teeth The processing technology that two lathes of machine could be completed, and occupied area is small, use cost high-efficient, that reduce lathe and herringbone The processing cost of gear.It can reach 6 grades of national standard or more Gear Processing precision.
The present invention also provides a kind of method for turning of herringbone bear processing unit (plant), when carrying out turning, are based on BP nerve net Vertical distance and turning head and bench top circle of the network to the revolving speed of workbench, turning head and the bench top center of circle The horizontal distance of the heart is controlled, and is included the following steps:
Step 1: establishing BP neural network model.
Totally interconnected connection is formed on BP model between the neuron of each level, is not connected between the neuron in each level It connects, the output of input layer is identical as input, i.e. oi=xi.The operating characteristic of the neuron of intermediate hidden layer and output layer For
opj=fj(netpj)
Wherein p indicates current input sample, ωjiFor from neuron i to the connection weight of neuron j, opiFor neuron The current input of j, opjIt is exported for it;fjFor it is non-linear can micro- non-decreasing function, be generally taken as S type function, i.e. fj(x)=1/ (1 +e-x)。
For the BP network architecture that the present invention uses by up of three-layer, first layer is input layer, total n node, corresponding Indicate that n turning signal of double helical tooth processing unit (plant) input, these signal parameters are provided by data preprocessing module;The second layer is Hidden layer, total m node are determined in an adaptive way by the training process of network;Third layer is output layer, total p node, by System actual needs output in response to determining that.
The mathematical model of the network are as follows:
Input vector: x=(x1,x2,...,xn)T
Middle layer vector: y=(y1,y2,...,ym)T
Output vector: o=(o1,o2,...,op)T
In the present invention, input layer number is n=4, and output layer number of nodes is p=4, hidden layer number of nodes m=6.
x1For turning type, x2For turning specification, x3For the hardness of turning insert, x4It is described defeated for the hardness of turner Enter neuronWherein, A is size, and B is turning inner hole, and C is turning end, the input neuronWherein, D is size radius, and E is turning inner hole radius, and F is turning end thickness;
4 parameters of output layer respectively indicate are as follows: o1For the revolving speed of workbench, o2For turning head and the bench top center of circle Vertical distance, o3For the horizontal distance of turning head and the bench top center of circle, o4For the turning time.
The turning time meets:
Wherein, ω is the angular velocity of rotation (rad/min) of workbench.
It enables to workpiece turning complete, improves turning accuracy.
Step 2: carrying out the training of BP neural network;
(1) training method
Each subnet is using individually trained method;When training, first have to provide one group of training sample, each of these sample This, to forming, when all reality outputs of network and its consistent ideal output, is shown to train by input sample and ideal output Terminate;Otherwise, by correcting weight, keep the ideal output of network consistent with reality output;The input sample when training of each subnet As shown in table 1.
The input sample of 1 network training of table
(2) training algorithm
BP network is trained using error back propagation (Backward Propagation) algorithm, and step can be concluded It is as follows:
Step 1: a selected structurally reasonable network, is arranged the initial value of all Node B thresholds and connection weight.
Step 2: making following calculate to each input sample:
(a) forward calculation: to l layers of j unit
In formula,L layers of j unit information weighted sum when being calculated for n-th,For l layers of j units with it is previous Connection weight between the unit i of layer (i.e. l-1 layers),For preceding layer (i.e. l-1 layers, number of nodes nl-1) unit i send Working signal;When i=0, enableFor the threshold value of l layers of j unit.
If the activation primitive of unit j is sigmoid function,
And
If neuron j belongs to the first hidden layer (l=1), have
If neuron j belongs to output layer (l=L), have
And ej(n)=xj(n)-oj(n);
(b) retrospectively calculate error:
For output unit
To hidden unit
(c) weight is corrected:
η is learning rate.
Step 3: new sample or a new periodic samples are inputted, and until network convergence, the sample in each period in training Input sequence is again randomly ordered.
BP algorithm seeks nonlinear function extreme value using gradient descent method, exists and falls into local minimum and convergence rate is slow etc. Problem.A kind of more efficiently algorithm is Levenberg-Marquardt optimization algorithm, it makes the e-learning time shorter, Network can be effectively inhibited and sink into local minimum.Its weighed value adjusting rate is selected as
Δ ω=(JTJ+μI)-1JTe
Wherein J is error to Jacobi (Jacobian) matrix of weight differential, and I is input vector, and e is error vector, Variable μ is the scalar adaptively adjusted, for determining that study is completed according to Newton method or gradient method.
In system design, system model is one merely through the network being initialized, and weight needs basis using The data sample obtained in journey carries out study adjustment, devises the self-learning function of system thus.Specify learning sample and In the case where quantity, system can carry out self study, to constantly improve network performance.
Further stamping parts punching online test method provided by the invention is carried out below with reference to specific embodiment Explanation.
In order to detect the process data of different double helical tooths, different shape and size of double helical tooths is selected to be tested.It is testing In, herringbone bear is divided into 10 groups by workpiece hardness, i.e., 1,2,3,4,5 ..., 7,8,9,10, carry out respectively outer circle, inner hole and The turning insert of three kinds of different hardness is respectively adopted in facing, is equivalent to 90 groups of data altogether, choose include 60 groups of data into The training of row BP neural network, it is remaining to be equivalent to 30 groups of data for subsequent verifying.Record exradius, the inner hole of double helical tooth The hardness of radius, turning thickness, the hardness of workpiece and turning insert, data are as shown in table 2.
The specific sample data of 2 network training of table
It using above-mentioned 60 groups of data is trained to obtain BP neural network model, chooses remaining 27 groups of data to obtaining BP neural network model is verified, and error illustrates that product qualification, partial results are as shown in table 3 in 0.01.
3 result verification of table
As shown in Table 3, workpiece turning is carried out using the neural network model of above-mentioned training, accuracy can be up to 96.7%,;Thus, it is possible to show the workpiece turning model established be it is feasible, by the specifications parameter of different double helical tooths and The turning insert of different hardness constantly obtains different turnery processing parameters, and then constantly improve workpiece turnery processing model, It will realize high-precision workpiece turnery processing.
The method for turning of herringbone bear processing unit (plant) of the present invention, the turning based on BP neural network control workpiece turn Speed, feed distance and turning time, turning accuracy are higher.
The present invention also provides a kind of method for milling of herringbone bear processing unit (plant), after workpiece completes turning, controller control Milling-teeth blade horizontal feed processed controls the horizontal distance of milling slide and the bench top center of circle are as follows:
Wherein, L0For the horizontal distance (m) of milling slide and the bench top center of circle, r is excircle of workpiece radius, and l is people The depth (m) of word tooth,For the length (m) for stretching out milling-teeth blade from milling slide end face;
The vertical feed of milling slide is controlled, so that milling-teeth blade is contacted with the workpiece top surface;
Workbench is controlled to rotate forward, so that the angular speed of worktable rotary meets:
Wherein, ω is the angular velocity of rotation (rad/min) of workbench, and ξ is correction coefficient (m-3·min-9/8), e is nature The truth of a matter of logarithm, ε are the hardness (HRC) of milling-teeth blade, and ζ is the hardness (HRC) of workpiece, r0For inner hole of workpiece radius (m), D is The distance (m) at double helical tooth both ends, n are the speed (r/min) of milling-teeth blade rotation, and x is that herringbone is a little arrived in the roller seating space of double helical tooth The distance (min) of tooth outer end face;
Speed of the control milling slide along mill teeth column axial downward movement while workbench rotates forward are as follows:
Wherein, υ is speed (m/min) of the milling slide along mill teeth column axial downward movement, and θ is the angle of double helical tooth (rad);
Workbench rotates forward after a certain period of time, and control workbench is inverted with identical angular velocity of rotation, and withdrawing after same time is complete At the milling of a double helical tooth.
The time t that the workbench rotates forward1(min) are as follows:
After withdrawing, workbench is controlled with ω angular velocity of rotation and rotates t2(min) after the time,
Wherein, d is the distance (m) of adjacent double helical tooth;
Aforesaid operations are repeated, until completing the milling of workpiece circumferential direction double helical tooth.
The method for milling of herringbone bear processing unit (plant) of the present invention can accurately control revolving speed and the milling of workbench The axial movement speed of teeth cutter blade and workbench positive and negative rotation time, improve the machining accuracy of double helical tooth.
Although embodiment of the present invention discloses as above, listed fortune not only in the description and the implementation With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily real Now other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is not limited to Specific details and legend shown and described herein.

Claims (7)

1. a kind of method for turning of herringbone bear processing unit (plant), which is characterized in that when carrying out turning, be based on BP neural network pair The revolving speed of workbench, the vertical distance of turning head and the bench top center of circle and turning head and the bench top center of circle Horizontal distance is controlled, and is included the following steps:
Step 1: input turning type, turning specification, the hardness of turning insert hardness and turner;
Step 2: determining the input layer vector x={ x of three layers of BP neural network1,x2,x3,x4};Wherein, x1For turning class Type, x2For turning specification, x3For the hardness of turning insert, x4For the hardness of turner, the input neuronIts In, A is size, and B is turning inner hole, and C is turning end, the input neuronWherein, D is vehicle Exradius is cut, E is turning inner hole radius, and F is turning end thickness;
Step 3: the input layer DUAL PROBLEMS OF VECTOR MAPPING to middle layer, the middle layer vector y={ y1,y2,…,ym};M is Middle layer node number;
Step 4: obtaining output layer neuron vector o={ o1,o2,o3,o4};Wherein, o1For the revolving speed of workbench, o2For turning knife The vertical distance of frame and the bench top center of circle, o3For the horizontal distance of turning head and the bench top center of circle, o4When for turning Between.
2. the method for turning of herringbone bear processing unit (plant) as described in claim 1, which is characterized in that the middle layer node Number m meets:Wherein n is input layer number, and p is output layer node number.
3. the method for turning of herringbone bear processing unit (plant) as claimed in claim 1 or 2, which is characterized in that the turning time Meet:
Wherein, ω is the angular velocity of rotation of workbench.
4. the method for turning of herringbone bear processing unit (plant) as claimed in claim 3, which is characterized in that the middle layer and described The excitation function of output layer is all made of S type function fj(x)=1/ (1+e-x)。
5. a kind of method for milling of herringbone bear processing unit (plant), which is characterized in that after workpiece completes turning, controller control milling Teeth cutter blade horizontal feed controls the horizontal distance of milling slide and the bench top center of circle are as follows:
Wherein, L0For the horizontal distance of milling slide and the bench top center of circle, r is excircle of workpiece radius, and l is the depth of double helical tooth Degree,For the length for stretching out milling-teeth blade from milling slide end face;
The vertical feed of milling slide is controlled, so that milling-teeth blade is contacted with the workpiece top surface;
Workbench is controlled to rotate forward, so that the angular speed of worktable rotary meets:
Wherein, ω is the angular velocity of rotation of workbench, and ξ is correction coefficient, and e is the truth of a matter of natural logrithm, and ε is the hard of milling-teeth blade Degree, ζ are the hardness of workpiece, r0For inner hole of workpiece radius, D is the distance at double helical tooth both ends, and n is the speed of milling-teeth blade rotation, x For the distance for a little arriving double helical tooth outer end face in the roller seating space of double helical tooth;
Speed of the control milling slide along mill teeth column axial downward movement while workbench rotates forward are as follows:
Wherein, υ is speed of the milling slide along mill teeth column axial downward movement, and θ is the angle of double helical tooth;
Workbench rotates forward after a certain period of time, and control workbench is inverted with identical angular velocity of rotation, and withdrawing after same time completes one The milling of a double helical tooth.
6. the method for milling of herringbone bear processing unit (plant) as claimed in claim 5, which is characterized in that the workbench rotated forward Time t1Are as follows:
7. such as the method for milling of herringbone bear processing unit (plant) described in claim 5 or 6, which is characterized in that after withdrawing, control work Make platform and t is rotated with ω angular velocity of rotation2After time,
Wherein, d is the distance of adjacent double helical tooth;
Method for milling described in claim 5 or 6 is repeated, until completing the milling of workpiece circumferential direction double helical tooth.
CN201810454630.4A 2018-05-14 2018-05-14 A kind of herringbone bear processing unit (plant) and its turning and method for milling Active CN108356364B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810454630.4A CN108356364B (en) 2018-05-14 2018-05-14 A kind of herringbone bear processing unit (plant) and its turning and method for milling

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810454630.4A CN108356364B (en) 2018-05-14 2018-05-14 A kind of herringbone bear processing unit (plant) and its turning and method for milling

Publications (2)

Publication Number Publication Date
CN108356364A CN108356364A (en) 2018-08-03
CN108356364B true CN108356364B (en) 2019-05-24

Family

ID=63011932

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810454630.4A Active CN108356364B (en) 2018-05-14 2018-05-14 A kind of herringbone bear processing unit (plant) and its turning and method for milling

Country Status (1)

Country Link
CN (1) CN108356364B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110509285A (en) * 2019-07-31 2019-11-29 清华大学 A kind of huge revolving class component movable type machining robot

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104874867A (en) * 2015-05-06 2015-09-02 宝鸡市新福泉机械科技发展有限责任公司 High-precision and high-efficiency herringbone gear machine tool
CN107992939A (en) * 2017-12-06 2018-05-04 湖北工业大学 Cutting force gear working method is waited based on depth enhancing study

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0471933A (en) * 1990-07-10 1992-03-06 Toyota Motor Corp Travel control device for vehicle
KR101426658B1 (en) * 2013-06-26 2014-08-07 경희대학교 산학협력단 Method and apparatus for estimating shape of gear

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104874867A (en) * 2015-05-06 2015-09-02 宝鸡市新福泉机械科技发展有限责任公司 High-precision and high-efficiency herringbone gear machine tool
CN107992939A (en) * 2017-12-06 2018-05-04 湖北工业大学 Cutting force gear working method is waited based on depth enhancing study

Also Published As

Publication number Publication date
CN108356364A (en) 2018-08-03

Similar Documents

Publication Publication Date Title
Ruijun et al. The thermal error optimization models for CNC machine tools
Li et al. Multi-objective optimization of cutting parameters in sculptured parts machining based on neural network
Waiyagan et al. Intelligent feature based process planning for five-axis mill-turn parts
CN105425727B (en) Five axis Flank machining cutter path method for fairing
CN108356364B (en) A kind of herringbone bear processing unit (plant) and its turning and method for milling
Rashid et al. Surface roughness prediction for CNC milling process using artificial neural network
Pham et al. A manufacturing model of an end mill using a five-axis CNC grinding machine
CN108672835A (en) A kind of herringbone bear shaping method based on symmetry error on-line checking and compensation
CN105446264A (en) Feature-based machine tool accuracy optimization design method
CN104400649A (en) Rotary part arc trimming algorithm and control system using same
CN110355608B (en) Cutter wear amount prediction method based on self-attention mechanism and deep learning
CN106202755A (en) Electric main shaft structure Optimization Design based on kinetic model and genetic algorithm
CN109822576B (en) Method for generating virtual fixture for robot machining
Lu et al. Surface roughness prediction model of micro-milling Inconel 718 with consideration of tool wear
CN107850886A (en) Method for orienting workpiece
Choudhary et al. CNC PCB milling and wood engraving machine
López de Lacalle* et al. The CAM as the centre of gravity of the five-axis high speed milling of complex parts
Youn et al. Interference-free tool path generation in five-axis machining of a marine propeller
CN106502201B (en) A kind of three-axis numerical control rough machining method of simple variable cross-section part
Eski Vibration analysis of drilling machine using proposed artificial neural network predictors
Kakati et al. Prediction of optimum cutting parameters to obtain desired surface in finish pass end milling of aluminium alloy with carbide tool using artificial neural network
CN101893430A (en) Processing method of abnormal measured values based on CNC gear measuring center
Tolouei-Rad Intelligent analysis of utilization of special purpose machines for drilling operations
Kawasaki et al. Accuracy measurement and evaluation of straight bevel gear manufactured by end mill using CNC milling machine
Oberlé et al. A Use Case to Implement Machine Learning for Life Time Prediction of Manufacturing Tools

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CP03 Change of name, title or address
CP03 Change of name, title or address

Address after: 721000, Shaanxi Province, Weibin District, Baoji province Gao Zhen Zhen Village two groups

Patentee after: BAOJI XINFUQUAN MACHINERY TECHNOLOGY Co.,Ltd.

Address before: 721008 Shaanxi Province, Weibin City, the town of the town of the tower of a small village of the group of two

Patentee before: BAOJI XINFUQUAN MACHINERY TECHNOLOGY DEVELOPMENT Co.,Ltd.