CN102785129B - The online test method of the surface machining accuracy of complex parts - Google Patents
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Abstract
The present invention is the online test method of the surface machining accuracy of a kind of complex parts.Comprise the steps: 1) contact is triggered gauge head it is arranged on the main shaft of CNC milling machine；2) carry out tested curved surface detecting path planning；3) drive CNC milling machine, obtain the coordinate surveying ball center at gauge head and curved face contact point to be measured one by one；Surveying ball is the parts that contact triggers gauge head, is a ball with high accuracy and high rigidity, is arranged in gauge head main body and directly contacts with tested curved surface；4) coordinate to above-mentioned survey ball center carries out surveying radius of a ball compensation, gauge head pretravel error compensation and machine tool error compensation, thus obtains the testing result of measuring point high precision；5) the preferable cad model of testing result with part is analyzed, finds the deviation that each measuring point is corresponding with cad model, thus obtain the machining accuracy of curved surface to be measured.The present invention makes high-precision precision measurement and detection process directly carry out in CNC milling machine, it is to avoid the position error that part multiple clamping is brought.
Description
Technical field
The present invention is the online test method of the surface machining accuracy of a kind of complex parts, a kind of in CNC milling machine, complex curved surface parts is processed after, directly on this lathe, this part is processed the online test method of the surface machining accuracy of the complex parts of the on-line checking of precision, belong to the renovation technique of the online test method of the surface machining accuracy of complex parts.
Background technology
Along with the continuous progress of manufacturing industry technology and equipment, the highest to precision, efficiency, quality and the appearance requirement of complex parts/product.In the production process of complex curved surface parts, need by corresponding detection technique its machining accuracy to be detected and control.Detection technique based on three coordinate measuring machine (CMM) is usually used in the accuracy of form and position detection of precision component, but there is workpiece secondary clamping position error problem and the confinement problems of heavy parts measurement.Directly being processed the on-line checking of precision in CNC milling machine, form the closed loop processing detecting system of " processing-measure-compensate ", tool is of great significance.
Online measuring technique is i.e. directly to detect the part after digital control processing in CNC milling machine, by being analyzed obtaining the machining accuracy of part to detection data.This technology is suitable for the precision measurement and detection of needles of various sizes size, complex curved surface parts, can be effectively improved the part processing precision of CNC milling machine, obtain the extensive concern of academia and industrial quarters.The online test method of CNC milling machine part processing precision, is with a wide range of applications.
The most domestic developed on-line detecting system, detection function is the weakest, substantially stay in some functions that digital control system itself is provided, detection object great majority are for simple rule body (such as plane, circle, cylinder and boss etc.), and less for complex-curved on-line checking research.
CNC milling machine measures circumstance complication, and error influence factor is many, and CNC milling machine on-line checking yet suffers from bigger gap compared with high-precision CMM, it is difficult to obtain satisfied Surveying Actual Precision.
Summary of the invention
It is an object of the invention to consider that the problems referred to above provide one can obtain high-precision testing result, and then obtain the online test method of the surface machining accuracy of the complex parts of the machining accuracy of processed curved surface.Instant invention overcomes the complex-curved weak point needing and moving to obtain high precision test result on CMM, directly in CNC milling machine, the part with complex-curved feature can be carried out the on-line checking of surface accuracy, high-precision testing result is obtained by error compensation, finally give the shape face machining accuracy of part, be effectively improved production efficiency.
The technical scheme is that the online test method of the surface machining accuracy of the complex parts of the present invention, comprise the following steps that
1) contact is triggered gauge head to be arranged on the main shaft of CNC milling machine；
2) carry out tested curved surface detecting path planning；
3) drive CNC milling machine, obtain the coordinate of survey ball center (3) at gauge head and curved face contact point to be measured one by one；Surveying ball is the parts that contact triggers gauge head, and its shape is a ball with the high accuracy of manufacture and high rigidity, is arranged in gauge head main body and directly contacts with tested curved surface；
4) coordinate to above-mentioned survey ball center carries out surveying radius of a ball compensation, gauge head pretravel error compensation and machine tool error compensation, thus obtains the testing result of measuring point high precision；Wherein machine tool error need to use machine tool error detecting instrument to obtain；
5) the preferable cad model of testing result with part is analyzed, finds the deviation that each measuring point is corresponding with cad model, thus obtain the machining accuracy of curved surface to be measured.
The above-mentioned survey radius of a ball compensates, gauge head pretravel error compensation needs to calculate the direction of normal of curved surface measuring point, for gauge head pretravel error compensation, also needing to the pretravel error calculating gauge head at each measuring point direction of normal, compensation method is to use neutral net based on RBF (RBF) to be predicted.
Machine tool error detecting instrument used by the compensation of above-mentioned machine tool error is laser interferometer.
The deviation that above-mentioned measuring point is corresponding with cad model uses the computational methods of the minimum range of point to curved surface to solve.
The method that above-mentioned neutral net based on RBF RBF is predicted is as follows:
Regularization RBF network is a kind of three layers of feedforward partial approximation network with single hidden layer, it has proved that, it can approach arbitrary continuation function with arbitrary accuracy with BP network；And, compare BP network, its training time is shorter, and it meets the approximate error to sample and the flatness of approximating curve simultaneously, in practice, the supervised training of network can regard the process of a kind of curve matching as, utilizes regularization RBF algorithm, by the training to network, it is achieved input and export the nonlinear mapping between space；
Regularization RBF topology of networks is made up of the radial direction hidden layer of base neuron, an output layer for a linear neuron, and the input point quantity of network is N, and hidden node quantity is P, and output node quantity is l；The Hidden nodes of network is equal to inputting sample number, and all input samples are set to the center of RBF, and each RBF takes unified extension constant；
RBF realizes by inputtingTo outputMapping,() to use RBF be the activation primitive of arbitrary hidden node, selects Gauss function as RBF；W is output weight matrix, wherein(；) it is hidden layerIndividual node is to output layerIndividual internodal synaptic weight；Use linear activation primitive as output layer neuron；
According to regularization RBF Principles of Network, the training process of RBF is: (1) determines RBF neural input and output variable, and i.e. using detection direction as the input node of network, corresponding pretravel error is the output node of network；(2) network is trained by composition training set, i.e. randomly selects the some groups of teacher's data as network from the pretravel error information detected；(3) input prediction sample, arbitrarily detects the pretravel error in direction with the neural network forecast trained, with remaining measuring point data as forecast sample.
The method that the computational methods of the minimum range of above-mentioned point to curved surface solve is as follows: curved surface is divided into sufficiently small grid, calculates measuring point (xm,ym,zm) to the distance of total-grid node, the minima of all these distances is exactly the minimum range of point to curved surface.
Due to the fact that employing is after complex surface machining to be detected completes, the method directly carrying out detecting on the workbench of CNC milling machine, the data obtained are carried out error compensation thus obtains high-precision testing result, this testing result is analyzed and then obtains the machining accuracy of tested curved surface.The invention have the advantage that the method for the present invention directly can carry out on-line checking to complex-curved after machining in CNC milling machine, compensate by the data obtained being carried out survey radius of a ball compensation, pretravel error compensation and machine tool error, obtain high-precision testing result, and then obtain the machining accuracy of processed curved surface, overcome the complex-curved weak point needing and moving to obtain high precision test result on CMM, being effectively improved production efficiency, the present invention has significant economic benefit, social benefit.The present invention is that a kind of design is ingenious, function admirable, the online test method of the surface machining accuracy of convenient and practical complex parts.
Accompanying drawing explanation
Fig. 1 is that the present invention surveys radius of a ball compensation principle figure；
Fig. 2 is pretravel Error Graph of the present invention；
Fig. 3 is the method flow diagram of the present invention；
Fig. 4 is the schematic diagram of regularization RBF network；
Fig. 5 is the schematic diagram of the minimum range of point to curved surface.
In figure: 1-direction of normal, the tested curved surface of 2-, 3-surveys ball center, and 4-contact triggers gauge head, 5-contact point, and 6-detects direction, 7-pretravel error, 8-gauge head location moving direction, 9-gauge head low speed direction of closing, the pre-contact distance of 10-gauge head, 11-workpiece at a high speed.
Detailed description of the invention
Embodiment:
The online test method of the surface machining accuracy of the complex parts of the present invention,
The online test method of the surface machining accuracy of the complex parts of the present invention, comprises the following steps that
1) contact triggers gauge head 4 to be arranged on the main shaft of CNC milling machine；
2) carry out tested curved surface 2 detecting path planning；
3) drive CNC milling machine, obtain the coordinate surveying ball center 3 at gauge head and curved face contact point to be measured one by one；Surveying ball is the parts that contact triggers gauge head, and its shape is a ball with the high accuracy of manufacture and high rigidity, is arranged in gauge head main body and directly contacts with tested curved surface；
4) coordinate to above-mentioned survey ball center 3 carries out surveying radius of a ball compensation, gauge head pretravel error compensation and machine tool error compensation, thus obtains the testing result of measuring point high precision；Wherein machine tool error need to use machine tool error detecting instrument to obtain；
5) the preferable cad model of testing result with part is analyzed, finds the deviation that each measuring point is corresponding with cad model, thus obtain the machining accuracy of curved surface to be measured.
The above-mentioned survey radius of a ball compensates, gauge head pretravel error compensation needs to calculate the direction of normal of curved surface measuring point, for gauge head pretravel error compensation, also needing to the pretravel error calculating gauge head at each measuring point direction of normal, compensation method is to use neutral net based on RBF (RBF) to be predicted.
Machine tool error detecting instrument used by the compensation of above-mentioned machine tool error is laser interferometer.
The deviation that above-mentioned measuring point is corresponding with cad model uses the computational methods of the minimum range of point to curved surface to solve.
The method that above-mentioned neutral net based on RBF (RBF) is predicted is as follows:
Regularization RBF network is a kind of three layers of feedforward partial approximation network with single hidden layer, it has proved that, it can approach arbitrary continuation function with arbitrary accuracy with BP network；And, compare BP network, its training time is shorter, and it meets the approximate error to sample and the flatness of approximating curve simultaneously, in practice, the supervised training of network can regard the process of a kind of curve matching as, utilizes regularization RBF algorithm, by the training to network, it is achieved input and export the nonlinear mapping between space；
Regularization RBF topology of networks is made up of the radial direction hidden layer of base neuron, an output layer for a linear neuron, and the input point quantity of network is N, and hidden node quantity is P, and output node quantity is l；The Hidden nodes of network is equal to inputting sample number, and all input samples are set to the center of RBF, and each RBF takes unified extension constant；
RBF realizes by inputtingTo outputMapping,() to use RBF be the activation primitive of arbitrary hidden node, selects Gauss function as RBF；W is output weight matrix, wherein(；) it is hidden layerIndividual node is to output layerIndividual internodal synaptic weight；Use linear activation primitive as output layer neuron；
According to regularization RBF Principles of Network, the training process of RBF is: (1) determines RBF neural input and output variable, and i.e. using detection direction as the input node of network, corresponding pretravel error is the output node of network；(2) network is trained by composition training set, i.e. randomly selects the some groups of teacher's data as network from the pretravel error information detected；(3) input prediction sample, arbitrarily detects the pretravel error in direction with the neural network forecast trained, with remaining measuring point data as forecast sample.
The method that the computational methods of the minimum range of above-mentioned point to curved surface solve is as follows: curved surface is divided into sufficiently small grid, calculates measuring point (xm,ym,zm) to the distance of total-grid node, the minima of all these distances is exactly the minimum range of point to curved surface.
The embodiment of the present invention is to utilize CNC milling machine that complex curved surface part is carried out high-precision detection method, the method is adapted to when workpiece 11 is processed by CNC milling machine, the workpiece 11 of the embodiment of the present invention is complex curved surface parts, after workpiece 11 completes a manufacturing procedure, directly on the workbench of CNC milling machine, workpiece 11 is detected, realize processing and detection is all carried out in CNC milling machine, can avoid that workpiece 11 is moved to other detection equipment (such as three coordinate measuring machine) and above detect the second positioning error brought, also the workpiece 11 to size and weight are big can be avoided to carry brought inconvenience.Workpiece 11 detected in the method for the present embodiment, after machining, directly detects on the workbench of CNC milling machine, comprises the following steps:
Step one: contact is triggered gauge head 4 and is arranged on the main shaft of CNC milling machine.The contact that drives main shaft triggers gauge head 4 and moves, and contact triggers gauge head 4 and implements the coordinate measurement to tested curved surface 2, and testing result record is in inspection software.
Step 2: carry out tested curved surface 2 detecting path planning.Utilize inspection software that tested curved surface carries out points planning and detection path planning.
Step 3: drive CNC milling machine, obtains contact one by one and triggers the coordinate surveying ball center 3 at gauge head 4 and tested curved face contact point 5；
Step 4: above-mentioned survey ball center 3 coordinate carries out survey radius of a ball compensation, contact triggers gauge head 4 pretravel error compensation and machine tool error compensates, thus obtains the testing result of measuring point high precision；
As it is shown in figure 1, survey the radius of a ball compensate it is crucial that obtain the direction of normal 1 of measured point, then utilize formula carry out survey the radius of a ball compensate
(1)
In above formula, (X, Y, Z) is the coordinate of contact point A, and (x, y, z) coordinate of Shi Ce ball center B, r is for surveying the radius of a ball, and n is measuring point unit normal vector.
The compensation aspect of gauge head pretravel error 7, as shown in Figure 2, from contact trigger gauge head 4 contact surface of the work to trigger that signal produces during this period of time in, contact triggers gauge head 4 additional movements slight distance, and being commonly referred to as error amount caused by this section of slight distance is gauge head pretravel error.Standard ball need to be utilized to detect gauge head pretravel error in all directions, and utilize RBF (RBF) algorithm predicts to go out the pretravel error 7 on any direction of normal 1.
In terms of machine tool error compensation, according to kinematic principle, object has six-freedom degree along a certain linear motion, i.e. three translation freedoms and three revolution degree of freedom, namely there are six geometric error components, i.e. along the straightness error of three mutually perpendicular directions and the rotation error to three mutually perpendicular directions.Milling Motion in Three-axes NC the most all has (X, Y, Z) three orthogonal linear motion axis.Therefore, for Milling Motion in Three-axes NC, move along three axles and co-exist in 18 error components, add and between three axles, there is also the error of perpendicularity, a total of 21 error components.The present embodiment utilizes laser interferometer to measure this 21 error components.
Measuring point method arrow, pretravel error and the machine tool error of above-mentioned acquisition are input in inspection software system, and the survey ball center coordinate feeding back to digital control system compensates.
The present embodiment uses TP6L gauge head system.
Step 5: be analyzed by the preferable cad model of testing result with part, finds the deviation that each measuring point is corresponding with cad model, thus obtains the machining accuracy of curved surface to be measured.
Above-mentioned steps two needs to carry out points planning (i.e. measuring point arrangement mode on curved surface), and calculates the direction of normal 1 of each measuring point, then carry out detecting path planning.Described method is vowed as on the curved surface of measuring point place and by the method arrow of described tested point.
In above-mentioned steps three, contact triggers gauge head 4 and at the uniform velocity contacts the measuring point on tested curved surface along direction of normal 1, in this process, contact triggers gauge head 4 and moves to gauge head low speed direction of closing 9 from gauge head location moving direction 8 at a high speed along detection direction 6, the pre-contact distance 10 of gauge head in figure, utilizes software system to receive contact in contact process and triggers the centre coordinate information of gauge head 4.
In above-mentioned steps four, standard ball need to be utilized to detect gauge head pretravel error in all directions, and utilize RBF (RBF) algorithm predicts to go out the pretravel error on any direction of normal.Laser interferometer measurement is utilized to obtain the geometric error of lathe.
Claims (4)
1. the online test method of the surface machining accuracy of complex parts, it is characterised in that comprise the following steps that
1) contact triggers gauge head (4) to be arranged on the main shaft of CNC milling machine；
2) carry out tested curved surface (2) detecting path planning；
3) drive CNC milling machine, obtain the coordinate of survey ball center (3) at gauge head and curved face contact point to be measured one by one；Surveying ball is the parts that contact triggers gauge head, and its shape is a ball with the high accuracy of manufacture and high rigidity, is arranged in gauge head main body and directly contacts with tested curved surface；
4) coordinate to above-mentioned survey ball center (3) carries out surveying radius of a ball compensation, gauge head pretravel error compensation and machine tool error compensation, thus obtains the testing result of measuring point high precision；Wherein machine tool error need to use machine tool error detecting instrument to obtain；
5) the preferable cad model of testing result with part is analyzed, finds the deviation that each measuring point is corresponding with cad model, thus obtain the machining accuracy of curved surface to be measured；
The above-mentioned survey radius of a ball compensates, gauge head pretravel error compensation needs to calculate the direction of normal of curved surface measuring point, for gauge head pretravel error compensation, also needing to the pretravel error calculating gauge head at each measuring point direction of normal, compensation method is to use neutral net based on RBF RBF to be predicted；
The method that above-mentioned neutral net based on RBF RBF is predicted is as follows:
Regularization neutral net based on RBF RBF is a kind of three layers of feedforward partial approximation network with single hidden layer, it has proved that, it can approach arbitrary continuation function with arbitrary accuracy with BP network；And, compare BP network, its training time is shorter, and it meets the approximate error to sample and the flatness of approximating curve simultaneously, in practice, the supervised training of network can regard the process of a kind of curve matching as, utilizes regularization RBF algorithm, by the training to network, it is achieved input and export the nonlinear mapping between space；
The topological structure of regularization neutral net based on RBF RBF is made up of the radial direction hidden layer of base neuron, an output layer for a linear neuron, and the input point quantity of network is N, and hidden node quantity is P, and output node quantity is l；The Hidden nodes of network is equal to inputting sample number, and all input samples are set to the center of RBF, and each RBF takes unified extension constant；
The realization of neutral net based on RBF RBF is by inputting X=(x1,x2,…,xN)TTo output Y=(y1,y2,…,yl)TMapping,The activation primitive using RBF to be arbitrary hidden node, selects Gauss function as RBF；W is output weight matrix, wherein wjk(j=1,2 ..., P；K=1,2 ..., it is l) that hidden layer jth node is to the internodal synaptic weight of output layer kth；Use linear activation primitive as output layer neuron；Wherein X,Y is input, output sample,For basic function；
Principle according to regularization neutral net based on RBF RBF, training process based on RBF RBF is: (1) determines input and the output variable of neutral net based on RBF RBF, i.e. using detection direction as the input node of network, corresponding pretravel error is the output node of network；(2) network is trained by composition training set, i.e. randomly selects the some groups of teacher's data as network from the pretravel error information detected；(3) input prediction sample, arbitrarily detects the pretravel error in direction with the neural network forecast trained, with remaining measuring point data as forecast sample.
The online test method of the surface machining accuracy of complex parts the most according to claim 1, it is characterised in that the machine tool error detecting instrument used by the compensation of above-mentioned machine tool error is laser interferometer.
The online test method of the surface machining accuracy of complex parts the most according to claim 1, it is characterised in that the deviation that above-mentioned measuring point is corresponding with cad model uses the computational methods of the minimum range of point to curved surface to solve.
The online test method of the surface machining accuracy of complex parts the most according to claim 3, it is characterised in that the method that the computational methods of the minimum range of above-mentioned point to curved surface solve is as follows: curved surface is divided into sufficiently small grid, calculates measuring point (xm,ym,zm) to the distance of total-grid node, the minima of all these distances is exactly the minimum range of point to curved surface.
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