CN102785129A - On-line detection method of curved surface machining precision of complex part - Google Patents
On-line detection method of curved surface machining precision of complex part Download PDFInfo
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Abstract
The invention relates to an on-line detection method of curved surface machining precision of a complex part, which comprises the following steps that 1) a touch trigger probe is arranged on a spindle of a numerically controlled lathe; 2) the detection path of the detected curved surface is planned; 3) the numerically controlled lathe is driven to obtain the coordinate of the center of a ball at the contact point of the probe and the curved surface to be detected one by one; the ball is a component of the touch trigger probe, is a round ball with high precision and high hardness and is arranged on the main body of the probe and is in direct contact with the detected curved surface; 4) the ball radius compensation of the coordinate of the ball center, the probe pre-stroke error compensation and the lathe error compensation are carried out to obtain the high-precision results of detected points; and 5) the detection results and ideal CAD (Computer Aided Design) models of the parts are analyzed by comparison to find the corresponding deviation of various detected points and the CAD models so as to obtain the machining precision of the curved surface to be detected. By the on-line detection method, the high-precision machining precision detection process is directly carried out on the numerically controlled lathe so as to avoid the positioning error caused by multiple clamping of the parts.
Description
Technical field
The present invention is a kind of online test method of surface machining accuracy of complex parts; Particularly a kind ofly on the CNC milling machine complex curved surface parts processed the back, directly on this lathe, this part carried out the online test method of surface machining accuracy of complex parts of the online detection of machining accuracy, belonging to the renovation technique of online test method of the surface machining accuracy of complex parts.
Background technology
Along with the continuous progress of manufacturing industry technology and equipment, more and more high to precision, efficient, quality and the appearance requirement of complex parts/product.In the production process of complex curved surface parts, need detect and control its machining accuracy with the relevant detection technology.Be usually used in the accuracy of form and position detection of precision component based on the detection technique of three coordinate measuring machine (CMM), but have the limitation problem of workpiece secondary clamping position error problem and heavy parts measurement.On CNC milling machine, directly carry out the online detection of machining accuracy, form the closed loop processing detection system of " processing-measurement-compensation ", have crucial meaning.
Online measuring technique promptly is directly the part after the digital control processing to be detected on the CNC milling machine, through analyzing the machining accuracy that obtains part to detecting data.The machining accuracy that this technology is suitable for needles of various sizes size, complex curved surface parts detects, and can effectively improve the part processing precision of CNC milling machine, has obtained 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 present domestic on-line detecting system of developing; Measuring ability is comparatively weak; Basically stay in some functions that digital control system itself is provided; The detected object great majority are to simple rule body (like plane, circle, cylinder and boss etc.), and less to complex-curved online detection research.
The CNC milling machine measurement environment is complicated, and the error effect factor is many, and the online detection of CNC milling machine is compared with high-precision CMM and still had big gap, is difficult to obtain satisfied actual measurement precision.
Summary of the invention
The objective of the invention is to consider the problems referred to above and a kind of high-precision test result that can obtain is provided, and then obtain the online test method of surface machining accuracy of complex parts of the machining accuracy of processed curved surface.The present invention has overcome complex-curved needs and has moved to the weak point that CMM upward could obtain the high Precision Detection result; Can be directly on CNC milling machine, the part with complex-curved characteristic be carried out the online detection of shape surface accuracy; Obtain the high-precision test result through error compensation; Finally obtain the shape face machining accuracy of part, improved production efficiency effectively.
Technical scheme of the present invention is: the online test method of the surface machining accuracy of complex parts of the present invention includes following steps:
1) contact is triggered on the main shaft that gauge head is installed in CNC milling machine;
2) tested curved surface is detected path planning;
3) drive CNC milling machine, obtain the coordinate of the survey ball center (3) at gauge head and curved surface contact point to be measured place 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 installed on the gauge head main body and with tested curved surface directly to contact;
4) coordinate of above-mentioned survey ball center is surveyed radius of a ball compensation, gauge head pretravel error compensation and machine tool error compensation, thereby obtain the testing result of measuring point high precision; Wherein machine tool error need adopt the machine tool error detecting instrument to obtain;
5) the desirable cad model with testing result and part compares analysis, finds each measuring point deviation corresponding with cad model, thereby obtains the machining accuracy of curved surface to be measured.
Above-mentioned survey radius of a ball compensation, gauge head pretravel error compensation need calculate the direction of normal of curved surface measuring point; For gauge head pretravel error compensation; Also need calculate the pretravel error of gauge head at each measuring point direction of normal, compensation method is to adopt to predict based on the neutral net of RBF (RBF).
The used machine tool error detecting instrument of above-mentioned machine tool error compensation is a laser interferometer.
The deviation that above-mentioned measuring point is corresponding with cad model adopts the computational methods of the minimum range of point to curved surface to find the solution.
It is following that above-mentioned neutral net based on RBF RBF is carried out forecast method:
Regularization RBF network is that network is approached in a kind of three layers of feedforward part with single hidden layer, and verified, it and BP network can both approach any continuous function with arbitrary accuracy; And, compare the BP network, its training time is shorter; And it satisfies the approximate error of sample and the flatness of approximating curve simultaneously; In practice, the supervised training of network can be regarded a kind of process of curve match as, utilizes regularization RBF algorithm; Through training, realize the Nonlinear Mapping between the input and output space to network;
Regularization RBF topology of networks is made up of the output layer of a radially basic neuronic latent layer, a linear neuron, and the input point quantity of network is N, and latent number of nodes is P, and output node quantity is l; The latent node number of network equals to import sample number, and all are imported the center that samples are made as RBF, and each RBF is got unified expansion constant;
RBF achieved by the input ?
to the output
mapping,?
(
) using the radial basis function as either a hidden node activation function, the choice of Gauss function as the radial basis function; W of output power matrix, where
(
;
) for the hidden layer
to the output node Level
nodes between synaptic weights; linear activation function as the output layer neurons;
According to regularization RBF Principles of Network, the training process of RBF is: RBF neutral net input and output variable are confirmed in (1), promptly with the detection side to input node as network, corresponding pretravel error is the output node of network; (2) form training set network is trained, be i.e. some groups of teacher's data of picked at random from detected pretravel error information as network; (3) input forecast sample, with the network that trains predict any detection side to the pretravel error, 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 are found the solution is following: curved surface is divided into enough little grid, the calculating measuring point (
x m,
y m,
z m) to the distance of total-grid node, all these minimum value and value are exactly the minimum range of point to curved surface.
The present invention is because after being employed in complex-curved machining to be detected; The method that on the workbench of CNC milling machine, directly detects; Obtain the high-precision test result thereby the data of obtaining are carried out error compensation, this testing result is analyzed and then obtained the machining accuracy of tested curved surface.Advantage of the present invention is: method of the present invention can directly carried out online detection to complex-curved after machining on the CNC milling machine; Through the data of obtaining being surveyed radius of a ball compensation, pretravel error compensation and machine tool error compensation; Obtain the high-precision test result; And then obtain the machining accuracy of processed curved surface; Overcome complex-curved needs and moved to the weak point that CMM upward could obtain the high Precision Detection result, improved production efficiency effectively, the present invention has remarkable economic efficiency, 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.
Description of drawings
Fig. 1 surveys radius of a ball compensation principle figure for the present invention;
Fig. 2 is a pretravel Error Graph of the present invention;
Fig. 3 is a method flow diagram of the present invention;
Fig. 4 is the sketch map of regularization RBF network;
Fig. 5 is the sketch map of the minimum range of point to curved surface.
Among the figure: the 1-direction of normal, the tested curved surface of 2-, 3-surveys ball center, and the 4-contact triggers gauge head; The 5-contact point, the 6-detection side is to, 7-pretravel error, and the 8-gauge head is located moving direction at a high speed; 9-gauge head low speed direction of closing, the preparatory contact distance of 10-gauge head, 11-workpiece.
The specific embodiment
Embodiment:
The online test method of the surface machining accuracy of complex parts of the present invention,
The online test method of the surface machining accuracy of complex parts of the present invention includes following steps:
1) contact is triggered on the main shaft that gauge head 4 is installed in CNC milling machine;
2) tested curved surface 2 is detected path planning;
3) drive CNC milling machine, obtain the coordinate of the survey ball center 3 at gauge head and curved surface contact point to be measured place 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 installed on the gauge head main body and with tested curved surface directly to contact;
4) coordinate of above-mentioned survey ball center 3 is surveyed radius of a ball compensation, gauge head pretravel error compensation and machine tool error compensation, thereby obtain the testing result of measuring point high precision; Wherein machine tool error need adopt the machine tool error detecting instrument to obtain;
5) the desirable cad model with testing result and part compares analysis, finds each measuring point deviation corresponding with cad model, thereby obtains the machining accuracy of curved surface to be measured.
Above-mentioned survey radius of a ball compensation, gauge head pretravel error compensation need calculate the direction of normal of curved surface measuring point; For gauge head pretravel error compensation; Also need calculate the pretravel error of gauge head at each measuring point direction of normal, compensation method is to adopt to predict based on the neutral net of RBF (RBF).
The used machine tool error detecting instrument of above-mentioned machine tool error compensation is a laser interferometer.
The deviation that above-mentioned measuring point is corresponding with cad model adopts the computational methods of the minimum range of point to curved surface to find the solution.
It is following that above-mentioned neutral net based on RBF (RBF) is carried out forecast method:
Regularization RBF network is that network is approached in a kind of three layers of feedforward part with single hidden layer, and verified, it and BP network can both approach any continuous function with arbitrary accuracy; And, compare the BP network, its training time is shorter; And it satisfies the approximate error of sample and the flatness of approximating curve simultaneously; In practice, the supervised training of network can be regarded a kind of process of curve match as, utilizes regularization RBF algorithm; Through training, realize the Nonlinear Mapping between the input and output space to network;
Regularization RBF topology of networks is made up of the output layer of a radially basic neuronic latent layer, a linear neuron, and the input point quantity of network is N, and latent number of nodes is P, and output node quantity is l; The latent node number of network equals to import sample number, and all are imported the center that samples are made as RBF, and each RBF is got unified expansion constant;
RBF achieved by the input
to the output
mapping,?
(
) using the radial basis function as either a hidden node activation function, the choice of Gauss function as the radial basis function; W of output power matrix, where
(
;
) for the hidden layer
a node to the output layer
nodes between the synaptic weights; linear activation function as the output layer neurons;
According to regularization RBF Principles of Network, the training process of RBF is: RBF neutral net input and output variable are confirmed in (1), promptly with the detection side to input node as network, corresponding pretravel error is the output node of network; (2) form training set network is trained, be i.e. some groups of teacher's data of picked at random from detected pretravel error information as network; (3) input forecast sample, with the network that trains predict any detection side to the pretravel error, 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 are found the solution is following: curved surface is divided into enough little grid, the calculating measuring point (
x m,
y m,
z m) to the distance of total-grid node, all these minimum value and value are exactly the minimum range of point to curved surface.
The embodiment of the invention is to utilize CNC milling machine that complex-curved workpiece is carried out the high-precision test method; This method is adapted to when CNC milling machine workpiece 11 processed; The workpiece 11 of the embodiment of the invention is a complex curved surface parts; After workpiece 11 is accomplished a manufacturing procedure, directly on the workbench of CNC milling machine, workpiece 11 is detected, realize processing and detecting and all on CNC milling machine, carry out; Can avoid that workpiece 11 is moved to other checkout equipments (like three coordinate measuring machine) and go up the second positioning error that detection brings, also can avoid size and the big workpiece 11 of weight are carried the inconvenience that is brought.Workpiece 11 to be detected in the method for present embodiment directly detects on the workbench of CNC milling machine after machining, and may further comprise the steps:
Step 1: contact is triggered on the main shaft that gauge head 4 is installed in CNC milling machine.The contact that drives main shaft triggers gauge head 4 motions, and contact triggers gauge head 4 and implements the coordinate of tested curved surface 2 is detected, and testing result is recorded in and detects in the software.
Step 2: tested curved surface 2 is detected path planning.Utilize detection software that tested curved surface is carried out points planning and detects path planning.
Step 3: drive CNC milling machine, obtain the coordinate that contact triggers the survey ball center 3 at gauge head 4 and tested curved surface contact point 5 places one by one;
Step 4: above-mentioned survey ball center 3 coordinates are surveyed radius of a ball compensation, contact triggering gauge head 4 pretravel error compensations and machine tool error compensation, thereby obtain the testing result of measuring point high precision;
As shown in Figure 1, the key of surveying radius of a ball compensation is to obtain the direction of normal 1 of measured point, utilizes formula to survey radius of a ball compensation then
(1)
In the following formula, (
X,
Y,
Z) be the coordinate of contact point A, (
x,
y,
z) be the coordinate of surveying the B of ball center,
rBe the survey radius of a ball,
nBe measuring point per unit system vector.
The compensation aspect of gauge head pretravel error 7; As shown in Figure 2; From contact trigger gauge head 4 contact workpiece surfaces to triggering signal produce during this period of time in, contact triggers gauge head 4 additional movements slight distance, the general title because the caused error amount of this section slight distance is a gauge head pretravel error.Need utilize standard ball to detect the pretravel error of gauge head on all directions, and utilize RBF (RBF) algorithm predicts to go out the pretravel error 7 on any direction of normal 1.
Aspect the machine tool error compensation; According to kinematic principle; Object has six-freedom degree along a certain rectilinear motion; Promptly three translation freedoms and three revolution frees degree just have six geometric error components, promptly along the straightness error of three mutual vertical direction with to the rotation error of three mutual vertical direction.The three-axis numerical control milling machine generally all has (X, Y, Z) three orthogonal linear motion axis.Therefore for the three-axis numerical control milling machine, three axles in edge move and co-exist in 18 error components, add between three axles also to have the error of perpendicularity, always have 21 error components.Present embodiment utilizes laser interferometer to measure this 21 error components.
Measuring point method arrow, the pretravel sum of errors machine tool error of above-mentioned acquisition are input in the detection software systems, and the survey ball center coordinate that the numerical control system feedback is returned is compensated.
Present embodiment uses TP6L gauge head system.
Step 5: the desirable cad model of testing result and part is compared analysis, find each measuring point deviation corresponding, thereby obtain the machining accuracy of curved surface to be measured with cad model.
Need carry out points planning (being the arrangement mode of measuring point on curved surface) in the above-mentioned steps two, and calculate the direction of normal 1 of each measuring point, detect path planning then.Said method is vowed to vowing on the curved surface of measuring point place and through the method for said tested point.
Contact triggers gauge head 4 and at the uniform velocity contacts the measuring point on the tested curved surface along direction of normal 1 in the above-mentioned steps three; In this process; Contact triggering gauge head 4 is at a high speed located moving direction 8 to 6 from gauge head along the detection side and is moved to gauge head low speed direction of closing 9; The preparatory contact distance 10 of gauge head utilizes software systems to receive the centre coordinate information that contact triggers gauge head 4 in contact process among the figure.
In the above-mentioned steps four, need utilize standard ball to detect the pretravel error of gauge head on all directions, and utilize RBF (RBF) algorithm predicts to go out the pretravel error on any direction of normal.Utilize laser interferometer measurement to obtain the geometric error of lathe.
Claims (6)
1. the online test method of the surface machining accuracy of complex parts is characterized in that including following steps:
1) contact being triggered gauge head (4) is installed on the main shaft of CNC milling machine;
2) tested curved surface (2) is detected path planning;
3) drive CNC milling machine, obtain the coordinate of the survey ball center (3) at gauge head and curved surface contact point to be measured place 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 installed on the gauge head main body and with tested curved surface directly to contact;
4) coordinate of above-mentioned survey ball center (3) is surveyed radius of a ball compensation, gauge head pretravel error compensation and machine tool error compensation, thereby obtain the testing result of measuring point high precision; Wherein machine tool error need adopt the machine tool error detecting instrument to obtain;
5) the desirable cad model with testing result and part compares analysis, finds each measuring point deviation corresponding with cad model, thereby obtains the machining accuracy of curved surface to be measured.
2. the online test method of the surface machining accuracy of complex parts according to claim 1; It is characterized in that above-mentioned survey radius of a ball compensation, gauge head pretravel error compensation need calculate the direction of normal of curved surface measuring point; For gauge head pretravel error compensation; Also need calculate the pretravel error of gauge head at each measuring point direction of normal, compensation method is to adopt to predict based on the neutral net of RBF (RBF).
3. the online test method of the surface machining accuracy of complex parts according to claim 1 is characterized in that the used machine tool error detecting instrument of above-mentioned machine tool error compensation is a laser interferometer.
4. the online test method of the surface machining accuracy of complex parts according to claim 1 is characterized in that the above-mentioned measuring point deviation corresponding with cad model adopts the computational methods of the minimum range of point to curved surface to find the solution.
5. the online test method of the surface machining accuracy of complex parts according to claim 1, it is following to it is characterized in that above-mentioned neutral net based on RBF (RBF) is carried out forecast method:
Regularization RBF network is that network is approached in a kind of three layers of feedforward part with single hidden layer, and verified, it and BP network can both approach any continuous function with arbitrary accuracy; And, compare the BP network, its training time is shorter; And it satisfies the approximate error of sample and the flatness of approximating curve simultaneously; In practice, the supervised training of network can be regarded a kind of process of curve match as, utilizes regularization RBF algorithm; Through training, realize the Nonlinear Mapping between the input and output space to network;
Regularization RBF topology of networks is made up of the output layer of a radially basic neuronic latent layer, a linear neuron, and the input point quantity of network is N, and latent number of nodes is P, and output node quantity is l; The latent node number of network equals to import sample number, and all are imported the center that samples are made as RBF, and each RBF is got unified expansion constant;
RBF achieved by the input ?
to the output
mapping,?
(
) using the radial basis function as either a hidden node activation function, the choice of Gauss function as the radial basis function; W of output power matrix, where
(
;
) for the hidden layer
nodes to the output layer
between two nodes synaptic weights; linear activation function as the output layer neurons;
According to regularization RBF Principles of Network, the training process of RBF is: RBF neutral net input and output variable are confirmed in (1), promptly with the detection side to input node as network, corresponding pretravel error is the output node of network; (2) form training set network is trained, be i.e. some groups of teacher's data of picked at random from detected pretravel error information as network; (3) input forecast sample, with the network that trains predict any detection side to the pretravel error, with remaining measuring point data as forecast sample.
6. the online test method of the surface machining accuracy of complex parts according to claim 1 is characterized in that the method that the computational methods of the minimum range of above-mentioned point to curved surface find the solution is following: curved surface is divided into enough little grid, calculate measuring point (
x m,
y m,
z m) to the distance of total-grid node, all these minimum value and value are exactly the minimum range of point to curved surface.
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