CN102183205A - Method for matching optimal assembly poses of large-sized parts - Google Patents

Abstract

The invention discloses a measurement data processing method for pose measurement and adjustment in digital assembly of large-sized parts, comprising the following steps: comparing the current pose of a digital theory model matching assembly part according to actually measured data; and calculating actual optimal target assembly poses according to the current pose. The position of each critical characteristic on the part and corresponding detection points of each assembly detection item are measured by using a laser tracking instrument. Measurement data after processed by the method can provide accurate assembly position and pose data and positioning adjustment parameters for a large-sized part digital flexible assemble system, and the optimal assembly effect of parts is achieved by matching real-time measurement.

Description

The method of the best assembling of a kind of large parts pose coupling

Technical field:

The present invention relates to the method for the best assembling pose coupling in a kind of large parts digitizing alignment measurement process.

Background technology:

Measuring auxiliary mounting technology is to realize large product digitizing assembling, one of effective way of control assembly quality and key characteristic, utilize portable large-scale metrology equipment in the product assembling, each part pose to be carried out real-time follow-up, check the position of key feature, to reach the technical requirement of product assembly quality.The accurate adjustment of pose is to guarantee one of focus of product assembly precision with control in the large parts assembling, and especially the effect when parts butt joint, product final assemble is more outstanding.

Assembling pose coupling is a key link of Measurement and Data Processing in the large parts digitizing assembling, being intended to provides the accurate pose data of assembly so that its accurate location for the enforcement of measuring auxiliary mounting technology, and provide optimum target assembling pose to guarantee the assembling accuracy, reach best practical set effect.

On the current pose of assembly and optimum target pose definite, general processing mode is simply to utilize each critical size and form and position tolerance whether to be in the tolerances in design scope to judge, is in fact rough a kind of finding the solution in large component assembling.Therefore, to realize under this mode that high-precision assembly quality still needs to adopt the raising Allowance Design to require to control, this means that the manufacturing accuracy of parts has requirements at the higher level, all not ideal enough on effect and the economy.The present invention proposes finding the solution of can be in the tolerances in design allowed band accurate more object pose of realizing best assembling effect of method, adjusts parameter for the digitizing locating device provides better location.

Summary of the invention:

The objective of the invention is needs, a kind of comparatively desirable pose matching process of proposition at the deficiency and the auxiliary assembling and positioning of large parts digitizing of the general processing mode existence of the data in the assembling pose measurement.

The method of best assembling pose coupling in a kind of large parts assembling, it comprises that current pose coupling of parts and parts optimum target assembling pose mated for 2 stages:

Current pose matching stage comprises following basic step:

1) locus of fixed reference reference point in the mensuration erecting yard;

2) the reference point is fitted to benchmark assembling coordinate system, unify with global coordinate system in the digitizing assembling model;

3) locus of each position reference point on the mensuration removable assembly to be positioned;

4) nominal position of each position reference point in the contrast digitizing assembling model uses current pose matching algorithm to ask for six independent parameters of the current spatial pose of assembly;

Optimum target assembling pose matching stage comprises following basic step:

5) measure on the oriented benchmark assembly position with the corresponding measuring point of each assembling accuracy detection, fit to corresponding geometric element according to the type of reference data geometric element;

6) measure the position of assembling the corresponding measuring point of accuracy detection on the removable assembly to be positioned with each, and measuring point data is transformed under the local parts coordinate system of assembly;

7) each point position of connecting firmly with assembly to be positioned of supposition is along with assembly moves by rule in the certain space scope, the accuracy error of each detection when the calculating assembly is in the series of discrete position and attitude, and calculate the comprehensive overall accuracy Z-factor of multiple goal to the single goal mapping;

8) calculate each individual event accuracy error and overall accuracy Z-factor and whether satisfy the setting requirement, otherwise repeating step 7, until the spatial pose of the removable assembly to be positioned that obtains to meet the demands, this pose is the actual optimum target assembling pose of assembly to be positioned.

The measurement of pose reference point and each detection measuring point all adopts laser tracker to carry out the data acquisition operations on described measurement erecting yard reference point, the parts.Laser tracker is positioned over the field position that can observe each common point and corresponding measuring point.

The step that the reference measurement point is fitted to the frame of reference is: earlier each benchmark measuring point is fitted to reference plane XOY, the projection of selected wherein two somes straight line on XOY plane is as X-direction, selected a bit in the projection of XOY plane as true origin O, determine the basic parameter of match coordinate system thus, and this original match coordinate system is carried out the certain space conversion as overall reference for assembling coordinate system.

The pose of parts can be represented by the locus of this parts coordinate system under overall situation assembling coordinate system, its hexa-atomic group of being made of 6 independent parameters

The expression parts,, rotate around the z axle around y axle rotation θ degree successively around the x of reference frame axle rotation ψ degree from initial pose to current pose

Degree, at last at x, y, each translation p of z direction _x, p _y, p _zObtain, carry out spatial pose and these 6 independent parameter argument tables are shown when calculating 4 * 4 spatial alternation matrix T and participate in computing again, wherein R is the rotation matrix component, and P is a translational component:

$T=\left(\begin{array}{cc}\mathrm{<figure-callout\; id="0"\; label="R\; P"\; filenames="HDA0000049056240000011.png"\; state="\{\{state\}\}">R</figure-callout>}& P\\ 0& 1\end{array}\right)$

$P=\left(\begin{array}{c}{p}_x\\ p_y\\ p_z\end{array}\right)$

Described current pose matching algorithm, the coupling of measuring the locus of parts B under global coordinate system and the nominal position of digitizing master pattern mid point with retrain the form that all is expressed as least square, adopt the model of multiple-objection optimization, constraint distributes weights to a coupling and each, the optimization aim function as:

min{sum(ε _i)}

ε wherein _iThe matching error of representing each pose reference point, represent with the range deviation that physical location of putting and model are in this following nominal position of spatial pose state:

Constraint condition: E _{I_low}＜ε _i＜E _{I_up}, E _{I_low}, E _{I_up}Be each reference point of regulation and the position deviation bound of theoretical value.{ P _I-0Be nominal position point group on the entire assembly model, coordinate figure is with respect to local parts coordinate system, { P _I-1Being location point group on the actual measurement parts, coordinate figure is with respect to assembling coordinate system, T ₁For waiting to ask the parts spatial pose matrix of representing with 6 independent parameters, on this basis, the optimization aim function further is refined as:

min{sum(ε _i)}＝min{sum(P _i-1-T ₁P _i-0)}

Each measuring point name and measured data all are expressed as the form (x, y, z, 1) of homogeneous coordinates ^TParticipate in calculating, the computing formula of each point coupling deviation is:

$\left[\begin{array}{c}{\mathrm{\&epsiv;}}_i\end{array}\right]=\left[\begin{array}{c}{\mathrm{\&epsiv;}}_{\mathrm{ix}}\\ {\mathrm{\&epsiv;}}_{\mathrm{iy}}\\ {\mathrm{\&epsiv;}}_{\mathrm{iz}}\\ 0\end{array}\right]=\left[\begin{array}{c}{x}_{i-1}\\ y_{i-1}\\ z_{i-1}\\ 1\end{array}\right]-T_1\left[\begin{array}{c}{x}_{i-0}\\ y_{i-0}\\ z_{i-0}\\ 1\end{array}\right]$

Described current pose matching algorithm uses heuristic particle cluster algorithm to realize finding the solution, and on behalf of a possible spatial pose, each particle separate, 6 dimension x of particle _i=(x _I1, x _I2..., x _ID) respectively expression determine 6 independent parameter amounts of pose

Each particle i is included as the position vector x of a D dimension _i=(x _I1, x _I2..., x _ID) and velocity vector v _i=(v _I1, v _I2..., v _ID), during particle i search solution space, preserve its optimum that searches experience position p _i=(p _I1, p _I2..., p _ID), at the beginning of each iteration, according to self inertia and the optimum experience of experience and colony position p _g=(p _G1, p _G2..., p _GD) adjust oneself velocity vector to adjust self-position, until the optimum solution that obtains to satisfy condition.R is to position renewal the time, and a coefficient in that speed adds previously is constraint factor.c ₁, c ₂For positive constant, be referred to as speedup factor.ξ, η is for all there being the random number of distribution in [0 1].W is the inertia weight factor.

Each particle position changes and is undertaken by following formula:

x _id＝x _id+rv _id

v _id＝wv _id+c ₁ξ(p _id-x _id)+c ₂η(p _gd-x _id)

D is the dimension in the D dimension in the formula, and this value is 6 in the pose coupling.

Described optimum target assembling pose matching stage, each assembles the accuracy detection and comprises general size, form and position tolerance and the detection content that is provided with by special matching requirements.Wherein must earlier the reference measurement data be fitted to the standard basis geometric element by the least square rule, comprise three types of point, line, surface the detection that has reference to require.

Described optimum target assembling pose matching stage, basic procedure is will respectively to detect corner group coordinate figure { P on the removable parts to be positioned earlier _kBe transformed into { P under the local coordinate system of parts from global coordinate system _KL, these measuring points that convert then move to global position coordinate figure { P different pose state T under by rule with these parts in the space _KS, then in conjunction with benchmark measuring point group numerical value { P _KDThese parts be in the space this detection assessment result that may assemble under the pose state predict that its computing formula is:

ε _I-k＝f _I-k(P _kD，P _kS)

f _I-kFor calculating the function universal expression form of detection numerical result, determine by type of detection.The accuracy error of each detection when calculating parts to be positioned and being in the series of discrete position, and calculate the comprehensive overall accuracy accuracy error of multiple goal to the single goal mapping, find the spatial pose Ta of overall accuracy accuracy error minimum to assemble pose as optimum target.

Described best assembling pose matching process, algorithm model is for all being expressed as the matching constraint of positioning reference parts and parts assembling accuracy detection of each key characteristic under global coordinate system to be positioned the form of detection deviate, adopt the Optimization Model of multiple goal, each detection coupling and each constraint are distributed weights W to the unified mapping of single goal _kAfter ask the weighted comprehensive deviation,, the optimization aim function as:

$\min \left\{E\right\}=\min \{\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k{\mathrm{\&epsiv;}}_k/\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k\}$

$=\min \{\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k{f}_k(P_{\mathrm{kD}},P_{\mathrm{kS}})/\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k\}$

$=\min \{\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k{f}_k(P_{\mathrm{kD}},{\mathrm{TT}}_1^{-1}{P}_k)/\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k\}$

Constraint condition: E _{K_low}＜ε _I-k＜E _{K_up}Be each matching requirements detection normal value bound,

ε wherein _kThe matching error of representing k item assembling detection, T ₁Result of calculation for the rapid current pose matching stage of previous step.The assign weight method of suing for peace behind the coefficient of employing is transformed into the value that belongs under the same dimension with all kinds of deviations and compares differentiating the size of whole synthesis assembling accuracy precision, and synthesis precision is high more, and then to be considered as the assembly quality effect good more.

Described optimum target assembling pose matching algorithm equally with current pose matching algorithm uses heuristic particle cluster algorithm to realize finding the solution, and difference is that the parameters of bounding algorithm rule is provided with different.

The invention has the advantages that: the flow process and the data processing method that 1) provide detailed large parts to assemble pose measurement; 2) finding the solution of can be in the tolerances in design allowed band accurate more object pose of realizing best assembling effect adjusted parameter for the digitizing locating device provides better location; 3) by once or the data of minority pose measurement just can get access to comparatively ideal pose and adjust data, make assembling reach the effect of actual the best;

Description of drawings

Fig. 1 is the current pose matching algorithm flow process according to embodiment of the present invention;

Fig. 2 is the optimum target assembling pose matching algorithm flow process according to embodiment of the present invention;

Fig. 3 is the scene according to the invention process large parts alignment measurement example;

Fig. 4 is that the corresponding with it measurement of correlation point of cylindrical compartment section parts 1 to be positioned among the embodiment distributes;

Fig. 5 is the corresponding with it relevant measuring point distribution plan of oriented middle part interface frame, mating frame parts 3 among the embodiment;

Fig. 6 is the corresponding with it relevant measuring point distribution plan of oriented conical section parts 2 among the embodiment;

Among the figure: cylindrical compartment section parts 1, circular cone cabin section parts 2, interface frame, mating frame 3, supporting tool 4, laser tracker 5, cylindrical compartment fragment position hole measuring point group 6, cylindrical compartment section and circular cone cabin section interface depth of parallelism measuring point group 7, cylindrical compartment section and circular cone cabin section outside surface right alignment measuring point group 8, assembling coordinate system benchmark measuring point group 9.

Embodiment:

The method of best assembling pose coupling in the large parts assembling, it comprises that current pose coupling of parts and parts optimum target assembling pose mated for 2 stages:

Current pose matching stage comprises following basic step:

1) locus of fixed reference reference point in the mensuration erecting yard;

2) the reference point is fitted to benchmark assembling coordinate system, unify with global coordinate system in the digitizing assembling model;

3) locus of each position reference point on the mensuration removable assembly to be positioned;

4) nominal position of each position reference point in the contrast digitizing assembling model uses current pose matching algorithm to ask for six independent parameters of the current spatial pose of assembly;

Optimum target assembling pose matching stage comprises following basic step:

5) measure on the oriented benchmark assembly position with the corresponding measuring point of each assembling accuracy detection, fit to corresponding geometric element according to the type of reference data geometric element;

6) measure the position of assembling the corresponding measuring point of accuracy detection on the removable assembly to be positioned with each, and measuring point data is transformed under the local parts coordinate system of assembly;

7) each point position of connecting firmly with assembly to be positioned of supposition is along with assembly moves by rule in the certain space scope, the accuracy error of each detection when the calculating assembly is in the series of discrete position and attitude, and calculate the comprehensive overall accuracy Z-factor of multiple goal to the single goal mapping;

8) calculate each individual event accuracy error and overall accuracy Z-factor and whether satisfy the setting requirement, otherwise repeating step 7, until the spatial pose of the removable assembly to be positioned that obtains to meet the demands, this pose is the actual optimum target assembling pose of assembly to be positioned.

At first with reference to figure 3 Fig. 5, disclosure example relates to and is used for method and the process that large parts digitizing assembling establishing criteria model and measured data are carried out the pose coupling.As used herein, term " part ", " parts ", " assembly " are intended to comprise the assembly of independent part, the assembling of a plurality of part.In an illustrated embodiment, parts comprise the big assembly that is used to build aircraft, and this method and process can be used to and be applicable to the part assemblies of various other types of widespread adoption.

As shown in Figure 3, the Measurement and Data Processing system at the large parts digitizing flexible assembly scene that one embodiment of the present of invention are used for the best assembling pose matching process that proposes according to the present invention, the robotization that this conjunction measuring system of system, posture adjustment control system and digitizing locating device are finished a plurality of parts is located and is docked.The situation of the butt joint of 2 large-scale cabin sections in certain the satellite agent structure that relates among the embodiment, cabin section 1 is cylindrical, and cabin section 2 is conical, and the cabin is intersegmental realizes being located by connecting by interface frame, mating frame 3, before being connected and fixed, need each cabin section is navigated under the desirable assembling pose state.Its middle deck section 2 has supported and has navigated on the frock, and cabin section 1 need be carried out pose measurement and is located by connecting on the interface frame, mating frame 3 that fixedly mounts cabin section 1 by optimum target assembling pose.

The measurement of pose reference point and each detection measuring point all adopts laser tracker to measure on described measurement erecting yard reference point, the parts.For guaranteeing measuring accuracy, adopt the scheme of many laser tracker combined measurements, each instrument is installed on the field position that should be able to observe each common point and corresponding measuring point mutually by measuring programme.Laser tracker adopts Switzerland Leica LTD640 laser tracker in the example, and the measurement radius of this instrument can reach 40m, and resolution is 0.001mm, and measuring accuracy can reach 15 μ+5 μ/m in the total travel scope.

The step that in the example reference measurement point is fitted to the frame of reference is: 4 fixed reference measuring points (some group 9) on the frock are fitted to reference plane XOY, the projection of selected wherein adjacent 2 somes straight line on XOY plane is as X-direction, selected wherein 1 projection in XOY plane is as true origin O, determine the basic parameter of match coordinate system thus, and this original match coordinate system is carried out spatial alternation arrive this four point geometry center as overall reference for assembling coordinate system O-XYZ, all raw measurement datas are all unified to be transformed into based under this overall situation assembling coordinate system, and assemble aliging of coordinate system in realization and the digitizing master pattern.

Set up global coordinate system, will make measuring system, pose adjust software systems, servo-control system and digital detent mechanism and under unified assembling coordinate system, work exactly, make the data of transmitting each other under same coordinate system.Each steady arm of control system cooperative motion under unified coordinate system is realized the adjustment of stressless large parts attitude.

The pose of parts 1 can be represented by the locus of this parts rigid body coordinate system under overall situation assembling coordinate system, its hexa-atomic group of being made of 6 independent parameters

Form, the expression parts,, rotate around the z axle around y axle rotation θ degree successively around the x of reference frame axle rotation ψ degree from initial pose to current pose

Degree, at last at x, y, each translation p of z direction _x, p _y, p _zObtain.

Carry out spatial pose coupling and these 6 independent parameter argument tables are shown when calculating 4 * 4 spatial alternation matrix T and participate in computing again, wherein R is the rotation matrix component, and P is a translational component, and expression formula is as follows:

$T=\left(\begin{array}{cc}\mathrm{<figure-callout\; id="0"\; label="R\; P"\; filenames="HDA0000049056240000011.png"\; state="\{\{state\}\}">R</figure-callout>}& P\\ 0& 1\end{array}\right),$

$P=\left(\begin{array}{c}{p}_x\\ p_y\\ p_z\end{array}\right),$

Described current pose matching algorithm, the coupling of measuring the nominal position of each reference point (some group 6) in the locus of parts 2 under global coordinate system and the digitizing master pattern with retrain the form that all is expressed as least square, adopt the model of multiple-objection optimization, constraint distributes weights to a coupling and each, the optimization aim function as:

min{sum(ε _i)}

ε wherein _iThe matching error of representing each pose reference point, represent with the range deviation that physical location of putting and model are in this following nominal position of spatial pose state:

Constraint condition: E _{I_low}＜ε _i＜E _{I_up}, E _{I_low}, E _{I_up}Be each reference point of regulation and the position deviation bound of theoretical value.

Among the embodiment, { P _I-0Be nominal position point group on the model, coordinate figure is with respect to local parts coordinate system, { P _I-1Being location point group on the actual measurement parts 1, coordinate figure is with respect to assembling coordinate system, T ₁For waiting to ask the parts spatial pose of representing with 6 independent parameters.On this basis, the optimization aim function further is refined as:

min{sum(ε _i)}＝min{sum(P _i-1-T ₁P _i-0)}

Each measuring point name and measured data all are expressed as the form (x, y, z, 1) of homogeneous coordinates ^TParticipate in calculating, the computing formula of each pose reference point coupling deviation is:

$\left[\begin{array}{c}{\mathrm{\&epsiv;}}_i\end{array}\right]=\left[\begin{array}{c}{\mathrm{\&epsiv;}}_{\mathrm{ix}}\\ {\mathrm{\&epsiv;}}_{\mathrm{iy}}\\ {\mathrm{\&epsiv;}}_{\mathrm{iz}}\\ 0\end{array}\right]=\left[\begin{array}{c}{x}_{i-1}\\ y_{i-1}\\ z_{i-1}\\ 1\end{array}\right]-T_1\left[\begin{array}{c}{x}_{i-0}\\ y_{i-0}\\ z_{i-0}\\ 1\end{array}\right]$

Described current pose matching algorithm uses heuristic particle cluster algorithm to realize finding the solution, and on behalf of a possible spatial pose, each particle separate, 6 dimension x of particle _i=(x _I1, x _I2..., x _ID) respectively expression determine 6 independent parameter amounts of pose Each particle i is included as the position vector x of a D dimension _i=(x _I1, x _I2..., x _ID) and velocity vector v _i=(v _I1, v _I2..., v _ID), during particle i search solution space, preserve its optimum that searches experience position p _i=(p _I1, p _I2..., p _ID), at the beginning of each iteration, according to self inertia and the optimum experience of experience and colony position p _g=(p _G1, p _G2..., p _GD) adjust oneself velocity vector to adjust self-position, until the optimum solution that obtains to satisfy condition.R is to position renewal the time, and a coefficient in that speed adds previously is constraint factor.c ₁, c ₂For positive constant, be referred to as speedup factor.ξ, η is for all there being the random number of distribution in [0 1].W is the inertia weight factor.

Each particle position changes and is undertaken by following formula:

x _id＝x _id+rv _id，

x _id＝wv _id+c ₁ξ(p _id-x _id)+c ₂η(p _gd-x _id)，

D is the dimension in the D dimension in the formula, and this value is 6 in the pose coupling.

Among the described embodiment, by using optimum target assembling pose matching process of the present invention, the utilization particle cluster algorithm carries out current pose matching algorithm and finds the solution, through after about 450 iteration, fitness function is restrained fully, the average coupling deviation for each position reference point of result of calculation is 0.108mm, and maximum deviation is 0.159mm; Adhere to specification.

Described optimum target assembling pose matching stage, each assembles the accuracy detection and comprises: size, Geometrical Tolerance Principle reach by the accurate requirement of special assembling.Form and position tolerance comprises form tolerance and position of related features two big classes, position of related features need be considered the reference element requirement, wherein must earlier the reference measurement data be fitted to the standard basis geometric element by the least square rule, comprise three types of point, line, surface the detection reference.

Described optimum target assembling pose matching stage, basic procedure is will respectively to detect corner group coordinate figure { P on the parts 1 to be positioned earlier _kBe transformed into { P under the local coordinate system of parts from global coordinate system _KL, these measuring points that convert then move to global position coordinate figure { P different pose state T under by rule with parts 1 in the space _KS, then in conjunction with benchmark measuring point group numerical value { P _KDCalculate parts 1 and be in the space this detection assessment result that may assemble under the pose state and predict that its computing formula is:

ε _I-k＝f _I-k(P _kD，P _kS)

f _I-kFor calculating the function universal expression form of detection numerical result, determine by type of detection.The accuracy error of each detection when calculating assembling parts 1 are in the series of discrete position, and calculate the comprehensive overall accuracy accuracy error coefficient of multiple goal to the single goal mapping, find the spatial pose Ta of overall accuracy accuracy error coefficient minimum to assemble pose by rule as optimum target.

Shown in Figure 6 as Fig. 4, assembling accuracy detection comprises among the described embodiment: the depth of parallelism of cylindrical compartment section 1 and butt end frame 3 interfaces, circular cone cabin section 2 and cylindrical compartment section 1 outside surface right alignment, the position degree of a plurality of location holes on the cylindrical compartment section 1.Wherein the corresponding measuring point of depth of parallelism detection is the some group 7 that is distributed on the interface; The corresponding measuring point of right alignment detection is some group 8; Each location hole measuring point is the some group 6 of each center, hole on the cylindrical compartment section 1.

Described best assembling pose matching process, algorithm model is for all being expressed as the matching constraint of positioning reference parts and parts assembling accuracy detection of each key characteristic under global coordinate system to be positioned the form of detection deviate, adopt the Optimization Model of multiple goal, each detection coupling and each constraint are distributed weights W to the unified mapping of single goal _kAfter ask the weighted comprehensive deviation, the optimization aim function as:

$\min \left\{E\right\}=\min \{\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k{\mathrm{\&epsiv;}}_k/\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k\}$

$=\min \{\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k{f}_k(P_{\mathrm{kD}},P_{\mathrm{kS}})/\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k\}$

$=\min \{\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k{f}_k(P_{\mathrm{kD}},{\mathrm{TT}}_1^{-1}{P}_k)/\underset{k=1}{\overset{m}{\mathrm{\&Sigma;}}}{W}_k\},$

Constraint condition: E _{K_low}＜ε _I-k＜E _{K_up}Be each matching requirements detection normal value bound,

ε wherein _kThe matching error of representing k item assembling detection, T ₁Result of calculation for current pose matching stage.The assign weight method of suing for peace behind the coefficient of employing is transformed into the value that belongs under the same dimension with all kinds of deviations and compares differentiating the size of whole synthesis assembling accuracy precision, and synthesis precision is high more, and then to be considered as the assembly quality effect good more.

Among the described embodiment, by using optimum target assembling pose matching process of the present invention, the utilization particle cluster algorithm carries out optimum target assembling pose matching algorithm and finds the solution, through after about 500 iteration, fitness function is restrained fully, matching result and digitizing master pattern name pose side-play amount are [0.009mm, 0.03mm, 0.0mm ,-0.002rad ,-0.004rad,-0.002rad], this shows that detect to require the actual optimum target assembling pose asked for the measured data of assembling parts very approaching with the nominal value of standard digital model according to assembling, this illustrates the validity of matching algorithm.After 1 realization is located to the cabin section according to this optimum target assembling pose, each accuracy error that assembles the accuracy matching result is respectively: parallel misalignment is 0.156mm between interface, the mean place degree deviation of each location hole is 0.184mm, two cabin section appearance coaxiality deviations are 0.129mm, adhere to specification the validity of this explanation matching algorithm.

Claims (8)

1. the method for best assembling pose coupling during a large parts assembles, it comprises that current pose coupling of parts and parts optimum target assembling pose mated for 2 stages:

Current pose matching stage comprises following basic step:

1) locus of fixed reference reference point in the mensuration erecting yard;

2) the reference point is fitted to benchmark assembling coordinate system, unify with global coordinate system in the digitizing assembling model;

3) locus of each position reference point on the mensuration removable assembly to be positioned;

4) nominal position of each position reference point in the contrast digitizing assembling model uses current pose matching algorithm to ask for six independent parameters of the current spatial pose of assembly;

Optimum target assembling pose matching stage comprises following basic step:

5) measure on the oriented benchmark assembly position with the corresponding measuring point of each assembling accuracy detection, fit to corresponding geometric element according to the type of reference data geometric element;

6) measure the position of assembling the corresponding measuring point of accuracy detection on the removable assembly to be positioned with each, and measuring point data is transformed under the local parts coordinate system of assembly;

7) each point position of connecting firmly with assembly to be positioned of supposition is along with assembly moves by rule in the certain space scope, the accuracy error of each detection when the calculating assembly is in the series of discrete position and attitude, and calculate the comprehensive overall accuracy Z-factor of multiple goal to the single goal mapping;

8) calculate each individual event accuracy error and overall accuracy Z-factor and whether satisfy the setting requirement, otherwise repeating step 7, until the spatial pose of the removable assembly to be positioned that obtains to meet the demands, this pose is the actual optimum target assembling pose of assembly to be positioned.

2. best assembling pose matching process according to claim 1 is characterized in that actual measurement data and digitizing standard assembling model are mated calculating, obtains the pose process of parts under global coordinate system:

The parts pose can be represented with the hexa-atomic group of v that rotation matrix and translation vector constitute The expression parts,, rotate around the z axle around y axle rotation θ degree successively around the x of reference frame axle rotation ψ degree from initial pose to current pose

Degree, at last at x, y, each translation p of z direction _x, p _y, p _zObtain, spatial pose 6 independent parameters thus is that basic variable is expressed as 4 * 4 spatial alternation matrix T:

Wherein, R represents the rotation matrix component, and P represents translation vector, and with T presentation-entity spatial pose the time, the each point coordinate figure all is transformed into and participates in data operation behind the homogeneous form and handle, coordinate promptly by originally (x, y, z) ^TForm increases one dimension and becomes (x, y, z, 1) ^TFormal representation.

3. best assembling pose matching process according to claim 1, current pose matching stage, it is characterized in that the spatial pose of measurement parts to be positioned under global coordinate system all is expressed as the form of least square with reference to the coupling of the nominal position of eyeball and digitizing master pattern mid point and constraint, the optimization aim function as:

min{sum(ε _i)}，

ε wherein _iThe matching error of expression each point, represent with the range deviation that physical location of putting and model are in the following nominal position of spatial pose state undetermined:

Constraint condition: E _{I_low}＜ε _i＜E _{I_up}, E _{I_low}, E _{I_up}Be each reference point of regulation and the position deviation bound of theoretical value.

4. best assembling pose matching process according to claim 1, current pose matching stage is characterized in that eyeball and name point two groups of data computing processing procedures, wherein { P _I-0Be nominal position point group on the entire assembly model to be measured, coordinate figure is with respect to local parts coordinate system, { P _I-1Be eyeball group in position on the UUT, coordinate figure is with respect to assembling coordinate system, T ₁For waiting to ask the parts spatial pose of representing with 6 independent parameters to be measured.On this basis, the optimization aim function further is refined as:

min{sum(ε _i)}＝min{sum(P _i-1-T ₁P _i-0)}。

5. best assembling pose matching process according to claim 1, it is characterized in that using particle cluster algorithm to realize that current pose mates the calculating of mating with optimum target assembling pose and finds the solution, wherein each particle represents one of the parts spatial pose to separate, and it has 6 dimension x _i=(x _I1, x _I2..., x _ID) respectively representative show 6 independent variables of spatial pose

6. best assembling pose matching process according to claim 1, optimum target assembling pose matching stage is characterized in that the assembling accuracy detection constraint that relates to optimum target assembling pose comprises general dimensional tolerence, form and position tolerance and the special detection item type of formulating according to the product matching requirements.

7. best assembling pose matching process according to claim 1, optimum target assembling pose matching stage is characterized in that earlier each detection point coordinate value { P on the removable parts to be positioned _kBe transformed into { P under the local coordinate system of parts from global coordinate system _KL, calculate these measuring points then and in the space, move to global position coordinate figure { P under the different pose state T by rule with these parts _KS, then in conjunction with benchmark measuring point group numerical value { P _KDCalculate parts and be in that each may assemble the detection assessment result under the pose state in the space, its computing formula is:

ε _I-k＝f _I-k(P _kD，P _kS)，

f _I-kFor calculating the function of detection numerical result, determine by type of detection.

8. best assembling pose matching process according to claim 1, optimum target assembling pose matching stage, it is characterized in that the matching constraint of positioning reference parts and the removable parts to be positioned assembling accuracy detection of each key characteristic under global coordinate system all is expressed as the form of detection deviate, adopt the Optimization Model of multiple goal, each detection coupling and each constraint are distributed weights W to the unified mapping of single goal _kAfter ask the weighted comprehensive deviation, the optimization aim function as:

Constraint condition: E _{K_low}＜ε _I-k＜E _{K_up is}Each matching requirements detection normal value bound,

ε wherein _kThe matching error of representing k item assembling detection, T ₁Result of calculation for current pose matching stage.

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