CN115891168A - A continuous 3D printing method for long trusses based on laser ranging feedback control - Google Patents

Abstract

The invention discloses a long truss continuous 3D printing method based on laser ranging feedback control. In the process of continuous 3D printing of long trusses, firstly, the 3D model of the current layer is extracted. When the 3D printing head drives the laser ranging sensor in the overall movement process Among them, the laser sensor collects the distance measurement data of the printed model in real time, and combines it with the axis position to form point cloud data, and then performs feature recognition on the measurement data and compares it with the current layer 3D model features to obtain the compensation control of the 3D model Finally, through multi-axis collaborative control, adaptive compensation control in the entire printing process is realized; the present invention designs a continuous 3D printing method for long trusses based on laser ranging feedback adaptive compensation control, which can replace staff monitoring 3D In the printing process, whether the printed matter is abnormal or not and the self-adaptive compensation control is performed on the printed matter, thereby saving printing materials and improving printing efficiency.

Description

A continuous 3D printing method for long trusses based on laser ranging feedback control

technical field

The invention belongs to the technical field of 3D printing state detection and compensation control, and in particular relates to a continuous 3D printing method for long trusses based on laser ranging feedback control.

Background technique

3D printing technology has been applied to aerospace on-orbit manufacturing in recent years. By carrying 3D printing raw materials and 3D printers, on-orbit maintenance tools, parts and related structural parts can be printed on-orbit according to actual needs, and in-orbit zero-gravity environment This enables super-long prints to be designed without support, without having to consider the impact of gravity. However, it takes a long time to print super-long parts, and there may be abnormalities or printing failures in the middle, such as broken printing filaments, insufficient filament feeding due to insufficient extrusion wheel pressure, and extrusion due to nozzle wear. Uneven output or unreasonable motion parameter setting will lead to problems such as deviation of print size and breakage of prints. These problems seriously affect the entire printing efficiency or serious waste of filaments.

The present invention proposes a solution to this kind of problem. By combining the laser ranging data at the same time and the current X and Y axis stepping motor positions to form point cloud data, and performing pose coordinate conversion, it can be compared with the slice model printed on the current layer. Identify the characteristics and status of the data, and finally calculate the difference between the current layer print and the slice model, and identify whether the current print is normal. If it is abnormal, perform compensation control according to the difference or judge that the print has failed and stop protection. Compensation control is performed on each movement axis within the allowable range of deviation. Therefore, a continuous 3D printing method for long trusses based on laser ranging feedback adaptive compensation control is proposed.

Contents of the invention

In view of this, the present invention provides a continuous 3D printing method for long trusses based on laser ranging feedback control to self-adaptively compensate the printed parts in real time to avoid printing abnormalities or printing failures, including:

Step 1, obtain the source point cloud data set P _s at the installation position of the laser sensor, and obtain the 3D model target point cloud data set P _t of the current printing layer;

Step 2, obtaining the second source point cloud data set p _snew by performing preprocessing and coordinate transformation on the laser ranging and Z-axis motor position data in the source point cloud data set P _s ;

Step 3, extracting the corresponding coordinate point cloud data of the target point cloud data set P _t , and recomposing the second target point cloud data set p _tnew of the corresponding line segment;

Step 4: Fit the second source point cloud data set p _snew and the second target point cloud data set p _tnew respectively to obtain a line segment set l _s ={l _s0 ,l _s1 ,.. ..,l _sm }, line segment set l _t ＝{l _t0 ,l _t1 ,....,l _tm }; compare whether the eigenvalue difference of each line segment is within the set threshold ∈ range, and judge the position of the current printing part Whether the attitude deviation is within the range of control compensation, and obtain the compensable control state word set s _k ={s _k0 ,s _k1 ,....,s _km };

Step 5, according to the state word set _sk , perform matching point calculation on the point cloud data in the line segment corresponding to the second source point cloud data set p _snew and the second point target cloud data set p _tnew , and obtain the line segment set deviation Square sum set ε _l , and generate compensation control quantity γ _b ＝{γ _b0 ,γ _b1 ,...,γ _bm } according to threshold ε _j ;

Step 6, calculating the compensation control quantity δ _b of each motion axis according to the compensation control quantity γ _b .

In particular, step 1 includes:

Step 1-1, based on the laser sensor data at the same moment and the current X, Y, Z axis motor position data to form the source point cloud data set P _s at the installation position of the laser sensor; where Δt is established according to the current slice data coordinate axis of the scale, generate the combined data P _si =(t _i , x _si , y _si , z _si , l _si ) at time t _i , and combine it into the source point cloud data set P _s ={P _s0 , P _s1 ,...,P _sn }; where l _si represents the eigenvalue of the line segment in the combined data of the current slice, which is the laser sensor data at time t _i ; x _si , y _si , z _si represent three-dimensional coordinates;

Step 1-2, according to the Δt, extract P _ti =(t _i , x _ti , y _ti , z _ti ) corresponding to the current slice data, and combine it into a 3D model target point cloud data set P _t = {P _t0 ,P _t1 ,...,P _tn }.

In particular, said step 2 includes:

Step 2-1, set the preprocessing threshold ε _p , and perform preprocessing on the source point cloud data set P _s corresponding to P _si = (t _i , x _si , y _si , z _si , l _si ) at time t _i , according to the formula

Clear the data outside the range of the threshold ε _p to generate the preprocessed source point cloud data set P′ _s ;

Step 2-2, for the preprocessed source point cloud data set P′ _s , perform coordinate conversion according to the installation position of the laser sensor and the installation position of the print head, the relationship between the two is:

In the above formula (Δδ _x , Δδ _y , θ _z ) is the installation pose of the laser sensor relative to the print head, and recalculated to obtain the second source point cloud data set p _snew ={p _s0 ,p _s1 ,... , p _sn }.

In particular, the step 3 includes:

Step 3-1, eliminate the invalid point data outside the threshold range at time _{t i} in the corresponding preprocessed source point cloud data set P′ _s in the current layer slice model data set P _t , and recompose the second target point cloud data Set p _tnew = {p _t0 , p _t1 , . . . , p _tn }.

In particular, step 4 includes:

Step 4-1, for the second source point cloud data set p _snew , according to the step 2-1, the continuous points in the preprocessed source point cloud data set P' _s form a new Line segment set d _s ={d _s0 ,d _s1 ,...,d _sm }, the continuous points in the second target point cloud data set p _tnew form a new line segment set d _t ={d _t0 ,d _t1 ,...,d _tm };

Step 4-2, according to the characteristics of the target printing model, establish f(y _i )=k _i x _i + _bi fitting function through the i-th segment of the line segment set d _s , and pass the loss function J(k _i ,b _i ) Calculate the partial derivatives for ki _{and bi} respectively, let the partial derivatives be 0 and deduce the corresponding _ki and _bi , that is, l _si =( _ki ,bi ₎ , and form a line segment set l _s ={l _s0 , l _s1 ,....,l _sm };

Step 4-3, according to the step 4-2, the second target point cloud data set p _tnew of the 3D model of the current printing layer is also fitted with the linear least squares method l _t = {l _t0 , l _t1 , ....,l _tm };

Step 4-4, set the effective threshold of the line segment feature value ∈=(∈ _k , ∈ _b ), compare the line segment set l _s and l _t , and judge whether the pose deviation of the current printing part is within the controllable compensation range, and obtain Get the compensable control state word set s _k ={s _k0 ,s _k1 ,....,s _km }.

In particular, step 5 includes:

Step 5-1, according to the state word set s _k , select the line segment that needs to be calculated for matching points;

Step 5-2, calculate the sum of squared deviations ε _li of each axis for the corresponding point data of l _si in the line segment set l _s and l _ti of the line segment set l _t , namely:

Obtain the square root set ε _l ={ε _l0 ,ε _l1 ,...,ε _lm } of the deviation sum of the squares of the line segment set; and generate the compensation coefficient μ _l =max(ε _l );

Step 5-3, according to the compensation coefficient μ _l , calculate the compensation control quantity γ _b ={γ _b0 ,γ _b1 ,...,γ _bm } of the concentrated point of the line segment, where:

Particularly, wherein said step 6 includes:

Step 6-1, through the compensation control quantity γ _bk ={σ _xk ,σ _yk ,σ _zk } at time k, calculate the compensation control quantity δ _bk of each motion axis at the corresponding time:

δ _bk (x,y,z)=(σ _xk x _tk ,σ _yk y _tk ,σ _zk z _tk )

Among them (x _tk , y _tk , z _tk ) are the print trajectory coordinates of the next slice 3D model corresponding to time k; for the x, y axis, the compensated x, y axis coordinate data (x' _tk , y ' _tk ):

(x' _tk ,y' _tk )=((1+σ _xk )x _tk ,(1+σ _yk )y _tk )

Step 6-2, since the movement of the z-axis is realized through the combined movement of the A, B, C and z-axis, when the entire printing is in the normal printing section, that is, when the hand is not changed, the A, B, and C axes are in a fixed state. Set the z-axis compensation control amount δ _b (z):

When the printing is in the hand-changing operation section, the A and C axes are pressed, and the B axis is lifted. At this time, the z axis moves in the z _min direction to realize the z axis back to zero; then the B axis is pressed, and the A and C are lifted. At this time, the z-axis can move in the z _max direction and enter the normal printing stage. During this process, the z-axis compensation control amount δ _b (z):

Among them, d _bz is the z-axis distance of a single normal printing, h _z is the return clearance on the z-axis; that is, the compensated z-axis coordinate data z' _tk : z' _tk =z _tk +δ _b (z).

Beneficial effect:

1) Through the present invention, it can replace the staff to monitor whether the printed parts are abnormal during the 3D printing process and perform adaptive compensation control on the printed parts, thereby saving printing materials and improving printing efficiency;

2) Through the present invention, the current state of 3D printing can be accurately grasped according to the real-time acquisition of the source point cloud data set at the installation position of the laser sensor and the acquisition of the 3D model target point cloud data set of the current printing layer;

3) by the present invention, by the preprocessing to source point cloud data set and the elimination of invalid points in source point cloud data set and target data set, improved detection efficiency;

4) Through the present invention, according to the characteristics of the target printing model, the pose deviation of the current printing part is determined by least squares fitting, which improves the accuracy of detection;

5) Through the present invention, the compensation control amount of each motion axis at the corresponding time is calculated through the compensation control amount at a certain moment, and different compensation methods are performed for different coordinate axes, thereby ensuring the printing quality to the maximum extent.

Description of drawings

Fig. 1 is the schematic flow chart of method in the embodiment of the present invention;

Fig. 2 is a schematic flowchart of a method for identifying abnormal shapes of 3D printing models provided by the present invention.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings and examples.

The present invention provides a long truss continuous 3D printing method based on laser ranging feedback control. The specific steps of the method include:

Step 1: Based on the laser sensor data at the same time and the current X, Y, and Z axis motor position data, the source point cloud data set P _s at the laser sensor installation position is combined, and at the same time, the 3D data of the current printing layer is obtained based on the single-chip storage model slice data. Model target point cloud dataset P _t ;

Among them, step 1 specifically includes:

Step 1-1, according to the current slice data, establish the coordinate axis with Δt as the time scale, generate the combined data P _si =(t _i ,x _si ,y _si ,z _si ,l _si ) at time t _i , and combine them into Source point cloud data set P _s at the laser sensor installation position = {P _s0 , P _s1 ,...,P _sn };

Step 1-2, according to Δt in step 1-1, extract P _ti =(t _i , x _ti , y _ti , z _ti ) corresponding to the current slice data, and combine it into the 3D model target point cloud data set of the current printing layer P _t == {P _t0 ,P _t1 ,...,P _tn };

Step 2, by preprocessing the laser ranging and Z-axis motor position data in the source point cloud dataset P _s , filtering out invalid data and recomposing multiple line segment point cloud datasets P′ _s ={P _s0 ,P _s1 ,...,P _sn }, while rotating and translating p _s based on the installation position of the laser sensor, to obtain the second source point cloud data set p _snew ={p _s0 ,p _s1 ,...,p _sn };

Among them, step 2 specifically includes:

Step 2-1, set the preprocessing threshold ε _p , and perform preprocessing on the source point cloud data set P _s corresponding to time t _i at P _{si =} (t _i , x _si , y _si , z _si , l _si ). Filter out if outside the threshold range:

Where l _si represents the eigenvalue of the line segment in the combined data of the current slice, which is the laser sensor data at time t _i ; x _si , y _si , z _si represent three-dimensional coordinates;

According to the above steps, the data at each moment are preprocessed, and a new point cloud data set P' _s is generated.

Step 2-2, perform coordinate conversion on the installation position of the laser sensor and the installation position of the print head, the relationship between the two is:

In the above formula (Δδ _x ,Δδ _y ,θ _z ) is the installation pose of the laser sensor relative to the print head, and recalculate the new p _snew ={p _s0 ,p _s1 ,...,p _sn };

Step 3, extract the corresponding coordinate point cloud data of the slice model data set P _t of the current layer, and recompose the second point cloud data set p _tnew ={p _t0 , p _t1 ,..., p _tn } of the corresponding line segment;

Wherein, said step 3 includes:

Step 3-1: Eliminate invalid point data in the current layer slice model data set P _t that is outside the threshold range at time t _i corresponding to P′ _s , and recompose a new second point cloud data set p _tnew ={p _t0 ,p _t1 ,...,p _tn };

Step 4, use the linear least squares method to fit the line segment set l _s ={l _s0 ,l _s1 ,...,l _sm } for _the point cloud dataset p snew, and do the same for the second target point cloud dataset p _tnew Use the linear least squares method to fit the line segment l _t = {l _t0 ,l _t1 ,....,l _tm }, and judge whether the current printing is by comparing whether the eigenvalue difference of each line segment is within the set threshold ∈ range Whether part of the pose deviation is within the control compensation range, and obtain the compensable control state word set s _k ={s _k0 ,s _k1 ,....,s _km };

Among them, step 4 includes:

Step 4-1, for the second source point cloud data set p _snew , according to the step 2-1, the continuous points in the preprocessed source point cloud data set P' _s form a new Line segment set d _s ={d _s0 ,d _s1 ,...,d _sm }, the continuous points in the second target point cloud data set p _tnew form a new line segment set d _t ={d _t0 ,d _t1 ,...,d _tm };

Step 4-2, according to the characteristics of the target printing model, establish f(y _i )=k _i x _i + _bi fitting function through the i-th segment of the line segment set d _s , that is, adopt the linear least square method, and pass the loss The function J(k _i , b _i ) calculates partial derivatives for k _i and b _i respectively, and sets the partial derivatives to 0 to deduce the corresponding k _i and b _i , that is, l _si = (k _i , b _i ), and forms a set of line segments l _s = {l _s0 ,l _s1 ,...,l _sm };

Step 4-3, according to step 4-2, the line segment l _t ={l _t0 ,l _t1 ,....,l _tm } is also fitted to the point cloud data set p _tnew using the linear least squares method;

Step 4-4, set the effective threshold of the line segment feature value ∈=(∈ _k , ∈ _b ), compare the line segment set l _s and l _t , and judge whether the pose deviation of the current printing part is within the controllable compensation range, and obtain Output compensable control state word set s _k = {s _k0 , s _k1 ,...., s _km };

Step 5, according to the state word set s _k , perform matching point calculation on the point cloud data in the corresponding line segment of the point cloud data set p _s and p _t , obtain the line segment set deviation square sum set ε _l , and generate compensation control according to the threshold ε _j Quantity γ _b = {γ _b0 ,γ _b1 ,...,γ _bm };

Wherein, the step 5 includes:

Step 5-1, according to the state word set s _k , select the line segment that needs to be calculated for matching points;

Step 5-2, calculate the sum of the square deviations ε _li of each axis for the corresponding point data of l _si in the line segment set l _s and l _ti in the line segment set l _t , namely:

Obtain the square root set ε _l ={ε _l0 ,ε _l1 ,...,ε _lm } of the deviation sum of the squares of the line segment set; and generate the compensation coefficient μ _l =max(ε _l );

Step 5-3, according to the compensation coefficient μ _l , calculate the compensation control quantity γ _b ={γ _b0 ,γ _b1 ,...,γ _bm } of the point where the line segment is concentrated, where:

Step 6, calculate the compensation control amount δ _b of each motion axis according to the compensation control amount γ _b , where the compensation amount of the x-axis and y-axis are directly related to the x-axis and y-axis coordinates of the next slice 3D model, and the z-axis is compensated Quantity is completed by multi-axis combined control. Wherein, said step 6 includes:

Step 6-1, through the compensation control quantity γ _bk ={σ _xk ,σ _yk ,σ _zk } at time k, calculate the compensation control quantity δ _bk of each motion axis at the corresponding time:

δ _bk (x,y,z)=(σ _xk x _tk ,σ _yk y _tk ,σ _zk z _tk )

Among them (x _tk , y _tk , z _tk ) are the print trajectory coordinates corresponding to time k of the sliced 3D model of the next layer. For the x and y axes, the compensated x and y axis coordinate data (x' _tk , y' _tk ) are directly generated:

(x' _tk ,y' _tk )=((1+σ _xk )x _tk ,(1+σ _yk )y _tk )

Step 6-2, since the movement of the z-axis is realized through the combined movement of the A, B, C and z-axis, when the entire printing is in the normal printing section, that is, when the hand is not changed, the A, B, and C axes are in a fixed state. Set the z-axis compensation control amount δ _b (z):

When the printing is in the hand-changing operation section, the A and C axes are pressed, and the B axis is lifted. At this time, the z axis moves in the z _min direction to realize the z axis "return to zero"; then the B axis is pressed, and the A and C are lifted. , at this time, the z-axis can move in the z _max direction and enter the normal printing stage. During this process, the z-axis compensation control amount δ _b (z):

Among them, d _bz is the z-axis distance of a single normal printing, and h _z is the return clearance on the z-axis.

That is, the compensated z-axis coordinate data z' _tk :

z' _tk ＝z _tk +δ _b (z)

To sum up, the above are only preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

For those skilled in the art, it is obvious that the embodiments of the present invention are not limited to the details of the above-mentioned exemplary embodiments, and that the embodiments of the present invention can be implemented in other specific forms without departing from the spirit or essential features of the embodiments of the present invention. example. Therefore, no matter from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present invention is defined by the appended claims rather than the above description, so it is intended that the All changes within the meaning and range of equivalents to the claims are included in the embodiments of the present invention. Any reference sign in a claim should not be construed as limiting the claim concerned. In addition, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Multiple units, modules or devices stated in system, device or terminal claims may also be realized by the same unit, module or device through software or hardware. The words first, second, etc. are used to denote names and do not imply any particular order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention and not to limit them. Although the embodiments of the present invention have been described in detail with reference to the above preferred embodiments, those of ordinary skill in the art should understand that they can Modifications or equivalent replacements to the technical solutions of the embodiments of the present invention should not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (7)

1. A continuous 3D printing method of a long truss based on laser ranging feedback control is characterized by comprising the following steps:

step 1, acquiring a source point cloud data set P at the installation position of a laser sensor _s Obtaining a 3D model target point cloud data set P of the current printing layer _t ；

Step 2, the source point cloud data set P is processed _s Preprocessing and coordinate converting the medium laser ranging and Z-axis motor position data to obtain a second source point cloud data set p _snew ；

Step 3, extracting the target point cloud data set P _t And a second target point cloud data set p of corresponding line segments is reconstructed _tnew ；

Step 4, aiming at the second source point cloud data set p _snew And the second target point cloud dataset p _tnew Respectively adopting linear least square method to fit to obtain line segment set l _s ＝{l _s0 ,l _s1 ,....,l _sm }, line segment set l _t ＝{l _t0 ,l _t1 ,....,l _tm }; comparing whether the difference value of the characteristic values of all the line segments is in the set threshold value E range, judging whether the pose deviation of the current printing part is in the control compensation range, and obtaining the compensable control stateCharacter set s _k ＝{s _k0 ,s _k1 ,....,s _km }；

Step 5, according to the state word set s _k For the second source point cloud data set p _snew And the second point target cloud data set p _tnew Calculating matching points according to the point cloud data in the line segments to obtain the deviation square and epsilon of the line segment set _l And according to a threshold value epsilon _j Generating a compensation control quantity gamma _b ＝{γ _b0 ,γ _b1 ,...,γ _bm }；

Step 6, according to the compensation control quantity gamma _b Calculating compensation control quantity delta of each motion axis _b 。

2. The laser ranging feedback control based stringer continuous 3D printing method of claim 1, wherein said step 1 comprises:

step 1-1, combining laser sensor data and current X, Y and Z axis motor position data at the same time into a source point cloud data set P at the laser sensor installation position _s (ii) a Wherein, according to the current slice data, a coordinate axis with delta t as time scale is established to generate t _i Combined data P of time _si ＝(t _i ,x _si ,y _si ,z _si ,l _si ) Combined into a source point cloud data set P at the laser sensor mounting position _s ＝{P _s0 ,P _s1 ,...,P _sn }; wherein l _si The feature value of the line segment in the combined data representing the current slice is t _i Temporal laser sensor data; x is a radical of a fluorine atom _si ,y _si ,z _si Representing three-dimensional coordinates;

step 1-2, extracting P corresponding to the current slice data according to the delta t _ti ＝(t _i ,x _ti ,y _ti ,z _ti ) And combining into a 3D model target point cloud data set P of the current printing layer _t ＝{P _t0 ,P _t1 ,...,P _tn }。

3. The laser ranging feedback control based stringer continuous 3D printing method of claim 2, wherein said step 2 comprises:

step 2-1, setting a preprocessing threshold epsilon _p For the source point cloud data set P _s Corresponds to t _i P of the moment _si ＝(t _i ,x _si ,y _si ,z _si ,l _si ) Performing pretreatment according to the formula

Will be at the threshold value epsilon _p Clearing out data outside the range to generate a preprocessed source point cloud data set P _s ^′ ；

Step 2-2, the preprocessed source point cloud data set P _s ^′ And performing coordinate conversion according to the mounting position of the laser sensor and the mounting position of the printing head, wherein the two relations are as follows:

in the above formula (Delta delta) _x ,Δδ _y ,θ _z ) Obtaining the second source point cloud data set p for the installation pose of the laser sensor relative to the printing head through recalculation _snew ＝{p _s0 ,p _s1 ,...,p _sn }。

4. The continuous 3D printing method of a stringer based on laser ranging feedback control according to claim 2 or 3, wherein said step 3 comprises:

step 3-1, eliminating the current layer slice model data set P _t In-process correspondence preprocessed source point cloud data set P _s ^′ Middle t _i The invalid point data outside the time threshold range is recombined into the second target point cloud data set p _tnew ＝{p _t0 ,p _t1 ,...,p _tn }。

5. The laser ranging feedback control based stringer continuous 3D printing method according to claim 4, wherein said step 4 comprises:

step 4-1, for the second source point cloud data set p _snew According to the step 2-1, the preprocessed source point cloud data set P is processed _s ^′ The continuous points in (a) constitute a new line segment set d _s ＝{d _s0 ,d _s1 ,...,d _sm H, the second target point cloud data set p _tnew The continuous points in (1) form a new line segment set d _t ＝{d _t0 ,d _t1 ,...,d _tm }；

Step 4-2, according to the characteristics of the target printing model, a line segment set d is passed _s I section of (c) to establish f (y) _i )＝k _i x _i +b _i Fitting the function and passing through the pair of loss functions J (k) _i ,b _i ) Are respectively paired with k _i ,b _i Calculating the partial derivatives, making the partial derivatives 0 and reversely deducing the corresponding k _i ,b _i I.e. l _si ＝(k _i ,b _i ) And form a line segment set l _s ＝{l _s0 ,l _s1 ,....,l _sm }；

Step 4-3, according to the step 4-2, a second target point cloud data set p of the 3D model of the current printing layer is processed _tnew Fitting the line segment l by linear least square method _t ＝{l _t0 ,l _t1 ,....,l _tm }；

Step 4-4, setting a valid threshold value of the line segment characteristic value, belonging to the field of (∈ C) _k ,∈ _b ) To line segment set l _s And l _t Comparing, judging whether the pose deviation of the current printing part is in the controllable compensation range, and obtaining a character set s of a controllable compensation state _k ＝{s _k0 ,s _k1 ,....,s _km }。

6. The laser range feedback control-based stringer continuous 3D printing method of claim 5, wherein said step 5 comprises:

step 5-1, according to the state word set s _k Selecting a line segment needing to be subjected to matching point calculation;

step 5-2, for the line segment set l _s L in _si And the set of line segments l _t L of _ti Calculating the sum of squares of deviations epsilon of each axis from the corresponding point data of (c) _li Namely:

the evolution set epsilon of the deviation square sum of the line segment set is obtained _l ＝{ε _l0 ,ε _l1 ,...,ε _lm }; and generates a compensation coefficient mu _l ＝max(ε _l )；

Step 5-3, according to the compensation coefficient mu _l Calculating the compensation control amount gamma of the line segment concentration point _b ＝{γ _b0 ,γ _b1 ,...,γ _bm }, wherein:

7. the laser range feedback control-based stringer continuous 3D printing method of claim 6, wherein said step 6 comprises:

step 6-1, control quantity gamma is compensated through time k _bk ＝{σ _xk ,σ _yk ,σ _zk Calculating compensation control quantity delta of each motion axis at corresponding time _bk ：

δ _bk (x,y,z)＝(σ _xk x _tk ,σ _yk y _tk ,σ _zk z _tk )

Wherein (x) _tk ,y _tk ,z _tk ) Printing track coordinates corresponding to the k moment for the next layer of slice 3D model; for x, y axes, compensated x, y axis coordinate data (x' _tk ,y’ _tk )：

(x’ _tk ,y’ _tk )＝((1+σ _xk )x _tk ,(1+σ _yk )y _tk )

Step (ii) of6-2, because the z-axis movement is realized by the combined movement of the A, B, C and z axes, when the whole printing is in a normal printing section, namely, in a non-hand-changing process, the A, B and C axes are in a fixed state, and the z-axis compensation control quantity delta is set at the time _b (z):

When the printing is in the hand-changing operation section, the B shaft is lifted up by the pressing of the A shaft and the C shaft, and the z shaft goes to the z shaft at the moment _min The directional motion realizes the zero return of the z axis; then B axis is pressed, A and C are lifted, and the z axis can move to z _max Directional movement, entering a normal printing stage, during which the z-axis compensation control quantity delta _b (z)：

Wherein d is _bz Z-axis distance, h, for a single normal print _z Is the return gap in the z-axis; i.e. compensated z-axis coordinate data z' _tk ：z’ _tk ＝z _tk +δ _b (z)。

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