CN111077223A - Additive manufacturing method with three-dimensional display, online detection and repair functions - Google Patents
Additive manufacturing method with three-dimensional display, online detection and repair functions Download PDFInfo
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- CN111077223A CN111077223A CN201911317417.XA CN201911317417A CN111077223A CN 111077223 A CN111077223 A CN 111077223A CN 201911317417 A CN201911317417 A CN 201911317417A CN 111077223 A CN111077223 A CN 111077223A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
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Abstract
The invention discloses an additive manufacturing method with three-dimensional display, online detection and repair functions. The method mainly comprises the following implementation steps: 1. prefabricating a reference block, establishing a corresponding relation table of defect wave amplitude values and pixel gray values forming an image, and uploading the table to a computer; 2. building an STL format three-dimensional model of a part to be processed, and importing the STL format three-dimensional model into a computer for three-dimensional display; 3. setting a movable vernier; 4. carrying out layered slice setting on the three-dimensional model in the STL format; 5. and (3) an additive manufacturing process for online detection and repair of parts. The method realizes the three-dimensional display of the part in the additive manufacturing process, realizes the accurate positioning of the defect position, and overcomes the defects that the part can be subjected to plane display, the defect positioning cannot be accurately carried out, and the online repair cannot be carried out in the existing method.
Description
Technical Field
The invention relates to an additive manufacturing method, in particular to an additive manufacturing method with three-dimensional display, online detection and repair functions.
Background
With the rapid development of the additive manufacturing technology, the types of additive manufacturing parts are more and more, the quality requirements on the parts are higher and higher, in order to ensure the manufacturing cost and the reliability of the manufactured parts, the online detection of the additive manufacturing parts is an indispensable important step when the additive manufacturing parts are successfully applied to equipment, and the laser ultrasonic detection can realize non-contact online detection.
Patent No. CN 200910075712-construction method of C-scan phase reversal image of ultrasonic scanning microscope discloses a construction method of C-scan phase reversal image, setting related data gate and threshold voltage, determining whether phase reversal occurs to positive and negative peak voltage values of each point at a detection position, converting the peak result into a gray value, and displaying on a screen to form a gray image. The process can detect the defects of internal layering, air holes and the like of the detection part, and overcomes the defects of high requirements on the surface flatness and the placement position of the detected target, inaccurate image construction position, low construction speed, inaccurate phase reversal judgment and the like.
However, the method belongs to traditional contact type ultrasonic detection, the part to be detected is required to be contacted during detection, and the method can only display in a two-dimensional mode and cannot identify the shape, size and defect position of the defect, so that the method cannot realize online detection of the defect of the part in the additive manufacturing process.
Disclosure of Invention
The invention provides an additive manufacturing method with three-dimensional display, online detection and repair functions, and aims to solve the problems that the traditional ultrasonic wave adopted by the prior art can only carry out offline detection on part defects and cannot realize real-time online detection and online repair in the online processing process of parts.
The specific technical scheme of the invention is as follows:
the invention provides an additive manufacturing method with three-dimensional display, online detection and repair functions, which comprises the following specific implementation steps of:
step 1: prefabricating a reference block, establishing a corresponding relation table of defect wave amplitude values and pixel gray values forming an image, and uploading the table to a computer;
step 2: building an STL format three-dimensional model of a part to be processed, and constructing an STL format three-dimensional model of the part to be processed
Importing the STL format three-dimensional model into a computer for three-dimensional display;
and step 3: setting a movable vernier;
setting a movable cursor in the three-dimensional model in the STL format, and dragging the movable cursor to display the position coordinate value of a designated point in the three-dimensional model in the STL format;
and 4, step 4: carrying out layered slice setting on the three-dimensional model in the STL format;
slicing the part to be processed on the three-dimensional model in the STL format according to the thickness of a forming layer required by additive manufacturing, wherein the thickness of the slice is consistent with that of the forming layer;
and 5: the additive manufacturing process of online detection and repair of parts;
step 5.1: the additive manufacturing cladding head begins to print a first layer of the part; the laser ultrasonic probe detects according to the printing path and feeds back position information and ultrasonic signals corresponding to all detection points in the first layer to the computer;
step 5.2: the computer carries out data processing on all the collected laser ultrasonic signals in the first layer to obtain a first layer characteristic signal wave peak value sequence, and the first layer characteristic signal wave peak value sequence is converted into a corresponding first layer gray value sequence by adopting a defect wave amplitude value and gray value corresponding table forming image pixels;
step 5.3: the computer three-dimensionally displays the first layer of the part to be processed through the first layer gray value sequence;
step 5.4: judging whether the first layer of the printed part is defective or not through the three-dimensionally displayed first layer image;
if the first layer is found to be defect-free, continuing to execute second layer printing according to the steps 5.1-5.3; if the first layer is found to be defective, dragging the movable cursor to a defective point to obtain the position information of the defective point; and feeding back the position information of the defect point to an upper computer to control the additive manufacturing cladding head to perform additive repair on the defect point until all the defect points in the first layer are completely repaired, and continuing to perform second-layer printing according to the steps 5.1-5.3 until the part is machined.
Further, the specific way of prefabricating the reference block in the step 1 is as follows;
prefabricating at least two reference blocks according to the material attribute of the part to be machined and the defect size in the allowable value range;
the sizes and materials of the at least two reference blocks are the same as those of the parts to be processed; one of the reference blocks is a non-defective reference block, and the other reference blocks are defective reference blocks; and N flat-bottom hole defects with the same aperture and different hole depths or N flat-bottom hole defects with the same aperture and different hole depths are arranged on the defect comparison test block.
Further, the specific process of establishing the characteristic peak-to-peak value and gray value mapping table of the image pixels in step 1 is as follows:
s1: the laser ultrasonic detection system carries out off-line detection on at least two reference blocks to obtain the amplitude values of the defect waves of different reference blocks;
marking the size of the peak value of the characteristic peak of the defect-free reference block as F0;
respectively marking the sizes of the characteristic peak values corresponding to N flat-bottom hole defects in the defective reference block as F1-FN;
s2: establishing a corresponding table of the characteristic peak value and the gray value of the pixels forming the image, and uploading the table to a computer;
and in the corresponding table of the characteristic peak value and the gray value of the image pixel: setting the gray value corresponding to the characteristic peak value F0 of the defect-free reference block as X; corresponding gray values to X + Y1 to X + YN for characteristic peak values F1 to FN corresponding to N flat-bottom hole defects in the defective reference block;
wherein X is more than or equal to 0, the gray value X + YN is less than or equal to 255, and X + YN is more than or equal to X + Y1 and more than or equal to X.
Further, the specific process of step 2 is as follows:
and building a three-dimensional model of the part to be processed by adopting three-dimensional drawing software, building a three-dimensional coordinate system of the three-dimensional model, carrying out grid division on the three-dimensional model, and storing the three-dimensional model as the STL-format three-dimensional model.
Further, the three-dimensional drawing software is SolidWorks.
The invention has the beneficial effects that:
the invention adopts laser ultrasonic waves, the laser ultrasonic detection system can realize detection without contacting with a part to be processed, safety accidents are avoided, meanwhile, the method can carry out real-time online detection in the manufacturing process of the part, obtain the current detection position according to the returned current detection coordinate and return the current detection position to the three-dimensional model, display the current detection position on an interface, realize three-dimensional visual display of laser ultrasonic detection data by intercepting the characteristic signal peak value of the ultrasonic signal of the current detection point, represent the size of the characteristic signal peak value by different gray values and map the position coordinate of the current detection point and the gray value of the pixel forming the image in the three-dimensional model one by one, thereby providing powerful guarantee for the defect detection of the part.
According to the method, the movable vernier is added into the three-dimensional model, information such as the defect number and the defect size of the current detection layer is displayed through gray value comparison, the specific position with the abnormality is represented through the movable vernier, the position coordinate of the position is returned, and then the defect is repaired on line in an additive mode, so that the machining efficiency of additive manufacturing is greatly improved.
Drawings
FIG. 1 is a block flow diagram of the method of the present invention.
Detailed Description
The additive manufacturing method with three-dimensional display, online detection and repair functions provided by the invention is described in detail below with reference to the accompanying drawings:
step 1: prefabricating at least two reference blocks according to the material attribute of the part to be machined and the defect size in the allowable value range;
wherein, the size and the material of the reference block are the same as those of the part to be processed; one of the reference blocks is a non-defective reference block, and the other reference blocks are defective reference blocks; the defect comparison test block is provided with N flat-bottom hole defects with the same aperture and different hole depths or N flat-bottom hole defects with different aperture and the same hole depth;
in this embodiment: four reference blocks are designed, and the sizes of the four reference blocks are all 60mmX80mmX4mm
Wherein, the reference block 1 is a defect-free reference block; the reference blocks 2, 3 and 4 are all defective reference blocks;
the aperture of the flat-bottom defect hole on the reference block 2 is 0.5mm, and the hole depth is respectively as follows: 1mm, 1.5 mm;
the aperture of the flat-bottom defective hole on the reference block 3 is 0.5mm, and the hole depth is 2mm and 2.5 mm;
the aperture of the flat-bottom defective hole on the reference block 4 is 0.5mm, and the hole depth is 3mm and 3.5 mm;
step 2: the laser ultrasonic detection system carries out off-line detection on at least two reference blocks to obtain the amplitude values of the defect waves of different reference blocks;
performing a laser ultrasonic detection experiment on a defect-free reference block in a detection area of 10mmX10mm, when the defect exists in the defect-free reference block, setting a gate between an initial wave (surface wave) and a bottom wave (bottom echo) when a defect wave appears in an ultrasonic signal and the appearance position of the defect wave is between the initial wave (surface wave) and the bottom wave (bottom echo), wherein the gate threshold is 0, namely the gate is overlapped with a zero scale line, and the size of a characteristic peak value of the defect-free reference block is recorded as F0;
carrying out 10mmX10mm laser ultrasonic detection experiment (the defect of a flat bottom hole in a detection region is 0.5mmX1mm) on a defective reference block 2, wherein the detection surface is the back of a prefabricated defect, simulating internal defect detection, arranging a gate between an initial wave and a bottom wave, and extracting a defect wave amplitude F1 in the gate, wherein the gate has an amplitude of 0, namely the gate is overlapped with a zero scale line;
repeating the steps to respectively perform laser ultrasonic detection experiments on the other flat-bottom hole defect of the reference block 2 and the flat-bottom hole defects of the reference blocks 3 and 4 to respectively obtain the defect wave amplitude values of F2, F3, F4, F5 and F6;
marking the peak values of the characteristic peaks corresponding to the 6 flat-bottom hole defects in the defective reference block 2, the defective reference block 3 and the defective reference block 4 as F1-F6 respectively;
in performing this step, the following points need to be introduced:
determining the initial wave: in the ultrasonic signal excited in the laser ultrasonic detection system, the surface wave signal (initial wave) is strongest, a gate 1 is arranged in the initial wave area, wherein the threshold value of the gate 1 is A;
determining bottom waves: in a laser ultrasonic detection system, different gates are adopted for analyzing different types of waves of acquired ultrasonic waveforms, so that defect identification is conveniently carried out on detected parts. Arranging a gate 2 in a bottom wave (primary bottom echo) area, wherein the threshold value of the gate 2 is B;
and arranging a gate between the initial wave and the bottom wave, extracting the size of the ultrasonic peak in a selected area of a gate frame, and converting the size of the characteristic peak in the gate into a gray value according to the mapping relation between the amplitude of the defect wave and the gray value.
Converting the ultrasonic signal of each detection point in the detection area into a characteristic signal peak value, converting the characteristic signal peak value into a gray value according to a defect wave amplitude value and a gray value corresponding table forming image pixels, namely outputting the gray value of each detection point into a three-dimensional model one by one according to the position coordinates of the current detection point fed back by a robot feedback system, and realizing the three-dimensional visual display of the detection part of the laser ultrasonic detection system.
The accurate setting of the gate 1 and the gate 2 ensures the accuracy of the gate setting position, and can obtain the correct characteristic peak value. The gate amplitude is F1 (the amplitude of the defect wave generated by the allowable defect size of the part), the peak value of the extracted characteristic signal is smaller than the gate threshold, the gray value of the point is 0, and if the peak value of the extracted characteristic signal exceeds the gate threshold, the gray value corresponding table of the defect wave amplitude and the gray value of the pixel forming the image is inquired to obtain the small gray value of the point.
And step 3: establishing a corresponding table of the characteristic peak value and the gray value of the pixels forming the image, and uploading the table to a computer;
and in the corresponding table of the characteristic peak value and the gray value of the image pixel: wherein, the gray value refers to the color depth in the black-and-white image, and generally ranges from 0 to 255, white is 255, and black is 0;
setting the gray value corresponding to the characteristic peak value F0 of the defect-free reference block as X;
corresponding gray values to X + Y1 to X + YN for characteristic peak values F1 to FN corresponding to N flat-bottom hole defects in the defective reference block;
wherein X is more than or equal to 0, the gray value X + YN is less than or equal to 255, and X + YN is more than or equal to X + Y1 and more than or equal to X;
the specific way of this embodiment is: and mapping the extracted characteristic peak value of each ultrasonic signal and the gray value of the image pixel one by one according to a certain mode. The flawless test block has the advantages that the gray value of a gate cut peak value F0 is 0, F1 corresponds to 100, F2 corresponds to 130, F3 corresponds to 160, F4 corresponds to 190, F5 corresponds to 220, and F6 corresponds to 250; thereby obtaining a characteristic peak value and a gray value corresponding table of the image pixels;
and 4, step 4: building a three-dimensional model of a part to be processed;
establishing a three-dimensional model of a part to be processed by adopting SolidWorks drawing software, establishing a three-dimensional coordinate system of the three-dimensional model, carrying out grid division on the three-dimensional model, and storing the three-dimensional model in an STL format;
and 5: importing a model;
importing the three-dimensional model in the STL format into a computer to realize three-dimensional display of the three-dimensional model in the STL format;
step 6: setting a movable vernier;
setting a movable cursor in the three-dimensional model in the STL format, and dragging the movable cursor to display the position coordinate value of a designated point in the three-dimensional model in the STL format;
and 7: carrying out layered slice setting on the three-dimensional model in the STL format;
slicing the part to be processed on the three-dimensional model in the STL format according to the thickness of a forming layer required by additive manufacturing, wherein the thickness of the slice is consistent with that of the forming layer;
and 8: the additive manufacturing process of online detection and repair of parts;
step 8.1: the additive manufacturing cladding head begins to print a first layer of the part; the laser ultrasonic probe detects according to the printing path and feeds back position information and ultrasonic signals corresponding to all detection points in the first layer to the computer;
step 8.2: the computer carries out data processing on all the collected laser ultrasonic signals in the first layer to obtain a first layer characteristic signal wave peak value sequence, and the first layer characteristic signal wave peak value sequence is converted into a corresponding first layer gray value sequence by adopting a defect wave amplitude value and gray value corresponding table forming image pixels;
in this embodiment, the specific process of data processing is as follows:
if the peak value of the point is less than F1, judging that no defect exists at the point, and the gray value is 0;
if the peak value of the point is larger than F1 and smaller than F2, converting the point into a corresponding pixel value according to a linear relation;
if the peak value of the point is larger than F2 and smaller than F3, establishing a linear relation between the gray value corresponding to F2 and the gray value corresponding to F3, and obtaining the gray value of the image pixel corresponding to the peak value of the point according to the linear relation;
if the peak value of the point is larger than F3 and smaller than F4, establishing a linear relation between the gray value corresponding to F3 and the gray value corresponding to F4, and obtaining the gray value corresponding to the peak value of the point according to the linear relation;
if the peak value of the point is larger than F4 and smaller than F5, establishing a linear relation between the gray value corresponding to F4 and the gray value corresponding to F5, and obtaining the gray value corresponding to the peak value of the point according to the linear relation;
if the peak value of the point is larger than F5 and smaller than F6, establishing a linear relation between the gray value corresponding to F5 and the gray value corresponding to F6, and obtaining the gray value corresponding to the peak value of the point according to the linear relation;
if the peak value of the point is larger than F6, establishing a linear relation between the gray value corresponding to F6 and the gray value 255, and obtaining the gray value corresponding to the peak value of the point according to the linear relation;
step 8.3: the computer three-dimensionally displays the first layer of the part to be processed through the first layer gray value sequence;
step 8.4: judging whether the first layer has defects or not through a three-dimensional displayed first layer image;
if the first layer is found to be defect-free, continuing to execute second layer printing according to the steps 8.1-8.3; if the first layer is found to be defective, dragging the movable cursor to a defective point to obtain the position information of the defective point; feeding back the position information of the defect points to an additive manufacturing cladding head controlled by an upper computer to perform additive repair on the defect points until all the defect points in the first layer are completely repaired, and continuing to perform second-layer printing according to the steps 8.1-8.3 until the part processing is completed.
Claims (5)
1. The additive manufacturing method with the functions of three-dimensional display, online detection and repair is characterized by comprising the following specific implementation steps of:
step 1: prefabricating a reference block, establishing a corresponding relation table of defect wave amplitude values and pixel gray values forming an image, and uploading the table to a computer;
step 2: building an STL format three-dimensional model of a part to be processed, and importing the STL format three-dimensional model into a computer for three-dimensional display;
and step 3: setting a movable vernier;
setting a movable cursor in the three-dimensional model in the STL format, and dragging the movable cursor to display the position coordinate value of a designated point in the three-dimensional model in the STL format;
and 4, step 4: carrying out layered slice setting on the three-dimensional model in the STL format;
slicing the part to be processed on the three-dimensional model in the STL format according to the thickness of the forming layer required by additive manufacturing, wherein the thickness of the slice is consistent with that of the forming layer;
and 5: the additive manufacturing process of online detection and repair of parts;
step 5.1: the additive manufacturing cladding head begins to print a first layer of the part; the laser ultrasonic probe detects according to the printing path and feeds back position information and ultrasonic signals corresponding to all detection points in the first layer to the computer;
step 5.2: the computer carries out data processing on all the collected laser ultrasonic signals in the first layer to obtain a first layer characteristic signal wave peak value sequence, and the first layer characteristic signal wave peak value sequence is converted into a corresponding first layer gray value sequence by adopting a defect wave amplitude value and gray value corresponding table forming image pixels;
step 5.3: the computer three-dimensionally displays the first layer of the part to be processed through the first layer gray value sequence;
step 5.4: judging whether the first layer of the printed part is defective or not through the three-dimensionally displayed first layer image;
if the first layer is found to be defect-free, continuing to execute second layer printing according to the steps 5.1-5.3;
if the first layer is found to be defective, dragging the movable cursor to a defective point to obtain the position information of the defective point; and feeding back the position information of the defect point to an upper computer to control the additive manufacturing cladding head to perform additive repair on the defect point until all the defect points in the first layer are completely repaired, and continuing to perform second-layer printing according to the steps 5.1-5.3 until the part is machined.
2. The additive manufacturing method with three-dimensional display, online detection and repair functions according to claim 1, wherein:
the specific mode of prefabricating the reference block is as follows;
prefabricating at least two reference blocks according to the material attribute of the part to be machined and the defect size in the allowable value range;
the sizes and materials of the at least two reference blocks are the same as those of the parts to be processed; one of the reference blocks is a non-defective reference block, and the other reference blocks are defective reference blocks; and N flat-bottom hole defects with the same aperture and different hole depths or N flat-bottom hole defects with the same aperture and different hole depths are arranged on the defect comparison test block.
3. The additive manufacturing method with three-dimensional display, online detection and repair functions according to claim 2, wherein:
the specific process of formulating the characteristic peak-to-peak value and gray value corresponding table of image pixels is as follows:
s1: the laser ultrasonic detection system carries out off-line detection on at least two reference blocks to obtain the amplitude values of the defect waves of different reference blocks;
marking the size of the peak value of the characteristic peak of the defect-free reference block as F0;
respectively marking the sizes of the characteristic peak values corresponding to N flat-bottom hole defects in the defective reference block as F1-FN;
s2: establishing a corresponding table of the characteristic peak value and the gray value of the pixels forming the image, and uploading the table to a computer;
and in the corresponding table of the characteristic peak value and the gray value of the image pixel: setting the gray value corresponding to the characteristic peak value F0 of the defect-free reference block as X; corresponding gray values to X + Y1 to X + YN for characteristic peak values F1 to FN corresponding to N flat-bottom hole defects in the defective reference block;
wherein X is more than or equal to 0, the gray value X + YN is less than or equal to 255, and X + YN is more than or equal to X + Y1 and more than or equal to X.
4. The additive manufacturing method with three-dimensional display, online detection and repair functions according to claim 1, 2 or 3, wherein: the specific process of the step 2 is as follows:
and building a three-dimensional model of the part to be processed by adopting three-dimensional drawing software, building a three-dimensional coordinate system of the three-dimensional model, carrying out grid division on the three-dimensional model, and storing the three-dimensional model as the STL-format three-dimensional model.
5. The additive manufacturing method with three-dimensional display, online detection and repair functions according to claim 4, wherein: the three-dimensional drawing software is SolidWorks.
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| CN112712554B (en) * | 2020-12-08 | 2022-08-26 | 上海交通大学烟台信息技术研究院 | Method for extracting central line of laser stripe on surface of semitransparent Lambert surface |
| CN114818162A (en) * | 2021-01-29 | 2022-07-29 | 欧特克公司 | Automatically generating a probe path for surface inspection and part alignment |
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