JP2004090406A - Laminate molding apparatus and program for controlling laminate molding apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To directly input three-dimensional bit map data (CT data) obtained by imaging an article into a number of tomographic images by a CT apparatus. <P>SOLUTION: A laminate molding apparatus successively repeats formation of a unit molding layer by forming a thin layer of a molding material based on data for molding and selectively curing of this thin layer, and performs molding of a three-dimensional article by laminating the unit molding layers repeatedly formed. The laminate molding apparatus is provided with a CT data inputting part 7 capable of directly inputting the three-dimensional bit map data obtained by imaging the article being an origin of the aimed molded article into a number of tomographic images by the CT apparatus. <P>COPYRIGHT: (C)2004,JPO

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to an additive manufacturing apparatus used for modeling a three-dimensional object and a control program therefor.
[0002]
[Prior art]
The additive manufacturing method is a technology for forming a three-dimensional shape of a target object using three-dimensional shape data relating to the target object as forming data, and forming a thin layer of a forming material based on the data for forming and irradiating a laser beam. The formation of the unit forming layer by selective curing of the thin layer in response to the above is sequentially repeated, and the unit forming layer of the repetitively formed is laminated to form a three-dimensional object. Such an additive manufacturing method includes an SLS method (selective laser sintering method) (for example, Japanese Patent Application Laid-Open No. H11-508322 and Japanese Patent Application Laid-Open No. H11-219538) and an optical manufacturing method (for example, Japanese Patent Application Laid-Open No. 2001-347572). Gazette), a sheet laminating method (for example, JP-A-7-195533, JP-A-2000-37782), an ink-jet method (for example, JP-A-2002-67171, JP-A-2002-178413), an FDM method, and the like. is there.
[0003]
[Problems to be solved by the invention]
In conventional additive manufacturing, it has been general to design a target object by CAD and create modeling data based on the CAD data. In other words, conventional additive manufacturing generally uses design data based on CAD. On the other hand, the three-dimensional shape data is obtained from an existing article or a clay model, and the three-dimensional shape data is used as modeling data to produce a duplicate of the existing article, or a product based on the clay model is produced. There is an idea that it is effective to use the additive manufacturing method even when manufacturing. In this case, as the three-dimensional shape data, three-dimensional bitmap data, that is, CT data obtained by imaging an existing article, a clay model, or the like into a large number of tomographic images with a CT device such as an X-ray CT device is used. Become.
[0004]
By the way, the conventional additive manufacturing apparatus inputs modeling data into STL (Stereolithography File) data, which is a kind of polygon data, due to the historical background of its development and the like, and internally inputs the 3D bitmap data. It is used to control the additive manufacturing. There is no problem in using the STL data as input data in the conventional general method of creating modeling data based on CAD data. However, when CT data is used as a basis for modeling data, it becomes a major obstacle. That is, if the CT data is converted into the STL data format to be used as the input data of the additive manufacturing apparatus, the data size increases 10 to 100 times at that time. For this reason, a large amount of time is required for data processing, and it is not practical to convert CT data into STL data. Therefore, it is desired that CT data can be directly input to the additive manufacturing apparatus. The present invention has been made in order to meet such a demand, and has as one object to provide a layered manufacturing apparatus capable of directly inputting CT data.
[0005]
Another object of the present invention is to solve a problem associated with direct input of CT data to an additive manufacturing apparatus. One of the problems is a problem of noise included in CT data. That is, when an article (existing article, clay model, or the like) that is a source of a target object is imaged by a CT apparatus, a fine image is often generated as noise in a portion where an image source is not supposed to exist. If the CT data containing such noise is used as modeling data, for example, in the case of the above-described SLS method, when the unfused powder is collected and reused, it is welded due to noise. The resulting small lumps will be mixed into the powder for reuse, and using it as it is will cause problems such as a decrease in the accuracy of additive manufacturing. Therefore, it is desired that the CT data be used as input data of the additive manufacturing apparatus so that the noise can be effectively removed. One of the objects of the present invention is to meet this demand. is there.
[0006]
As another problem associated with direct input of CT data to the additive manufacturing apparatus, there is a gap between the imaging interval of tomographic images in the CT apparatus and the thickness of the thin layer in the additive manufacturing. That is, while the imaging interval in the CT apparatus is generally, for example, about 1 mm, the thickness of the thin layer in the additive manufacturing is usually, for example, about 0.1 mm, and there is a gap of about 10 times. Therefore, it is necessary to interpolate between tomographic images in CT data to fill the gap. One of the objects of the present invention is to meet this demand.
[0007]
Another object of the present invention is to solve other problems in the additive manufacturing method using CT data. The problem is of particular importance when producing duplicates, and is to give the object a texture. That is, even if the surface has fine irregularities, and thus the original article has a unique texture, the texture information is lost in the CT data obtained by imaging the original article. For this reason, it is usual that only a molded product with a moderate surface can be obtained from a replica product by additive manufacturing using CT data, which is insufficient for producing a replica product. In view of the above, one of the objects of the present invention is to make it possible to form irregularities for texture on the surface of a target object.
[0008]
[Means for Solving the Problems]
In the present invention, in order to enable CT data to be directly input data, the formation of a thin layer of a molding material based on the input modeling data and the formation of a unit molding layer by selective curing of the thin layer are sequentially performed. Repeatedly, in a laminate molding apparatus that forms a three-dimensional object by laminating unit molding layers of this repetitive formation, an article that is the original of the target molded object is imaged as a number of tomographic images with a CT device and imaged. It is characterized in that it has an input unit that can directly input the obtained three-dimensional bitmap data as the modeling data.
[0009]
Further, in the present invention, in order to effectively remove noise from the three-dimensional bitmap data, the three-dimensional bitmap data is subjected to an inward offset and then an outward offset, so that the three-dimensional bitmap data is offset outward. Noise removing means for removing noise included in the three-dimensional bitmap data is provided in the additive manufacturing apparatus.
[0010]
Further, in the present invention, in order to be able to fill the gap between the interval between the tomographic images in the three-dimensional bitmap data by the CT apparatus and the thickness of the thin layer in the additive manufacturing, the distance between the tomographic images in the three-dimensional bitmap data is reduced. In addition, an interlayer interpolation means for adding an interpolation tomographic image for the thin layer is provided in the additive manufacturing apparatus. In one embodiment, the interlayer interpolation means performs a blurring process on each of the tomographic images. The tomographic image subjected to the blurring process is subjected to a tomographic image Sn and a tomographic image Sn + 1. The average value corresponding to the number of layers to be interpolated with respect to the amount of change in luminance between the pixel and the pixel of the tomographic image Sn + 1 corresponding to this pixel is obtained, and based on the average amount of change in luminance, Performing an average interpolation process for setting the brightness of the pixel at the corresponding position; binarizing the brightness of the pixel of each of the interpolated tomographic images with a predetermined threshold based on the brightness set in the average interpolation process Each of the interpolation tomographic images is configured to include a step of performing a binarization process. In another embodiment, the tomographic images adjacent to each other are defined as a tomographic image Sn and a tomographic image Sn + 1, and the outline of the tomographic image Sn is regarded as an electrode of Y volt, while the outline of the tomographic image Sn + 1 is defined as an electrode of Y ′ volt. Assuming the contour of the X-th interpolated tomographic image from the tomographic image Sn as the equipotential surface of (| Y−Y ′ |) · X / Z (where Z is the number of layers of the interpolated tomographic image), The configuration is such that an interpolation tomographic image is set.
[0011]
Further, in the present invention, in order to be able to give a texture to a target object, a thin layer of a molding material is formed based on input modeling data and a unit molding layer is formed by selective curing of the thin layer. The object is formed based on the shaping data with respect to the shaping data in a layered shaping apparatus in which the formation is sequentially repeated and a three-dimensional object is formed by stacking the unit shaping layers of the repeated formation. It is characterized in that a texture-imparting means is provided for forming texture irregularities on the surface of the target object by increasing or decreasing the number of pixels serving as a shadow image in a portion close to the surface of the object.
[0012]
Further, in the present invention, three-dimensional bitmap data obtained by imaging an article, which is a source of a target object, into many tomographic images with a CT device is input as modeling data. A layered molding apparatus that sequentially repeats formation of a thin layer of a molding material based on the thin layer and formation of a unit molding layer by selective curing of the thin layer, and forms a three-dimensional object by laminating the unit molding layers of the repeated formation. Is a control program used in the above. The noise for removing noise included in the three-dimensional bitmap data by applying an inward offset after applying an inward offset to the three-dimensional bitmap data Removal processing: Inter-layer interpolation processing for adding an interpolation tomographic image for the thin layer between each tomographic image in the three-dimensional bitmap data: The three-dimensional By adding or subtracting a portion of the target image formed on the basis of the three-dimensional bitmap data to a portion close to the surface of the target object according to the desired pattern, the texture of the surface of the target object is increased. A program for controlling an additive manufacturing apparatus, which comprises at least one of the texture imparting processes for forming irregularities for use.
[0013]
Further, in the present invention, as the interlayer interpolation processing in the above-described additive manufacturing apparatus control program, a step of performing a blurring process on each of the tomographic images, a tomographic image Sn that has been subjected to the blurring process, With respect to the tomographic image Sn + 1, an average value corresponding to the number of layers to be interpolated with respect to the amount of change in luminance between the pixel of the tomographic image Sn and the pixel of the tomographic image Sn + 1 corresponding to this pixel is obtained. Performing an average interpolation process of setting the luminance of the pixel at the corresponding position in each of the interpolation tomographic images based on the luminance of the pixels of each of the interpolation tomographic images based on the luminance set in the average interpolation process. A process including a step of performing a binarization process of binarizing with a threshold value: or a tomographic image adjacent to each other as a tomographic image Sn and a tomographic image Sn + 1, and a contour of the tomographic image Sn On the other hand, the contour of the tomographic image Sn + 1 is regarded as a Y 'volt electrode while the contour of the X-th interpolated tomographic image from the tomographic image Sn is (| Y-Y' |) .X Any of the processes for setting the interpolated tomographic image by obtaining an equipotential surface of / Z (where Z is the number of layers of the interpolated tomographic image) is used.
[0014]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, embodiments of the present invention will be described. FIG. 1 is a block diagram showing a configuration of an additive manufacturing apparatus according to an embodiment of the present invention. This additive manufacturing apparatus has a data input unit 1, a data processing unit 2, a control unit 4, and a modeling processing unit 5. The data input unit 1 includes an STL data input unit 6 and a CT data input unit 7. The STL data input section 6 is also provided in a conventional additive manufacturing apparatus, and from here, STL data converted from CAD data or the like is input as modeling data as in the conventional case. On the other hand, the CT data input unit 7 is a feature of the present invention, and is a dimension obtained by imaging an article, which is a source of a target object, into a number of tomographic images with a CT device such as an X-ray CT device. Bitmap data (CT data) can be directly input to the additive manufacturing apparatus from this as modeling data.
[0015]
The data processing unit 2 includes an STL / bitmap conversion unit 8 used for STL data, and a noise removal unit 9, an interlayer interpolation unit 10, and a texture imparting unit 11 used for three-dimensional bitmap data. Have. Then, the STL data input from the STL data input unit 6 is converted into bitmap data by the STL / bitmap conversion unit 8 and output to the control unit 4 in the same manner as in the conventional additive manufacturing apparatus. Used for controlling the unit 5.
[0016]
On the other hand, the CT data input from the CT data input unit 7 is subjected to a processing having a flow as shown in FIG. 2 by a program for controlling the additive manufacturing apparatus, and is processed into more appropriate modeling data. That is, when the CT data is input from the CT data input unit 7 (step 1), the data is first subjected to noise removal processing by the noise removal means 9 (step 2).
[0017]
As shown schematically in FIG. 3, the noise in the CT data is a small image Na, Nb, Nc,... Due to some factor in a portion where there should be no image source, such as around the tomographic image S of the original article. Has occurred. To remove such noises Na, Nb, Nc,..., An offset process, which is a general-purpose technique in the field of image processing, is used. To perform noise removal by offset processing, first, an inward offset is applied to the three-dimensional bitmap data. That is, as shown by the dotted line in FIG. 4, the tomographic image S is thinned. The offset amount is set to be slightly larger than the size of the noise. Here, the size of the noise is based on the largest size of the normally occurring noise, which is empirically determined. When such an inward offset is performed, the noises Na, Nb, Nc,... In FIG. That is, the noises Na, Nb, Nc,... Are made thinner than their sizes by offsetting inward, so that the noises disappear and disappear. When the noise is eliminated and the outward offset is applied with the same offset amount as the inward offset to restore the original value, data containing no noise is obtained.
[0018]
Subsequent to the noise removal processing, interlayer interpolation processing is performed by the interlayer interpolation means 10 (step 3). In the interlayer interpolation processing, as described above, there is a gap between the imaging interval of the tomographic image by the CT apparatus and the thickness of the thin layer (unit molding layer) of the molding material handled in the additive manufacturing. This is a process for inserting an interpolation tomographic image into the. Several methods are possible for the interlayer interpolation processing. Representative examples include a method based on a luminance change between tomographic images to be interpolated and a method based on a voltage model between tomographic images to be interpolated. FIG. 5 shows a flow of processing in interlayer interpolation by a method based on a luminance change between tomographic images to be interpolated, and FIG. 6 shows an image of the processing contents. In the interlayer interpolation process, first, a blur process is performed on each tomographic image S in the CT data (step 11: (a) → (b) in FIG. 6). Here, the blurring processing is performed by making the luminance of each pixel of the tomographic image averaged by the luminance of the surrounding pixels, that is, by mixing the luminance of one pixel with the luminance of the surrounding pixels. .
[0019]
After performing the blurring process, an average interpolation process is performed next (step 12: (b) → (c) in FIG. 6). In the average interpolation processing, first, for the tomographic image Sn and the tomographic image Sn + 1 adjacent to each other, an average luminance change amount between respective position-corresponding pixels is obtained. Specifically, the interpolation tomographic image C1 is inserted between the pixels Pn-1, Pn-2,... Of the tomographic image Sn and the pixels Pn + 1-1, Pn + 1-2,. , C2,..., That is, the average change in luminance according to the number of layers to be interpolated. That is, if it is assumed that the luminance of the pixel Pn-1 is 10, the luminance of the pixel Pn + 1-1 corresponding to the pixel is 20, and the number of layers of the interpolated tomographic image is 10, (20-10) / 10 = 1 And the average luminance change amount per layer of the interpolation tomographic image is obtained as 1. After calculating the average luminance change amount for all the pixels of both tomographic images Sn and Sn + 1 in this way, the luminance is set for all the pixels of the interpolated tomographic images C1, C2,. For example, since the pixel C1-1 of the interpolated tomographic image C1 adjacent to the tomographic image Sn corresponds to the position of the pixel Pn-1 of the tomographic image Sn, the luminance average change amount = 1 is added to the luminance of the pixel Pn-1 = 10. Brightness value = 11 is set. Although not shown, for the pixel C2-1 corresponding to the pixel Pn-1 in the interpolated tomographic image C2 adjacent to the interpolated tomographic image C1, 2 which is twice the average luminance change amount = 1 is used. The luminance value = 12 in addition to the luminance value = 10 of the pixel Pn-1 is set.
[0020]
FIG. 7 shows an image of the contents of processing in interlayer interpolation by a method based on a voltage model between tomographic images to be interpolated. For the tomographic images adjacent to each other, regarding the tomographic image Sn and the tomographic image Sn + 1, while the contour Pn of the tomographic image Sn is regarded as an electrode of Y volt (normally 0 volt), the contour Pn + 1 of the tomographic image Sn + 1 is regarded as Y ′ volt (normally). 1 volt) electrode. Then, the contour Px of the X-th interpolated tomographic image Cx from the tomographic image Sn is determined as an equipotential surface of (| Y−Y ′ |) · X / Z (where Z is the number of layers of the interpolated tomographic image), thereby obtaining an interpolated tomographic image. Set the image. In general, a method for solving the Laplace equation is used to calculate the equipotential surface.
[0021]
Subsequent to the average interpolation processing, a binarization processing for binarizing the luminance of the pixels of the interpolated tomographic image set in the average interpolation processing is performed (step 13: (c) → (d) in FIG. 6). . Thus, the interlayer interpolation processing is completed. The binarization process is performed based on a predetermined threshold value. The threshold value is usually obtained from the average luminance of the image part (the figure part) and the average luminance of the background part (the ground part). is there.
[0022]
After completion of the interlayer interpolation processing, it is determined whether or not the texture imparting processing is necessary (Step 4 in FIG. 2), and if not necessary, the data processing is ended. On the other hand, when the texture imparting process is required, it is performed by the texture imparting means 11 (step 5 in FIG. 2). The texture-imparting process is performed by increasing or decreasing the number of pixels that carry a shadow image in a desired pattern in a portion close to the surface of the target object. In other words, by adding or reducing pixels that carry an image in a portion close to the surface of the target object in a random pattern or a pattern according to an appropriate rule, fine texture irregularities are formed on the surface of the target object. To be formed. Thus, necessary processing for the CT data is completed. Then, the processed CT data is sent to the control unit 4, and the modeling processing unit 5 performs an additive manufacturing operation.
[0023]
The modeling processing unit 5 uses any of the well-known additive manufacturing methods such as the above-described SLS method and optical modeling method. For example, in the case of the SLS method, as an example, an additive manufacturing mechanism having a structure disclosed in Japanese Patent Publication No. 11-508322 is used.
[0024]
In the above embodiment, the texture imparting process is performed only on the CT data. This is because when CT data is used as modeling data, there is an article that is the source of the object, and it is often desired that the texture of the article be reproduced in the object. That's what it was. Therefore, the present invention is not necessarily limited to this, and even when the STL data is used as input data, a texture imparting process may be performed as necessary. However, in this case, the texture adding process is performed after converting the STL data into three-dimensional bitmap data.
[0025]
【The invention's effect】
As described above, according to the present invention, CT data can be directly used as modeling data in an additive manufacturing apparatus. In addition, it is possible to solve the problem of noise included in CT data and the gap between the tomographic image interval in CT data and the thickness of a thin layer in additive manufacturing due to the direct use of CT data as modeling data. Further, it is possible to give a texture to a modeled product which is important in the production of a duplicate product by additive manufacturing. Therefore, the present invention can greatly contribute to further expanding the usefulness of additive manufacturing.
[Brief description of the drawings]
FIG. 1 is a block diagram illustrating a configuration of an additive manufacturing apparatus according to an embodiment.
FIG. 2 is a diagram showing a flow of data processing on CT data.
FIG. 3 is a diagram schematically illustrating noise in CT data.
FIG. 4 is a diagram showing the contents of an inside offset process for CT data as an image.
FIG. 5 is a diagram showing a processing flow in the interlayer interpolation processing.
FIG. 6 is a diagram showing the contents of processing in the interlayer interpolation processing as an image.
FIG. 7 is a diagram showing the contents of processing in an interlayer interpolation processing by another method as an image.
[Explanation of symbols]
7 CT data input unit (input unit)
9 noise removing means 10 interlayer interpolation means 11 texture giving means C interpolated tomographic image P pixel S tomographic image

Claims (9)

The formation of a thin layer of molding material based on the input modeling data and the formation of a unit molding layer by selective curing of this thin layer are sequentially repeated, and a three-dimensional object is formed by stacking the unit molding layers of this repetitive formation. In the additive manufacturing device that is
A laminate comprising an input unit capable of directly inputting three-dimensional bitmap data obtained by imaging a plurality of tomographic images of an article serving as a source of a target object with a CT apparatus as the object forming data. Modeling equipment. 2. The apparatus according to claim 1, further comprising: a noise removing unit that removes noise included in the three-dimensional bitmap data by performing an inward offset after performing an inward offset on the three-dimensional bitmap data. 3. An additive manufacturing apparatus as described in the above. 3. The additive manufacturing apparatus according to claim 1, further comprising an interlayer interpolation unit configured to add an interpolation tomographic image for the thin layer between the tomographic images in the three-dimensional bitmap data. 4. The interlayer interpolation means performs a blurring process on each of the tomographic images. For the tomographic image subjected to the blurring process, for the tomographic image Sn and the tomographic image Sn + 1 adjacent to each other, the pixel of the tomographic image Sn and the position An average value corresponding to the number of layers to be interpolated with respect to the amount of change in luminance between the pixel of the tomographic image Sn + 1 to be obtained is determined, and the luminance of a pixel at a corresponding position in each of the interpolated tomographic images is set based on the average amount of change in luminance. Performing an average interpolation process, and performing a binarization process of binarizing the brightness of the pixels of each of the interpolated tomographic images with a predetermined threshold based on the brightness set in the average interpolation process. The additive manufacturing apparatus according to claim 3, wherein each of the interpolation tomographic images is set including the interpolation tomographic image. The interlayer interpolation unit regards the tomographic images adjacent to each other as a tomographic image Sn and a tomographic image Sn + 1, and regards the contour of the tomographic image Sn as an electrode of Y volt, while regarding the contour of the tomographic image Sn + 1 as an electrode of Y ′ volt. Then, the contour of the X-th interpolated tomographic image from the tomographic image Sn is determined as an equipotential surface of (| Y−Y ′ |) · X / Z (where Z is the number of layers of the interpolated tomographic image), whereby the interpolation is performed. The additive manufacturing apparatus according to claim 3, wherein a tomographic image is set. The formation of a thin layer of molding material based on the input modeling data and the formation of a unit molding layer by selective curing of this thin layer are sequentially repeated, and a three-dimensional object is formed by stacking the unit molding layers of this repetitive formation. In the additive manufacturing device that is
For the modeling data, a portion close to the surface of the target modeling object that is modeled on the basis of the modeling data, by adding or subtracting a desired pattern of pixels carrying an image to the surface of the target modeling object. An additive manufacturing apparatus comprising a texture imparting means for forming textured irregularities. As the modeling data, three-dimensional bitmap data obtained by imaging an article, which is the source of the target modeled object, into a large number of tomographic images with a CT device is input, and a modeling material based on the three-dimensional bitmap data is input. A control unit used in an additive manufacturing apparatus that forms a three-dimensional object by sequentially repeating the formation of a unit molding layer by forming a thin layer and selectively curing the thin layer, and stacking the unit molding layers of this repeated formation. Program
Noise removal processing for removing noise included in the three-dimensional bitmap data by applying an inward offset to the three-dimensional bitmap data and then performing an outer offset. Interlayer interpolation processing for adding an interpolation tomographic image for the thin layer between each tomographic image: a portion of the three-dimensional bitmap data that is close to the surface of a target object formed based on the three-dimensional bitmap data A program for controlling an additive manufacturing apparatus, which comprises at least one of texture adding processes for forming texture unevenness on the surface of the target object by adding or subtracting a desired pattern of pixels that carry an image. The interlayer interpolation process includes a step of performing a blurring process on each of the tomographic images. With respect to the tomographic image subjected to the blurring process, pixels of a tomographic image Sn and a position of the pixel of the tomographic image Sn + 1 which are adjacent to each other are located. An average value corresponding to the number of layers to be interpolated with respect to the amount of change in luminance between the pixel of the corresponding tomographic image Sn + 1 is obtained, and the luminance of a pixel at a corresponding position in each of the interpolated tomographic images is calculated based on the average amount of change in luminance. Performing an average interpolation process to be set, and performing a binarization process to binarize the brightness of the pixels of each of the interpolation tomographic images at a predetermined threshold based on the brightness set in the average interpolation process. The program according to claim 7, which is a process including: In the interlayer interpolation processing, the tomographic images adjacent to each other are regarded as a tomographic image Sn and a tomographic image Sn + 1, and the outline of the tomographic image Sn is regarded as an electrode of Y volt, while the outline of the tomographic image Sn + 1 is regarded as an electrode of Y ′ volt. Assuming the contour of the X-th interpolated tomographic image from the tomographic image Sn as the equipotential surface of (| Y−Y ′ |) · X / Z (where Z is the number of layers of the interpolated tomographic image), 8. The program according to claim 7, wherein the program is a process for setting an interpolation tomographic image.

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