Analysis method for measuring porosity in weld bead cross section

Abstract

To provide an analysis method for porosity measurement in a weld bead cross section capable of obtaining a quality result at a high level by suppressing variations in measurement results.SOLUTION: An analysis TP production step of producing an analysis TP (test piece) from a weld zone of a work welded with a non-ferrous material; an image input step of inputting a weld bead cross-sectional image obtained by imaging the weld bead cross-section in the analysis TP to an analysis program; and a data generation step of generating an analysis TP (test piece) from the analysis TP using bead shape learning data previously acquired; A pre-processing step of generating a mask image of a weld bead in a weld bead cross-sectional image, a post-processing step of superimposing the weld bead cross-sectional image and the mask image to generate a processed image in which a portion other than the weld bead is cut out, and a porosity measurement step of measuring a porosity of the weld bead from the processed image, in which the learning data is a combination of a plurality of weld bead cross-sectional images obtained by polishing the weld bead cross-section with a plurality of abrasives and a resolution of the weld bead cross-sectional image.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to analytical methods for measuring porosity in a weld bead cross section. [Background technology]

[0002] The following Patent Document 1 discloses an analysis method for calculating the probability of hole occurrence based on an image of a weld bead and learning data, and determining whether a bead has passed or failed an appearance inspection. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 7308461 Summary of the Invention [Problem to be solved by the invention]

[0004] Typically, the interior of a weld bead is inspected based on the porosity analyzed from a captured image of the weld bead cross section. When analyzing a captured image of the weld bead cross section, the captured image must be binarized and then cut out from the image any areas other than the weld bead, which increases the number of processing steps. Furthermore, because this process is performed visually, there are concerns that the measurement results may vary depending on the operator. This is presumably due to the fact that the raw materials used for the welding consumable and the base metal are the same, and therefore there is no significant difference in color. [Means for solving the problem]

[0005] In order to solve the above problem, an analysis method for measuring porosity in a weld bead cross section according to one embodiment includes the following steps: An analytical method for measuring porosity in a weld bead cross section, comprising: a test piece (TP) preparation process in which the welded portion of a workpiece welded with a non-ferrous material is cut to expose the weld bead cross section, which is then filled with resin and polished with an abrasive to prepare a test piece (TP) for analysis; an image input process of inputting a weld bead cross-sectional image obtained by capturing the weld bead cross-section on the analysis TP into an analysis program; a pre-processing step of generating a mask image of the weld bead in the weld bead cross-sectional image using previously acquired learning data of the bead shape; a post-processing step of superimposing the weld bead cross-sectional image and the mask image to generate a processed image in which portions that are not weld beads are cut out; a porosity measuring step of measuring the porosity of the weld bead from the processed image, The learning data is a combination of a plurality of weld bead cross-sectional images obtained by polishing the weld bead cross-section with a plurality of abrasives, and the resolution of the weld bead cross-sectional images. [Effects of the Invention]

[0006] According to the present invention, it is possible to provide an analytical method for measuring porosity in a weld bead cross section, which can suppress variation in measurement results and obtain results of higher quality. [Brief explanation of the drawings]

[0007] [Figure 1] 1 is an example of a flowchart relating to an analysis method for measuring porosity in a weld bead cross section according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0008] (Analysis method for measuring porosity in weld bead cross section)

[0009] The analytical method for measuring the porosity in a weld bead cross section includes an analytical TP preparation step, an image input step, a pre-processing step, a post-processing step, and a porosity measurement step, and may include other steps as necessary.

[0010] The analytical method for measuring porosity in a weld bead cross section according to the present invention will be specifically described with reference to Fig. 1. Fig. 1 is an example of a flowchart relating to the analytical method for measuring porosity in a weld bead cross section according to the present invention.

[0011] The analytical method for measuring porosity in the cross section of a weld bead of the present invention begins by randomly selecting several workpieces to be inspected for quality from a group of workpieces welded with non-ferrous materials, and subjecting them to a process of preparing test pieces (TPs) for analysis.

[0012] The analysis TP preparation process involves cutting the welded portion of a workpiece welded with non-ferrous material, filling the exposed weld bead cross section with resin, and then polishing it with an abrasive to prepare an analysis TP. The steps are explained below.

[0013] <Step 1> First, the welded portion of the workpiece, which has been welded with a non-ferrous material, is cut to expose the cross section of the weld bead. The non-ferrous material is not particularly limited as long as it is a material that is generally used in welding, and can be appropriately selected depending on the purpose.

[0014] <Step 2> Next, the exposed cross section of the weld bead is filled with resin so as to include the resin. There are no particular restrictions on the resin, and it can be selected appropriately depending on the purpose, as long as it is a resin that is generally used for image analysis.

[0015] <Step 3> Next, the cross section of the resin-filled weld bead is polished using an abrasive. Through this process, scratches and dirt on the cross section of the weld bead can be removed.

[0016] <Step 4> Next, the polished cross section of the weld bead is imaged to obtain weld bead cross section image data.

[0017] Once the TP for analysis is prepared in the TP for analysis preparation step, the porosity analysis step is carried out. The porosity analysis step includes an image input step, a pre-processing step, a post-processing step, and a porosity measurement step.

[0018] <Step 5> In the porosity analysis step, first, an image input step is performed in which a weld bead cross-sectional image obtained by capturing an image of the weld bead cross-section on the analysis TP is input into the analysis program.

[0019] <Step 6> Next, a pre-processing step is performed in which a mask image of the weld bead in the weld bead cross-sectional image is generated using previously acquired bead shape training data. The bead shape training data is a combination of multiple weld bead cross-sectional images obtained by polishing the weld bead cross-section with multiple abrasives and the resolution of the weld bead cross-sectional image. This configuration improves the accuracy of detecting porosity in the weld bead cross-sectional image.

[0020] Here, the multiple abrasives used when acquiring the learning data are not particularly limited and can be selected appropriately depending on the purpose, and examples include abrasives a to c shown in Table 1 below. When acquiring the learning data, these abrasives may be used alone or in combination, but from the viewpoint of improving the accuracy of detecting pores in the weld bead cross-sectional image, it is preferable to use multiple abrasives in combination.

[0021] [Table 1]

[0022] <Step 7> Next, a post-processing step is performed in which the weld bead cross-sectional image and the mask image are superimposed to generate a processed image in which the portions that are not weld beads are cut out.

[0023] <Step 8> Next, a porosity measuring step is carried out to measure the porosity of the weld bead from the processed image obtained in the post-processing step.

[0024] The welding conditions may be changed as appropriate by providing feedback based on the porosity value of the obtained weld bead. By providing such feedback and adjusting the condition settings one by one, it is possible to prevent the occurrence of defective products and improve quality.

[0025] Although the preferred embodiments of the present invention have been described in detail above, the present invention is not limited to these embodiments, and various modifications and changes are possible within the scope of the gist of the present invention described in the claims.

Claims

[Claim 1] An analytical method for measuring porosity in a weld bead cross section, comprising: a test piece (TP) preparation process in which a welded portion of a workpiece welded with a non-ferrous material is cut to expose the weld bead cross section, which is then filled with resin and polished with an abrasive to prepare a test piece (TP) for analysis; an image input process of inputting a weld bead cross-sectional image obtained by capturing an image of the weld bead cross-section on the analysis TP into an analysis program; a pre-processing step of generating a mask image of the weld bead in the weld bead cross-sectional image using previously acquired learning data of the bead shape; a post-processing step of superimposing the weld bead cross-sectional image and the mask image to generate a processed image in which portions that are not weld beads are cut out; a porosity measuring step of measuring the porosity of the weld bead from the processed image, An analysis method characterized in that the learning data is a combination of multiple weld bead cross-sectional images obtained by polishing the weld bead cross-section with multiple abrasives and the resolution of the weld bead cross-sectional images.

Images