JPS6410781B2 - - Google Patents

Description

[Detailed description of the invention]

The present invention relates to a fracture surface analysis method for cast iron that enables rapid determination of the material strength of cast iron, which is a casting material. Cast iron includes gray cast iron with flaky graphite precipitated, spheroidal graphite cast iron with spheroidal graphite precipitated, and an intermediate type between these gray cast irons and spheroidal graphite cast iron, in which graphite is precipitated in the form of incomplete spheres, corals, or fibers. There are intermediate-type graphite cast irons (the definition of structure, material, etc. is still unclear, so in this specification, it is referred to as intermediate-type graphite cast iron), and fracture surface analysis methods are usually adopted to determine the material properties of these cast irons. There is. As is well known, fracture surface analysis is a method in which a chisel is inserted near one end of the material and the material is broken with a hammer, etc., and the material quality, structure, and internal defects can be determined from the appearance of the fracture surface. At times, the quality of the material was determined by manually polishing the sample and observing its structure under a microscope. Of course, this makes it impossible to quickly determine materials for many products, and it is difficult to say that objective and unified determinations are being made. This invention was made in view of the above circumstances.
The object of the present invention is to provide a method for analyzing fracture surfaces of cast iron, which allows the tensile strength of cast iron materials to be quickly determined based on comprehensive judgment. That is, this invention focuses on the fact that there is a strong correlation between the ratio of the black part of the fracture surface of a cast material to the total fracture surface area and the tensile strength of the cast material, and based on this correlation, it is possible to determine the tensile strength of cast iron. Specifically, the fracture surface of the cast iron is read and scanned with a video camera, etc., and this is extracted as an image signal, and this image signal is used as a white or black 2
After creating a value image, use a microcomputer or the like to calculate the area ratio occupied by, for example, a black part in the binary image, and further substitute, for example, the calculated area ratio into the preset relational expression of the above correlation. The tensile strength of the cast iron is calculated by DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The method for analyzing fracture surfaces of cast iron according to the present invention will be described in detail below with reference to embodiments shown in the accompanying drawings. In this example, the above-mentioned intermediate type graphite cast iron was used as a sample for material determination. Intermediate graphite cast iron has recently attracted attention because it has better castability and better thermal conductivity than completely spherical graphite cast iron, but from a manufacturing standpoint, it is easier to make it completely spherical, and it is difficult to make the entire casting. It is rather difficult to use intermediate graphite for all materials, and requires considerable effort in manufacturing, so determining the quality of the material after manufacturing is particularly important in order to ensure stable quality. Figure 1 shows an enlarged photograph of the fracture surface of intermediate graphite cast iron. In FIG. 1, the black parts of each fracture surface have a ferrite composition, and the white parts have a pearlite composition.
Generally, a ferrite structure has a lower tensile strength than a pearlite structure. Therefore, we investigated the correlation between the percentage of the total fracture surface area of the portion identified as black with a predetermined threshold (hereinafter referred to as black fracture surface ratio) and the tensile strength of the intermediate graphite cast iron.
It was found that there is a strong correlation between these (correlation coefficient of 0.82 or higher). Figure 2 approximates the above correlation to a linear relationship, and according to Figure 2, the relationship between the black fracture surface ratio and tensile strength of each intermediate type graphite cast iron shown in Figures 1a to 1e. is shown in the table below.

[Table] Next, FIG. 3 shows a specific configuration example for carrying out the cast iron fracture surface analysis method according to the present invention. In Fig. 3, 1 is a sample of intermediate graphite cast iron with a diameter of about 10 to 30 mm, 2 is a video camera, 3 is a first monitor, 4 is a second monitor, and 10 is an analog
An image processing unit 2 comprising a digital (A/D) conversion section 11, an input/output section 12, and a memory 13.
0 is the input/output unit 21, CPU 22, memory 23,
This is a so-called microcomputer that includes a printer 24 and the like. The image processing unit 10 is a unit that connects the video camera 2 and the microcomputer 20 to perform image analysis and image processing. It is stored as digital data so that it can be processed by The digitally converted image data is stored in one screen of 256 x 256 pixels, each with 16 brightness levels (4 bits). The microcomputer 20 converts the digitally converted image data into the 16 brightness levels into a black or white binary image using an appropriate brightness level as a threshold, and calculates the black fracture rate in the binary image. Then, by substituting the calculation result into the relational expression between the tensile strength and black fracture ratio of intermediate graphite cast iron, which was set in advance based on the measurement results obtained from a large number of samples, the estimated strength of intermediate graphite cast iron was calculated. Derive. Next, the operation of the embodiment shown in FIG. 3 will be explained with reference to FIG. 4 and the like. Note that a in Fig. 4 shows a simple example of the fracture surface of intermediate graphite cast iron. It shows.
Also, the horizontal axis of the graphs shown in Figures 4b to 4d is the 4th axis.
This corresponds to scanning line X in figure a. First, a chisel is placed in a sample 1 with a diameter of 10 to 30 mm taken from a ladle and broken with a hammer or the like.
Then, this sample 1 is placed on a sample stage, and positioned directly below the lens of the video camera 1 using a suitable jig. Next, video camera 2
The fracture surface image of the sample 1 is read by the , and the read image is input to the first monitor 3 . This first
The operator adjusts the aperture, focus, etc. of the video camera 2 while viewing the image on the monitor 3. At this time, the image actually projected on the first monitor 3 is
It is an analog image as shown in the figure, and the camera 2
The brightness distribution of the output is as shown in FIG. 4b. Thereafter, the image signal read by the video camera 2 is input to the A/D converter 11 of the image processing unit 10. The signal taken into the A/D converter 11 is
The divided signal is divided into 256 x 256 pixels, and the divided signal is converted into 16 values into 16 brightness levels from pure white (brightness 15) to pure black (brightness 0) according to the black and white shading, as shown in Figure 4c. Ru. The image signal divided into 16 brightness levels is input to the memory 13 via the input/output section 12 and stored in the memory 13. Further, this 16-valued image signal is input to the second monitor 4 via the input/output section 12 and displayed on the screen of the second monitor 4. Next, the 16-valued image signal stored in the memory 13 is input to the CPU 22 via the input/output section 21 of the microcomputer 20. CPU22
The image signals input to the image signal processing apparatus 2 are processed according to a program stored in the memory 23 in advance. In this process, first, the 16-valued image signal is set to a predetermined brightness level, for example, a brightness of 7 is set as a threshold value, and parts smaller than the threshold value are pure black (brightness 0), and parts larger than the threshold value are black. A portion or an equal portion is converted into a binary signal of black or white, such as pure white (luminance 15). 4d is an example of binarization using the luminance level of FIG. 4c as a threshold, and FIG. 4e is an example of binarization using the luminance level of FIG. 4c as a threshold. In this way,
The binarized image signal is sent to input/output sections 21 and 12.
The signal is inputted to the memory 13 via the memory 13, and the stored contents of the memory 13 are rewritten into a signal corresponding to a binary image. This binarized image signal is then inputted again to the second monitor 4 via the input/output unit 12 and displayed on the screen of the second monitor 4 (see reference diagram:
(a to e in this reference figure correspond to a to e in the photograph in FIG. 1 above, respectively). Along with this, the microcomputer 20
The CPU 22 calculates, for example, the ratio of the black portion of the sample 1 to the total fracture surface area (black fracture surface ratio) based on the image signal binarized into black or white. The program stored in the memory 23 includes a program related to the relational expression (see Fig. 2) between the tensile strength of intermediate graphite cast iron and the above-mentioned black fracture surface ratio, which was set based on the measurement results of a large number of samples as described above. is also included. The CPU 22 derives the estimated tensile strength of the sample 1 based on this program and the calculated black fracture ratio of the sample 1, and outputs this to the printer 24. The operator can immediately know the estimated strength of the sample 1 by simply looking at the output content of the printer 24. In the field of image processing, brightness levels can be divided into 2 levels, 4 levels, 8 levels, 16 levels, 32 levels,
It is possible to divide it into 64 levels, 128 levels, 256 levels, and 512 levels, but considering the influence of external light, cost, processing speed, etc., it is considered that 16 levels or higher is unnecessary. Of course, since the image signal ultimately becomes a binary signal, it is of course possible to employ a two-brightness level image processing unit with a predetermined brightness level as the threshold. Furthermore, although intermediate graphite cast iron was used as the sample in this example, it goes without saying that the present invention can also be applied to determining the tensile strength of other spheroidal graphite cast irons or gray cast irons. Furthermore, the present invention is particularly effective if incorporated into the material testing process of the casting manufacturing process. For example, if the casting material to be tested is sequentially passed directly under a video camera, and the material strength of the passed material is automatically output from the printer, the tester can simply look at the content output from the printer. can easily identify defective materials. As explained above, according to the cast iron fracture surface analysis method according to the present invention, (1) the tensile strength of cast iron can be quickly determined based on comprehensive judgment. (2) It can be an effective method for determining material properties for a large number of samples. and other excellent effects.

[Brief explanation of drawings]

Figure 1 is a photograph showing the fracture surface of intermediate graphite cast iron, Figure 2 is a graph showing the relationship between the tensile strength and black fracture ratio of intermediate graphite cast iron, and Figure 3 is an analysis of the fracture surface of cast iron according to the present invention. A block diagram showing one embodiment of the method, FIG. 4 is an explanatory diagram for explaining the operation of the embodiment shown in FIG. 3. 1...Sample, 2...Video camera, 3...
First monitor, 4... Second monitor, 10... Image processing unit, 11... A/D conversion section, 12, 21
...Input/output section, 13, 23...Memory, 20...
Microcomputer, 22...CPU, 24...
...Printer.

Claims (1)

[Claims] 1 In a cast iron fracture surface analysis method that derives the tensile strength of the cast iron by analyzing the cast iron fracture surface, the fracture surface of the cast iron is read and scanned to extract it as an image signal, and the extracted image signal is set to a predetermined brightness. After creating a white or black binary image using the level as a threshold value, calculate the area ratio occupied by the white part or black part in the binary image, and then calculate the tensile strength of cast iron with the calculated area ratio preset. 1. A fracture surface analysis method for cast iron, characterized in that the tensile strength of the cast iron is derived by relating it to the correlation between the area ratio and the area ratio.