JP2013088310A - Aluminum die casting component defect detection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an aluminum die casting component defect detection method capable of properly detecting an internal defect of an actual aluminum die casting component, specially a state of a fracture chill layer.SOLUTION: Image outputs of both an image obtained by ultrasonic crack inspection and an image obtained by X-ray CT are adjusted in advance such that defect areas to the same defect of the images are the same, an internal defect of a preset prescribed range of an aluminum die casting component is subjected to ultrasonic crack inspection and X-ray CT, the total sum of defect areas obtained by performing image analysis of the internal defect by ultrasonic crack inspection of the prescribed range is calculated as the total defect amount by ultrasonic crack inspection, the total sum of defect areas obtained by performing image analysis of the internal defect by X-ray CT of the prescribed range is calculated as the total defect amount by X-ray CT, and the total amount of a fracture chill layer of the preset prescribed range of the aluminum die casting component is calculated by subtracting the total defect amount by X-ray CT from the total defect amount by ultrasonic crack inspection.

Description

  The present invention relates to a method for detecting a defect in an aluminum die-cast part, and is suitable for detecting a defect such as a part used in an electric power steering device for a vehicle.

  For example, a column housing used for an electric power steering device of a vehicle is made of an aluminum die cast part. As a method for evaluating the strength of such an aluminum die-cast part, for example, there are methods described in Patent Document 1 and Patent Document 2 below. Among these, in Patent Document 1, for example, the cast product is irradiated with ultrasonic waves to detect the cast hole and the broken chill layer based on the sound wave information from the cast product, and the first internal defect three-dimensional distribution data is obtained. The X-ray CT measurement of the same cast product is performed to detect the cavities of the cast product from a plurality of cross-sectional images of the cast product, the second internal defect three-dimensional distribution data is acquired, and the first internal defect three-dimensional data is obtained. The distribution data and the second internal defect three-dimensional distribution data are compared to obtain the three-dimensional distribution data of the broken chill layer of the cast product. Moreover, in patent document 2, the test piece is cut out from the molten metal solidified in the runner part in the vicinity of the gate of the aluminum die cast part, and the fractured chill layer exposed on the test surface with respect to the area of the test surface that is the cut surface of the test piece is disclosed. The area ratio of the area is calculated, and the area ratio is compared with a predetermined reference value to determine the defect of the aluminum die cast part.

JP 2005-91288 A JP 2007-1111728 A

  However, the defect detection method of the aluminum die-cast part described in Patent Document 2 is merely an inspection of the solidified melt in the runner portion of the aluminum die-cast part, and is not a defect detection of the aluminum die-cast part itself. On the other hand, the defect detection method of the aluminum die-cast part described in Patent Document 1 enables evaluation of the aluminum die-cast part itself, but for an actual aluminum die-cast part, internal defect three-dimensional distribution data by ultrasonic flaw detection. It is extremely difficult to acquire the three-dimensional internal defect distribution data by X-ray CT and acquire the distribution data of the fractured chill layer by comparing the two.

  The present invention has been made paying attention to the above-mentioned problems, and is capable of properly detecting an internal defect of an actual aluminum die-cast part, in particular, a state of a broken chill layer. It is intended to provide a method.

  In order to solve the above problems, the defect detection method for an aluminum die-cast part according to the present invention is performed in advance so that the defect areas for the same defect in the image obtained by ultrasonic flaw detection and the image obtained by X-ray CT become equal. Adjust the image output, ultrasonically detect a predetermined range of internal defects in the aluminum die-cast part, analyze the image of the internal defects of the predetermined range of ultrasonic defects, determine the defect area, Calculate the total defect area of internal defects by ultrasonic flaw detection as the total amount of defects by ultrasonic flaw detection, perform X-ray CT of internal defects in a predetermined range of the aluminum die cast part, and analyze the internal defects by X-ray CT in the predetermined range Then, the defect area is obtained, the sum of the defect areas of the internal defects by the X-ray CT in the predetermined range is calculated as the total defect amount by the X-ray CT, and the total defect by the ultrasonic flaw detection is calculated. It is characterized in that to calculate the total amount of the fracture chill layer of preset predetermined range of said aluminum die-cast component by subtracting the defect amount by X-ray CT from.

Further, when calculating the sum of the defect areas of the internal defects by the ultrasonic flaw detection and the sum of the defect areas of the internal defects by the X-ray CT, the sum of the defect areas is calculated for a defect area having a predetermined defect area or more. It is characterized by seeking.
In addition, a histogram of the number of internal defects is created for each predetermined defect area when calculating the sum of defect areas of internal defects by ultrasonic flaw detection and the sum of defect areas of internal defects by X-ray CT. It is what.

  Thus, according to the defect detection of the aluminum die cast part of the present invention, the image output of both is performed in advance so that the defect area for the same defect of the image obtained by ultrasonic flaw detection and the image obtained by X-ray CT becomes equal. Adjust, ultrasonically detect a predetermined range of internal defects in the aluminum die-cast part, analyze the image of the internal defects of the predetermined range of ultrasonic flaws, determine the defect area, and by ultrasonic detection of the predetermined range The total defect area of the internal defects is calculated as the total amount of defects by ultrasonic flaw detection, X-ray CT is performed for internal defects in the same predetermined range of the aluminum die-cast part, and the internal defects by X-ray CT in the predetermined range are image analyzed The area is obtained, the sum of the defect areas of the internal defects by the X-ray CT in the predetermined range is calculated as the total defect amount by the X-ray CT, and the X-ray CT is calculated from the total defect amount by the ultrasonic flaw detection. Since it was decided to Recessed by subtracting the total amount to calculate the amount of breakage chill layer of preset predetermined range of aluminum die cast parts, internal defects of the aluminum die-cast part, in particular properly detect the state of breaking the chill layer.

Further, when obtaining the sum of defect areas of internal defects by ultrasonic flaw detection and the sum of defect areas of internal defects by X-ray CT, the sum of defect areas is obtained for defect areas having a predetermined defect area or more. Therefore, the internal defect of the aluminum die cast part, particularly the state of the fractured chill layer can be detected more appropriately.
In addition, when calculating the sum of the defect areas of the internal defects by ultrasonic flaw detection and the sum of the defect areas of the internal defects by X-ray CT, it was decided to create a histogram of the number of internal defects for each defect area in a predetermined range. Easily recognize the state of internal defects in aluminum die-cast parts.

It is explanatory drawing of the ultrasonic flaw detection which shows one Embodiment of the defect detection method of the aluminum die-casting part of this invention. It is explanatory drawing of the high stress part of the aluminum die-casting part of FIG. It is the image and cross-sectional photograph image of a fractured chill layer and a cast hole obtained by ultrasonic flaw detection. It is the image of a cast hole and a fracture | rupture chill layer by ultrasonic testing and X-ray CT with respect to a strip-shaped test piece, and the photograph image of a fracture | rupture chill layer. 2 is an image of a cast hole and a fractured chill layer by ultrasonic flaw detection and X-ray CT on a tensile test piece and a photographic image of a fracture surface. It is the image and photographic image of the artificial defect by ultrasonic flaw detection and X-ray CT. It is an image of a cast hole and a fractured chill layer by ultrasonic flaw detection and X-ray CT of an aluminum die cast part. It is the image and cross-sectional photographic image of a fractured chill layer by ultrasonic flaw detection and X-ray CT. It is explanatory drawing of the defect total amount which consists of the image of an internal defect by ultrasonic flaw, a defect area, a histogram of a defect area, and the sum total of a defect area. It is explanatory drawing of total amount calculation of a fracture | rupture chill layer.

Next, an embodiment of a defect detection method for an aluminum die cast part according to the present invention will be described with reference to the drawings.
FIG. 1 is an explanatory view of a six-axis movable ultrasonic flaw detector used in the defect detection method for aluminum die cast parts of the present embodiment, FIG. 1a is an overall view of the device, and FIG. 1b is a detail of a flaw detection object and a turntable. FIG. 1 and FIG. 1 c are explanatory diagrams of internal defect inspection. Reference numeral 1 in the figure denotes an aluminum die-cast part that is an object of internal defect detection in the present embodiment, for example, a column housing of an electric power steering apparatus.

  In this embodiment, the aluminum die-cast component 1 is mounted on the turntable 2, the probe (probe) 3 is moved downward from above while rotating the turntable 2, and the inside of the aluminum die-cast component 1 is spiraled Detect flaws. Since the aluminum die-cast part 1 of the present embodiment has a cylindrical portion, the inner peripheral surface of the cylindrical portion that has been machined is detected by an ultrasonic flaw detector to detect internal defects, and at the same time, X-ray CT also detects internal defects. . 2 is a development view of the inner peripheral surface of the aluminum die-cast part to be ultrasonically detected. Reference numeral 5 shown in FIG. 2 is a high-stress part obtained by stress analysis in advance, and the aluminum die-cast part 1 is destroyed. When evaluating the strength, the high stress portion 5 is preferably detected by an ultrasonic flaw detector to detect an internal defect, and the defect area is evaluated.

  The defect evaluation method for aluminum die-cast parts according to the present invention performs internal defect detection in a predetermined range including the above-described high stress portion, calculates the defect existence rate from the total amount of defects and the volume of the measurement range, Is expected to decrease. In particular, when a defect exists in a high stress portion, the strength is remarkably reduced. Below, the specific method of the defect detection method of the aluminum die-cast component of this embodiment is explained in full detail along the procedure of development. First, the ultrasonic flaw detection image portion where the fractured chill layer of the aluminum die cast part can be confirmed was observed by cross-section and verified. FIG. 3a shows a broken chill layer detected by ultrasonic flaw detection, and FIG. 3b shows a cross-sectional photographic image thereof. It is also known that an ultrasonic flaw can detect a cast hole. FIG. 3c shows a cast hole detected by ultrasonic flaw detection, and FIG. 3d shows a cross-sectional photographic image thereof. As is apparent from these drawings, in the ultrasonic flaw detection, both the fractured chill layer and the cast hole of the aluminum die cast part can be detected. Incidentally, although not shown here, ultrasonic flaw detection can also detect inclusions in the structure of aluminum die-cast parts.

  On the other hand, in the case of X-ray CT (Computed Tomography), it is possible to detect a broken hole but not a fractured chill layer. Images of the cast hole and the fractured chill layer were acquired. These images are shown in FIG. 4a. In addition, UT in the figure is an abbreviation for Ultrasonic Testing and indicates ultrasonic flaw detection. FIG. 4b shows a cross-sectional photographic image of the portion where the broken chill layer is detected by ultrasonic flaw detection in FIG. 4a. The broken chill layer shown in FIG. 4b was confirmed in the image portion where the broken chill layer was detected by ultrasonic flaw detection, but this broken chill layer could not be detected by X-ray CT.

  Next, a tensile test piece was made of the same aluminum material as that of the aluminum die cast part, and an internal defect in the parallel part (test part) was detected by X-ray CT and ultrasonic flaw detection. After detecting and detecting internal defects, the specimen was subjected to a tensile test and the fracture surface was observed. The internal defect image was examined by X-ray CT and ultrasonic flaw detection for each of the casting hole and fractured chill layer, which are the starting points of damage. Two types of results are shown in FIGS. 5a and 5b, respectively. FIG. 5a shows the breakage of the casting cavity starting point, and the casting defect observed on the fracture surface coincides with the internal defect image by X-ray CT and ultrasonic flaw detection, that is, the casting defect image. On the other hand, FIG. 5b shows a fracture at the origin of the fractured chill layer, and the fractured chill layer observed on the fracture surface coincides with the internal defect image by ultrasonic flaw detection, that is, the fractured chill layer image, but the internal defect by X-ray CT. It does not match the image. X-ray CT can also detect inclusions in the structure of aluminum die-cast parts.

  From these results, the X-ray CT flaw detection detects the void (and inclusions) from the sum of the defect areas of the internal defect image by the ultrasonic flaw detection that detects the void and the broken chill layer (and inclusions). It was found that the total defect area of the broken chill layer could be obtained by reducing the total defect area of the internal defect image. For this purpose, for the same internal defect, the defect area of the internal defect image by ultrasonic flaw detection and the defect area of the internal defect image by X-ray CT must be equivalent. Therefore, a circular hole (artificial defect) with a diameter of 0.5 mm as shown in Fig. 6a is made in a cylindrical test piece cut out from an aluminum die-cast part, and it is acquired as an image of X-ray CT and ultrasonic flaw detection. did. FIG. 6B is an artificial defect image by X-ray CT, and FIG. 6C is an artificial defect image by ultrasonic flaw detection. In the artificial defect image by X-ray CT, it was confirmed that the inner diameter of the detected artificial defect was 0.5 mm. In an artificial defect image by ultrasonic flaw detection, the threshold value for defect recognition can be adjusted to adjust the size of the defect image. Therefore, the threshold value is adjusted so that the inner diameter of the artificial defect is 0.5 mm. Thus, the output adjustment of the X-ray CT image and the ultrasonic flaw detection image is completed.

In FIG. 7, the ultrasonic flaw detection internal defect images of the same part as the X-ray CT internal defect image for an actual aluminum die cast part are shown side by side. The defect image by X-ray CT and the defect image by ultrasonic flaw detection coincide with each other for a casting hole having an area of 0.2 mm ² or more, but the broken chill layer is detected in the defect image by ultrasonic flaw detection although it is detected by X-ray. It is not detected in a defect image by CT. Among these, when the actual cross-sectional photograph was acquired about the upper part by which the fracture | rupture chill layer was detected with the defect image by ultrasonic flaw detection, as shown in FIG. 8, the fracture | rupture chill layer was confirmed.

Therefore, the following processing is performed on the internal defect image by ultrasonic flaw detection. In other words, ultrasonic flaw detection is performed on a predetermined range of an aluminum die-cast part, and an internal defect by ultrasonic flaw detection is performed with a predetermined threshold value obtained by using an artificial defect test piece having a diameter of φ0.5 mm as shown in FIG. 9A. The image is binarized, and the defect area of the internal defect having an area of 0.2 mm ² or more is calculated by image analysis software as shown in FIGS. 9b and 9c. For easy understanding, as shown in FIG. 9d, a histogram for each defect area is created for each test number of the aluminum die cast part. Then, for each test number of the aluminum die cast part, the sum of the defect areas is calculated as a total defect amount by ultrasonic flaw detection. The total amount of defects by ultrasonic flaw detection includes the defect area of the cast hole and the defect area of the fractured chill layer (and the defect area of inclusions).

Thus, for example, as shown in FIG. 10a, for a predetermined range of the cylindrical portion of the aluminum die cast parts subjected to ultrasonic flaw detection, after binarization as shown in FIG. 10b, the internal 0.2 mm ² or more as shown in Figure 10c The defect area of the defect is calculated. X-ray CT is performed on a predetermined range of the cylindrical portion of the aluminum die-cast part, and as shown in FIG. 10d, an internal defect image by ultrasonic flaw detection and an internal defect image by X-ray CT are obtained for each test number of the predetermined range of the same part. Image analysis is performed to calculate the total defect area as the total defect amount. In this case, no. 1-3 are fractured chill layers, It can be determined that 4 is a cast hole. Next, as shown in FIG. 10e, the total amount of fracture chill layers in a predetermined range of the aluminum die cast part is calculated by subtracting the total amount of defects by X-ray CT from the total amount of defects by ultrasonic flaw detection.

By the way, the reason why the defect area of the internal defect is 0.2 mm ² or more is that the internal defect having a defect area of less than 0.2 mm ² has no problem in strength, and at least the defect area of less than 0.2 mm ² at present. This is due to two points that the internal defect of the above cannot be accurately detected by X-ray CT. In ultrasonic flaw detection, internal defects having a defect area of less than 0.2 mm ² can also be detected. Therefore, if the defect total amount by X-ray CT is simply subtracted from the total defect amount by ultrasonic flaw detection without limiting the defect area of the internal defect to 0.2 mm ² or more, it is less than 0.2 mm ² detected only by ultrasonic flaw detection. Therefore, an internal defect having a defect area of 10 mm, that is, a cast hole or a fractured chill layer, which is not obvious and has no problem in strength, is evaluated. Therefore, the defect evaluation method was established by setting the defect area of the internal defect to 0.2 mm ² or more.

  As described above, in the defect detection method of the aluminum die cast part according to the present embodiment, both of the images are obtained in advance so that the defect areas of the image obtained by ultrasonic flaw detection and the image obtained by X-ray CT with respect to the artificial defect (identical defect) are equal. Adjust the image output, ultrasonically detect a predetermined range of internal defects in the aluminum die-cast part, analyze the image of the internal defects of the predetermined range of ultrasonic defects, determine the defect area, The sum of the defect areas of the internal defects due to ultrasonic flaw detection is calculated as the total amount of defects due to ultrasonic flaw detection, X-ray CT is performed on the internal defects in the same predetermined range of the aluminum die cast part, and the internal defects due to the X-ray CT within the predetermined range are imaged, for example Analyze the defect area, calculate the total defect area of the internal defects by X-ray CT in the predetermined range as the total defect amount by X-ray CT, By subtracting the total amount of defects by X-ray CT from the total amount and calculating the total amount of fracture chill layer in a predetermined range of the aluminum die cast part, the internal defect of the aluminum die cast part, especially the state of the fracture chill layer, can be detected properly can do.

In addition, when calculating the sum of defect areas of internal defects by ultrasonic flaw detection and the sum of defect areas of internal defects by X-ray CT, the sum of defect areas should be calculated for defect areas having a predetermined defect area or more. Thus, the internal defect of the aluminum die cast part, in particular, the state of the fractured chill layer can be detected more appropriately.
In addition, in determining the sum of the defect areas of the internal defects by ultrasonic flaw detection and the sum of the defect areas of the internal defects by X-ray CT, a histogram of the number of internal defects is created for each defect area in a predetermined range. Easily recognize the state of internal defects in die-cast parts. Moreover, it is possible to confirm in which part of the part the defect is distributed from the image obtained by ultrasonic flaw detection and X-ray CT.

1 is an aluminum die-cast part 2 is a turntable 3 is a probe 5 is a high stress part

Claims (3)

  Adjust the image output of both in advance so that the defect area for the same defect of the image obtained by ultrasonic flaw detection and the image obtained by X-ray CT is equal, and the internal defect within a predetermined range of the aluminum die cast part Ultrasonic flaw detection, image analysis of the internal defects due to the ultrasonic inspection of the predetermined range to determine the defect area, and the total defect area of the internal defects due to the ultrasonic inspection of the predetermined range is calculated as the total amount of defects by the ultrasonic inspection , X-ray CT of an internal defect in a predetermined range of the aluminum die cast part, image analysis of the internal defect by the X-ray CT in the predetermined range to obtain a defect area, defect area of the internal defect by the X-ray CT in the predetermined range Is calculated as the total amount of defects by X-ray CT, the total amount of defects by X-ray CT is subtracted from the total amount of defects by ultrasonic flaw detection, and the aluminum die cast part is preset. Defect detection method of an aluminum die cast parts and calculates the total amount of breakage chilled layer of predetermined ranges.   When calculating the sum of the defect areas of the internal defects by the ultrasonic flaw detection and the sum of the defect areas of the internal defects by the X-ray CT, calculating the sum of the defect areas for the defect areas having a predetermined defect area or more. The method for detecting a defect of an aluminum die cast part according to claim 1.   A histogram of the number of internal defects is created for each defect area in a predetermined range when obtaining the sum of the defect areas of the internal defects by the ultrasonic flaw detection and the sum of the defect areas of the internal defects by the X-ray CT. The defect detection method of the aluminum die-casting part of Claim 1 or 2.

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