Metal casting rapid detection device and method based on ultrasonic technology

Abstract

The present invention relates to the field of ultrasonic detection technology, and specifically to a metal casting rapid detection device and method based on ultrasonic technology, including using an ultrasonic flaw detector to perform preliminary detection and analysis on a number of detection points to obtain abnormal points; performing secondary detection and analysis on the area near the abnormal point to obtain the defect area; performing defect analysis based on the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area; judging the defect type of all defect areas to obtain the quality detection result of the metal casting. In the present invention, the position relationship and amplitude relationship of the reflected wave in the defect area are analyzed to confirm whether it is caused by the structure of the metal casting itself, which effectively improves the accuracy of ultrasonic detection in metal casting defect detection and lays a solid foundation for the quality assessment of metal castings.

Description

Technical Field

[0001] The invention relates to the technical field of ultrasonic detection, and in particular to a metal casting rapid detection device and method based on ultrasonic technology. Background Art

[0002] In the production process of metal castings, it is impossible to ensure that every link is in an ideal state. Therefore, in the actual production process, defects such as pores and cracks will inevitably occur. If the defects are located on the surface of the metal casting, they can be quickly discovered, but the defects inside the metal casting cannot be detected through image recognition.

[0003] Ultrasonic testing is a non-destructive testing method that uses the probe of an ultrasonic flaw detector to be close to the surface of a metal casting and emit ultrasonic waves into the metal casting. When ultrasonic waves propagate inside the metal, if they encounter metal defects such as holes and inclusions, they will be reflected back to the probe. The propagation of ultrasonic waves inside the metal casting is then displayed on the display screen of the ultrasonic flaw detector. However, since some metal castings will retain smaller holes according to the model diagram, it is easy to regard some of the smaller holes as metal casting defects during ultrasonic testing. However, it is impossible to directly distinguish whether it is a hole left in the metal casting or a defect inside the metal casting based on the reflected wave. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a metal casting rapid detection device and method based on ultrasonic technology to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present application provides a method for rapid detection of metal castings based on ultrasonic technology, the method comprising: using an ultrasonic flaw detector to perform preliminary detection and analysis on several detection points of the metal casting to obtain several abnormal points, the results of the preliminary detection include ultrasonic data corresponding to each of the detection points, and the abnormal points are detection points where abnormalities exist in the ultrasonic data; using an ultrasonic flaw detector to perform secondary detection and analysis on each group of measurement cells of the metal casting to obtain a defect area, a group of the measurement cells is obtained by dividing an area where an abnormal point is located according to a preset division rule, there is a correlation between two adjacent measurement cells in the defect area, and the correlation is calculated by the time and amplitude corresponding to the ultrasonic internal reflection wave; defect analysis is performed according to the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area; and quality inspection results of the metal casting are obtained by judging the defect types of all defect areas.

[0006] In combination with the first aspect, in a possible implementation method, an ultrasonic flaw detector is used to perform preliminary detection and analysis on several detection points of a metal casting to obtain several abnormal points, including: using an ultrasonic flaw detector to measure several detection points of the metal casting to obtain ultrasonic data corresponding to each detection point; extracting waveform data from the ultrasonic data corresponding to each of the detection points to obtain at least two ultrasonic waveforms contained in each ultrasonic data; confirming in all the ultrasonic waveforms according to preset waveform data to obtain an original pulse in each ultrasonic data; comparing the recording time of the original pulse with the recording time of other waveform data to obtain whether the detection point is an abnormal point, the ultrasonic data corresponding to the abnormal point includes an original pulse, a first reflected wave and a bottom reflected wave, the recording time corresponding to the first reflected wave is greater than the original pulse, and the recording time corresponding to the bottom reflected wave is greater than the first reflected wave.

[0007] In combination with the first aspect, in a possible implementation method, an ultrasonic flaw detector is used to perform secondary inspection and analysis on each group of measurement cells of the metal casting to obtain a defect area, including: measuring and analyzing adjacent measurement cell groups with an initial measurement cell as the center to obtain several defect correlation parameters, the initial measurement cell is the cell where the abnormal point is located, and the adjacent measurement cell group is the measurement cell adjacent to the initial measurement cell, and each defect correlation parameter is calculated by a preset correlation parameter calculation formula, the initial measurement cell and the ultrasonic data corresponding to a measurement cell in the adjacent measurement cell group; based on a preset defect threshold and a size relationship judgment and analysis of all the defect correlation parameters, the defect area is obtained.

[0008] In combination with the first aspect, in a possible implementation manner, the preset defect threshold is 0.3.

[0009] In combination with the first aspect, in a possible implementation, defect analysis is performed according to the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area, including: grouping the cells measured in a defect area to obtain a plurality of cell groups, wherein the cell group includes three measurement cells, namely a first cell, a second cell and a third cell, and the second cell is adjacent to the first cell and the third cell respectively; based on a preset correlation parameter calculation formula and the ultrasonic data corresponding to each of the cell groups, a defect correlation parameter set corresponding to each of the cell groups is obtained, wherein the defect correlation parameter set includes the defect correlation parameters of the second cell and the first cell and the third cell. Defect correlation parameters between the second cell and the third cell; based on the ultrasonic wave velocity and the ultrasonic data corresponding to the measuring cell, the depth corresponding to each measuring cell is obtained; based on the depth calculation corresponding to each measuring cell, a line segment vector set corresponding to each of the cell groups is obtained, and the line segment vector set includes the depth vector from the second cell to the first cell and the depth vector from the second cell to the third cell; based on the preset smoothing coefficient calculation formula, the line segment vector set corresponding to each of the cell groups and the defect correlation parameter set, the smoothing coefficient corresponding to each of the cell groups is obtained; based on the preset smoothing threshold and the smoothing coefficient corresponding to each of the cell groups, the defect type of each defect area is obtained.

[0010] In combination with the first aspect, in a possible implementation method, the defect type of each defect area is obtained based on a preset leveling threshold and a leveling coefficient corresponding to each group of the unit groups, including: calculating the absolute value of the difference between each leveling coefficient and 1, respectively, and recording it as a difference value; counting the number of all the difference values ​​that are less than the preset leveling threshold, and recording it as a first value; judging whether the first value is equal to the total number of unit groups, if so, the defect type is the self-structure, if not, the defect type is a structural defect.

[0011] In combination with the first aspect, in a possible implementation manner, the preset smoothing threshold is 0.1.

[0012] In combination with the first aspect, in a possible implementation, the defect type includes structural defects, and the quality inspection result of the metal casting is obtained according to the defect type judgment of all defect areas, including: counting the number of defect areas whose defect type is structural defects, recorded as the number of small defects; obtaining the number of surface defects; calculating the sum of the number of surface defects and the number of small defects, recorded as the total number of defects; calculating based on the number of surface defects and the total number of defects, obtaining the surface defect ratio; when the surface defect ratio and the total number of defects meet a first logical condition, the quality of the metal casting is poor, and the first logical condition includes that the surface defect ratio is greater than or equal to two-thirds and the total number of defects is greater than or equal to 9; when the surface defect ratio and the total number of defects meet a second logical condition, the quality of the metal casting is good, and the second logical condition includes that the surface defect ratio is equal to zero and the total number of defects is less than 4; when the surface defect ratio and the total number of defects do not meet both the first logical condition and the second logical condition, the quality of the metal casting is general.

[0013] In the second aspect, the present application also provides a rapid detection device for metal castings based on ultrasonic technology, including: a preliminary detection unit, used to use an ultrasonic flaw detector to perform preliminary detection and analysis on several detection points of the metal casting to obtain several abnormal points, the preliminary detection results include ultrasonic data corresponding to each of the detection points, and the abnormal points are detection points with abnormalities in the ultrasonic data; a secondary detection unit, used to use an ultrasonic flaw detector to perform secondary detection and analysis on each group of measurement cells of the metal casting to obtain a defect area, a group of the measurement cells is obtained by dividing the area where an abnormal point is located according to a preset division rule, and there is a correlation between two adjacent measurement cells in the defect area, and the correlation is calculated by the corresponding time and amplitude of the ultrasonic wave; a defect analysis detection unit, used to perform defect analysis according to the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area; a logical judgment unit, used to judge according to the defect types of all defect areas to obtain the quality inspection result of the metal casting.

[0014] In combination with the second aspect, in a possible implementation, the secondary detection unit includes: a measurement and analysis unit, which is used to measure and analyze adjacent measurement cell groups with an initial measurement cell as the center to obtain several defect correlation parameters, the initial measurement cell is the cell where the abnormal point is located, and the adjacent measurement cell group is the measurement cell adjacent to the initial measurement cell, and each defect correlation parameter is calculated by a preset correlation parameter calculation formula, the initial measurement cell and the ultrasonic data corresponding to a measurement cell in the adjacent measurement cell group; a judgment and analysis unit, which is used to judge and analyze based on a preset defect threshold and the size relationship of all the defect correlation parameters to obtain a defect area.

[0015] The present invention has the following beneficial effects:

[0016] In the present invention, the metal casting is first inspected by an ultrasonic flaw detector to confirm the abnormal points where the ultrasonic wave has problems; then the abnormal points and adjacent inspection points are inspected, and combined with the attenuation change of the ultrasonic wave to confirm whether they belong to the same defect area, and finally combined with the change of the ultrasonic wave in the same defect area to confirm whether the defect is an actual defect. Compared with the method of directly judging based on the reflected wave graph, the present invention can more accurately judge whether the defect area detected by the ultrasonic wave belongs to the hole left in the metal casting or the defect inside the metal casting by mining and analyzing the correlation between the appearance time and amplitude of the ultrasonic wave. It can more effectively judge the quality type of the metal casting. It also expands the application of ultrasonic flaw detectors in metal casting inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A schematic diagram of a process of a rapid detection method for metal castings based on ultrasonic technology provided in one embodiment 1 of the present invention;

[0019] Figure 2 A schematic flow chart of step S1 provided in Example 1 of the present invention;

[0020] Figure 3 This is a schematic diagram of ultrasonic echo data according to Embodiment 1 of the present invention;

[0021] Figure 4 A schematic diagram of the flow of step S2 provided in Example 1 of the present invention;

[0022] Figure 5 A schematic flow chart of step S3 provided in Example 1 of the present invention;

[0023] Figure 6 A schematic flow chart of step S4 provided in Example 1 of the present invention;

[0024] Figure 7 This is a schematic diagram of the structure of the metal casting rapid detection device based on ultrasonic technology described in Example 2 of the present invention. DETAILED DESCRIPTION

[0025] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a metal casting rapid detection device and method based on ultrasonic technology proposed by the present invention, its specific implementation, structure, features and effects, in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0026] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0027] Embodiment 1:

[0028] The specific scheme of the metal casting rapid detection method based on ultrasonic technology provided by the present invention is described in detail below with reference to the accompanying drawings.

[0029] See also Figure 1 , which shows a flow chart of a metal casting rapid detection method based on ultrasonic technology provided by an embodiment of the present invention, specifically including step S1, step S2, step S3 and step S4.

[0030] S1. Use an ultrasonic flaw detector to perform preliminary detection and analysis on several detection points of the metal casting to obtain several abnormal points, wherein the results of the preliminary detection include ultrasonic data corresponding to each of the detection points, and the abnormal points are detection points where abnormalities exist in the ultrasonic data.

[0031] Specifically, in the present invention, the probe of the ultrasonic flaw detector is placed on the surface of the metal casting and emits ultrasonic waves, which will propagate inside the metal. If the metal casting does not have defects such as hollowness or inclusions, the ultrasonic wave will propagate to the bottom surface of the metal casting detection position and then reflect to generate reflected waves, and finally return to the probe of the ultrasonic flaw detector. On the contrary, if there is a hollow or inclusion inside the metal casting, the ultrasonic wave will be reflected in advance at the hollow or inclusion position before reaching the bottom surface during propagation, and the reflected wave will be returned to the probe.

[0032] At the same time, it should be noted that some metal castings may have thicker areas. When testing such thicker areas, it is necessary to adjust the ultrasonic sensitivity parameters so that the gain of the ultrasonic flaw detector is set very high to ensure that the detection depth covers the thickness of the detection area. In addition, since the adjustment of the sensitivity parameters will make the instrument gain set very high, the surface of the metal casting will generate a lot of clutter during the detection process, which will cause the clutter to be mixed with the echo of the metal defect and be difficult to distinguish, affecting the ultrasonic defect detection results of the metal casting.

[0033] Therefore, in the present invention, for metal castings with particularly large thickness, a layered method can be used for detection, that is, the thickness of the casting is divided into several layers during detection, and each layer is detected by adjusting the sensitivity according to the depth of the layer. For the near-surface layer, since the thickness of this layer is small, the acoustic attenuation is small, the required instrument gain is relatively low, and the clutter amplitude is correspondingly reduced. Defects that cannot be distinguished by the defect echo method of general full-thickness detection may be observed at this time. This not only meets the sensitivity requirements for deep defect detection, but also solves the problem of defect detection in areas with smaller thickness. The distance amplitude compensation (DAC) function of the ultrasonic flaw detector can be directly used to achieve the above effect, and the distance amplitude compensation function is a prior art and will not be repeated in the present invention. At the same time, for the sake of ease of understanding, it is assumed in this embodiment that the thickness is uniform and the detection can be achieved without using the distance amplitude compensation function. For thicker metal castings, it is only necessary to repeat steps S1-S3 of the present invention to confirm all defect areas, and the specific process will not be repeated in the present invention.

[0034] Furthermore, in this step, the division of the detection points is determined according to the shape of the metal casting, for example, the detection points are divided into equal intervals. This is a prior art and is not specifically limited in the present invention.

[0035] In the process of preliminary detection and analysis, it is determined whether there are multiple reflected waves in the ultrasonic data. Figure 2 , this step includes step S11, step S12, step S13 and step S14.

[0036] S11. Use an ultrasonic flaw detector to measure several inspection points of the metal casting to obtain ultrasonic data corresponding to each inspection point.

[0037] S12, respectively extracting waveform data from the ultrasonic data corresponding to each of the detection points to obtain at least two ultrasonic waveforms contained in each ultrasonic data.

[0038] S13, confirming in all the ultrasonic waveforms according to the preset waveform data to obtain the original pulse in each ultrasonic data.

[0039] S14. Compare the recording time of the original pulse with the recording time of other waveform data to determine whether the detection point is an abnormal point. The ultrasonic data corresponding to the abnormal point includes the original pulse, the first reflected wave and the bottom reflected wave. The recording time corresponding to the first reflected wave is greater than the original pulse, and the recording time corresponding to the bottom reflected wave is greater than the first reflected wave.

[0040] For the ultrasonic echo data mentioned in this step, please refer to Figure 3 , Figure 3 Where T represents the original pulse and B represents the reflected wave. Figure 3 The ultrasonic echo data displayed is for the detection point without defects. If there is a defect, a first reflected wave will appear at any position between T and B, which is the situation mentioned in the abnormal point in step S14. And it is necessary to record the time when the first reflected wave appears and the amplitude of the waveform.

[0041] S2. Use an ultrasonic flaw detector to perform secondary detection and analysis on each group of measurement cells of the metal casting to obtain a defect area. A group of measurement cells is obtained by dividing an area where an abnormal point is located according to a preset division rule. There is a correlation between two adjacent measurement cells in the defect area, and the correlation is calculated by the time and amplitude corresponding to the ultrasonic echo.

[0042] It should be noted that the preset division rule mentioned in this step can be an octagonal division method or a regular hexagonal grid division method, etc., and the present invention does not make specific restrictions. It should be noted that in this application, it is recommended to divide the area where the abnormal point is located with the abnormal point as the center point.

[0043] In practice, defects generated inside metal castings usually form longer defective areas. Therefore, in this embodiment, a pair of adjacent measurement cells are analyzed to determine whether they belong to the same defective area based on the change in the time from the original pulse to the reception of the first reflected wave and the amplitude of the first reflected wave. It should be noted that the above-mentioned analysis is performed on adjacent measurement cells that all have first reflected waves, and measurement cells that do not have first reflected waves do not need to be analyzed. Specifically, see Figure 4 , wherein step S2 includes step S21 and step S22.

[0044] S21. Taking the initial measurement cell as the center, respectively measure and analyze the adjacent measurement cell groups to obtain a number of defect correlation parameters. The initial measurement cell is the cell where the abnormal point is located, and the adjacent measurement cell group is the measurement cells adjacent to the initial measurement cell. Each defect correlation parameter is calculated by a preset correlation parameter calculation formula, the initial measurement cell, and ultrasonic data corresponding to a measurement cell in the adjacent measurement cell group.

[0045] It should be noted that the calculation formula for the correlation parameter mentioned in this step is:

[0046]

[0047] in, represents the defect correlation parameter between the adjacent i-th measurement cell and the i+1-th measurement cell, Indicates the total number of measurement cells into which the metal casting surface is divided. represents the combination of the adjacent i-th measurement cell and the i+1-th measurement cell, represents the time from sending the original pulse to receiving the first reflected wave in the ultrasonic data detected in the i-th measurement cell; represents the duration from the emission of the original pulse to the reception of the first reflected wave in the ultrasonic data detected in the i+1th measurement cell; It represents the attenuation value of the amplitude of the original pulse of the i-th measurement cell after it is transmitted and propagated to the first reflected wave received; It represents the attenuation value of the amplitude after the original pulse of the i+1th measurement cell is sent out and propagates to the receiving first reflected wave; it should be noted that the attenuation value of the amplitude is calculated by subtracting the amplitude of the original pulse from the amplitude of the first reflected wave.

[0048] In the above calculation formula, and They are used to indicate the distance between the suspected defect position in a measurement unit and the surface of the metal casting where the probe is located. It represents the ratio of the suspected defect depth in the i-th measurement cell to the suspected defect depth in the i+1-th measurement cell. The closer the ratio is to 1, the greater the possibility that the defects at adjacent positions are the same defect. Otherwise, the smaller the possibility is. It represents the ratio of the attenuation values ​​of the ultrasonic wave from the ith measurement unit cell to the i+1th measurement unit cell to the reflected wave. The attenuation amplitude of the ultrasonic wave is the same when it propagates in the same medium. Therefore, when the depth of the defect is similar, the attenuation degree of the ultrasonic wave from the time of emission to the time of re-reception after reflection is similar. Therefore, When the value is close to 1, the suspected defects at the two locations are in the same area; otherwise, they are not in the same area.

[0049] In this step, It represents the absolute value of the difference between the product of the ratio of the propagation time in the ultrasonic data of two adjacent measurement cells and the ratio of the ultrasonic propagation attenuation degree and 1, because and When the values ​​of are close to 1, the suspected defects of the two adjacent measurement cells are in the same area, so The smaller the value, the greater the possibility that the suspected defects in two adjacent measurement cells are in the same area, and vice versa.

[0050] S22, determining and analyzing the relationship between the preset defect threshold and all the defect correlation parameters to obtain the defect area.

[0051] The defect threshold mentioned in step S22 is 0.3. That is, in this step, adjacent measurement cells with defect correlation parameters less than or equal to 0.3 are merged into one defect area. However, since the defect area confirmed in the above step may include the structure of the metal casting itself, the present application also includes step S3 to distinguish whether the first reflected wave of the ultrasonic echo is caused by the structure of the metal casting itself.

[0052] S3. Perform defect analysis based on the ultrasonic echo data corresponding to each defect area to obtain the defect type of each defect area.

[0053] Specifically, in this application, it is considered that the defects generated in the casting process of metal castings are usually irregular and have randomness in direction and depth, while the holes in the structure of the metal castings themselves are regular and have consistency in direction and depth. In other words, the holes in the structure of the metal castings themselves are generally linear channels that are directly connected inside. This is different from the defects generated in the casting process. Therefore, in the present invention, the defect type is determined by analyzing the relationship between the three measurement cells, see Figure 5 , Figure 5 It is shown in FIG. 1 that step S3 also includes step S31 , step S32 , step S33 , step S34 , step S35 and step S36 .

[0054] S31. Group cells measured in a defect area to obtain a plurality of cell groups, wherein the cell group includes three measured cells, namely a first cell, a second cell and a third cell, and the second cell is adjacent to the first cell and the third cell respectively.

[0055] S32. Based on a preset correlation parameter calculation formula and the ultrasonic data corresponding to each of the unit groups, a defect correlation parameter set corresponding to each of the unit groups is obtained, wherein the defect correlation parameter set includes defect correlation parameters between the second cell and the first cell and defect correlation parameters between the second cell and the third cell.

[0056] It should be noted that the calculation result of step S21 can also be directly used in this step.

[0057] S33. Calculate the depth corresponding to each measurement cell based on the wave velocity of the ultrasound and the ultrasound data corresponding to the measurement cell.

[0058] S34. Based on the depth calculation corresponding to each measurement cell, a line segment vector set corresponding to each of the cell groups is obtained, where the line segment vector set includes a depth vector from the second cell to the first cell and a depth vector from the second cell to the third cell.

[0059] For example: the depth vector mentioned in this step refers to the depth from the first cell where the defect is detected to the depth from the second cell where the defect is detected.

[0060] S35. The leveling coefficient corresponding to each of the unit groups is calculated based on a preset leveling coefficient calculation formula, a line segment vector set corresponding to each of the unit groups, and a defect correlation parameter set.

[0061] It should be noted that the calculation formula for the leveling coefficient mentioned in this step is:

[0062]

[0063] in, represents the leveling coefficient corresponding to a cell group, k represents the measurement cell combination of the second cell and the first cell; k+1 represents the measurement cell combination of the second cell and the third cell; A defect correlation parameter representing a second cell and the first cell; A defect correlation parameter representing the second cell and the third cell; is the depth vector from the second cell to the first cell; is the depth vector from the second cell to the third cell.

[0064] In the above calculation formula, It represents the ratio of the correlation parameters of two adjacent measurement cell combinations. It represents the ratio of the correlation parameters of the first two and the correlation parameters of the last two of the three connected detection positions suspected of having defects. The defects generated in the metal casting process cannot guarantee that the adjacent positions in the defect area are always the same, while the holes in the metal casting structure have the same data parameters at different positions. When it is equal to 1, the area is the structure of the metal casting itself, otherwise it is not; It represents the dot product result of the depth vectors corresponding to two adjacent measurement unit cell combinations. When the value is equal to 1, the directions of the two adjacent direction groups are the same, indicating that the defects detected by the two adjacent measurement unit cell combinations are on a straight line. Therefore, If the value is equal to 1, the area is the metal casting structure itself, otherwise it is not.

[0065] S36, determining the defect type of each defect area based on a preset leveling threshold and a leveling coefficient corresponding to each group of the unit groups.

[0066] If the flattening coefficient calculated in step S35 is close to 1, the probability that the defect type of the defect area is the structure of the metal casting itself is greater, and vice versa. The specific judgment process includes steps S361, S362 and S363.

[0067] S361. Calculate the absolute value of the difference between each leveling coefficient and 1 respectively, and record it as the difference value.

[0068] S362: Count the number of all the difference values ​​that are smaller than the preset smoothing threshold value, and record it as a first value.

[0069] S363. Determine whether the first value is equal to the total number of unit groups. If so, the defect type is the self-structure; if not, the defect type is a structural defect.

[0070] That is, in the embodiment, it is considered that as long as there is a unit group whose absolute value of the difference between the flattening coefficient and 1 is greater than 0.1, the defective area is considered to be an internal defect.

[0071] S4. Determine the defect types of all defect areas and obtain the quality inspection results of the metal castings.

[0072] The quality of metal castings varies from one production unit to another. Figure 6 , Figure 6 The exemplary judgment steps given in the embodiment include step S41, step S42, step S43, step S44, step S45, step S46 and step S37.

[0073] S41. Count the number of defective areas of all defect types that are structural defects, and record them as the number of small defects.

[0074] S42. Obtain the number of surface defects.

[0075] S43. Calculate the number of surface defects and the sum of the number of small defects, and record it as the total number of defects.

[0076] S44. Calculate the surface defect ratio based on the number of surface defects and the total number of defects.

[0077] S45. When the proportion of surface defects and the total number of defects meet a first logical condition, the quality of the metal casting is poor. The first logical condition includes that the proportion of surface defects is greater than or equal to two-thirds and the total number of defects is greater than or equal to 9.

[0078] S46. When the surface defect ratio and the total number of defects satisfy a second logical condition, the quality of the metal casting is good. The second logical condition includes that the surface defect ratio is equal to zero and the total number of defects is less than 4.

[0079] S47. When the surface defect ratio and the total number of defects do not satisfy the first logical condition and the second logical condition, the quality of the metal casting is average.

[0080] Embodiment 2:

[0081] like Figure 7 As shown, this embodiment provides a metal casting rapid detection device based on ultrasonic technology, and the device includes:

[0082] A preliminary detection unit, used to use an ultrasonic flaw detector to perform preliminary detection and analysis on a plurality of detection points of the metal casting to obtain a plurality of abnormal points, wherein the preliminary detection result includes ultrasonic data corresponding to each of the detection points, and the abnormal points are detection points where abnormalities exist in the ultrasonic data;

[0083] A secondary detection unit is used to use an ultrasonic flaw detector to perform secondary detection and analysis on each group of measurement cells of the metal casting to obtain a defect area, wherein a group of the measurement cells is obtained by dividing an area where an abnormal point is located according to a preset division rule, and there is a correlation between two adjacent measurement cells in the defect area, and the correlation is calculated by the corresponding time and amplitude of the ultrasonic wave;

[0084] A defect analysis and detection unit, used to perform defect analysis based on the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area;

[0085] The logic judgment unit is used to judge the defect types of all defect areas and obtain the quality inspection results of the metal castings.

[0086] In some specific embodiments, the secondary detection unit includes:

[0087] The measurement and analysis unit is used to measure and analyze adjacent measurement cell groups with the initial measurement cell as the center to obtain a number of defect correlation parameters. The initial measurement cell is the cell where the abnormal point is located, and the adjacent measurement cell group is the measurement cell adjacent to the initial measurement cell. Each defect correlation parameter is calculated by a preset correlation parameter calculation formula, the initial measurement cell and the ultrasonic data corresponding to a measurement cell in the adjacent measurement cell group;

[0088] The judgment and analysis unit is used to judge and analyze based on a preset defect threshold and the size relationship of all the defect correlation parameters to obtain a defect area.

[0089] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0090] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0091] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A rapid detection method for metal castings based on ultrasonic technology, characterized in that: The method comprises: Using an ultrasonic flaw detector to perform preliminary detection and analysis on several detection points of the metal casting to obtain several abnormal points, wherein the result of the preliminary detection includes ultrasonic data corresponding to each of the detection points, and the abnormal points are detection points where abnormalities exist in the ultrasonic data; Using an ultrasonic flaw detector, each group of measurement cells of the metal casting is subjected to secondary inspection and analysis to obtain a defect area, wherein a group of measurement cells is obtained by dividing an area where an abnormal point is located according to a preset division rule, and there is a correlation between two adjacent measurement cells in the defect area, and the correlation is calculated by the time and amplitude corresponding to the ultrasonic internal reflection wave; Perform defect analysis based on the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area; According to the defect type judgment of all defect areas, the quality inspection results of metal castings are obtained; The method for obtaining the defect area is as follows: taking the initial measurement cell as the center, respectively measuring and analyzing the adjacent measurement cell groups to obtain a number of defect correlation parameters, the initial measurement cell is the cell where the abnormal point is located, and the adjacent measurement cell group is the measurement cell adjacent to the initial measurement cell, and each defect correlation parameter is calculated by a preset correlation parameter calculation formula, the initial measurement cell and the ultrasonic data corresponding to a measurement cell in the adjacent measurement cell group; based on the preset defect threshold and the size relationship of all the defect correlation parameters, the defect area is obtained; Wherein, the method for obtaining the defect type is as follows: grouping the cells measured in a defect area to obtain several cell groups, wherein the cell group includes three measurement cells, namely the first cell, the second cell and the third cell, and the second cell is adjacent to the first cell and the third cell respectively; based on the preset correlation parameter calculation formula and the ultrasonic data corresponding to each of the cell groups, a defect correlation parameter set corresponding to each of the cell groups is obtained, and the defect correlation parameter set includes the defect correlation parameters of the second cell and the first cell and the defect correlation parameters of the second cell and the third cell; based on the wave velocity of the ultrasonic wave and the ultrasonic data corresponding to the measurement cell, the depth corresponding to each measurement cell is obtained; based on the depth calculation corresponding to each measurement cell, a line segment vector set corresponding to each of the cell groups is obtained, and the line segment vector set includes the depth vector from the second cell to the first cell and the depth vector from the second cell to the third cell; based on the preset leveling coefficient calculation formula, the line segment vector set corresponding to each of the cell groups and the defect correlation parameter set, the leveling coefficient corresponding to each of the cell groups is obtained; based on the preset leveling threshold and the leveling coefficient corresponding to each of the cell groups, the defect type of each defect area is obtained; Among them, based on the preset leveling threshold and the leveling coefficient judgment corresponding to each unit group, the method for obtaining the defect type of each defect area is: respectively calculating the absolute value of the difference between each leveling coefficient and 1, recorded as the difference value; counting the number of all the difference values ​​that are less than the preset leveling threshold, recorded as the first value; judging whether the first value is equal to the total number of unit groups, if so, the defect type is the self-structure, if not, the defect type is a structural defect; The correlation parameter calculation formula is: in, represents the defect correlation parameter between the adjacent i-th measurement cell and the i+1-th measurement cell, Indicates the total number of measurement cells into which the metal casting surface is divided. represents the combination of the adjacent i-th measurement cell and the i+1-th measurement cell, represents the time from sending the original pulse to receiving the first reflected wave in the ultrasonic data detected in the i-th measurement cell; represents the duration from the emission of the original pulse to the reception of the first reflected wave in the ultrasonic data detected in the i+1th measurement cell; It represents the attenuation value of the amplitude of the original pulse of the i-th measurement cell after it is transmitted and propagated to the first reflected wave received; It represents the attenuation value of the amplitude of the original pulse from the i+1th measurement cell after it is transmitted and propagated to the first reflected wave received; The calculation formula of the leveling coefficient is: in, represents the leveling coefficient corresponding to a cell group, k represents the measurement cell combination of the second cell and the first cell; k+1 represents the measurement cell combination of the second cell and the third cell; A defect correlation parameter representing a second cell and the first cell; A defect correlation parameter representing the second cell and the third cell; is the depth vector from the second cell to the first cell; is the depth vector from the second cell to the third cell.

2. The method for rapid detection of metal castings based on ultrasonic technology according to claim 1 is characterized in that: Using ultrasonic flaw detector to conduct preliminary inspection and analysis on several inspection points of metal castings, several abnormal points were obtained, including: Use an ultrasonic flaw detector to measure several inspection points of metal castings to obtain ultrasonic data corresponding to each inspection point; Extracting waveform data from the ultrasonic data corresponding to each of the detection points to obtain at least two ultrasonic waveforms contained in each ultrasonic data; Confirming in all the ultrasonic waveforms according to the preset waveform data to obtain the original pulse in each ultrasonic data; The recording time of the original pulse is compared with the recording time of other waveform data to determine whether the detection point is an abnormal point. The ultrasonic data corresponding to the abnormal point includes the original pulse, the first reflected wave and the bottom reflected wave. The recording time corresponding to the first reflected wave is greater than the original pulse, and the recording time corresponding to the bottom reflected wave is greater than the first reflected wave.

3. The method for rapid detection of metal castings based on ultrasonic technology according to claim 1 is characterized in that: The preset defect threshold is 0.

3.

4. The rapid detection method for metal castings based on ultrasonic technology according to claim 1 is characterized in that: The preset smoothing threshold is 0.

1.

5. The method for rapid detection of metal castings based on ultrasonic technology according to claim 1, characterized in that: The defect types include structural defects. According to the defect types of all defect areas, the quality inspection results of metal castings are obtained, including: Count the number of defective areas of all structural defects and record them as the number of minor defects; Get the number of surface defects; Calculate the number of surface defects and the sum of the number of small defects and record it as the total number of defects; The surface defect ratio is calculated based on the number of surface defects and the total number of defects; When the surface defect ratio and the total number of defects meet a first logical condition, the quality of the metal casting is poor, and the first logical condition includes that the surface defect ratio is greater than or equal to two-thirds and the total number of defects is greater than or equal to 9; When the surface defect ratio and the total number of defects meet the second logical condition, the quality of the metal casting is good, and the second logical condition includes that the surface defect ratio is equal to zero and the total number of defects is less than 4; When the surface defect ratio and the total number of defects do not satisfy the first logical condition and the second logical condition, the quality of the metal casting is average.

6. A metal casting rapid detection device based on ultrasonic technology, characterized in that: The device is used to implement a metal casting rapid detection method based on ultrasonic technology as described in any one of claims 1 to 5, and the device comprises: A preliminary detection unit, used to use an ultrasonic flaw detector to perform preliminary detection and analysis on a plurality of detection points of the metal casting to obtain a plurality of abnormal points, wherein the preliminary detection result includes ultrasonic data corresponding to each of the detection points, and the abnormal points are detection points where abnormalities exist in the ultrasonic data; A secondary detection unit is used to use an ultrasonic flaw detector to perform secondary detection and analysis on each group of measurement cells of the metal casting to obtain a defect area, wherein a group of the measurement cells is obtained by dividing an area where an abnormal point is located according to a preset division rule, and there is a correlation between two adjacent measurement cells in the defect area, and the correlation is calculated by the corresponding time and amplitude of the ultrasonic wave; A defect analysis and detection unit, used to perform defect analysis based on the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area; The logic judgment unit is used to judge the defect types of all defect areas and obtain the quality inspection results of the metal castings.

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