CN118817840B - Rapid detection device and method for metal castings based on ultrasonic technology - Google Patents
Rapid detection device and method for metal castings based on ultrasonic technology Download PDFInfo
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Abstract
The invention relates to the technical field of ultrasonic detection, in particular to a metal casting rapid detection device and method based on an ultrasonic technology, comprising the steps of using an ultrasonic flaw detector to perform preliminary detection analysis on a plurality of detection points to obtain abnormal points; performing secondary detection analysis on the areas near the abnormal points to obtain defect areas, performing defect analysis according to ultrasonic data corresponding to each defect area to obtain defect types of each defect area, and judging according to the defect types of all the defect areas to obtain quality detection results of the metal castings. The method and the device aim at analyzing the position relation and the amplitude relation of the reflected wave in the defect area to confirm whether the reflected wave belongs to the influence caused by the self structure of the metal casting, thereby effectively improving the accuracy of ultrasonic detection in the defect detection of the metal casting and providing a solid foundation for the quality assessment of the metal casting.
Description
Technical Field
The invention relates to the technical field of ultrasonic detection, in particular to a device and a method for rapidly detecting a metal casting based on an ultrasonic technology.
Background
In the production process of metal castings, each link cannot be guaranteed to be in an ideal state. Therefore, in the actual production process, defect problems such as air holes and cracks are inevitably generated. If the defects are positioned on the surface of the metal casting, the defects can be quickly found, but the defects in the metal casting cannot be detected through image recognition.
Ultrasonic detection is a nondestructive detection method, and a probe of an ultrasonic flaw detector is tightly attached to the surface of a metal casting to emit ultrasonic waves into the metal casting. When the ultrasonic wave propagates in the metal, if the ultrasonic wave encounters defects such as holes, inclusions and the like, the ultrasonic wave can be reflected back to the probe. And then the propagation condition of ultrasonic waves in the metal casting is displayed in a display screen of the ultrasonic flaw detector. However, since some metal castings can leave smaller pores according to the model diagram, a part of the smaller pores are easy to be regarded as metal casting defects when ultrasonic detection is carried out. But it is not possible to directly distinguish whether it is a metal casting holding hole or a defect existing inside the metal casting according to the reflected wave.
Disclosure of Invention
In order to solve the above technical problems, the present invention aims to provide a device and a method for rapidly detecting metal castings based on ultrasonic technology, so as to improve the above problems. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
The application provides a rapid detection method of a metal casting based on an ultrasonic technology, which comprises the steps of carrying out preliminary detection analysis on a plurality of detection points of the metal casting by using an ultrasonic flaw detector to obtain a plurality of abnormal points, carrying out defect analysis on ultrasonic data corresponding to each detection point in a preliminary detection result, respectively carrying out secondary detection analysis on each group of measurement cells of the metal casting by using the ultrasonic flaw detector to obtain a defect area, dividing the area where one abnormal point is located by one group of measurement cells by using a preset division rule, calculating the correlation between two adjacent measurement cells in the defect area by using the time and amplitude corresponding to ultrasonic internal reflection waves, carrying out defect analysis according to the ultrasonic data corresponding to each defect area, obtaining the defect type of each defect area, and judging according to the defect types of all the defect areas to obtain the quality detection result of the metal casting.
In combination with the first aspect, in one possible implementation manner, the method comprises the steps of performing preliminary detection analysis on a plurality of detection points of a metal casting by using an ultrasonic flaw detector to obtain a plurality of abnormal points, measuring the plurality of detection points of the metal casting by using the ultrasonic flaw detector to obtain ultrasonic data corresponding to each detection point, respectively extracting waveform data of the ultrasonic data corresponding to each detection point to obtain at least two ultrasonic waveforms contained in each ultrasonic data, confirming all the ultrasonic waveforms according to preset waveform data to obtain original pulses in each ultrasonic data, comparing the recording time of the original pulses with the recording time of other waveform data to obtain whether the detection points are abnormal points or not, wherein the ultrasonic data corresponding to the abnormal points comprise the original pulses, first reflected waves and bottom reflected waves, the recording time corresponding to the first reflected waves is larger than the original pulses, and the recording time corresponding to the bottom reflected waves is larger than the first reflected waves.
In combination with the first aspect, in one possible implementation manner, the defect area is obtained by respectively carrying out secondary detection analysis on each group of measurement cells of the metal casting by using an ultrasonic flaw detector, wherein the method comprises the steps of respectively carrying out measurement analysis on adjacent measurement cell groups by taking an initial measurement cell as a center to obtain a plurality of defect correlation parameters, wherein the initial measurement cell is a cell where an abnormal point is located, the adjacent measurement cell groups are adjacent measurement cells of the initial measurement cell, each defect correlation parameter is obtained by calculating ultrasonic data corresponding to one measurement cell in a preset correlation parameter calculation formula, the initial measurement cell and the adjacent measurement cell groups, and judging and analyzing based on a preset defect threshold and the size relation of all the defect correlation parameters to obtain the defect area.
With reference to the first aspect, in one possible implementation manner, the preset defect threshold is 0.3.
In combination with the first aspect, in a possible implementation manner, defect analysis is performed according to ultrasonic data corresponding to each defect area to obtain defect types of each defect area, wherein the defect analysis comprises the steps of grouping the cells measured in one defect area to obtain a plurality of cell groups, wherein the cell groups comprise three measurement cells which are respectively a first cell, a second cell and a third cell, the second cell is respectively adjacent to the first cell and the third cell, the defect correlation parameter set corresponding to each cell group is obtained based on a preset correlation parameter calculation formula and ultrasonic data corresponding to each cell group, the defect correlation parameter set comprises defect correlation parameters of the second cell and the first cell and defect correlation parameters of the second cell and the third cell, the depth corresponding to each measurement cell is obtained based on ultrasonic wave velocity and ultrasonic data corresponding to the measurement cell, the depth corresponding to each measurement cell is calculated based on the depth corresponding to each measurement cell, the depth corresponding to each segment vector is calculated based on a preset segment vector, and the depth corresponding to each segment vector is calculated based on the first segment vector, and the depth vector of each segment is calculated based on the first segment vector and the first segment vector, and the depth vector is calculated to the first segment vector and the segment vector is calculated based on the depth vector.
In combination with the first aspect, in one possible implementation manner, the defect type of each defect area is obtained based on a preset flattening threshold and flattening coefficients corresponding to each unit group, wherein the method comprises the steps of calculating absolute values of differences between each flattening coefficient and 1 respectively, recording the absolute values as difference values, counting the number of the flattening thresholds smaller than the preset flattening threshold in all the difference values, recording the number as a first value, judging whether the first value is equal to the total number of the unit groups, if yes, the defect type is a self structure, and if not, the defect type is a structural defect.
With reference to the first aspect, in one possible implementation manner, the preset flattening threshold is 0.1.
With reference to the first aspect, in one possible implementation manner, the defect types include structural defects, the quality detection result of the metal casting is obtained according to defect types of all defect areas, wherein the quality detection result comprises the steps of counting the number of defect areas with all defect types being structural defects, recording 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, recording the total number of defects, calculating the surface defect ratio 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 logic condition, the quality of the metal casting is poor, the first logic condition comprises 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 logic condition, the quality of the metal casting is good, the second logic condition comprises that the surface defect ratio is equal to zero and the total number of defects is less than 4, and when the surface defect ratio and the total number of defects do not meet the first logic condition and the second logic condition, the quality of the metal casting is general.
The application further provides a metal casting rapid detection device based on the ultrasonic technology, which comprises a preliminary detection unit, a secondary detection unit, a logic judgment unit and a detection unit, wherein the preliminary detection unit is used for carrying out preliminary detection analysis on a plurality of detection points of a metal casting by using an ultrasonic flaw detector to obtain a plurality of abnormal points, the preliminary detection result comprises ultrasonic data corresponding to each detection point, the abnormal points are detection points with abnormality in the ultrasonic data, the secondary detection unit is used for carrying out secondary detection analysis on each group of measurement cells of the metal casting by using the ultrasonic flaw detector to obtain a defect area, one group of measurement cells is obtained by dividing the area where one abnormal point is located by a preset dividing rule, correlation exists between two adjacent measurement cells in the defect area, the correlation is obtained by calculating time and amplitude corresponding to ultrasonic waves, the defect analysis detection unit is used for carrying out defect analysis according to the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area, and the logic judgment unit is used for judging the defect type of all the defect areas to obtain the quality detection result of the metal casting.
In combination with the second aspect, in one possible implementation manner, the secondary detection unit comprises a measurement analysis unit and a judgment analysis unit, wherein the measurement analysis unit is used for respectively carrying out measurement analysis on adjacent measurement cell groups by taking an initial measurement cell as a center to obtain a plurality of defect correlation parameters, the initial measurement cell groups are cells where abnormal points are located, the adjacent measurement cell groups are adjacent measurement cells of the initial measurement cell, each defect correlation parameter is obtained by calculating ultrasonic data corresponding to one measurement cell in a preset correlation parameter calculation formula, the initial measurement cell and the adjacent measurement cell groups, and the judgment analysis unit is used for judging and analyzing based on a preset defect threshold value and the size relation of all the defect correlation parameters to obtain a defect area.
The invention has the following beneficial effects:
Firstly, detecting and confirming a metal casting by an ultrasonic flaw detector to obtain an abnormal point position with problems of ultrasonic waves, then detecting the abnormal point position and adjacent detection points, confirming whether the abnormal point position and the adjacent detection points belong to the same defect area by combining attenuation change of the ultrasonic waves, and finally confirming whether the defect belongs to an actual defect by combining change condition of the ultrasonic waves of the same defect area. Compared with a mode of judging directly according to the reflected wave graph, the method can accurately judge whether the defect area detected by the ultrasonic wave belongs to a reserved hole of the metal casting or the defect existing in the metal casting through excavating and analyzing the association relation between the occurrence time and the amplitude of the ultrasonic wave. The quality type of the metal casting can be more effectively judged. The application of the ultrasonic flaw detector in metal casting detection is also expanded.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for rapidly detecting metal castings based on ultrasonic technology according to an embodiment 1 of the present invention;
FIG. 2 is a flow chart of step S1 according to an embodiment 1 of the present invention;
FIG. 3 is a schematic view of ultrasound echo data according to an embodiment 1 of the present invention;
fig. 4 is a flow chart of step S2 provided in embodiment 1 of the present invention;
FIG. 5 is a flowchart of step S3 according to embodiment 1 of the present invention;
FIG. 6 is a flowchart of step S4 according to embodiment 1 of the present invention;
Fig. 7 is a schematic structural diagram of a rapid metal casting detection apparatus based on ultrasonic technology according to embodiment 2 of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following description refers to the specific implementation, structure, characteristics and effects of the device and the method for rapidly detecting the metal castings based on the ultrasonic technology according to the invention by combining the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
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.
Example 1:
The invention provides a metal casting rapid detection method based on an ultrasonic technology, which is specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of a method for rapidly detecting a metal casting based on an ultrasonic technology according to an embodiment of the invention is shown, which specifically includes step S1, step S2, step S3 and step S4.
S1, performing preliminary detection analysis on a plurality of detection points of a metal casting by using an ultrasonic flaw detector to obtain a plurality of abnormal points, wherein the result of the preliminary detection comprises ultrasonic data corresponding to each detection point, and the abnormal points are detection points with abnormality in the ultrasonic data.
Specifically, the probe of the ultrasonic flaw detector in the invention is placed on the surface of the metal casting and emits ultrasonic waves, and the ultrasonic waves propagate inside the metal. If the metal casting has no defects such as hollowness or inclusion, ultrasonic waves can be transmitted to the bottom surface of the detection position of the metal casting and then reflected to generate reflected waves, and finally the reflected waves return to the probe of the ultrasonic flaw detector. If there is hollow or inclusion in the metal casting, the ultrasonic wave will be reflected in advance at the hollow or inclusion position and return the reflected wave to the probe.
Meanwhile, it is also required to explain that a thicker area may exist in part of the metal casting, and an adjusting function is required to be carried out on the ultrasonic sensitivity parameter when the thicker area is detected, so that the gain setting of the ultrasonic flaw detector is large, and the thickness of the detection area is ensured to be covered by the detection depth. In addition, the instrument gain setting is large due to the fact that the sensitivity parameters are adjusted, however, clutter generated in the detection process of the surface layer of the metal casting is large, so that clutter and echoes of metal defects are mixed together and are difficult to distinguish, and the defect detection result of ultrasonic waves on the metal casting is affected.
Therefore, in the invention, for the metal casting with particularly large thickness, a layering method can be adopted, namely, the thickness of the casting is divided into a plurality of layers during detection, and each layer is detected by adopting the depth adjustment sensitivity of the layer. For near-surface layers, due to the small layer thickness, less acoustic attenuation, relatively low instrument gain, and correspondingly reduced clutter amplitude, defects that cannot be resolved using the defect echo method of typical full thickness detection may be observed. Thus, the requirement of sensitivity of deep defect detection is met, and the defect detection problem of the part with smaller thickness is solved. The Distance Amplitude Compensation (DAC) function of the ultrasonic flaw detector can be directly utilized, so that the above effects can be achieved, and the distance amplitude compensation function is the prior art, and is not repeated in the present invention. Meanwhile, in order to facilitate understanding, in the embodiment, it is assumed that the thickness is uniform, and detection can be realized without using a distance amplitude compensation function, and for thicker metal castings, only the steps S1-S3 of the invention are repeated to confirm all defect areas, and the specific process is not repeated in the invention.
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 equally divided. Which is the prior art, and the present invention is not particularly limited.
In the process of preliminary detection analysis, whether a plurality of reflected waves appear in the ultrasonic data is judged. Specifically, referring to fig. 2, step S11, step S12, step S13, and step S14 are included in the present step.
And S11, measuring a plurality of detection points of the metal casting by using an ultrasonic flaw detector to obtain ultrasonic data corresponding to each detection point.
And S12, respectively extracting waveform data of the ultrasonic data corresponding to each detection point position to obtain at least two ultrasonic waveforms contained in each ultrasonic data.
S13, confirming in all the ultrasonic waveforms according to preset waveform data, and obtaining original pulses in each ultrasonic data.
S14, 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, wherein the ultrasonic data corresponding to the abnormal point comprises the original pulse, a first reflected wave and a bottom surface reflected wave, the recording time corresponding to the first reflected wave is larger than that of the original pulse, and the recording time corresponding to the bottom surface reflected wave is larger than that of the first reflected wave.
The ultrasound echo data mentioned in relation to this step can be seen in fig. 3, where T represents the original pulse and B represents the reflected wave. It should be noted that, the ultrasonic echo data shown in fig. 3 is a detection point where no defect exists. If there is a defect, a first reflected wave will also appear at any position between T and B, i.e. the case mentioned by the abnormal point in step S14. And the moment of occurrence of the first reflected wave and the amplitude of the waveform need to be recorded.
S2, respectively carrying out secondary detection analysis on each group of measurement cells of the metal casting by using an ultrasonic flaw detector to obtain a defect area, wherein one group of measurement cells is obtained by dividing an area where an abnormal point is located by a preset dividing rule, and correlation exists between two adjacent measurement cells in the defect area and is obtained by calculating the time and amplitude corresponding to ultrasonic echo.
It should be noted that, the preset dividing rule mentioned in this step may be an eight-ortho dividing manner, or a regular hexagonal meshing dividing manner, etc., which is not specifically limited in the present application. It should be noted that, in the present application, it is recommended to divide the area where the abnormal point is located by taking the abnormal point as the center point.
In practice, defects created inside metal castings often create longer defect areas. In this embodiment, therefore, a pair of adjacent measurement cells are analyzed, and whether the first reflected wave belongs to the same defect area is confirmed based on the time period from the original pulse to the reception of the first reflected wave and the change in the amplitude of the first reflected wave. It should be noted that the above analysis is performed on adjacent measurement cells in which the first reflected wave exists, and the analysis is not required for measurement cells in which the first reflected wave does not exist. Specifically, see fig. 4, wherein step S2 includes step S21 and step S22.
S21, respectively carrying out measurement analysis on adjacent measurement cell groups by taking an initial measurement cell as a center to obtain a plurality of defect correlation parameters, wherein the initial measurement cell is a cell in which an abnormal point is located, the adjacent measurement cell groups are adjacent measurement cells of the initial measurement cell, and each defect correlation parameter is obtained by calculating ultrasonic data corresponding to one measurement cell in a preset correlation parameter calculation formula, the initial measurement cell and the adjacent measurement cell groups.
It should be noted that, the calculation formula of the correlation parameter mentioned in this step is:
Wherein, Representing a defect correlation parameter between adjacent i-th measurement cell and i + 1-th measurement cell,Representing the total number of measurement cells of the surface of the metal casting divided,Representing a combination of adjacent i-th measurement cells and i + 1-th measurement cells,Representing a time period from the emission of the original pulse to the reception of the first reflected wave in the ultrasonic data detected in the i-th measurement cell; Representing a time period from the emission of the original pulse to the reception of the first reflected wave in the ultrasonic data detected in the (i+1) th measurement cell; an attenuation value representing the amplitude of the original pulse of the i-th measurement cell after being sent out, propagating to the time of receiving the first reflected wave; The attenuation value representing the amplitude of the original pulse of the (i+1) th measurement cell after being sent out is transmitted to the first reflected wave, wherein the attenuation value of the amplitude is calculated by the difference between the amplitude of the original pulse and the amplitude of the first reflected wave.
In the above-mentioned calculation formula, the calculation formula,AndRespectively used for representing the distance between the suspected defect position in one measuring cell and the surface of the metal casting where the probe is positioned,Representing the ratio of the suspected defect depth in the ith measurement cell to the suspected defect depth in the (i+1) th measurement cell, wherein the closer the ratio is to 1, the greater the probability that the defects in adjacent positions are the same defect, and conversely, the smaller the probability that the defects in adjacent positions are the same defect; Representing the ratio between the attenuation values of the ultrasonic waves respectively emitted from the i-th measurement cell and the i+1-th measurement cell to the time when the reflected waves are received, the amplitudes of the attenuation of the ultrasonic waves when propagating in the same medium are the same, so that when the depths of the defects are similar, the attenuation degrees of the ultrasonic waves when the ultrasonic waves are received again after being emitted from the emission to the reflection are similar, and therefore, When the value is close to 1, the defects which exist in two positions are the same region, otherwise, the defects are not the same region.
In this step byAn absolute value of a difference representing a product of a ratio between propagation durations and a ratio between propagation attenuation degrees of ultrasonic waves in ultrasonic data of adjacent two measurement cells and 1, becauseAndWhen the values of the two adjacent measurement cells are close to 1, the suspected defects of the two adjacent measurement cells are the same area, soThe smaller the value, the greater the likelihood that two adjacent measurement cells are suspected to have defects in the same region, and vice versa.
S22, judging and analyzing based on the preset defect threshold and the size relation of all the defect correlation parameters to obtain a defect area.
Wherein the defect threshold mentioned in this step S22 is 0.3. That is, in this step, adjacent measurement cells having a defect correlation parameter of 0.3 or less are merged into one defect area. But may include the structure of the metal casting itself due to the defective area identified in the above step. Therefore, the application also comprises a step S3 of distinguishing whether the ultrasonic echo caused by the self structure of the metal casting has the first reflected wave.
S3, performing defect analysis according to the ultrasonic echo data corresponding to each defect area to obtain the defect type of each defect area.
In particular, in the present application, it is considered that the defects generated in the casting process of the metal casting are generally irregular and have randomness in direction and depth, while the holes of the structure of the metal casting are regular and have uniformity in direction and depth. In other words, the holes of the self structure of the metal casting are generally linear channels, and the inside of the holes is directly communicated. Unlike defects generated during casting. Therefore, in the present application, the defect type is judged by analyzing the correlations between the three measurement cells, and referring to fig. 5, step S31, step S32, step S33, step S34, step S35, and step S36 are further included in step S3 shown in fig. 5.
S31, grouping the measured cells in one defect area to obtain a plurality of cell groups, wherein the cell groups comprise 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.
S32, calculating based on a preset correlation parameter calculation formula and ultrasonic data corresponding to each unit group to obtain a defect correlation parameter set corresponding to each unit group, wherein the defect correlation parameter set comprises defect correlation parameters of a second unit cell and the first unit cell and defect correlation parameters of the second unit cell and the third unit cell.
In this step, the calculation result of step S21 may be directly used.
And S33, calculating based on the wave velocity of the ultrasonic wave and the ultrasonic data corresponding to the measurement cells, and obtaining the depth corresponding to each measurement cell.
S34, calculating based on the depth corresponding to each measurement cell to obtain a line segment vector set corresponding to each cell group, wherein the line segment vector set comprises a depth vector from the second cell to the first cell and a depth vector from the second cell to the third cell.
By way of example, the depth vector mentioned in this step refers to the depth at which the first cell detects a defect to the depth at which the second cell detects a defect.
S35, calculating to obtain the flattening coefficient corresponding to each unit group based on a preset flattening coefficient calculation formula, a line segment vector set corresponding to each unit group and a defect correlation parameter set.
It should be noted that the calculation formula of the flattening coefficient mentioned in this step is:
Wherein, K represents the combination of the second cell and the first cell, k+1 represents the combination of the second cell and the third cell; a defect-related parameter representing a second cell and the first cell; a defect-related parameter representing a second cell and the third cell; a depth vector from a second cell to the first cell; is a depth vector from the second cell to the third cell.
In the above-mentioned calculation formula, the calculation formula,Representing the ratio of correlation parameters of two adjacent measurement cell combinations, representing the ratio of the correlation parameters of the two front and the correlation parameters of the two rear connected to three detection positions suspected of defects, wherein the defects generated in the metal casting process cannot ensure that the adjacent positions in the defect area are always the same, while the holes of the metal casting structure and the data parameters of different positions are consistent, so thatWhen the temperature is equal to 1, the area is the self structure of the metal casting, otherwise, the area is not; Representing the depth vector dot product corresponding to two adjacent measurement cell combinations, the direction of the two adjacent direction groups being the same when the value is equal to 1, representing that the detected defects of the two adjacent measurement cell combinations are in a straight line, and therefore, The value is equal to 1, and the area is the structure of the metal casting, otherwise, the area is not.
S36, judging based on a preset flattening threshold and flattening coefficients corresponding to each unit group to obtain the defect type of each defect area.
Wherein the flatness coefficient is calculated to be approximately 1 in step S35, the greater the likelihood that the defect type of the defective area is the structure of the metal casting itself, and conversely, the smaller. The specific judging process includes step S361, step S362 and step S363.
S361, respectively calculating absolute values of differences between each leveling coefficient and 1, and recording the absolute values as difference values.
S362, counting the number of the flattening thresholds smaller than a preset flattening threshold in all the difference values, and recording the number as a first numerical value.
S363, judging whether the first value is equal to the total number of the unit groups, if so, the defect type is self-structure, and if not, the defect type is structural defect.
That is, it is considered that the defective area belongs to an internal defect as long as there is a difference between the flatness coefficient and 1 of an element group having an absolute value larger than 0.1 in the embodiment.
And S4, judging according to the defect types of all the defect areas, and obtaining a quality detection result of the metal casting.
The production unit specifications are different for the quality of the metal castings. Therefore, referring to fig. 6, exemplary judgment steps are given in fig. 6 including step S41, step S42, step S43, step S44, step S45, step S46, and step S37.
S41, counting the number of defect areas with all defect types being structural defects, and recording the number as the small defect number.
S42, acquiring the number of the surface defects.
S43, calculating the sum of the number of the surface defects and the number of the small defects, and recording the sum as the total number of the defects.
S44, calculating based on the number of the surface defects and the total number of the defects to obtain the surface defect ratio.
S45, when the surface defect ratio and the total number of defects meet a first logic condition, the quality of the metal casting is poor, and the first logic condition comprises that the surface defect ratio is more than or equal to two thirds and the total number of defects is more than or equal to 9.
S46, when the surface defect ratio and the total number of defects meet a second logic condition, the quality of the metal casting is good, and the second logic condition comprises that the surface defect ratio is equal to zero and the total number of defects is smaller than 4.
S47, when the surface defect ratio and the total number of defects do not meet the first logic condition and the second logic condition, the quality of the metal casting is general.
Example 2:
as shown in fig. 7, the present embodiment provides a rapid metal casting detection apparatus based on ultrasonic technology, the apparatus comprising:
The preliminary detection unit is used for carrying out preliminary detection analysis on a plurality of detection points of the metal casting by using the ultrasonic flaw detector to obtain a plurality of abnormal points, the preliminary detection result comprises ultrasonic data corresponding to each detection point, and the abnormal points are detection points with abnormality in the ultrasonic data;
The secondary detection unit is used for respectively carrying out secondary detection analysis on each group of measurement cells of the metal casting by using an ultrasonic flaw detector to obtain a defect area, wherein one group of measurement cells is obtained by dividing an area where an abnormal point is located by a preset division rule, and correlation exists between two adjacent measurement cells in the defect area and is obtained by calculating the time and amplitude corresponding to ultrasonic waves;
the defect analysis detection unit is used for carrying out defect analysis according to the ultrasonic data corresponding to each defect area to obtain the defect type of each defect area;
and the logic judging unit is used for judging according to the defect types of all the defect areas to obtain the quality detection result of the metal casting.
In some specific embodiments, the secondary detection unit includes:
The measurement analysis unit is used for respectively carrying out measurement analysis on adjacent measurement cell groups by taking an initial measurement cell as a center to obtain a plurality of defect correlation parameters, wherein the initial measurement cell is a cell where an abnormal point is located, the adjacent measurement cell groups are adjacent measurement cells of the initial measurement cell, and each defect correlation parameter is obtained by calculating ultrasonic data corresponding to one measurement cell in the preset correlation parameter calculation formula, the initial measurement cell and the adjacent measurement cell groups;
And the judging and analyzing unit is used for judging and analyzing based on the preset defect threshold value and the magnitude relation of all the defect correlation parameters to obtain a defect area.
It should be noted that, regarding the apparatus in the above embodiments, the specific manner in which the respective modules perform the operations has been described in detail in the embodiments regarding the method, and will not be described in detail herein.
It should be noted that the sequence of the 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 particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109142533A (en) * | 2018-10-22 | 2019-01-04 | 广东工业大学 | A kind of rapid detection method and equipment of internal defect in cast |
| CN112147223A (en) * | 2020-10-14 | 2020-12-29 | 首钢京唐钢铁联合有限责任公司 | Method for detecting internal defects of casting blank |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
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| JP2004205430A (en) * | 2002-12-26 | 2004-07-22 | Sumitomo Chem Co Ltd | Ultrasonic inspection method |
| JP3725126B2 (en) * | 2003-02-04 | 2005-12-07 | 川崎重工業株式会社 | Ultrasonic flaw detection method and apparatus |
| RU2524451C1 (en) * | 2013-01-09 | 2014-07-27 | Федеральное государственное бюджетное учреждение науки Ордена Трудового Красного Знамени Институт физики металлов Уральского отделения Российской академии наук (ИФМ УрО РАН) | Method of determining type of defect in metal articles |
| JP6833366B2 (en) * | 2016-07-06 | 2021-02-24 | キヤノン株式会社 | Information processing device, control method and program of information processing device |
| EP3388827B1 (en) * | 2017-04-12 | 2019-05-15 | Fujitsu Limited | Defect detection using ultrasound scan data |
| JP7508384B2 (en) * | 2021-02-09 | 2024-07-01 | 株式会社日立パワーソリューションズ | Ultrasonic inspection device, ultrasonic inspection method, and program |
| CN114397365B (en) * | 2022-01-13 | 2024-04-09 | 南京市城市建设投资控股(集团)有限责任公司 | A method for ultrasonically detecting defects in steel-concrete structures |
| CN115308310B (en) * | 2022-09-29 | 2022-12-20 | 誉隆半导体设备(江苏)有限公司 | Ultrasonic flaw detection identification method for inner wall of pipeline |
| CN118330023A (en) * | 2023-01-10 | 2024-07-12 | 北京新联铁集团股份有限公司 | Defect identification method, device, medium and detection system based on ultrasonic detection |
| CN117388372A (en) * | 2023-11-17 | 2024-01-12 | 国网四川省电力公司映秀湾水力发电总厂 | A non-destructive testing method and system for pressure steel pipes |
| CN117871679A (en) * | 2024-03-11 | 2024-04-12 | 陕西昌硕科技有限公司 | High-sensitivity ultrasonic defect detection method and device |
| CN118533969A (en) * | 2024-07-04 | 2024-08-23 | 南通世森布业有限公司 | Ultrasonic-based non-woven fabric comprehensive quality inspection method, device and system |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109142533A (en) * | 2018-10-22 | 2019-01-04 | 广东工业大学 | A kind of rapid detection method and equipment of internal defect in cast |
| CN112147223A (en) * | 2020-10-14 | 2020-12-29 | 首钢京唐钢铁联合有限责任公司 | Method for detecting internal defects of casting blank |
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