Porous ceramic structural member hole processing method

Abstract

The invention relates to the field of image processing, in particular to a porous ceramic structural member hole processing method, which comprises the following steps: arranging an infrared thermal imager and acquiring and processing an infrared image in a processing process; obtaining an early warning factor according to the gray value fluctuation degree of the pixel points in each preprocessed image and the overall gray value of the pixel points; obtaining early warning parameters according to the gray scale gradient model of each preprocessed image; obtaining an early warning coefficient according to the similarity of the gray distribution of the two adjacent preprocessed images; and obtaining a structural member evaluation parameter by combining the early-warning factor, the early-warning parameter and the early-warning coefficient, setting an evaluation parameter threshold value, and performing early warning on the temperature abnormity of the structural member by combining the evaluation parameter, thereby completing the hole processing treatment of the porous ceramic structural member. According to the invention, the temperature abnormity early warning of the structural member is more accurate.

Description

Technical Field

[0001] The invention relates to the field of data processing, and in particular to a method for processing holes of a porous ceramic structural part. Background Art

[0002] Porous ceramic materials are widely used in aerospace, automobile manufacturing, electronics and other fields due to their high hardness, wear resistance, corrosion resistance and other excellent properties. However, the processing of ceramic materials is complicated and prone to thermal stress, which has a significant impact on the quality and performance of the finished product. This is because ceramic materials usually have low thermal conductivity, which means that when they are heated, the heat transfer rate inside the material is relatively slow. Therefore, during the processing, especially when locally heated, heat tends to accumulate in the processing area, resulting in local temperature increases, which may cause material damage, performance degradation and other problems.

[0003] Traditional hole processing of porous ceramic structural parts is to provide temperature abnormality warning for structural parts processing based on a fixed processing temperature threshold. However, there are many reasons for causing thermal stress, such as low thermal conductivity, cutting heat, and structural part morphology. These factors affect each other. Therefore, using a fixed temperature threshold to provide temperature abnormality warning for structural parts processing is not accurate enough. There may be an over-sensitivity of the warning that affects production efficiency, or there may be an insensitive warning that may pose a threat to the quality of the structural parts and the safety of the processing equipment. Summary of the invention

[0004] The present invention provides a method for processing holes of a porous ceramic structural component to solve the existing problem that a fixed temperature threshold is not accurate enough in providing an early warning of temperature anomalies during structural component processing.

[0005] A method for processing holes in a porous ceramic structure of the present invention adopts the following technical solution:

[0006] In a first aspect of the present invention, a method for processing holes in a porous ceramic structure is provided, the method comprising the following steps:

[0007] Arrange infrared thermal imagers to continuously collect infrared images during the processing at fixed time intervals and perform preprocessing until the structural parts are processed and each preprocessed image is obtained;

[0008] According to the gray value fluctuation degree of the pixels in each preprocessed image and the overall gray value size of the pixels, the warning factor of each preprocessed image is obtained; according to the gray gradient model of each preprocessed image, the warning parameter of each preprocessed image is obtained; according to the similarity of the gray distribution of two adjacent preprocessed images, the warning coefficient of each preprocessed image is obtained; according to the warning factor, warning parameter and warning coefficient of each preprocessed image, the warning degree of each preprocessed image is obtained;

[0009] According to the warning degree of each preprocessed image, the evaluation parameters of the structural part are obtained, the evaluation parameter threshold is set, and the hole processing process of the porous ceramic structural part is warned according to the evaluation parameter threshold to complete the hole processing process of the porous ceramic structural part.

[0010] Furthermore, the infrared thermal imager is arranged to continuously collect infrared images during the processing at fixed time intervals and perform preprocessing until the structural part is processed, and each preprocessed image is obtained. The specific method is as follows:

[0011] According to the preset time interval T, the number of images Y is collected, infrared images of the porous ceramic structure during the processing are collected, and the collected infrared images are grayed. The grayed infrared images are traversed in the order of collecting infrared images to obtain each pre-processed image.

[0012] Furthermore, the warning factor of each preprocessed image is obtained according to the gray value fluctuation degree of the pixel points in each preprocessed image and the overall gray value size of the pixel points. The specific method is as follows:

[0013] E z =Dis z ×Mea z

[0014] Where EWf z Denotes the warning factor of the zth preprocessed image, Dis z Represents the standard deviation of the grayscale values ​​of all pixels in the z-th preprocessed image, Mea z Represents the mean grayscale value of all pixels in the z-th preprocessed image, and the warning factor of each preprocessed image is obtained according to the above method.

[0015] Furthermore, the grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image, and the warning parameter of each preprocessed image is obtained according to the grayscale gradient model of each preprocessed image. The specific method is as follows:

[0016] The grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image. The specific method is as follows:

[0017] The edge contour of the structural part in the preprocessed image and the circular hole contour when the structural part is hole-processed are extracted by using an edge extraction algorithm. The position of the structural part where the circular dot inside the circular hole contour is located is taken as the hotspot of the structural part. The pixel point closest to the circular dot among the pixel points of the edge contour of the structural part in the preprocessed image is found, and a circle is drawn with the circular dot as the center and the pixel point closest to the circular dot as the radius. Thus, the grayscale gradient model of the preprocessed image is obtained. The grayscale gradient model of each preprocessed image is obtained according to this method.

[0018] The warning parameters of each preprocessed image are obtained according to the gray gradient model of each preprocessed image. The specific method is as follows:

[0019]

[0020] Where Ewp z Represents the warning parameter of the zth preprocessed image, Rad z Indicates the radius of the circle in the zth preprocessed image, represents the mean gray value of the pixel points where the circular hole contour is located in the z-th preprocessed image, Represents the mean grayscale value of the pixel points on the circumference of the circle drawn in the zth preprocessed image. The warning parameter of each preprocessed image is obtained according to the above method.

[0021] Furthermore, the warning coefficient of each pre-processed image is obtained according to the similarity of the grayscale distribution of two adjacent pre-processed images, and the specific method is as follows:

[0022]

[0023] Where Ewa z represents the warning coefficient of the zth preprocessed image, w z represents the number of pixels in the zth preprocessed image, h z,i represents the gray value of the i-th pixel in the z-th preprocessed image, represents the mean grayscale value of all pixels in the z-th preprocessed image, h z-1,i represents the gray value of the i-th pixel in the z-1-th preprocessed image, represents the mean gray value of all pixels in the z-1th preprocessed image, h z,I represents the gray value of the I-th pixel in the z-th preprocessed image, h z-1,j represents the gray value of the jth pixel in the z-1th preprocessed image, Ewa z+1 represents the warning coefficient of the z+1th preprocessed image, and the warning coefficient of each preprocessed image is obtained according to the above method.

[0024] Furthermore, the warning degree of each preprocessed image is obtained according to the warning factor, warning parameter and warning coefficient of each preprocessed image, and the specific method is as follows:

[0025] Dow z =Ewf z ×Ewp z ×(1-Ewa z )

[0026] In the formula, Dow zIndicates the warning level of the zth preprocessed image, Ewp z Represents the warning parameter of the zth preprocessed image, Ewf z represents the warning factor of the zth preprocessed image, Ewa z It represents the warning coefficient of the zth preprocessed image, and the warning degree of each preprocessed image is obtained according to the above method.

[0027] Furthermore, according to the warning degree of each preprocessed image, the evaluation parameter of the structural part is obtained, the evaluation parameter threshold is set, and the hole processing process of the porous ceramic structural part is warned according to the evaluation parameter threshold, and the hole processing process of the porous ceramic structural part is completed. The specific method is as follows:

[0028] Calculate the mean value of the warning degree of Y pre-processed images collected and processed, record the mean value as the evaluation parameter of the structural part, compare the evaluation parameter of the structural part with the evaluation parameter threshold, if the evaluation parameter of the structural part is greater than the evaluation parameter threshold, then issue a warning to the hole processing process of the structural part, stop the hole processing of the structural part and check the abnormal cause; if the evaluation parameter of the structural part is less than the evaluation parameter threshold, continue to collect and process the evaluation parameter of the structural part according to the preset time interval T and the number of collected images Y, and compare the evaluation parameter of the structural part with the evaluation parameter threshold; if the evaluation parameter of the structural part is greater than the evaluation parameter threshold, then issue a warning to the hole processing process of the structural part, stop the hole processing of the structural part and check the abnormal cause; if the evaluation parameter of the structural part is less than the evaluation parameter threshold, repeat the above steps until the hole processing of the structural part is completed.

[0029] A second aspect of the present invention provides a porous ceramic structural part hole processing system, the system comprising a temperature acquisition module, a parameter calculation module and a processing warning module, wherein:

[0030] The temperature acquisition module is used to arrange the infrared thermal imager to continuously acquire infrared images during the processing at fixed time intervals and perform preprocessing until the processing of the structural parts is completed and each preprocessed image is obtained;

[0031] The parameter calculation module is used to obtain the warning factor of each preprocessed image according to the gray value fluctuation degree of the pixels in each preprocessed image and the overall gray value size of the pixels; obtain the warning parameter of each preprocessed image according to the gray gradient model of each preprocessed image; obtain the warning coefficient of each preprocessed image according to the similarity of the gray distribution of two adjacent preprocessed images; obtain the warning degree of each preprocessed image according to the warning factor, warning parameter and warning coefficient of each preprocessed image;

[0032] The processing warning module is used to obtain the evaluation parameters of the structural part according to the warning degree of each pre-processed image, set the evaluation parameter threshold, and issue a warning for the hole processing process of the porous ceramic structural part according to the evaluation parameter threshold, thereby completing the hole processing process of the porous ceramic structural part.

[0033] A third aspect of the present invention is a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned method for processing holes in a porous ceramic structure.

[0034] A fourth aspect of the present invention is a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for processing holes in a porous ceramic structure when executing the computer program.

[0035] The beneficial effects of the technical solution of the present invention are: arranging infrared thermal imagers, continuously collecting infrared images during the processing at fixed time intervals and preprocessing them until the processing of the structural parts is completed, and obtaining each preprocessed image; using the infrared images, the temperature distribution of the structural parts can be obtained more clearly;

[0036] According to the gray value fluctuation degree of the pixel points in each pre-processed image and the overall gray value size of the pixel points, the early warning factor of each pre-processed image is obtained; by judging the gray value distribution and the overall gray value size in the pre-processed image, the local temperature anomaly and the overall temperature of the structural parts can be given to preliminarily judge the temperature anomaly of the structural parts;

[0037] A grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image, and the warning parameters of each preprocessed image are obtained according to the grayscale gradient model of each preprocessed image; a temperature gradient model is constructed to eliminate the influence of the shape of the structural part on the temperature gradient calculation, and the abnormality of the structural part is judged according to the size of the temperature gradient of the structural part, avoiding the judgment of the abnormality of the structural part by the image noise itself, and at the same time avoiding the thermal stress of the structural part caused by excessive temperature gradient;

[0038] According to the similarity of the grayscale distribution of two adjacent pre-processed images, the warning coefficient of each pre-processed image is obtained; the influence of thermal stress on the structural parts caused by the rapid temperature change during the cooling process is taken into account, and the situation that a single pre-processed image with relatively balanced pixel distribution and low overall temperature is misjudged as normal processing data is avoided;

[0039] Obtain the warning degree of each pre-processed image according to the warning factor, warning parameter and warning coefficient of each pre-processed image; more comprehensively judge the abnormality of the hole processing temperature of the pre-processed image;

[0040] According to the warning degree of each preprocessed image, the assessment parameters of the structural part are obtained, the assessment parameter threshold is set, and the hole processing process of the porous ceramic structural part is warned according to the assessment parameter threshold, so as to complete the hole processing process of the porous ceramic structural part; a comprehensive temperature anomaly judgment is made in the production stage of the structural part, and it is chosen to continue the hole processing or issue a warning according to the judgment result, which can more accurately warn of the abnormal temperature of the structural part processing and improve the stability of the porous ceramic structural part. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be 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.

[0042] Figure 1 A flowchart of the steps of a method for processing holes in a porous ceramic structure according to the present invention;

[0043] Figure 2 The present invention is a structural block diagram of a porous ceramic structural component hole processing system. DETAILED DESCRIPTION

[0044] 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 the specific implementation method, structure, characteristics and effects of a porous ceramic structural part hole processing method proposed by the present invention in combination 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.

[0045] 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.

[0046] The specific scheme of the method for processing holes in a porous ceramic structure provided by the present invention is described in detail below with reference to the accompanying drawings.

[0047] See also Figure 1 , which shows the first object of the present invention, a flowchart of a method for processing holes in a porous ceramic structure, the method comprising the following steps:

[0048] Step S001: Arrange an infrared thermal imager to continuously collect infrared images during the processing at fixed time intervals and perform preprocessing until the processing of the structural part is completed and each preprocessing image is obtained.

[0049] It should be noted that infrared thermal imagers measure the surface temperature of an object by detecting the infrared radiation emitted by it. The higher the temperature of the object, the greater the infrared energy radiated. The detector inside the infrared thermal imager receives these infrared radiations and converts them into electrical signals. After processing, a thermal image is generated. This image represents the temperature distribution on the surface of the object in different colors or gray levels, so that the temperature difference can be seen intuitively. In the process of hole processing in porous ceramic materials, under normal circumstances, the temperature of the cutting area is the highest, that is, the temperature around the hole is the highest, and the temperature should decrease gradually with the increase of the distance from the cutting area. In order to more clearly observe the temperature distribution of the workpiece during processing, it is necessary to arrange an infrared thermal imager directly below the cutting head.

[0050] Specifically, an infrared thermal imager is arranged to continuously collect infrared images during the processing at fixed time intervals and perform preprocessing until the structural parts are processed and each preprocessed image is obtained. The specific method is as follows:

[0051] According to the preset time interval T, the number of images Y is collected, infrared images of the porous ceramic structure during the processing are collected, and the collected infrared images are grayed. The grayed infrared images are traversed in the order of collecting infrared images to obtain each pre-processed image.

[0052] It should be noted that in this embodiment, the time interval for collecting infrared images is 0.01 seconds each time, and the number of collected infrared images is 20. In other embodiments, the time interval for collecting infrared images and the number of collected infrared images depend on the specific implementation situation.

[0053] Step S002: Obtain the warning factor of each preprocessed image based on the grayscale value fluctuation degree of the pixels in each preprocessed image and the overall grayscale value of the pixels; obtain the warning parameters of each preprocessed image based on the grayscale gradient model of each preprocessed image; obtain the warning coefficient of each preprocessed image based on the similarity of the grayscale distribution of two adjacent preprocessed images; obtain the warning degree of each preprocessed image based on the warning factor, warning parameter and warning coefficient of each preprocessed image.

[0054] It should be noted that since the fixed temperature threshold does not take into account the differences in sensitivity of different processing conditions, material properties and structural parts to temperature changes, it may falsely report temperature anomalies during normal processing, resulting in production interruptions or adjustments, thereby affecting production efficiency; on the contrary, in some cases, due to the fixed temperature threshold being set too high or other factors in the processing process causing the actual temperature to be much higher than expected, but the early warning system fails to respond in time, which may pose a threat to the quality of the structural parts and the safety of the processing equipment.

[0055] It should be further explained that ceramic materials usually have low thermal conductivity, which means that when they are heated, the heat transfer rate inside the material is relatively slow. Therefore, during the processing, especially when locally heated, heat tends to accumulate in the processing area, resulting in local temperature rise; but in normal processing, if the cooling measures are appropriate, the temperature distribution of the pixels on the infrared image should be relatively uniform, without obvious hot spots or cold spots; and in high temperature environments, the microstructure of ceramic materials may change, such as grain growth, phase change, etc. These changes will directly affect the mechanical properties, thermal properties and electrical properties of the material. For example, mechanical properties such as hardness, strength, and toughness may decrease significantly, affecting the quality and service life of the processed product. Therefore, during the processing, the higher the temperature of the structural part and the more uneven the temperature distribution, the greater the probability that the structural part may be affected by thermal stress.

[0056] Specifically, according to the gray value fluctuation degree of the pixels in each pre-processed image and the overall gray value size of the pixels, the early warning factor of each pre-processed image is obtained. The specific method is as follows:

[0057] E z =Dis z ×Mea z

[0058] Where Ewf z Denotes the warning factor of the zth preprocessed image, Dis z Represents the standard deviation of the grayscale values ​​of all pixels in the z-th preprocessed image, Mea z Represents the mean grayscale value of all pixels in the z-th preprocessed image, and the warning factor of each preprocessed image is obtained according to the above method.

[0059] It should be noted that when Dis z The smaller it is, the more uniform the distribution of the grayscale values ​​of the pixels in the z-th preprocessed image is, that is, the more uniform the temperature distribution of the porous ceramic structure corresponding to the z-th preprocessed image is; when Mea z The smaller it is, the smaller the overall grayscale value of the pixels in the z-th preprocessed image is, that is, the lower the overall temperature of the porous ceramic structure corresponding to the z-th preprocessed image is; the smaller the warning factor is, the lower the probability of abnormality in the processing of the porous ceramic structure is.

[0060] It should be further explained that, for the above steps, the temperature anomaly of the structural parts corresponding to the image is judged only based on the fluctuation degree of the grayscale values ​​of the pixels in the image and the overall size of the grayscale values ​​of the pixels. The fluctuation degree of the pixels in the image will also be affected by the noise itself, and when the temperature of the pixels around the hot spot forms an obvious temperature gradient, the local temperature of the structural parts corresponding to the image at this time is relatively high, which is prone to thermal stress. Therefore, the influence of thermal stress on the stability of the structural parts should be avoided and an early warning should be issued. Therefore, in the above steps, there may be a situation where the early warning factor of the structural parts corresponding to some images is small, but the probability of being affected by thermal stress is high; therefore, this step needs to judge the early warning risk of the structural parts according to the size of the temperature gradient around the hot spot.

[0061] Specifically, a grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image, and a warning parameter of each preprocessed image is obtained according to the grayscale gradient model of each preprocessed image. The specific method is as follows:

[0062] The grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image. The specific method is as follows:

[0063] The edge contour of the structural part in the preprocessed image and the circular hole contour when the structural part is hole-processed are extracted by using an edge extraction algorithm. The position of the structural part where the circular dot inside the circular hole contour is located is taken as the hotspot of the structural part. The pixel point closest to the circular dot among the pixel points of the edge contour of the structural part in the preprocessed image is found, and a circle is drawn with the circular dot as the center and the pixel point closest to the circular dot as the radius. Thus, the grayscale gradient model of the preprocessed image is obtained. The grayscale gradient model of each preprocessed image is obtained according to this method.

[0064] It should be noted that since the holes in the structural parts are processed, the temperature of the holes at the cutting point is the highest, and the thermal conductivity of the air is poor. Therefore, in the infrared temperature image, the temperature difference between the processed hole and the surrounding materials and air leads to different grayscale values, thus forming a clear edge. The algorithm can identify these grayscale differences and extract the contours of the processed holes and the structural parts. The purpose of drawing a circle based on the shortest distance is to avoid differences in the shapes of the structural parts and to facilitate unified measurement of the temperature distribution in all directions.

[0065] The warning parameters of each preprocessed image are obtained according to the gray gradient model of each preprocessed image. The specific method is as follows:

[0066]

[0067] Where Ewp z Represents the warning parameter of the zth preprocessed image, Rad z Indicates the radius of the circle in the zth preprocessed image, represents the mean gray value of the pixel points where the circular hole contour is located in the z-th preprocessed image, Represents the mean grayscale value of the pixel points on the circumference of the circle drawn in the zth preprocessed image. The warning parameter of each preprocessed image is obtained according to the above method.

[0068] It should be noted that due to the different sizes and shapes of structural parts, the sizes of circles made during the processing of different structural parts may be different, but the thermal conductivity coefficients of the structural parts are similar, so it is necessary to judge the temperature anomaly of the structural parts based on the ratio of temperature difference and heat conduction distance. The bigger the Rad z The smaller it is, the more obvious the temperature gradient of the structural part corresponding to the zth preprocessed image is, the greater the probability that the temperature of the structural part is abnormal and is affected by thermal stress, that is, the larger the warning parameter is.

[0069] It should be further explained that in the hole machining and cutting process of porous ceramic structural parts, the main function of the coolant is to quickly take away the heat generated during the cutting process and reduce the temperature of the cutting area. However, if the flow rate of the coolant is too large or the temperature is too low, it may quickly reduce the temperature of the cutting area in a short period of time, resulting in faster temperature fluctuations and thermal stress in the structural parts. However, at this time, in the preprocessed graphics, the grayscale value distribution of the pixels may be relatively uniform, and the grayscale value is relatively small overall, without an obvious temperature gradient. The above-mentioned warning factors and warning parameters cannot accurately judge the probability of the structural parts being affected by thermal stress. Therefore, this step needs to judge the degree of temperature change of the corresponding structural parts of the preprocessed images based on the similarity of the grayscale distribution of the two adjacent preprocessed images.

[0070] Specifically, according to the similarity of the grayscale distribution of two adjacent pre-processed images, the warning coefficient of each pre-processed image is obtained. The specific method is as follows:

[0071]

[0072] Where Ewa z represents the warning coefficient of the zth preprocessed image, w z represents the number of pixels in the zth preprocessed image, h z,i represents the gray value of the i-th pixel in the z-th preprocessed image, represents the mean grayscale value of all pixels in the z-th preprocessed image, h z-1,i represents the gray value of the i-th pixel in the z-1-th preprocessed image, represents the mean gray value of all pixels in the z-1th preprocessed image, h z,I represents the gray value of the I-th pixel in the z-th preprocessed image, h z-1,jrepresents the gray value of the jth pixel in the z-1th preprocessed image, Ewa z+1 represents the warning coefficient of the z+1th preprocessed image, and the warning coefficient of each preprocessed image is obtained according to the above method.

[0073] It should be noted that the above method compares the similarity of the pixel distribution of two adjacent pre-processed images in the discrete cosine transform, and limits the value range of the similarity to between 0 and 1. The larger the warning coefficient of a pre-processed image, the more similar the pre-processed image is to the pre-processed image obtained after the acquisition and processing at the previous moment, and the smoother the temperature change of the pre-processed image, and the smaller the probability of thermal stress in the structural parts caused by drastic temperature changes.

[0074] It should be further explained that, in the above process, the warning factors, warning parameters and warning coefficients of each pre-processed image are obtained, and the influence of thermal stress on the structural parts is comprehensively judged from multiple angles. Now, it is necessary to comprehensively judge the warning degree of each pre-processed image based on the above warning factors, warning parameters and warning coefficients.

[0075] Specifically, the warning degree of each preprocessed image is obtained according to the warning factor, warning parameter and warning coefficient of each preprocessed image. The specific method is as follows:

[0076] Dow z =Ewf z ×Ewp z ×(1-Ewa z )

[0077] In the formula, Dow z Indicates the warning level of the zth preprocessed image, Ewp z Represents the warning parameter of the zth preprocessed image, Ewf z represents the warning factor of the zth preprocessed image, Ewa z It represents the warning coefficient of the zth preprocessed image, and the warning degree of each preprocessed image is obtained according to the above method.

[0078] It should be noted that the larger the warning factor and the warning parameter, the greater the probability that the structural part corresponding to the image is affected by thermal stress. When the warning coefficient is larger, the probability that the structural part corresponding to the image is affected by thermal stress is smaller. When the warning factor is larger, the warning parameter is larger, the warning coefficient is smaller, and the probability that the structural part corresponding to the image is affected by thermal stress is greater.

[0079] Step S003: according to the warning degree of each preprocessed image, the evaluation parameter of the structural part is obtained, the evaluation parameter threshold is set, and the hole machining process of the porous ceramic structural part is warned according to the evaluation parameter threshold, thereby completing the hole machining process of the porous ceramic structural part.

[0080] It should be noted that the above method obtains the warning level of each pre-processed image. Next, it is necessary to obtain the assessment parameters of the structural parts in the current image acquisition period according to the warning levels of all the above pre-processed images, and set the assessment parameter threshold. According to the assessment parameter threshold, it is determined whether the structural parts processing needs warning. In this embodiment, the assessment parameter threshold is 110, and the assessment parameter threshold in other embodiments depends on the specific implementation situation.

[0081] Specifically, according to the warning degree of each preprocessed image, the evaluation parameter of the structural part is obtained, the evaluation parameter threshold is set, and the hole processing process of the porous ceramic structural part is warned according to the evaluation parameter threshold, and the hole processing process of the porous ceramic structural part is completed. The specific method is as follows:

[0082] Calculate the mean value of the warning degree of Y pre-processed images collected and processed, record the mean value as the evaluation parameter of the structural part, compare the evaluation parameter of the structural part with the evaluation parameter threshold, if the evaluation parameter of the structural part is greater than the evaluation parameter threshold, then issue a warning to the hole processing process of the structural part, stop the hole processing of the structural part and check the abnormal cause; if the evaluation parameter of the structural part is less than the evaluation parameter threshold, continue to collect and process the evaluation parameter of the structural part according to the preset time interval T and the number of collected images Y, and compare the evaluation parameter of the structural part with the evaluation parameter threshold; if the evaluation parameter of the structural part is greater than the evaluation parameter threshold, then issue a warning to the hole processing process of the structural part, stop the hole processing of the structural part and check the abnormal cause; if the evaluation parameter of the structural part is less than the evaluation parameter threshold, repeat the above steps until the hole processing of the structural part is completed.

[0083] See also Figure 2 , which shows the second object of the present invention, a structural block diagram of a porous ceramic structural part hole processing system, the system includes the following modules:

[0084] The temperature acquisition module is used to arrange the infrared thermal imager to continuously acquire infrared images during the processing at fixed time intervals and perform preprocessing until the processing of the structural parts is completed and each preprocessed image is obtained;

[0085] The parameter calculation module is used to obtain the warning factor of each preprocessed image according to the gray value fluctuation degree of the pixels in each preprocessed image and the overall gray value size of the pixels; obtain the warning parameter of each preprocessed image according to the gray gradient model of each preprocessed image; obtain the warning coefficient of each preprocessed image according to the similarity of the gray distribution of two adjacent preprocessed images; obtain the warning degree of each preprocessed image according to the warning factor, warning parameter and warning coefficient of each preprocessed image;

[0086] The processing warning module is used to obtain the evaluation parameters of the structural part according to the warning degree of each pre-processed image, set the evaluation parameter threshold, and issue a warning for the hole processing process of the porous ceramic structural part according to the evaluation parameter threshold, thereby completing the hole processing process of the porous ceramic structural part.

[0087] The third object of an embodiment of the present invention is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for processing holes in a porous ceramic structure when executing the computer program.

[0088] A fourth object of an embodiment of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for processing holes in a porous ceramic structure are implemented.

[0089] In this embodiment, an infrared thermal imager is arranged to continuously collect infrared images during the processing at fixed time intervals and perform preprocessing until the processing of the structural parts is completed, and each preprocessing image is obtained; the temperature distribution of the structural parts can be obtained more clearly by using the infrared images;

[0090] According to the gray value fluctuation degree of the pixel points in each pre-processed image and the overall gray value size of the pixel points, the early warning factor of each pre-processed image is obtained; by judging the gray value distribution and the overall gray value size in the pre-processed image, the local temperature anomaly and the overall temperature of the structural parts can be given to preliminarily judge the temperature anomaly of the structural parts;

[0091] A grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image, and the warning parameters of each preprocessed image are obtained according to the grayscale gradient model of each preprocessed image; a temperature gradient model is constructed to eliminate the influence of the shape of the structural part on the temperature gradient calculation, and the abnormality of the structural part is judged according to the size of the temperature gradient of the structural part, avoiding the judgment of the abnormality of the structural part by the image noise itself, and at the same time avoiding the thermal stress of the structural part caused by excessive temperature gradient;

[0092] According to the similarity of the grayscale distribution of two adjacent pre-processed images, the warning coefficient of each pre-processed image is obtained; the influence of thermal stress on the structural parts caused by the rapid temperature change during the cooling process is taken into account, and the situation that a single pre-processed image with relatively balanced pixel distribution and low overall temperature is misjudged as normal processing data is avoided;

[0093] Obtain the warning degree of each pre-processed image according to the warning factor, warning parameter and warning coefficient of each pre-processed image; more comprehensively judge the abnormality of the hole processing temperature of the pre-processed image;

[0094] According to the warning degree of each preprocessed image, the assessment parameters of the structural part are obtained, the assessment parameter threshold is set, and the hole processing process of the porous ceramic structural part is warned according to the assessment parameter threshold, and the hole processing process of the porous ceramic structural part is completed; a comprehensive temperature anomaly judgment is made in the production stage of the structural part, and the choice of continuing the hole processing or issuing a warning is made according to the judgment result, which can more accurately warn of the abnormal temperature of the structural part processing and improve the stability of the porous ceramic structural part.

[0095] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for processing holes in a porous ceramic structure, characterized in that: The method comprises the following steps: Arrange infrared thermal imagers to continuously collect infrared images during the processing at fixed time intervals and perform preprocessing until the structural parts are processed and each preprocessed image is obtained; According to the gray value fluctuation degree of the pixels in each preprocessed image and the overall gray value size of the pixels, the warning factor of each preprocessed image is obtained; according to the gray gradient model of each preprocessed image, the warning parameter of each preprocessed image is obtained; according to the similarity of the gray distribution of two adjacent preprocessed images, the warning coefficient of each preprocessed image is obtained; according to the warning factor, warning parameter and warning coefficient of each preprocessed image, the warning degree of each preprocessed image is obtained; According to the warning degree of each preprocessed image, the evaluation parameters of the structural part are obtained, the evaluation parameter threshold is set, and the hole processing process of the porous ceramic structural part is warned according to the evaluation parameter threshold to complete the hole processing process of the porous ceramic structural part.

2. A method for processing holes in a porous ceramic structure according to claim 1, characterized in that: The infrared thermal imager is arranged to continuously collect infrared images during the processing at fixed time intervals and perform preprocessing until the structural parts are processed, and each preprocessing image is obtained. The specific method is as follows: According to the preset time interval T, the number of images Y is collected, infrared images of the porous ceramic structure during the processing are collected, and the collected infrared images are grayed. The grayed infrared images are traversed in the order of collecting infrared images to obtain each pre-processed image.

3. A method for processing holes in a porous ceramic structure according to claim 1, characterized in that: The method of obtaining the early warning factor of each pre-processed image according to the gray value fluctuation degree of the pixel points in each pre-processed image and the overall gray value size of the pixel points is as follows: Ewf z =Dis z ×Mea z Where Ewf z Denotes the warning factor of the zth preprocessed image, Dis z Represents the standard deviation of the grayscale values ​​of all pixels in the z-th preprocessed image, Mea z Represents the mean grayscale value of all pixels in the z-th preprocessed image, and the warning factor of each preprocessed image is obtained according to the above method.

4. A method for processing holes in a porous ceramic structure according to claim 1, characterized in that: The grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image, and the warning parameter of each preprocessed image is obtained according to the grayscale gradient model of each preprocessed image. The specific method is as follows: The grayscale gradient model of each preprocessed image is constructed according to the grayscale distribution of each preprocessed image. The specific method is as follows: The edge contour of the structural part in the preprocessed image and the circular hole contour when the structural part is hole-processed are extracted by using an edge extraction algorithm. The position of the structural part where the circular dot inside the circular hole contour is located is taken as the hotspot of the structural part. The pixel point closest to the circular dot among the pixel points of the edge contour of the structural part in the preprocessed image is found, and a circle is drawn with the circular dot as the center and the pixel point closest to the circular dot as the radius. Thus, the grayscale gradient model of the preprocessed image is obtained. The grayscale gradient model of each preprocessed image is obtained according to this method. The warning parameters of each preprocessed image are obtained according to the gray gradient model of each preprocessed image. The specific method is as follows: Where Ewp z Represents the warning parameter of the zth preprocessed image, Rad z Indicates the radius of the circle in the zth preprocessed image, represents the mean gray value of the pixel points where the circular hole contour is located in the z-th preprocessed image, Represents the mean grayscale value of the pixel points on the circumference of the circle drawn in the zth preprocessed image. The warning parameter of each preprocessed image is obtained according to the above method.

5. A method for processing holes in a porous ceramic structure according to claim 1, characterized in that: The method of obtaining the warning coefficient of each pre-processed image according to the similarity of the grayscale distribution of two adjacent pre-processed images is as follows: Where Ewa z represents the warning coefficient of the zth preprocessed image, w z represents the number of pixels in the zth preprocessed image, h z，i represents the gray value of the i-th pixel in the z-th preprocessed image, represents the mean grayscale value of all pixels in the z-th preprocessed image, h z-1，i represents the gray value of the i-th pixel in the z-1-th preprocessed image, represents the mean gray value of all pixels in the z-1th preprocessed image, h z，I represents the gray value of the first pixel in the z-th preprocessed image, h z-1，j represents the gray value of the jth pixel in the z-1th preprocessed image, Ewa z+1 represents the warning coefficient of the z+1th preprocessed image, and the warning coefficient of each preprocessed image is obtained according to the above method.

6. A method for processing holes in a porous ceramic structure according to claim 1, characterized in that: The specific method of obtaining the warning degree of each pre-processed image according to the warning factor, warning parameter and warning coefficient of each pre-processed image is as follows: Dow z =Ewf z ×Ewp z ×(1-Ewa z ) In the formula, Dow z Indicates the warning level of the zth preprocessed image, Ewp z Represents the warning parameter of the zth preprocessed image, Ewf z represents the warning factor of the zth preprocessed image, Ewa z It represents the warning coefficient of the zth preprocessed image, and the warning degree of each preprocessed image is obtained according to the above method.

7. A method for processing holes in a porous ceramic structure according to claim 1, characterized in that: According to the warning degree of each pre-processed image, the evaluation parameter of the structural part is obtained, the evaluation parameter threshold is set, and the hole processing process of the porous ceramic structural part is warned according to the evaluation parameter threshold, and the hole processing process of the porous ceramic structural part is completed. The specific method is as follows: Calculate the mean value of the warning degree of Y pre-processed images collected and processed, record the mean value as the evaluation parameter of the structural part, compare the evaluation parameter of the structural part with the evaluation parameter threshold, if the evaluation parameter of the structural part is greater than the evaluation parameter threshold, then issue a warning to the hole processing process of the structural part, stop the hole processing of the structural part and check the abnormal cause; if the evaluation parameter of the structural part is less than the evaluation parameter threshold, continue to collect and process the evaluation parameter of the structural part according to the preset time interval T and the number of collected images Y, and compare the evaluation parameter of the structural part with the evaluation parameter threshold; if the evaluation parameter of the structural part is greater than the evaluation parameter threshold, then issue a warning to the hole processing process of the structural part, stop the hole processing of the structural part and check the abnormal cause; if the evaluation parameter of the structural part is less than the evaluation parameter threshold, repeat the above steps until the hole processing of the structural part is completed.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a method for processing holes in a porous ceramic structure as claimed in any one of claims 1 to 7 are implemented.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for processing holes in a porous ceramic structure as claimed in any one of claims 1 to 7 are implemented.

10. A porous ceramic structural part hole processing system, characterized in that: The system includes the following modules: The temperature acquisition module is used to arrange the infrared thermal imager to continuously acquire infrared images during the processing at fixed time intervals and perform preprocessing until the processing of the structural parts is completed and each preprocessed image is obtained; A parameter calculation module is used to obtain the early warning factor of each pre-processed image according to the gray value fluctuation degree of the pixel points in each pre-processed image and the overall gray value size of the pixel points; Obtaining the warning parameter of each preprocessed image according to the gray gradient model of each preprocessed image; According to the similarity of the grayscale distribution of two adjacent pre-processed images, the warning coefficient of each pre-processed image is obtained; Obtaining the warning degree of each preprocessed image according to the warning factor, warning parameter and warning coefficient of each preprocessed image; The processing warning module is used to obtain the evaluation parameters of the structural part according to the warning degree of each pre-processed image, set the evaluation parameter threshold, and issue a warning for the hole processing process of the porous ceramic structural part according to the evaluation parameter threshold, thereby completing the hole processing process of the porous ceramic structural part.

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