Composite material fan blade defect identification method and device and electronic equipment

Abstract

The invention relates to a composite material fan blade defect identification method and device and electronic equipment. The method comprises the steps that a first ultrasonic penetration C scanning result of a standard composite material fan blade and a second ultrasonic penetration C scanning result of a to-be-identified composite material fan blade are acquired; flattening the first ultrasonic penetration C scanning result into two-dimensional image energy data of the first C scanning result, and performing grid division to obtain a first energy grid diagram; flattening the second ultrasonic penetration C scanning result into second C scanning result two-dimensional image energy data, and performing grid division according to the grid division mode of the first C scanning result two-dimensional image energy data to obtain a second energy grid diagram; and determining the defect type of the to-be-identified composite material fan blade based on the first energy value corresponding to each grid in the first energy grid chart and the second energy value corresponding to each grid in the second energy grid chart. Therefore, the defects of the composite material fan blade can be identified accurately and quickly.

Description

Technical Field

[0001] The present disclosure relates to the field of aero-engine technology, and in particular to a composite material fan blade defect identification method, device and electronic equipment. Background Art

[0002] As one of the key parts of the engine, composite fan blades have harsh operating conditions and high strength and life requirements, which impose strict requirements on their internal quality. Therefore, composite fan blades must be 100% non-destructively tested, and the testing accuracy and acceptance requirements are much higher than other composite stator parts. At present, the commonly used detection method in the industry for defects such as delamination, looseness, and porosity in composite structures is ultrasonic testing.

[0003] However, due to the low symmetry and high complexity of the fan blade structure, which is mainly reflected in the large changes in curvature, large changes in thickness, and non-parallel surfaces of local structures, it poses great challenges to ultrasonic detection and evaluation.

[0004] Therefore, finding a method that can accurately and quickly identify defects in composite fan blades has become a research hotspot. Summary of the invention

[0005] In order to overcome the problems existing in the related art, the present disclosure provides a composite material fan blade defect identification method, device and electronic equipment.

[0006] According to a first aspect of an embodiment of the present disclosure, a method for identifying defects in composite fan blades is provided, the method comprising: obtaining a first ultrasonic penetration C-scan result of a standard composite fan blade, and a second ultrasonic penetration C-scan result of a composite fan blade to be identified, wherein performance parameters of the standard composite fan blade meet preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model; flattening the first ultrasonic penetration C-scan result into first C-scan result two-dimensional image energy data, and gridding the first C-scan result two-dimensional image energy data to obtain a first energy grid map, wherein the unit size of the grid is determined according to the target energy data. The target position of the corresponding standard composite fan blade is determined, and the target energy data corresponds to the grid; the second ultrasonic penetration C-scan result is flattened into the second C-scan result two-dimensional image energy data, and the second C-scan result two-dimensional image energy data is grid-divided according to the grid division method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map, the defect type of the composite fan blade to be identified is determined.

[0007] According to the defect identification method for composite fan blades provided by the present disclosure, the defect type of the composite fan blade to be identified is determined based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map, including: respectively performing difference processing on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map to obtain the energy difference value corresponding to each grid; when the energy difference value exceeds the energy difference value threshold, determining the grid in the second energy grid map corresponding to the energy difference value as the abnormal area grid; merging a plurality of abnormal area grids with adjacent positions and the same energy deviation direction to obtain an ultrasonic attenuation abnormal cloud map, wherein the energy deviation direction is determined according to the first energy value corresponding to the abnormal area grid and the second energy value corresponding to the abnormal area grid; respectively determining the energy attenuation value of the ultrasonic attenuation abnormal cloud map, the ultrasonic penetration C-scan result of the area corresponding to the ultrasonic attenuation abnormal cloud map, and the ultrasonic reflection scan result of the area corresponding to the ultrasonic attenuation abnormal cloud map; determining the defect type of the composite fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormal cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result.

[0008] According to the defect identification method for composite fan blades provided by the present disclosure, the defect type of the composite fan blade to be identified is determined based on the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, including: determining the energy difference between the energy attenuation value of the ultrasonic attenuation anomaly cloud map and the corresponding area of ​​the first energy grid map; when the energy difference is greater than an energy difference threshold, the ultrasonic penetration C-scan result shows that the regional boundary is clear, and the ultrasonic reflection scan result shows that a defect wave is found, determining that the defect type of the composite fan blade to be identified is a delamination / debonding defect; when the energy difference is less than or equal to the energy difference threshold, the ultrasonic penetration C-scan result shows that the regional boundary is not bounded, and the ultrasonic reflection scan result shows that no defect wave is found, determining that the defect type of the composite fan blade to be identified is a porosity / weak adhesion defect.

[0009] According to the composite fan blade defect identification method provided by the present disclosure, before determining the defect type of the composite fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the method also includes: respectively determining a first evaluation level of the energy attenuation value, a second evaluation level of the ultrasonic penetration C-scan result, and a third evaluation level of the ultrasonic reflection scan result; determining the defect type of the composite fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result includes: determining the defect type of the composite fan blade to be identified based on the priority order of the first evaluation level, the second evaluation level, and the third evaluation level, in combination with the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result.

[0010] According to the defect identification method for composite fan blades provided by the present disclosure, the energy attenuation value of the ultrasonic attenuation anomaly cloud map is determined in the following manner: multiple abnormal grids in the second energy grid map corresponding to the ultrasonic attenuation anomaly cloud map are obtained, and reference grids corresponding to the multiple abnormal grids in the first energy grid map are obtained; a first average energy value of the energy values ​​corresponding to each of the abnormal grids and a second average energy value of the energy values ​​corresponding to each of the reference grids are determined; based on the difference between the first average energy value and the second average energy value, the energy attenuation value of the ultrasonic attenuation anomaly cloud map is determined.

[0011] According to the defect identification method for composite fan blades provided in the present disclosure, the first energy value corresponding to each grid in the first energy grid map is determined in the following manner: based on the two-dimensional image energy data of the first C-scan result, the first site energy data of each first point in each grid in the first energy grid map is determined; based on the average value of the first site energy data, the first energy value corresponding to each grid in the first energy grid map is determined.

[0012] According to the defect identification method for composite fan blades provided in the present disclosure, the second energy value corresponding to each grid in the second energy grid map is determined in the following manner: based on the two-dimensional image energy data of the second C-scan result, the second site energy data of each second site in each grid in the second energy grid map is determined; based on the average value of the second site energy data, the second energy value corresponding to each grid in the second energy grid map is determined.

[0013] According to the composite fan blade defect identification method provided by the present disclosure, the unit size of the grid is negatively correlated with the blade thickness change rate corresponding to the target location, and / or the blade curvature corresponding to the target location.

[0014] According to a second aspect of an embodiment of the present disclosure, a composite fan blade defect identification device is provided, the device comprising: an acquisition module, used to acquire a first ultrasonic penetration C-scan result of a standard composite fan blade, and a second ultrasonic penetration C-scan result of a composite fan blade to be identified, wherein the performance parameters of the standard composite fan blade meet preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model; a first flattening module, used to flatten the first ultrasonic penetration C-scan result into first C-scan result two-dimensional image energy data, and grid the first C-scan result two-dimensional image energy data to obtain a first energy grid map, wherein the unit size of the grid is determined according to the target energy data. The target position of the corresponding standard composite fan blade is determined, and the target energy data corresponds to the grid; a second flattening module is used to flatten the second ultrasonic penetration C-scan result into a second C-scan result two-dimensional image energy data, and grid the second C-scan result two-dimensional image energy data according to the grid division method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; a processing module is used to determine the defect type of the composite fan blade to be identified based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map.

[0015] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, the method for identifying defects in a composite fan blade as described in any one of the embodiments of the first aspect is implemented.

[0016] According to a fourth aspect of an embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the composite fan blade defect identification method described in any one of the embodiments of the first aspect is implemented.

[0017] The technical solution provided by the embodiment of the present disclosure may include the following beneficial effects: obtaining the first ultrasonic penetration C-scan result of a standard composite fan blade and the second ultrasonic penetration C-scan result of a composite fan blade to be identified; flattening the first ultrasonic penetration C-scan result into the first C-scan result two-dimensional image energy data, and meshing the first C-scan result two-dimensional image energy data to obtain a first energy grid map; flattening the second ultrasonic penetration C-scan result into the second C-scan result two-dimensional image energy data, and meshing the second C-scan result two-dimensional image energy data according to the meshing method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; and then determining the defect type of the composite fan blade to be identified based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map. Accurate and rapid comparative analysis of data in various regions of the entire blade and ultrasonic abnormality recognition and extraction are achieved.

[0018] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0020] Figure 1 The present invention is a flow chart of a composite material fan blade defect identification method according to an exemplary embodiment.

[0021] Figure 2 It is a schematic diagram of the characteristic structure of meshing of an ultrasonic C-scan flattened image of a composite material fan blade according to an exemplary embodiment.

[0022] Figure 3It is a flowchart for determining the defect type of a composite material fan blade to be identified based on the first energy values corresponding to the grids in the first energy grid diagram and the second energy values corresponding to the grids in the second energy grid diagram, as shown in an exemplary embodiment.

[0023] Figure 4 It is a flowchart for determining the energy attenuation value of an ultrasonic attenuation anomaly cloud map, as shown in an exemplary embodiment.

[0024] Figure 5 It is a block diagram for identifying defects in a composite material fan blade, as shown in an exemplary embodiment.

[0025] Figure 6 It is a schematic structural diagram of an electronic device, as shown in an exemplary embodiment. Detailed implementation manners

[0026] The following will describe the detailed implementation manners of the present disclosure. It should be noted that in the process of the specific description of these implementation manners, for the sake of concise description, this specification cannot describe all the features of the actual implementation manners in detail. It should be understood that in the actual implementation process of any implementation manner, just as in the process of any engineering project or design project, in order to achieve the specific goals of the developer and to meet the system-related or business-related restrictions, various specific decisions are often made, and these will also change from one implementation manner to another. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for those of ordinary skill in the art related to the content disclosed in the present disclosure, some design, manufacturing or production changes based on the technical content disclosed in the present disclosure are only conventional technical means and should not be understood as the content of the present disclosure being insufficient.

[0027] Unless otherwise defined, the technical terms or scientific terms used in the claims and the specification should have the ordinary meanings understood by those of ordinary skill in the technical field to which the present disclosure belongs. The "first", "second" and similar terms used in the specification and claims of this patent application of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. The terms such as "a" or "an" do not indicate a quantity limitation, but indicate that there is at least one. The terms such as "including" or "comprising" mean that the elements or objects appearing before "including" or "comprising" cover the elements or objects listed after "including" or "comprising" and their equivalent elements, and do not exclude other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, nor are they limited to direct or indirect connections.

[0028] In order to improve the accuracy of defect identification and judgment as much as possible, the composite material fan blade defect identification method provided in the present invention is combined with the actual characteristics of the fan blade to establish an ultrasonic detection defect identification and judgment method with high consistency and accuracy.

[0029] Figure 1 The present invention is a flow chart of a composite material fan blade defect identification method according to an exemplary embodiment.

[0030] The following will be combined Figure 1 The process of the composite fan blade defect identification method provided by the present disclosure is described.

[0031] In an exemplary embodiment of the present disclosure, Figure 1 It can be seen that the composite material fan blade defect identification method may include steps 110 to 140, and each step will be introduced below.

[0032] In step 110, a first ultrasonic penetration C-scan result of a standard composite material fan blade and a second ultrasonic penetration C-scan result of a composite material fan blade to be identified are obtained.

[0033] Among them, the performance parameters of the standard composite fan blade meet the preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model.

[0034] In one embodiment, the preset requirements can be determined according to actual conditions, such as defect-free and zero porosity. During the application process, defect-free and zero porosity composite fan blades can be screened as standard composite fan blades.

[0035] In another embodiment, the blade to be inspected (corresponding to the composite fan blade to be identified) and the standard blade (corresponding to the standard composite fan blade) can be subjected to ultrasonic penetration C-scan detection, and full sensitivity recording can be performed to obtain the first ultrasonic penetration C-scan result of the standard composite fan blade and the second ultrasonic penetration C-scan result of the composite fan blade to be identified. The standard composite fan blade and the composite fan blade to be identified have the same model. In this embodiment, the standard composite fan blade and the composite fan blade to be identified have the same model, which can ensure the accuracy of defect identification based on the comparison result of the standard composite fan blade with the composite fan blade to be identified.

[0036] In step 120, the first ultrasonic penetration C-scan result is flattened into first C-scan result two-dimensional image energy data, and the first C-scan result two-dimensional image energy data is grid-divided to obtain a first energy grid map.

[0037] In one embodiment, the first ultrasonic penetration C-scan result can be flattened into the first C-scan result two-dimensional image energy data, wherein the first C-scan result two-dimensional image energy data can be understood as a two-dimensional image form of the first ultrasonic penetration C-scan result. Further, the first C-scan result two-dimensional image energy data is grid-divided to obtain a first energy grid map. In other words, the first C-scan result two-dimensional image energy data is divided into a plurality of grids to obtain a first energy grid map. Each grid of the first energy grid map corresponds to an energy value.

[0038] The unit size of the grid may be determined according to the target location of the standard composite fan blade corresponding to the target energy data, and the target energy data corresponds to the grid.

[0039] In yet another exemplary embodiment of the present disclosure, the unit size of the grid is negatively correlated with the blade thickness change rate corresponding to the target location, and / or the blade curvature corresponding to the target location.

[0040] Figure 2 It is a schematic diagram of the characteristic structure of meshing of an ultrasonic C-scan flattened image of a composite material fan blade according to an exemplary embodiment.

[0041] Combination Figure 2 It can be seen that for the composite body area, the thickness and curvature of the upper part of the blade body (corresponding to the target location) change relatively little, and the data grid can be divided according to 5mm×5mm; the lower part of the blade body (corresponding to the target location), especially below the flow line, has a large change in thickness and curvature, and the root extension area (corresponding to the target location) can be divided into 2mm×2mm data grids; the tenon part (corresponding to the target location) has a large change in curvature, and the data grid can be divided into 1mm×1mm. For the hemming bonding area, the data grid can be divided into 2mm×2mm.

[0042] In this embodiment, the unit size of each grid is determined in combination with the actual structural characteristics of the fan blades, which can improve the reference and accuracy of the obtained energy grid diagram (including the first energy grid diagram and the second energy grid diagram), thereby laying the foundation for avoiding missed defects.

[0043] In step 130, the second ultrasonic penetration C-scan result is flattened into second C-scan result two-dimensional image energy data, and the second C-scan result two-dimensional image energy data is gridded according to the gridding method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map.

[0044] In step 140, the defect type of the composite material fan blade to be identified is determined based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map.

[0045] In another embodiment, the second ultrasonic penetration C-scan result can be flattened into the second C-scan result two-dimensional image energy data. Since the standard composite fan blade and the composite fan blade to be identified have the same model, the second C-scan result two-dimensional image energy data can be grid-divided according to the grid-dividing method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map. In other words, there are as many grids in the second energy grid map as there are grids in the first energy grid map, and the grids between the two are one-to-one corresponding.

[0046] In another embodiment, the defect type of the composite fan blade to be identified can be determined based on the first energy value corresponding to each grid in the first energy grid diagram and the second energy value corresponding to each grid in the second energy grid diagram. Thus, the ultrasonic attenuation interference caused by the blade shape structure is eliminated by using the standard composite fan blade as a benchmark, and accurate comparative analysis of the data of each area of ​​the whole blade and ultrasonic abnormality identification and extraction are achieved.

[0047] The defect identification method of composite fan blades provided by the present disclosure obtains the first ultrasonic penetration C-scan result of a standard composite fan blade and the second ultrasonic penetration C-scan result of a composite fan blade to be identified; flattens the first ultrasonic penetration C-scan result into the first C-scan result two-dimensional image energy data, and meshes the first C-scan result two-dimensional image energy data to obtain a first energy grid map; flattens the second ultrasonic penetration C-scan result into the second C-scan result two-dimensional image energy data, and meshes the second C-scan result two-dimensional image energy data according to the meshing method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; then, based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map, the defect type of the composite fan blade to be identified is determined. Accurate and rapid comparative analysis of data in various regions of the entire blade and ultrasonic abnormality identification and extraction are achieved.

[0048] Figure 3 It is a flowchart for determining the defect type of a composite material fan blade to be identified based on a first energy value corresponding to each grid in a first energy grid diagram and a second energy value corresponding to each grid in a second energy grid diagram according to an exemplary embodiment.

[0049] The following will be combined Figure 3 The defect identification method of a composite material fan blade provided in the present disclosure is described.

[0050] In an exemplary embodiment of the present disclosure, Figure 3 It can be seen that determining the defect type of the composite fan blade to be identified based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map can include steps 310 to 350, and each step will be introduced below.

[0051] In step 310, a difference is performed between the first energy value corresponding to each grid in the first energy grid diagram and the second energy value corresponding to each grid in the second energy grid diagram to obtain an energy difference value corresponding to each grid.

[0052] In step 320, when the energy difference exceeds the energy difference threshold, the grid in the second energy grid map corresponding to the energy difference is determined to be an abnormal area grid.

[0053] In one embodiment, the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map can be respectively subtracted to obtain the energy difference value corresponding to each grid. Further, it is determined whether the energy difference value corresponding to each grid exceeds the energy difference threshold. In the case where the energy difference value exceeds the energy difference threshold, it indicates that there is a difference between the composite material fan blade to be identified and the standard composite material fan blade, and then the grid in the second energy grid map corresponding to the energy difference value can be determined as an abnormal area grid.

[0054] The energy difference threshold may be adjusted according to actual conditions and is not specifically limited in this embodiment.

[0055] In another embodiment, the ultrasonic energy value of each grid in the standard composite fan blade can be subtracted from the evaluation threshold of the corresponding area to obtain the ultrasonic anomaly threshold distribution of the entire blade; and the ultrasonic energy value of each grid in the composite fan blade to be identified can be compared with the ultrasonic anomaly threshold value of the same grid in the standard composite fan blade. If the former is lower than the latter, it indicates that the grid area has an ultrasonic anomaly, the grid is marked, and the difference between the two is recorded.

[0056] In another embodiment, the evaluation threshold Δ of the area where the grid is located (such as the composite body threshold Δbody=10dB, the edge area threshold Δedge=6dB) can be subtracted from each grid value (αi, i=grid number) in the standard composite fan blade grid data map, and finally a blade ultrasonic anomaly determination threshold data map (βi=αi-Δi, i=grid number) is formed. Then, the ultrasonic penetration energy value (γi, i=grid number) in each grid of the composite fan blade to be identified is compared with the same grid value (βi, i=grid number) of the ultrasonic anomaly determination threshold. If the grid of the composite fan blade to be identified has lower received energy (γi<βi), the grid is defined as an ultrasonic anomaly.

[0057] In step 330, multiple abnormal region grids with adjacent positions and the same energy deviation direction are merged to obtain an ultrasonic attenuation abnormal cloud map.

[0058] In one embodiment, multiple abnormal region grids with adjacent positions and the same energy deviation direction may be merged to obtain an ultrasonic attenuation abnormal cloud map, and the average attenuation value of each ultrasonic abnormal region may be calculated and recorded.

[0059] The energy deviation direction is determined according to the first energy value corresponding to the abnormal area grid and the second energy value corresponding to the abnormal area grid. For example, when the first energy value is greater than the second energy value, the energy deviation direction is determined to be a positive direction, or when the first energy value is less than the second energy value, the energy deviation direction is determined to be a positive direction. In other words, the second energy values ​​corresponding to multiple abnormal area grids with the same energy deviation direction need to be greater than the first energy value, or less than the first energy value.

[0060] In step 340, the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C-scan result of the area corresponding to the ultrasonic attenuation abnormality cloud map, and the ultrasonic reflection scan result of the area corresponding to the ultrasonic attenuation abnormality cloud map are determined respectively.

[0061] In step 350, the defect type of the composite material fan blade to be identified is determined based on the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result.

[0062] In one embodiment, the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result of the area corresponding to the ultrasonic attenuation anomaly cloud map, and the ultrasonic reflection scan result of the area corresponding to the ultrasonic attenuation anomaly cloud map can be determined respectively. Further, based on the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the defect type of the composite fan blade to be identified is determined. In this embodiment, the standard composite fan blade is used as a reference to eliminate the ultrasonic attenuation interference caused by the blade shape structure, and the ultrasonic detection of the data of each area of ​​the whole blade and the ultrasonic anomaly identification and extraction are achieved.

[0063] In another exemplary embodiment of the present disclosure, the defect type of the composite material fan blade to be identified is determined based on the energy attenuation value of the ultrasonic attenuation abnormal cloud map, the ultrasonic penetration C scan result, and the ultrasonic reflection scan result. This can be achieved in the following manner:

[0064] Determine the energy difference between the energy attenuation value of the ultrasonic attenuation abnormal cloud map and the energy of the corresponding area of ​​the first energy grid map;

[0065] When the energy difference is greater than the energy difference threshold, the ultrasonic penetration C-scan result shows that the regional boundary is clear, and the ultrasonic reflection scan result shows that a defect wave is found, it is determined that the defect type of the composite fan blade to be identified is a delamination / debonding defect;

[0066] When the energy difference is less than or equal to the energy difference threshold, the ultrasonic penetration C-scan result shows that the area has no boundaries, and the ultrasonic reflection scan result shows that no defect wave is found, it is determined that the defect type of the composite fan blade to be identified is a porosity / weak adhesion defect.

[0067] In one embodiment, the ultrasonic penetration method C-scan image, ultrasonic attenuation and ultrasonic reflection method can be combined to confirm and determine each abnormal area. In one example, if the penetration method C-scan image shows that the boundary of the area is clear and distinct, and the energy attenuation value of the ultrasonic attenuation abnormal cloud map is significantly different from the energy of the area corresponding to the first energy grid map (greater than the energy difference threshold), and the ultrasonic reflection method finds obvious defect waves, it can be determined as a delamination / debonding defect. In another example, if the penetration method C-scan image shows that the area has no obvious boundary, and the energy attenuation value of the ultrasonic attenuation abnormal cloud map is slightly different from the energy of the area corresponding to the first energy grid map (less than or equal to the energy difference threshold), and the ultrasonic reflection method has no obvious defect wave, and the bottom wave is reduced or disappears, it is determined to be a porosity / weak adhesion defect, or other types of quality problems. Through this embodiment, the defect type is determined based on three detection methods, which can improve the accuracy and stability of determining the defect type.

[0068] In another exemplary embodiment of the present disclosure, the above-mentioned embodiment is continued to be used as an example for explanation. Before determining the defect type of the composite material fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C scan result, and the ultrasonic reflection scan result, the composite material fan blade defect identification method may further include:

[0069] respectively determining a first evaluation level of the energy attenuation value, a second evaluation level of the ultrasonic penetration C-scan result, and a third evaluation level of the ultrasonic reflection scan result;

[0070] Among them, based on the energy attenuation value of the ultrasonic attenuation abnormal cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the defect type of the composite fan blade to be identified can be determined in the following ways:

[0071] Based on the priority order of the first evaluation level, the second evaluation level, and the third evaluation level, combined with the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the defect type of the composite fan blade to be identified is determined.

[0072] In one embodiment, if the priority order of the three evaluation levels is the highest, when the ultrasonic reflection scan result shows that no defect wave is found, the energy attenuation value of the ultrasonic attenuation abnormal cloud map and the energy difference of the corresponding area of ​​the first energy grid map are greater than the energy difference threshold, and the ultrasonic penetration C scan result shows that the regional boundary is clear, the ultrasonic reflection scan result will be used to determine the defect type of the composite material fan blade to be identified. Through this embodiment, the final defect type of the composite material fan blade to be identified is determined in combination with the priority order of various detection methods, which can be closer to the actual situation, so that various defects existing in reality can be better identified.

[0073] Figure 4 The present invention is a flow chart showing a method for determining an energy attenuation value of an ultrasonic attenuation abnormality cloud map according to an exemplary embodiment.

[0074] The following will be combined Figure 4 The process of determining the energy attenuation value of the ultrasonic attenuation anomaly cloud map is described.

[0075] In an exemplary embodiment of the present disclosure, Figure 4 It can be known that determining the energy attenuation value of the ultrasonic attenuation abnormal cloud map may include steps 410 to 440, and each step will be described below.

[0076] In step 410, a plurality of abnormal grids in a second energy grid map corresponding to the ultrasonic attenuation abnormal cloud map are obtained.

[0077] In step 420, a reference grid corresponding to a plurality of abnormal grids in the first energy grid map is obtained.

[0078] In step 430, a first average energy value of energy values ​​corresponding to each abnormal grid and a second average energy value of energy values ​​corresponding to each reference grid are determined.

[0079] In step 440, the energy attenuation value of the ultrasonic attenuation anomaly cloud map is determined based on the difference between the first average energy value and the second average energy value.

[0080] In one embodiment, multiple abnormal grids in the second energy grid map corresponding to the ultrasonic attenuation abnormal cloud map may be obtained, and multiple reference grids corresponding to the multiple abnormal grids may be determined in the first energy grid map based on the abnormal grids.

[0081] Furthermore, the energy values ​​corresponding to each abnormal grid are combined to obtain a first average energy value, and the energy values ​​corresponding to each reference grid are combined to obtain a second average energy value. Based on the difference between the first average energy value and the second average energy value, the energy attenuation value of the ultrasonic attenuation abnormal cloud map is determined. In another example, the energy attenuation value can be expressed as Indicates that, where δ j Represents the energy attenuation value of the ultrasonic attenuation abnormal cloud map; n is the number of abnormal grids; α i represents the energy value corresponding to the i-th abnormal grid; γ i Indicates the energy value corresponding to the i-th reference grid. In this embodiment, the energy attenuation value of the ultrasonic attenuation abnormal cloud map is determined based on the difference between the first average energy value and the second average energy value, which can improve the accuracy and reference of the energy attenuation value of the ultrasonic attenuation abnormal cloud map.

[0082] In another exemplary embodiment of the present disclosure, the first energy value corresponding to each grid in the first energy grid diagram may be determined in the following manner:

[0083] Determine the first point energy data of each first point in each grid in the first energy grid diagram based on the two-dimensional image energy data of the first C scan result;

[0084] Based on the average value of the first point energy data, the first energy value corresponding to each grid in the first energy grid map is determined.

[0085] In this embodiment, the first point energy data of each first point in each grid in the first energy grid diagram is combined to obtain the first energy value corresponding to each grid in the first energy grid diagram, thereby improving the accuracy and rationality of the first energy value and laying a foundation for accurately identifying the defect type of the composite fan blade to be identified.

[0086] In another exemplary embodiment of the present disclosure, the second energy value corresponding to each grid in the second energy grid diagram may be determined in the following manner:

[0087] Determine the second site energy data of each second site in each grid in the second energy grid map based on the two-dimensional image energy data of the second C scan result;

[0088] Based on the average value of the second site energy data, the second energy value corresponding to each grid in the second energy grid map is determined.

[0089] In this embodiment, the second site energy data of each second site in each grid in the second energy grid diagram is combined to obtain the second energy value corresponding to each grid in the second energy grid diagram, thereby improving the accuracy and rationality of the second energy value, laying the foundation for accurately identifying the defect type of the composite fan blade to be identified.

[0090] According to the foregoing description, the defect identification method for composite fan blades provided by the present disclosure eliminates the ultrasonic attenuation interference caused by the blade shape structure, realizes accurate comparative analysis of ultrasonic detection data of all regions of the blade and ultrasonic abnormality identification and extraction, and solves the problem of poor accuracy and consistency in artificial determination of defects in composite fan blade ultrasonic detection. This method can realize automatic identification and determination of defects in parts with complex shape structures.

[0091] Based on the same concept, an embodiment of the present disclosure also provides a composite material fan blade defect identification device.

[0092] It is understandable that in order to achieve the above functions, the composite fan blade defect identification device provided in the embodiment of the present disclosure includes hardware structures and / or software modules corresponding to the execution of each function. In combination with the units and algorithm steps of each example disclosed in the embodiment of the present disclosure, the embodiment of the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the technical solution of the embodiment of the present disclosure.

[0093] Figure 5 It is a block diagram showing defect identification of a composite material fan blade according to an exemplary embodiment.

[0094] In an exemplary embodiment of the present disclosure, referring to Figure 5 It can be seen that the device may include an acquisition module 510, a first flattening module 520, a second flattening module 530, and a processing module 540, and each module will be introduced below.

[0095] An acquisition module 510 can be configured to acquire a first ultrasonic through-transmission C-scan result of a standard composite fan blade and a second ultrasonic through-transmission C-scan result of a composite fan blade to be identified, wherein the performance parameters of the standard composite fan blade meet preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model;

[0096] A first flattening module 520 can be configured to flatten the first ultrasonic through-transmission C-scan result into first C-scan result two-dimensional image energy data, and perform grid division on the first C-scan result two-dimensional image energy data to obtain a first energy grid map, wherein the unit size of the grid is determined according to the target location of the standard composite fan blade corresponding to the target energy data, and the target energy data corresponds to the grid;

[0097] A second flattening module 530 can be configured to flatten the second ultrasonic through-transmission C-scan result into second C-scan result two-dimensional image energy data, and perform grid division on the second C-scan result two-dimensional image energy data in the same grid division manner as the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map;

[0098] A processing module 540 can be configured to determine the defect type of the composite fan blade to be identified based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map.

[0099] In another exemplary embodiment of the present disclosure, the processing module 540 can implement determining the defect type of the composite fan blade to be identified based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map in the following manner:

[0100] Subtract the first energy value corresponding to each grid in the first energy grid map from the second energy value corresponding to each grid in the second energy grid map respectively to obtain the energy difference corresponding to each grid;

[0101] In the case where the energy difference exceeds the energy difference threshold, determine the grid in the second energy grid map corresponding to the energy difference as an abnormal area grid;

[0102] Merge multiple adjacent abnormal area grids with the same energy deviation direction to obtain an ultrasonic attenuation abnormal cloud map, wherein the energy deviation direction is determined according to the first energy value corresponding to the abnormal area grid and the second energy value corresponding to the abnormal area grid;

[0103] respectively determining the energy attenuation value of the ultrasonic attenuation abnormal cloud map, the ultrasonic penetration C-scan result of the area corresponding to the ultrasonic attenuation abnormal cloud map, and the ultrasonic reflection scan result of the area corresponding to the ultrasonic attenuation abnormal cloud map;

[0104] Based on the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the defect type of the composite fan blade to be identified is determined.

[0105] In another exemplary embodiment of the present disclosure, the processing module 540 may determine the defect type of the composite material fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result in the following manner:

[0106] Determine the energy difference between the energy attenuation value of the ultrasonic attenuation abnormal cloud map and the energy of the corresponding area of ​​the first energy grid map;

[0107] When the energy difference is greater than the energy difference threshold, the ultrasonic penetration C-scan result shows that the regional boundary is clear, and the ultrasonic reflection scan result shows that a defect wave is found, it is determined that the defect type of the composite fan blade to be identified is a delamination / debonding defect;

[0108] When the energy difference is less than or equal to the energy difference threshold, the ultrasonic penetration C-scan result shows that the area has no boundaries, and the ultrasonic reflection scan result shows that no defect wave is found, it is determined that the defect type of the composite fan blade to be identified is a porosity / weak adhesion defect.

[0109] In yet another exemplary embodiment of the present disclosure, the processing module 540 may also be configured to:

[0110] respectively determining a first evaluation level of the energy attenuation value, a second evaluation level of the ultrasonic penetration C-scan result, and a third evaluation level of the ultrasonic reflection scan result;

[0111] The processing module 540 can determine the defect type of the composite material fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C scan result, and the ultrasonic reflection scan result in the following manner:

[0112] Based on the priority order of the first evaluation level, the second evaluation level, and the third evaluation level, combined with the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the defect type of the composite fan blade to be identified is determined.

[0113] In another exemplary embodiment of the present disclosure, the processing module 540 may determine the energy attenuation value of the ultrasonic attenuation abnormality cloud map in the following manner:

[0114] Acquire a plurality of abnormal grids in a second energy grid map corresponding to the ultrasonic attenuation abnormal cloud map, and

[0115] Acquire a reference grid corresponding to a plurality of abnormal grids in the first energy grid map;

[0116] Determine a first average energy value of energy values ​​corresponding to each abnormal grid, and a second average energy value of energy values ​​corresponding to each reference grid;

[0117] Based on the difference between the first average energy value and the second average energy value, an energy attenuation value of the ultrasonic attenuation anomaly cloud map is determined.

[0118] In another exemplary embodiment of the present disclosure, the processing module 540 may determine the first energy value corresponding to each grid in the first energy grid map in the following manner:

[0119] Determine the first point energy data of each first point in each grid in the first energy grid diagram based on the two-dimensional image energy data of the first C scan result;

[0120] Based on the average value of the first point energy data, the first energy value corresponding to each grid in the first energy grid map is determined.

[0121] In another exemplary embodiment of the present disclosure, the processing module 540 may determine the second energy value corresponding to each grid in the second energy grid map in the following manner:

[0122] Determine the second site energy data of each second site in each grid in the second energy grid map based on the two-dimensional image energy data of the second C scan result;

[0123] Based on the average value of the second site energy data, the second energy value corresponding to each grid in the second energy grid map is determined.

[0124] In yet another exemplary embodiment of the present disclosure, the unit size of the grid is negatively correlated with the blade thickness change rate corresponding to the target location, and / or the blade curvature corresponding to the target location.

[0125] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0126] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6As shown, the electronic device may include: a processor (processor) 610, a communication interface (Communications Interface) 620, a memory (memory) 630 and a communication bus 640, wherein the processor 610, the communication interface 620, and the memory 630 communicate with each other through the communication bus 640. The processor 610 can call the logic instructions in the memory 630 to execute the defect identification method of the composite fan blade, wherein the method includes: obtaining a first ultrasonic penetration C-scan result of a standard composite fan blade and a second ultrasonic penetration C-scan result of a composite fan blade to be identified, wherein the performance parameters of the standard composite fan blade meet the preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model; flattening the first ultrasonic penetration C-scan result into a first C-scan result two-dimensional image energy data, and gridding the first C-scan result two-dimensional image energy data to obtain a first energy grid map, wherein the unit size of the grid is based on the target The target position of the standard composite fan blade corresponding to the energy data is determined, and the target energy data corresponds to the grid; the second ultrasonic penetration C-scan result is flattened into the second C-scan result two-dimensional image energy data, and the second C-scan result two-dimensional image energy data is grid-divided according to the grid division method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map, the defect type of the composite fan blade to be identified is determined.

[0127] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0128] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the composite fan blade defect identification method provided by the above methods, wherein the method includes: obtaining a first ultrasonic penetration C-scan result of a standard composite fan blade and a second ultrasonic penetration C-scan result of a composite fan blade to be identified, wherein the performance parameters of the standard composite fan blade meet preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model; flattening the first ultrasonic penetration C-scan result into a first C-scan result two-dimensional image energy data, and performing a two-dimensional image analysis on the first C-scan result. Performing grid division to obtain a first energy grid map, wherein a unit size of the grid is determined according to a target location of a standard composite material fan blade corresponding to target energy data, and the target energy data corresponds to the grid; flattening the second ultrasonic penetration C-scan result into second C-scan result two-dimensional image energy data, and performing grid division on the second C-scan result two-dimensional image energy data according to a grid division method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; determining the defect type of the composite material fan blade to be identified based on a first energy value corresponding to each grid in the first energy grid map and a second energy value corresponding to each grid in the second energy grid map.

[0129] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the processor executes the composite fan blade defect identification method provided by the above methods, wherein the method comprises: obtaining a first ultrasonic penetration C-scan result of a standard composite fan blade, and a second ultrasonic penetration C-scan result of a composite fan blade to be identified, wherein the performance parameters of the standard composite fan blade meet preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model; flattening the first ultrasonic penetration C-scan result into a first C-scan result two-dimensional image energy data, and gridding the first C-scan result two-dimensional image energy data to obtain a first energy grid. A grid diagram is provided, wherein a unit size of the grid is determined according to a target position of a standard composite fan blade corresponding to target energy data, and the target energy data corresponds to the grid; the second ultrasonic penetration C-scan result is flattened into second C-scan result two-dimensional image energy data, and the second C-scan result two-dimensional image energy data is grid-divided according to the grid division method of the first C-scan result two-dimensional image energy data to obtain a second energy grid diagram, so that each grid in the first energy grid diagram corresponds to each grid in the second energy grid diagram; based on the first energy value corresponding to each grid in the first energy grid diagram and the second energy value corresponding to each grid in the second energy grid diagram, the defect type of the composite fan blade to be identified is determined.

[0130] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0131] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0132] It can be further understood that, although the operations are described in a specific order in the drawings in the embodiments of the present invention, it should not be construed as requiring the operations to be performed in the specific order shown or in a serial order, or requiring all the operations shown to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0133] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A defect identification method for composite fan blades, in, The method comprises: Obtaining a first ultrasonic penetration C-scan result of a standard composite fan blade and a second ultrasonic penetration C-scan result of a composite fan blade to be identified, wherein the performance parameters of the standard composite fan blade meet preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model; Flattening the first ultrasonic penetration C-scan result into first C-scan result two-dimensional image energy data, and gridding the first C-scan result two-dimensional image energy data to obtain a first energy grid map, wherein a unit size of the grid is determined according to a target location of a standard composite material fan blade corresponding to target energy data, and the target energy data corresponds to the grid; Flattening the second ultrasonic penetration C-scan result into second C-scan result two-dimensional image energy data, and gridding the second C-scan result two-dimensional image energy data according to the gridding method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; Based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map, the defect type of the composite material fan blade to be identified is determined.

2. The composite fan blade defect identification method according to claim 1, in, The determining the defect type of the composite material fan blade to be identified based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map includes: Subtracting the first energy value corresponding to each grid in the first energy grid diagram from the second energy value corresponding to each grid in the second energy grid diagram to obtain the energy difference value corresponding to each grid; In the case where the energy difference value exceeds the energy difference value threshold, determining a grid in the second energy grid map corresponding to the energy difference value as an abnormal area grid; Merging a plurality of abnormal region grids that are adjacent in position and have the same energy deviation direction to obtain an ultrasonic attenuation abnormal cloud map, wherein the energy deviation direction is determined according to a first energy value corresponding to the abnormal region grid and a second energy value corresponding to the abnormal region grid; Respectively determining an energy attenuation value of the ultrasonic attenuation abnormality cloud map, an ultrasonic penetration C scan result of an area corresponding to the ultrasonic attenuation abnormality cloud map, and an ultrasonic reflection scan result of an area corresponding to the ultrasonic attenuation abnormality cloud map; Based on the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the defect type of the composite material fan blade to be identified is determined.

3. The defect identification method of composite fan blade according to claim 2, in, The method of determining the defect type of the composite material fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C scan result, and the ultrasonic reflection scan result includes: Determine the energy difference between the energy attenuation value of the ultrasonic attenuation abnormal cloud map and the energy of the corresponding area of ​​the first energy grid map; When the energy difference is greater than the energy difference threshold, the ultrasonic penetration C-scan result shows that the regional boundary is clear, and the ultrasonic reflection scan result shows that a defect wave is found, it is determined that the defect type of the composite material fan blade to be identified is a delamination / debonding defect; When the energy difference is less than or equal to the energy difference threshold, the ultrasonic penetration C-scan result shows that the area has no boundaries, and the ultrasonic reflection scan result shows that no defect wave is found, it is determined that the defect type of the composite fan blade to be identified is a porosity / weak adhesion defect.

4. The composite fan blade defect identification method according to claim 3, It is characterized in that Before determining the defect type of the composite material fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C scan result, and the ultrasonic reflection scan result, the method further includes: respectively determining a first evaluation level of the energy attenuation value, a second evaluation level of the ultrasonic penetration C-scan result, and a third evaluation level of the ultrasonic reflection scan result; The method of determining the defect type of the composite material fan blade to be identified based on the energy attenuation value of the ultrasonic attenuation abnormality cloud map, the ultrasonic penetration C scan result, and the ultrasonic reflection scan result includes: Based on the priority order of the first evaluation level, the second evaluation level, and the third evaluation level, combined with the energy attenuation value of the ultrasonic attenuation anomaly cloud map, the ultrasonic penetration C-scan result, and the ultrasonic reflection scan result, the defect type of the composite fan blade to be identified is determined.

5. The composite fan blade defect identification method according to claim 2, in, The energy attenuation value of the ultrasonic attenuation abnormal cloud map is determined in the following manner: acquiring a plurality of abnormal grids in the second energy grid map corresponding to the ultrasonic attenuation abnormal cloud map, and Acquire a reference grid corresponding to the plurality of abnormal grids in the first energy grid map; Determine a first average energy value of energy values ​​corresponding to each of the abnormal grids, and a second average energy value of energy values ​​corresponding to each of the reference grids; An energy attenuation value of the ultrasonic attenuation anomaly cloud map is determined based on a difference between the first average energy value and the second average energy value.

6. The composite material fan blade defect identification method according to claim 1, in, The first energy value corresponding to each grid in the first energy grid diagram is determined in the following manner: Determine the first site energy data of each first site in each grid in the first energy grid map based on the two-dimensional image energy data of the first C scan result; Based on the average value of the first site energy data, a first energy value corresponding to each grid in the first energy grid map is determined.

7. The composite fan blade defect identification method according to claim 1, in, The second energy value corresponding to each grid in the second energy grid diagram is determined in the following manner: Determining second site energy data of each second site in each grid in the second energy grid map based on the two-dimensional image energy data of the second C scan result; Based on the average value of the energy data of the second site, the second energy value corresponding to each grid in the second energy grid map is determined.

8. The composite material fan blade defect identification method according to claim 1, in, The unit size of the grid is negatively correlated with the blade thickness change rate corresponding to the target location, and / or the blade curvature corresponding to the target location.

9. A composite material fan blade defect identification device, in, The device comprises: An acquisition module, used to acquire a first ultrasonic penetration C-scan result of a standard composite fan blade and a second ultrasonic penetration C-scan result of a composite fan blade to be identified, wherein the performance parameters of the standard composite fan blade meet preset requirements, and the standard composite fan blade and the composite fan blade to be identified have the same model; a first flattening module, used for flattening the first ultrasonic penetration C-scan result into first C-scan result two-dimensional image energy data, and performing grid division on the first C-scan result two-dimensional image energy data to obtain a first energy grid map, wherein a unit size of the grid is determined according to a target location of a standard composite material fan blade corresponding to target energy data, and the target energy data corresponds to the grid; a second flattening module, configured to flatten the second ultrasonic penetration C-scan result into second C-scan result two-dimensional image energy data, and perform grid division on the second C-scan result two-dimensional image energy data according to the grid division method of the first C-scan result two-dimensional image energy data to obtain a second energy grid map, so that each grid in the first energy grid map corresponds to each grid in the second energy grid map; A processing module is used to determine the defect type of the composite material fan blade to be identified based on the first energy value corresponding to each grid in the first energy grid map and the second energy value corresponding to each grid in the second energy grid map.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, in, When the processor executes the program, the composite material fan blade defect identification method as described in any one of claims 1 to 8 is implemented.

Images