CN116046907A - Composite material defect ultrasonic automatic identification method considering detection probability - Google Patents

Composite material defect ultrasonic automatic identification method considering detection probability Download PDF

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CN116046907A
CN116046907A CN202211383605.4A CN202211383605A CN116046907A CN 116046907 A CN116046907 A CN 116046907A CN 202211383605 A CN202211383605 A CN 202211383605A CN 116046907 A CN116046907 A CN 116046907A
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ultrasonic
defects
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defect
composite material
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刘松平
刘菲菲
章清乐
杨玉森
李治应
傅天航
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AVIC Beijing Aeronautical Manufacturing Technology Research Institute
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
    • G01N29/4409—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison
    • G01N29/4427—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by comparison with stored values, e.g. threshold values
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/048—Marking the faulty objects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
    • G01N29/0654—Imaging
    • G01N29/069—Defect imaging, localisation and sizing using, e.g. time of flight diffraction [TOFD], synthetic aperture focusing technique [SAFT], Amplituden-Laufzeit-Ortskurven [ALOK] technique
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/02—Indexing codes associated with the analysed material
    • G01N2291/023—Solids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2291/00—Indexing codes associated with group G01N29/00
    • G01N2291/02—Indexing codes associated with the analysed material
    • G01N2291/028—Material parameters
    • G01N2291/0289—Internal structure, e.g. defects, grain size, texture
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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Abstract

The invention relates to the technical field of nondestructive testing, in particular to an ultrasonic automatic identification method for defects of a composite material by considering detection probability. The method comprises the following steps: acquiring ultrasonic C scanning information; setting a defect automatic identification threshold G u The method comprises the steps of carrying out a first treatment on the surface of the Setting an automatic defect evaluation threshold; automatically identifying the defects; visual identification is carried out on the defects; and (5) evaluating the robustness of the automatic identification of the defects. The method has the advantages that the ultrasonic detection reference block of the composite material is not required to be prepared independently, the effectiveness and the correctness of the automatic evaluation result of the ultrasonic C-scan detection result of the large composite material structure can be better evaluated, the accuracy and the reliability of the evaluation of the ultrasonic C-scan detection result are further remarkably improved, and the visualization degree of the evaluation of the ultrasonic C-scan detection result is remarkably increased.

Description

Composite material defect ultrasonic automatic identification method considering detection probability
Technical Field
The invention relates to the technical field of nondestructive testing, in particular to an ultrasonic automatic identification method for defects of a composite material by considering detection probability.
Background
The large composite material structure is commonly applied in the industry at present, belongs to very important composite material parts, and has very high quality, cost, safety and performance requirements. To ensure the quality of such critical composite structures, they are typically subjected to 100% non-destructive inspection using ultrasonic C-scan, and then inspected by an inspection technician based on the ultrasonic C-scan image to evaluate whether there is a defect condition exceeding design requirements. For this reason, it is necessary to observe and judge the ultrasonic C-scan images one by a detection technician, and finally give a detection result.
At present, when ultrasonic C-scan detection of a composite material is carried out, an ultrasonic C-scan image is usually evaluated manually, and the detection result is judged, which has the remarkable defects that: (1) Because the ultrasonic C scanning data volume of the large composite material structure is very large, the physical display size of a computer screen is very limited, and only a compression display mode can be adopted, partial small defects are easy to miss display and visual missed judgment; (2) Because the ultrasonic C scanning data volume is large, the defect assessment is easy to generate teaching fatigue and evaluation drawing fatigue, and further defect missed judgment is easy to be caused; (3) The ultrasonic C scanning judgment result is marked and recorded manually, so that mistakes are easy to occur; (4) The detection result is judged by long-term visual computer screen, visual angle fatigue is easy to cause, and misjudgment and omission are further caused; (5) Is easily influenced by comprehensive technology and experience factors of detection result judges; and (6) the judging efficiency of the detection result is low. As an improvement, an automatic discrimination method is also introduced to evaluate the result of ultrasonic C-scan detection, but the main disadvantages are: (1) verification of the robustness of the automatic discrimination method is not considered; (2) The mutual influence relation among the ultrasonic C-scan image, the detected object, the material, the process and the structural behavior of the detected object is not considered, so that the applicability and the robustness of the automatic judging method are obviously influenced.
Disclosure of Invention
First, the technical problem to be solved
The embodiment of the invention provides a composite material defect ultrasonic automatic identification method considering detection probability, which solves the technical problems of low ultrasonic C scanning detection efficiency and poor detection reliability of a large composite material structure.
(II) technical scheme
The embodiment of the invention provides a composite material defect ultrasonic automatic identification method considering detection probability, which comprises the following steps: acquiring ultrasonic C scanning information; setting a defect automatic identification threshold G u The method comprises the steps of carrying out a first treatment on the surface of the Setting an automatic defect evaluation threshold; automatically identifying the defects; visual identification is carried out on the defects; and (5) evaluating the robustness of the automatic identification of the defects.
Further, the step of acquiring ultrasonic C-scan information includes the steps of: reading and storing the formed ultrasonic C scanning image format into a computer memory I nm In (x, y, z, C), x, y, z correspond to the position coordinates in the ultrasound C-scan image, respectively, and satisfy: x=k x x o (1)，y＝k y y o (2)，z＝k z z o (3) Wherein (x) o ,y o ,z o ) Respectively representing the position coordinates of the surface of the detected composite material part, (k) x ,k y ,k z ) Respectively representing conversion coefficients between the position coordinates of the surface of the detected composite material part and the position coordinates in the ultrasonic C-scan image; c is the ultrasonic C-scan image color value corresponding to (x, y, z), and satisfies: c=k u A u (4)，k u For the conversion coefficient of the ultrasonic signal and the color value in the image, A u An ultrasound signal for ultrasound C-scan imaging; for the ultrasonic C scanning result as the detection original data format, converting the ultrasonic C scanning original data into an ultrasonic C scanning image format according to the formulas (1) to (4), and reading into a computer memory I nm (x, y, z, c).
Further, the ultrasound C-scan image formats include BMP, TIFF, and JPEG bitmap formats.
Further, the defect automatic identification threshold G u The arrangement of (2) comprises: according to the detected composite material part materials, process and structural characteristics and ultrasonic C scanning image characteristics thereof, determining a calculation formula of the defect automatic identification threshold value is as follows:
Figure SMS_1
wherein Q is ij (x ij ,y ij ,c ij ) Scanning the ith row, jth column, x of the feature image region for selected ultrasound C ij ,y ij ,c ij The size of the ultrasonic C scanning characteristic image area is m multiplied by n, the ultrasonic C scanning characteristic image area is selected according to the read ultrasonic C scanning characteristic image, and the defect-free area of the detected composite material part corresponding to the ultrasonic C scanning characteristic image area is determined through an ultrasonic C scanning detection test.
Further, the setting of the defect automatic evaluation threshold includes: setting an automatic defect evaluation threshold according to the quality acceptance requirement of the detected composite material part
Figure SMS_2
Further, the said
Figure SMS_3
Is the area or diameter or length, < >>
Figure SMS_4
In millimeters.
Further, the automatic identification of the defect comprises the steps of: from I nm Automatically identifying image areas for reading defects in (x, y, z, c)
Figure SMS_7
Identification threshold comparison: if->
Figure SMS_8
No color value c is greater than G u If the recognition is completed, if the recognition is not completed, i=i+1, and continuing from I nm Reading defect auto-discrimination image area +.>
Figure SMS_11
If the identification is finished, ending the identification; if->
Figure SMS_6
The color value c is greater than G u Is calculated->
Figure SMS_9
The medium color value c is greater than G u Is +.>
Figure SMS_10
And the length L, width W and equivalent diameter D thereof, corresponding position coordinates (x, y) and stored in an array +.>
Figure SMS_12
In the step (a), whether the identification is completed is judged, if the identification is not completed, i=i+1, and the process continues from I nm Reading defect auto-discrimination image area +.>
Figure SMS_5
And if the identification is finished, ending the identification.
Further, visually identifying the defect includes: according to
Figure SMS_13
Recording the result, performing defect F in the ultrasonic C-scan image i And (5) identification.
Further, the automatic identification robustness evaluation of the defects comprises the steps of: selecting a standard sample for evaluating the ultrasonic C scanning detection effect of the composite material, wherein the selection of the standard sample is the same as that of the detected composite material part, and the defect distribution and the defect quantity in the standard sample meet the detection probability requirement of the ultrasonic C scanning requirement; respectively detecting the standard sample for 3 times by using the same ultrasonic C scanning detection conditions, and storing detection results of each time; performing automatic defect identification on the 3 ultrasonic three-dimensional automatic C scanning results of the part to be evaluated, and solving the defect number N automatically identified by 3 ultrasonic C scanning d The calculated stability formula is:
Figure SMS_14
Figure SMS_15
(III) beneficial effects
In summary, the invention considers that the ultrasonic C scanning data volume of the large composite material structure is very large, the physical display size of a computer screen is very limited, and the defects of partial small defect missed display and visual missed judgment are easily caused by adopting a compression display mode; the defects of teaching fatigue and drawing fatigue are overcome when manual judgment is performed, and defect missed judgment is avoided; the ultrasonic C scanning judgment result is automatically marked and recorded, so that errors are not easy to occur; misjudgment and omission caused by visual angle fatigue can not occur; is not influenced by comprehensive technology and experience factors of detection result judges; the judging efficiency of the detection result is very high; verification of stability of an automatic judging method is considered; the mutual influence relation between the ultrasonic C-scan image and the detected object and the material, process and structural behavior thereof is considered, and the applicability and the robustness of the automatic defect distinguishing method are obviously improved. And further, the accuracy and the reliability of the ultrasonic C-scan detection result evaluation of the large composite material structure are remarkably improved, and the visualization degree of the ultrasonic C-scan detection result evaluation is remarkably increased.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort to a person of ordinary skill in the art.
FIG. 1 is a flow chart of an ultrasonic automatic identification method for defects of a composite material, which considers the detection probability according to an embodiment of the invention.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings and examples. The following detailed description of the embodiments and the accompanying drawings are provided to illustrate the principles of the invention and are not intended to limit the scope of the invention, i.e., the invention is not limited to the embodiments described, but covers any modifications, substitutions and improvements in parts, components and connections without departing from the spirit of the invention.
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Referring to fig. 1, an embodiment of the present invention provides an ultrasonic automatic identification method for a composite defect, which considers detection probability, and includes the following steps: acquiring ultrasonic C scanning information; setting a defect automatic identification threshold G u The method comprises the steps of carrying out a first treatment on the surface of the Setting an automatic defect evaluation threshold; automatically identifying the defects; visual identification is carried out on the defects; and (5) evaluating the robustness of the automatic identification of the defects. Considering that the ultrasonic C scanning data volume of a large composite material structure is very large, the physical display size of a computer screen is very limited, and the defects of partial small defect missed display and visual missed judgment are easily caused by adopting a compression display mode; the defects of teaching fatigue and drawing fatigue are overcome when manual judgment is performed, and defect missed judgment is avoided; the ultrasonic C scanning judgment result is automatically marked and recorded, so that errors are not easy to occur; misjudgment and omission caused by visual angle fatigue can not occur; is not influenced by comprehensive technology and experience factors of detection result judges; the judging efficiency of the detection result is very high; verification of stability of an automatic judging method is considered; the mutual influence relation between the ultrasonic C-scan image and the detected object and the material, process and structural behavior thereof is considered, and the applicability and the robustness of the automatic defect distinguishing method are obviously improved. And further, the accuracy and the reliability of the ultrasonic C-scan detection result evaluation of the large composite material structure are remarkably improved, and the visualization degree of the ultrasonic C-scan detection result evaluation is remarkably increased.
In some embodiments, the acquiring ultrasound C-scan information comprises the steps of: reading and storing the formed ultrasonic C scanning image format into a computer memory I nm In (x, y, z, C), x, y, z correspond to the position coordinates in the ultrasound C-scan image, respectively, and satisfy: x=k x x o (1)，y＝k y y o (2)，z＝k z z o (3) Wherein (x) o ,y o ,z o ) Respectively representing the position coordinates of the surface of the detected composite material part, (k) x ,k y ,k z ) Respectively representing conversion coefficients between the position coordinates of the surface of the detected composite material part and the position coordinates in the ultrasonic C-scan image; c is corresponding toUltrasound C-scan image color values of (x, y, z), and satisfy: c=k u A u (4)，k u For the conversion coefficient of the ultrasonic signal and the color value in the image, A u An ultrasound signal for ultrasound C-scan imaging; for the ultrasonic C scanning result as the detection original data format, converting the ultrasonic C scanning original data into an ultrasonic C scanning image format according to the formulas (1) to (4), and reading into a computer memory I nm (x, y, z, c). Further, the ultrasound C-scan image formats include BMP, TIFF, and JPEG bitmap formats.
In some embodiments, the defect automatic identification threshold G u The arrangement of (2) comprises: according to the detected composite material part materials, process and structural characteristics and ultrasonic C scanning image characteristics thereof, determining a calculation formula of the defect automatic identification threshold value is as follows:
Figure SMS_16
wherein Q is ij (x ij ,y ij ,c ij ) Scanning the ith row, jth column, x of the feature image region for selected ultrasound C ij ,y ij ,c ij The size of the ultrasonic C scanning characteristic image area is m multiplied by n, the ultrasonic C scanning characteristic image area is selected according to the read ultrasonic C scanning characteristic image, and the defect-free area of the detected composite material part corresponding to the ultrasonic C scanning characteristic image area is determined through an ultrasonic C scanning detection test.
In some embodiments, the setting of the defect automatic evaluation threshold includes: setting an automatic defect evaluation threshold according to the quality acceptance requirement of the detected composite material part
Figure SMS_17
Further, said->
Figure SMS_18
Is the area or diameter or length, < >>
Figure SMS_19
In millimeters.
In some embodiments, automatically identifying the defect includes the steps of: from I nm Automatically identifying image areas for reading defects in (x, y, z, c)
Figure SMS_21
Identification threshold comparison: if->
Figure SMS_23
No color value c is greater than G u If the recognition is completed, if the recognition is not completed, i=i+1, and continuing from I nm Reading defect auto-discrimination image area +.>
Figure SMS_25
If the identification is finished, ending the identification; if->
Figure SMS_22
The color value c is greater than G u Is calculated->
Figure SMS_24
The medium color value c is greater than G u Is +.>
Figure SMS_26
And the length L, width W and equivalent diameter D thereof, corresponding position coordinates (x, y) and stored in an array +.>
Figure SMS_27
In the step (a), whether the identification is completed is judged, if the identification is not completed, i=i+1, and the process continues from I nm Reading defect auto-discrimination image area +.>
Figure SMS_20
And if the identification is finished, ending the identification.
In some embodiments, visually identifying the defect includes: according to
Figure SMS_28
Recording the result, performing defect F in the ultrasonic C-scan image i Identification; according to->
Figure SMS_29
The results of the recording were tabulated according to table 1.
Table 1 defect visualization list format
Figure SMS_30
In some embodiments, automatically identifying a defect for robustness assessment includes the steps of: selecting a standard sample for evaluating the ultrasonic C scanning detection effect of the composite material, wherein the selection of the standard sample is the same as that of the detected composite material part, and the defect distribution and the defect quantity in the standard sample meet the detection probability requirement of the ultrasonic C scanning requirement; respectively detecting the standard sample for 3 times by using the same ultrasonic C scanning detection conditions, and storing detection results of each time; performing automatic defect identification on the 3 ultrasonic three-dimensional automatic C scanning results of the part to be evaluated, and solving the defect number N automatically identified by 3 ultrasonic C scanning d The calculated stability formula is:
Figure SMS_31
Figure SMS_32
(1) When gamma is more than or equal to 98%, the automatic identification stability assessment of ultrasonic C scanning defects is very stable and is defined as class A;
(2) When 95% > gamma is more than or equal to 98%, the automatic identification robustness of the ultrasonic C scanning defect is evaluated as being robust, and is defined as class B;
(3) When gamma is more than or equal to 90% and less than 95%, the automatic identification robustness of the ultrasonic C scanning defect is evaluated as less robust and is defined as class D;
(4) When gamma is less than 90%, the ultrasonic C scanning defect automatic identification stability assessment is not robust and is defined as E level;
wherein, the A level indicates that the automatic defect identification result is most correct, the E level indicates that the automatic defect identification result is least correct, and the B level, the C level and the D level are sequentially arranged between the A level and the E level.
When the verification reaches the A level, the device can be used, when the verification reaches the B level, the device has practicability, and other levels are obtained, so that the device needs to be optimized.
Examples:
respectively selects ultrasonic C scanning data of the wall plates of the large composite materials with different 3200mm multiplied by 1600mm multiplied by 6000mm multiplied by 1600mm, respectively selects
Figure SMS_33
Performing defect automatic identification of a plurality of cases, combining the defect automatic evaluation results, and selecting N s Evaluation standard =93, subjected to stability evaluation, wherein, for +.>
Figure SMS_34
Two defects are automatically identified, and the defect number is M d The stability is gamma=100%, and belongs to class A, and test results show that the method can be used for efficiently and accurately evaluating the ultrasonic C-scanning detection result of the composite material, has high evaluation efficiency, high evaluation result correctness, extremely low labor intensity, extremely low non-cost and extremely short evaluation period, and is further beneficial to improving the accuracy, reliability and detection efficiency of the ultrasonic C-scanning detection result.
It should be understood that, in the present specification, each embodiment is described in an incremental manner, and the same or similar parts between the embodiments are all referred to each other, and each embodiment is mainly described in a different point from other embodiments. The invention is not limited to the specific steps and structures described above and shown in the drawings. Also, a detailed description of known method techniques is omitted here for the sake of brevity.
The foregoing is merely exemplary of the present application and is not limited thereto. Various modifications and alterations of this application will become apparent to those skilled in the art without departing from the scope of this invention. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims (9)

1. An ultrasonic automatic identification method for composite material defects considering detection probability is characterized by comprising the following steps:
acquiring ultrasonic C scanning information;
setting a defect automatic identification threshold G u ；
Setting an automatic defect evaluation threshold;
automatically identifying the defects;
visual identification is carried out on the defects;
and (5) evaluating the robustness of the automatic identification of the defects.
2. The ultrasonic automatic identification method of composite defects considering detection probability according to claim 1, wherein the step of acquiring ultrasonic C-scan information comprises the steps of:
reading and storing the formed ultrasonic C scanning image format into a computer memory I nm In (x, y, z, C), x, y, z correspond to the position coordinates in the ultrasound C-scan image, respectively, and satisfy:
x＝k x x o (1)
y＝k y y o (2)
z＝k z z o (3)
wherein, (x) o ,y o ,z o ) Respectively representing the position coordinates of the surface of the detected composite material part, (k) x ,k y ,k z ) Respectively representing conversion coefficients between the position coordinates of the surface of the detected composite material part and the position coordinates in the ultrasonic C-scan image;
c is the ultrasonic C-scan image color value corresponding to (x, y, z), and satisfies:
c＝k u A u (4)
k u for the conversion coefficient of the ultrasonic signal and the color value in the image, A u An ultrasound signal for ultrasound C-scan imaging;
for the ultrasonic C scanning result as the detection original data format, converting the ultrasonic C scanning original data into an ultrasonic C scanning image format according to the formulas (1) to (4), and reading into a computer memory I nm (x, y, z, c).
3. The ultrasonic automatic identification method of composite defects considering detection probability according to claim 2, wherein the ultrasonic C-scan image format comprises BMP, TIFF and JPEG bitmap formats.
4. The ultrasonic automatic identification method for defects of composite material taking detection probability into consideration as set forth in claim 2, wherein said automatic identification threshold value G for defects u The arrangement of (2) comprises:
according to the detected composite material part materials, process and structural characteristics and ultrasonic C scanning image characteristics thereof, determining a calculation formula of the defect automatic identification threshold value is as follows:
Figure FDA0003929656770000021
wherein Q is ij (x ij ,y ij ,c ij ) Scanning the ith row, jth column, x of the feature image region for selected ultrasound C ij ,y ij ,c ij The size of the ultrasonic C scanning characteristic image area is m multiplied by n, the ultrasonic C scanning characteristic image area is selected according to the read ultrasonic C scanning characteristic image, and the defect-free area of the detected composite material part corresponding to the ultrasonic C scanning characteristic image area is determined through an ultrasonic C scanning detection test.
5. The ultrasonic automatic identification method for defects of composite materials taking into account detection probability according to claim 4, wherein the setting of the defect automatic evaluation threshold value comprises: setting an automatic defect evaluation threshold according to the quality acceptance requirement of the detected composite material part
Figure FDA0003929656770000022
6. The ultrasonic automatic identification method for composite material defects taking detection probability into consideration according to claim 5, wherein the method comprises the following steps of
Figure FDA0003929656770000023
Is the area or diameter or length, < >>
Figure FDA0003929656770000024
In millimeters. />
7. An ultrasonic automatic identification method for defects of composite materials taking into account the probability of detection according to claim 5 or 6, characterized in that the automatic identification of the defects comprises the steps of:
from I nm Automatically identifying image areas for reading defects in (x, y, z, c)
Figure FDA0003929656770000025
Identification threshold comparison: if it is
Figure FDA0003929656770000026
No color value c is greater than G u If the recognition is completed, if the recognition is not completed, i=i+1, and continuing from I nm Reading defect auto-discrimination image area +.>
Figure FDA0003929656770000027
If the identification is finished, ending the identification;
if it is
Figure FDA0003929656770000028
The color value c is greater than G u Is calculated->
Figure FDA0003929656770000029
The medium color value c is greater than G u Is +.>
Figure FDA00039296567700000210
And its length L, width W and equivalent diameter D, corresponding position coordinates (x, y), andthere is array->
Figure FDA00039296567700000211
In the step (a), whether the identification is completed is judged, if the identification is not completed, i=i+1, and the process continues from I nm Reading defect auto-discrimination image area +.>
Figure FDA0003929656770000031
And if the identification is finished, ending the identification.
8. The ultrasonic automatic identification method for defects of composite materials taking into account detection probability as set forth in claim 7, wherein visually identifying the defects comprises: according to
Figure FDA0003929656770000032
Recording the result, performing defect F in the ultrasonic C-scan image i And (5) identification.
9. The ultrasonic automatic identification method of composite material defects considering detection probability according to claim 8, wherein the automatic identification robustness evaluation of defects comprises the steps of:
selecting a standard sample for evaluating the ultrasonic C scanning detection effect of the composite material, wherein the selection of the standard sample is the same as that of the detected composite material part, and the defect distribution and the defect quantity in the standard sample meet the detection probability requirement of the ultrasonic C scanning requirement;
respectively detecting the standard sample for 3 times by using the same ultrasonic C scanning detection conditions, and storing detection results of each time;
performing automatic defect identification on the 3 ultrasonic three-dimensional automatic C scanning results of the part to be evaluated, and solving the defect number N automatically identified by 3 ultrasonic C scanning d The calculated stability formula is:
Figure FDA0003929656770000033
Figure FDA0003929656770000034
/>
CN202211383605.4A 2022-11-07 2022-11-07 Composite material defect ultrasonic automatic identification method considering detection probability Pending CN116046907A (en)

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