CN111103361B - Self-adaptive defect automatic measurement algorithm for ultrasonic phased array image - Google Patents
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Abstract
The invention relates to the technical field of ultrasonic measurement, in particular to an ultrasonic phased array image self-adaptive defect automatic measurement algorithm. The invention adopts the following technical scheme: searching the maximum amplitude point in the C image, deriving a corresponding B image, respectively searching the defective areas of the C image and the B image, determining to use a relative sensitivity method or an absolute sensitivity method according to the search result, and finally obtaining the defective area. The invention has the advantages that: according to the acquisition rule of the defect area, the defect area is measured and calculated by adopting a method executable by a computer program, the defect area can be automatically measured and calculated only by manually roughly clamping the approximate position of the defect by using a measuring line and setting corresponding parameters, a relative sensitivity method or an absolute sensitivity method can be distinguished and used according to the search result, the true and false wave crests can be identified, the speed of evaluating the ultrasonic phased array image is improved, and the technical requirement on operators is reduced.
Description
Technical Field
The invention relates to the technical field of ultrasonic measurement, in particular to an ultrasonic phased array image self-adaptive defect automatic measurement algorithm.
Background
The ultrasonic phased array technology is the leading-edge technology in the technical field of nondestructive testing, develops rapidly in recent years, and is widely applied to various fields such as petroleum, chemical engineering, metallurgy, shipbuilding, aviation, aerospace and the like. The phased array technology adopts a plurality of piezoelectric wafers to form an array transducer, and an electronic system controls each wafer in the array to transmit and receive ultrasonic waves according to a certain delay rule, so that the functions of scanning, deflecting, focusing and the like of sound beams are realized.
Through the acquired phased array image, a flaw detector needs to identify and measure the defects of the image, and the measured content comprises the height and the corresponding amplitude of the defects, the length of the defects and the height of the defects. And acquiring the defect echo amplitude, namely finding the highest echo amplitude of the defect of different A scanning lines of B images at different positions, the position of the point and the height of the defect. The existing phased array image defect identification modes are all manual identification, are complex to operate, need to switch back and forth among a plurality of views, zoom images for measurement, and have accuracy depending on experience and skill level of operators.
Disclosure of Invention
The invention aims to provide an ultrasonic phased array image self-adaptive defect automatic measurement algorithm, and particularly provides an algorithm capable of measuring a defect part of a phased array image by using a computer program.
In order to achieve the purpose, the invention adopts the following technical scheme: an ultrasonic phased array image self-adaptive defect automatic measurement algorithm comprises the following steps:
s01, setting measurement parameters, including: defect reduction (D), resolution (T) and end-point peak (P).
S02, searching the coordinate (X) of the point with the highest amplitude in the defect range of the C image max ，Y max ) Is otherwise denoted as (X) 1 ，Y 1 ) Amplitude of H max Is otherwise denoted as H 1 And coordinate point (X) 1 ，Y 1 ) Is recorded as classification C 1 。
S03. With classification C 1 For diffusion from the center to the periphery, all points along the way with decreasing amplitude are marked, whose amplitude value satisfies Drop (H) 1 ，D)<H≤H 1 Then is marked as C 1 Amplitude value satisfying H ≦ Drop (H) 1 D) as classification C 1ex 。
S04, searching for the point which is not classified in the defect range and has the amplitude value H satisfying Drop (H) 1 ，D)<H≤H 1 Image point of (2), marked as C to be classified ？ 。
S05. In the classification C ？ Searching for the coordinate (X) of the next peak point 2 ，Y 2 ) Amplitude of H 2 Point (X) 2 ，Y 2 ) Is recorded as classification C 2 。
S06, with C 2 For diffusion from the center to the periphery, all points along the way with decreasing amplitude are marked, whose amplitude value satisfies Drop (H) 2 ，D))<H≤H 2 Then is marked as C 2 Amplitude value satisfying H ≦ Drop (H) 2 D) as classification C 2ex 。
S07, searching unclassified points in defect range for amplitude value H satisfying Drop (H) 2 ，D)<H≤H 2 Image point of (2), marked as C to be classified ？ 。
S08, the searching mode of the steps S05 to S07 is repeated to continuously search other peak classification points C in the defect range 3 、C 4 、…、C n Classification point C 1 、C 2 、…、C n The rectangular area is the sum of (X) s ，Y s ，F L ，F W )。
S09. call out X max In the B image, the (X, Y) coordinates are changed into (Y, Z) coordinates according to the searching mode of the steps S02 to S08, and a rectangular area (Y) is searched s ，Z s ，F W ，F H )。
In the above step, formula Drop (H, D) is the amplitude value after amplitude H is reduced by DdB, X s As coordinates of the starting point of the defect length, Y s As coordinates of the start of the defect width, Z s As coordinates of the starting point of the depth of the defect, F L As length of defect, F W Is the width of the defect, F H Is the defect depth.
Further, step S07 further includes identifying whether the peak classification point is true or false: search classification C 2 、C 2ex The boundary point with the classified point, where the boundary point is classified as C j Or C jex Then, the peak value H of the classification point where the boundary point is located is taken j If TDB (H) j ，H 2 )<T, then classify C 2 、C 2ex And C j 、C jex Merging, and making amplitude value meet Drop (H) j ，D)<H≤H j Is marked as C j And the remainder are denoted by C jex Otherwise, the classification C is retained 2 、C 2ex (ii) a Wherein formula TDB (H) 1 ，H 2 ) Is amplitude H 1 And amplitude H 2 The dB value of the phase difference.
Further, the measuring parameters in step S01 further include: full screen height (F) and absolute rule (R), step S02 first compares the amplitude value H max And (3) judging the full screen height: when H is present max If the frequency is larger than F, searching the defect area by adopting an absolute sensitivity method, and omitting the relative sensitivity method of the steps S03 to S08; when H is present max If the value is less than F, the relative sensitivity method of steps S03 to S08 is performed to search for a defective area.
Further, the absolute sensitivity method is: searching for points whose amplitude values satisfy H ≧ Abso (R), and marking the points at which they are locatedThe rectangular region of (A) is a defective region (X) s ，Y s ，F L ，F W )。
Further, in steps S02 to S08, the classification point C is searched 1 、C 2 、…、C n When the classification point C is found k+1 Amplitude value of (H) k+1 If < P, the search is ended and the classification point C is 1 、C 2 、…、C k The rectangular region is marked as a defect region (X) s ，Y s ，F L ，F W )。
The invention has the advantages that: according to the acquisition rule of the defect area, the defect area is measured and calculated by adopting a method executable by a computer program, the defect area can be automatically measured and calculated only by manually roughly clamping the approximate position of the defect by using a measuring line and setting corresponding parameters, the speed of evaluating the ultrasonic phased array is improved, and the technical requirements on operators are reduced.
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FIG. 1 is a block diagram of a searching procedure for a defective area of a C image in an embodiment;
fig. 2 is a block diagram of a searching procedure for a defective area of a B image in an embodiment.
Detailed Description
Example 1: referring to fig. 1-2, an adaptive defect automatic measurement algorithm for an ultrasonic phased array image comprises the following steps:
s01, setting measurement parameters, including: defect reduction (D), resolution (T) and end point peak (P).
S02, searching the coordinate (X) of the point with the highest amplitude in the defect range of the C image max ，Y max ) Is otherwise denoted as (X) 1 ，Y 1 ) Amplitude of H max Is otherwise denoted as H 1 And coordinate point (X) 1 ，Y 1 ) Is recorded as classification C 1 。
S03. With classification C 1 For diffusion from the center to the periphery, all points along the way with decreasing amplitude are marked, whose amplitude value satisfies Drop (H) 1 ，D)<H≤H 1 Then is recorded as C 1 Amplitude value satisfying H ≦ Drop (H) 1 D) as classification C 1ex 。
S04, searching for the point which is not classified in the defect range and has the amplitude value H satisfying Drop (H) 1 ，D)<H≤H 1 Image point of (2), marked as C to be classified ？ 。
S05, in waiting to classify C ？ Searching for the coordinate (X) of the next peak point 2 ，Y 2 ) Amplitude of H 2 A point (X) 2 ，Y 2 ) Is recorded as classification C 2 。
S06, with C 2 For diffusion from the center to the periphery, all points along the way with decreasing amplitude are marked, whose amplitude value satisfies Drop (H) 2 ，D))<H≤H 2 Then is marked as C 2 Amplitude value satisfying H ≦ Drop (H) 2 D) as classification C 2ex 。
S07, searching unclassified points in defect range for amplitude value H satisfying Drop (H) 2 ，D)<H≤H 2 Image point of (2), marked as C to be classified ？ 。
S08, the searching mode of the steps S05 to S07 is repeated to continuously search other peak classification points C in the defect range 3 、C 4 、…、C n Classification point C 1 、C 2 、…、C n The rectangular area is the sum of (X) s ，Y s ，F L ，F W )。
Referring to FIG. 1, in the logic of a computer program, C is searched out 1 Then, in the above steps S05 to S07, X 2 、Y 2 、H 2 、C 2 、C 2ex Is marked as X i 、Y i 、H i 、C i 、C iex I is set to 2, and steps S05 to S07 are executed once per cycle, i is added with 1, thereby obtaining all the peak points C in the defect area 1 、C 2 、…、C n 。
S09. call out X max In the B image, the (X, Y) coordinates are changed into (Y, Z) coordinates according to the searching mode of the steps S02 to S08, and a rectangular area (Y) is searched s ，Z s ，F W ，F H )。
In the above steps, the formula Drop (H, D) isAmplitude value, X, after amplitude H reduction DdB s As coordinates of the starting point of the defect length, Y s As coordinates of the starting point of the defect width, Z s As coordinates of the starting point of the depth of the defect, F L As length of defect, F W Is the width of the defect, F H Is the defect depth.
In this embodiment, a computer is used to search for one or more peaks in the defect region, and all the points near the peak satisfying the relative sensitivity method (i.e., the points descending from the peak point to the periphery of DdB) are searched out, so as to obtain the area of all the searched peak points and the areas of the points around the peak points satisfying the relative sensitivity method, thereby obtaining the position and size of the defect region according to the parameter settings. When the area search is carried out manually, for the defect area with only one peak point, adopting a DdB reducing method, namely, obtaining the position with the maximum amplitude, moving the position to the position range of DdB reduced by the dB value of the amplitude around the position, and obtaining the position and the size of the defect area; for the defect with a plurality of peak points, an end point drop DdB method is adopted, namely the peak points around the defect are obtained, the peak point positioned at the leftmost side moves leftwards to the position where the dB value of the peak amplitude is dropped DdB, the peak point positioned at the rightmost side moves rightwards to the position where the dB value of the peak amplitude is dropped DdB, and in the same way, the peak point at the uppermost side moves upwards to the position where the dB value of the peak amplitude is dropped DdB, and the peak point at the lowermost side moves downwards to the position where the dB value of the peak amplitude is dropped DdB, so that the position and the size of the defect area are obtained. In this embodiment, one or more peak points in the defect area are directly searched, and all the points where the peak points descend to DdB all around are searched, when only one peak point is found, the method of descending DdB is met, and when a plurality of peak points exist, the method of descending DdB is met. Therefore, the method is suitable for running of the computer program, and the searching speed of the computer program is much faster than that of manual work, so that even if some points are searched, the speed is much faster than that of manual work, the measurement efficiency is higher, and the technical requirement on the manual work is lower.
In a further embodiment, step S07 further includes performing identification of true or false peaks for the peak classification points: search classification C 2 、C 2ex With classified pointsThe boundary point of (1), the classification of the boundary point is C j Or C jex Then, the peak value H of the classification point where the boundary point is located is taken j If TDB (H) j ，H 2 )<T, then classify C 2 、C 2ex And C j 、C jex Merging, and making amplitude value meet Drop (H) j ，D)<H≤H j Is marked as C j And the remainder are denoted by C jex Otherwise, the classification C is retained 2 、C 2ex (ii) a Wherein formula TDB (H) 1 ，H 2 ) Is amplitude H 1 And amplitude H 2 The dB value of the phase difference.
In the parameter setting of step S01, the resolution (T) is a criterion for distinguishing whether two peaks are the same peak, and if the value is set to 6dB, the difference in dB between the found peak and the peak before the valley must exceed 6dB to be a true peak, otherwise, the peak is a false peak (i.e., a burr beside the main peak).
Similarly, in the computer program, X in steps S05 to S07 2 、Y 2 、H 2 、C 2 、C 2ex Is marked as X i 、Y i 、H i 、C i 、C iex I is set to 2, and steps S05-S07 are executed once per cycle if TDB (H) j ，H i )<T, then C i For a pseudo peak, i goes directly to the next cycle without adding 1, if TDB (H) j ，H i ) Not less than T, then C i For a true peak, i is incremented by 1 and then the next cycle is entered.
In a further embodiment, the measuring parameters in step S01 further comprises: full screen height (F) and absolute rule (R), step S02 first compares the amplitude value H max And (3) judging the full screen height: when H is present max If the frequency is larger than F, searching the defect area by adopting an absolute sensitivity method, and omitting the relative sensitivity method of the steps S03 to S08; when H is present max If the value is less than F, the relative sensitivity method of steps S03 to S08 is performed to search for a defective area.
In step S02, according to the highest amplitude value H searched out max Judging by absolute sensitivity method or relative sensitivity method, when H is max If the signal is larger than F, an absolute sensitivity method is adopted, steps S03-S08 are not required to be executed, and when H is larger than F max And if not more than F, executing the steps S03 to S08 by adopting a relative sensitivity method.
Specifically, the absolute sensitivity method is: searching for points whose amplitude value satisfies H ≧ Abso (R), and marking rectangular regions where these points are located as defective regions (X) s ，Y s ，F L ，F W ). Wherein, abso (R) is an amplitude value converted according to the rule R of the absolute method, and the data in the absolute sensitivity method must satisfy H ≧ Abso (R).
Specifically, in steps S02 to S08, the classification point C is searched 1 、C 2 、…、C n When the classification point C is found k+1 Wave peak value H of k+1 If < P, ending the search and classifying the point C 1 、C 2 、…、C k The rectangular region is marked as a defect region (X) s ，Y s ，F L ，F W ). In this embodiment, the end point peak (P) is used to distinguish whether the found peak is a valid peak according to the measurement parameter input in step S01, and the found peak is a valid peak only if the amplitude value exceeds the end point peak (P), otherwise, the found peak is invalid.
Similarly, in the computer program, X in steps S05 to S07 2 、Y 2 、H 2 、C 2 、C 2ex Is marked as X i 、Y i 、H i 、C i 、C iex Every time step S05 is executed, H is processed i Make a judgment if H i If < P, ending the search and classifying the peak searched before into C 1 、C 2 、…、C i-1 The region where the defect occurred was designated as a defective region (X) s ，Y s ，F L ，F W ) And quitting the program; at the same time, the highest amplitude value H is searched max At this time, the judgment is also made, if H max If the number is less than P, the defect area does not meet the defect setting, the program is directly exited, otherwise, the next operation is executed.
Referring to fig. 2, the searching method for the defective area of the B image is the same as the searching method for the image C, and details are not repeated herein, and the determining method for the B imageMethod, X of the maximum defect amplitude point found by C image max A determination is made.
It should be understood that the above-mentioned embodiments are merely preferred embodiments of the present invention, and not intended to limit the scope of the invention, therefore, all equivalent changes in the principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. An ultrasonic phased array image self-adaptive defect automatic measurement algorithm is characterized in that: the method comprises the following steps:
s01, setting measurement parameters, including: defect reduction D, resolution T and endpoint wave peak P;
s02, searching the coordinate (X) of the point with the highest amplitude in the defect range of the C image max ，Y max ) Is otherwise denoted as (X) 1 ，Y 1 ) Amplitude of H max And is additionally denoted as H 1 And coordinate point (X) 1 ，Y 1 ) Is recorded as classification C 1 ；
S03. With classification C 1 For diffusion from the center to the periphery, all points along the way with decreasing amplitude are marked, whose amplitude value satisfies Drop (H) 1 ，D)<H≤H 1 Then is marked as C 1 Amplitude value satisfying H ≦ Drop (H) 1 D) as classification C 1ex ；
S04, searching for the point which is not classified in the defect range and has the amplitude value H satisfying Drop (H) 1 ，D)<H≤H 1 Image point of (2), marked as C to be classified ？ ；
S05, in waiting to classify C ？ Searching for the coordinate (X) of the next peak point 2 ，Y 2 ) Amplitude of H 2 Point (X) 2 ，Y 2 ) Is recorded as classification C 2 ；
S06, using C 2 For diffusion from the center to the periphery, all points along the way with decreasing amplitude are marked, whose amplitude value satisfies Drop (H) 2 ，D))<H≤H 2 Then is marked as C 2 Amplitude value satisfying H ≦ Drop (H) 2 D) as classification C 2ex ；
S07, searching unclassified points in defect range for amplitude value H satisfying Drop (H) 2 ，D)<H≤H 2 Image point of (2), marked as C to be classified ？ ；
S08, the searching mode of the steps S05 to S07 is repeated to continuously search other peak classification points C in the defect range 3 、C 4 、…、C n Classification point C 1 、C 2 、…、C n The rectangular area is the sum of (X) s ，Y s ，F L ，F W )；
S09. call out X max In the B image, the (X, Y) coordinates are changed into (Y, Z) coordinates according to the searching mode of the steps S02 to S08, and a rectangular area (Y) is searched s ，Z s ，F W ，F H )；
In the above step, formula Drop (H, D) is the amplitude value after amplitude H is reduced by DdB, X s As coordinates of the starting point of the defect length, Y s As coordinates of the start of the defect width, Z s As coordinates of the starting point of the depth of the defect, F L As length of defect, F W Is the width of the defect, F H Is the defect depth.
2. The adaptive defect automatic measurement algorithm for the ultrasonic phased array image according to claim 1, characterized in that: the step S07 further includes identifying the true or false wave peak from the wave peak classification point: search classification C 2 、C 2ex The boundary point with the classified point, the classification of the boundary point is C j Or C jex Then, the peak value H of the classification point where the boundary point is located is taken j If TDB (H) j ，H 2 )<T, then classify C 2 、C 2ex And C j 、C jex Merging, and meeting the amplitude value with Drop (H) after merging j ，D)<H≤H j Is marked as C j And the remainder are denoted by C jex Otherwise, the classification C is retained 2 、C 2ex (ii) a Wherein formula TDB (H) 1 ，H 2 ) Is amplitude H 1 And amplitude H 2 The dB value of the phase difference.
3. The adaptive defect automatic measurement algorithm for the ultrasonic phased array image according to claim 1 or 2, characterized in that: the measuring parameters in step S01 further include: full height F and rule of absolute method R, step S02 first compares the amplitude value H max And (3) judging the full screen height: when H is present max If the frequency is larger than F, searching the defect area by adopting an absolute sensitivity method, and omitting the relative sensitivity method of the steps S03 to S08; when H is present max If the value is less than F, the relative sensitivity method of steps S03 to S08 is performed to search for a defective area.
4. The adaptive defect automatic measurement algorithm for the ultrasonic phased array image according to claim 3, is characterized in that: the absolute sensitivity method is as follows: searching points with amplitude values satisfying H ≧ Abso (R), and marking rectangular regions where the points are located as defect regions (X) s ，Y s ，F L ，F W ) (ii) a Where Abso (R) is an amplitude value converted according to the absolute rule R.
5. The adaptive defect automatic measurement algorithm for the ultrasonic phased array image according to claim 1 or 2, characterized in that: in the above steps S02 to S08, the classification point C is searched 1 、C 2 、…、C n When the classification point C is found k+1 Amplitude value of (H) k+1 If < P, the search is ended and the classification point C is 1 、C 2 、…、C k The rectangular region is marked as a defect region (X) s ，Y s ，F L ，F W )。
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