CN115452944A - Plate-shaped material multi-damage positioning method based on L-shaped sensor cluster - Google Patents

Plate-shaped material multi-damage positioning method based on L-shaped sensor cluster Download PDF

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CN115452944A
CN115452944A CN202211081089.XA CN202211081089A CN115452944A CN 115452944 A CN115452944 A CN 115452944A CN 202211081089 A CN202211081089 A CN 202211081089A CN 115452944 A CN115452944 A CN 115452944A
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damage
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receiving
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plate
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崔志文
周子贤
刘金霞
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Jilin University
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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
    • G01N29/04—Analysing solids
    • 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
    • G01N29/22—Details, e.g. general constructional or apparatus details
    • G01N29/24—Probes
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N9/00—Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity
    • G01N9/24—Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity by observing the transmission of wave or particle radiation through the material
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N9/00—Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity
    • G01N9/36—Analysing materials by measuring the density or specific gravity, e.g. determining quantity of moisture
    • 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
    • G01N2291/0231—Composite or layered materials
    • 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
    • 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
    • G01N2291/04—Wave modes and trajectories
    • G01N2291/042—Wave modes
    • G01N2291/0426—Bulk waves, e.g. quartz crystal microbalance, torsional waves
    • 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
    • G01N2291/10—Number of transducers
    • G01N2291/103—Number of transducers one emitter, two or more receivers

Abstract

The disclosure provides a plate-shaped material multi-damage positioning method based on L-shaped sensor clusters, which comprises the steps of arranging an L-shaped sensor cluster array on a plate-shaped material to be detected; obtaining a damage characteristic signal of each receiving sensor in the L-shaped sensor cluster array; calculating the time difference of the damage characteristic signals between two adjacent receiving sensors; determining possible damage point coordinates according to the damage characteristic signal time difference; removing damage artifacts existing in possible damage point coordinates; and (4) performing relative probability density imaging on the damage points by a nuclear density estimation method, and screening the damage points meeting the threshold value to obtain the damage positions. The plate-shaped material multi-damage positioning method based on the L-shaped sensor cluster can be simultaneously suitable for sound velocity isotropic materials and sound velocity anisotropic materials; the non-linear equation does not need to be solved, the positioning speed is high, the calculated amount is small, and the positioning efficiency is improved; the plate-shaped material damage positioning method has the advantages that the material properties are not required to be known, the plate-shaped material damage positioning method with unknown material can be used, and the application range of the positioning method is expanded.

Description

Plate-shaped material multi-damage positioning method based on L-shaped sensor cluster
Technical Field
The disclosure relates to the technical field of ultrasonic nondestructive testing, in particular to a plate-shaped material multi-damage positioning method based on an L-shaped sensor cluster.
Background
The Lamb guided wave technology is widely applied to the field of nondestructive testing and structural health testing of plate-shaped structures due to the advantages of large detection area, small energy attenuation, sensitivity to small defects and the like.
The plate-shaped structure is widely applied to various fields of aircraft skins, ship bodies, bridge supporting plates, pressure containers and the like. As operating time increases, various types of damage (e.g., cracks, corrosion, and delamination) inevitably occur and accumulate, presenting risks and challenges to the proper operation of the equipment and building structures. In practice, the plate-like structure may present multiple lesions simultaneously, making lesion localization more challenging. First, at multiple lesions, the signal received by the sensor is more complex, containing multiple wave packets resulting from reflections from various defects; second, it is difficult to distinguish the source of each wave packet because the relative positions of the defects are unknown.
In the traditional plate-shaped material multi-damage identification technology, known material parameters are needed to calculate the group velocity and the phase velocity corresponding to specific frequency and material thickness, meanwhile, a nonlinear equation needs to be solved or the exact number of scattering sources needs to be determined to identify and position multi-damage, so that the positioning efficiency is low, the calculated amount is large, and the application range is small.
Disclosure of Invention
The object of the present disclosure is to provide a method for positioning multiple damages of a plate-shaped material based on an L-shaped sensor cluster, which can solve one or more of the above-mentioned problems of the prior art.
According to one aspect of the disclosure, a plate-shaped material multi-damage positioning method based on an L-shaped sensor cluster is provided, and comprises the following steps:
step 1: arranging an L-shaped sensor cluster array on a plate-shaped material to be detected, wherein the L-shaped sensor cluster array comprises three groups of L-shaped sensor clusters, each group of L-shaped sensor clusters comprises three receiving sensors, and an excitation sensor is arranged at the center of the plate-shaped material to be detected;
step 2: obtaining a damage characteristic signal of each receiving sensor in the L-shaped sensor cluster array;
and step 3: calculating the time difference of the damage characteristic signals between two adjacent receiving sensors;
and 4, step 4: determining possible damage point coordinates according to the damage characteristic signal time difference;
and 5: removing damage artifacts existing in possible damage point coordinates according to the damage characteristic signal time difference and the relative position of the receiving sensor;
step 6: and (4) performing relative probability density imaging on the damage points by a nuclear density estimation method, and screening the damage points meeting the threshold value to obtain the damage positions.
In some embodiments, in step 1, arranging an array of L-shaped sensor clusters on a sheet of material to be measured comprises:
step 1.1: establishing a coordinate system, wherein the center of the plate-shaped material to be detected is taken as an original point, the long edge of the plate-shaped material to be detected is taken as an x axis, and the short edge of the plate-shaped material to be detected is taken as a y axis;
step 1.2: arranging an excitation sensor at the origin of the coordinate system, and recording the excitation sensor as O;
step 1.3: the multi-group L-shaped sensor cluster is arranged in a coordinate system, each group of L-shaped sensor cluster comprises three receiving sensors, the three receiving sensors in each group of L-shaped sensor cluster are distributed in an isosceles right triangle shape, the distance between the two receiving sensors on the right-angle side is d, and the receiving sensors are recorded as S i (i =1, 2, 3 \8230; 9), receiving sensor coordinate notation (p) i ，q i )。
In some embodiments, in step 1.3, the setting of the plurality of sets of L-shaped sensor clusters in the coordinate system specifically includes, optionally, three quadrants of the coordinate system, one set of L-shaped sensor clusters being set in each quadrant.
In some embodiments, in step 1.3, the right-angle sides of the isosceles right triangle formed by the three receiving sensors in each group of L-shaped sensor clusters are arranged parallel to the coordinate axis.
In some embodiments, in step 2, obtaining the lesion signature signal for each receiving sensor in the array of L-shaped sensor clusters comprises:
step 2.1: applying an excitation signal to the excitation sensor under the healthy state of the plate-shaped material, and sequentially collecting the base line signals fed back by the receiving sensors and recording the base line signals as
Figure BDA0003832602440000021
Step 2.2: in the damaged state of the plate-shaped material, the same excitation signal as that in the step 2.1 is applied to the excitation sensor, and detection signals fed back by the receiving sensors are sequentially acquired and recorded as
Figure BDA0003832602440000022
Figure BDA0003832602440000023
Step 2.3: obtaining a lesion signature of
Figure BDA0003832602440000024
In some embodiments, in step 3, calculating the lesion signature time difference between two adjacent receiving sensors comprises:
three groups of L-shaped sensor clusters are respectively set as a sensor cluster S 1 S 2 S 3 A sensor cluster S 4 S 5 S 6 And a sensor cluster S 7 S 8 S 9 In which the receiving sensor S 2 、S 5 And S 8 The receiving sensor is arranged at the right-angle vertex of the isosceles right triangle;
respectively carrying out cross-correlation processing on the damage characteristic signals recorded by two adjacent receiving sensors on the right-angle side of each group of L-shaped sensor clusters, calculating the time difference of the damage characteristic signals between the two adjacent receiving sensors on the right-angle side, and recording the time difference of the damage characteristic signals as delta t ij (i＝1、3、4、6、7、9，j＝2、5、8，|i-j|≤1)。
In some embodiments, in step 4, determining the possible damage point coordinates according to the damage characteristic signal time difference includes:
when the number of the damage characteristic signals obtained from each receiving sensor is n, judging that n damages exist in the plate-shaped material at the moment;
step 4.1: respectively determining a linear equation where a connection line of each damage and a receiving sensor on a right-angle vertex in the three L-shaped sensor clusters is located;
step 4.2: and solving the three linear equations corresponding to each damage pairwise in a simultaneous manner, wherein each damage corresponds to three solutions, namely each damage has three possible damage point coordinates.
In some embodiments, in step 4.1, the equation of the straight line in which each lesion is connected to the receiving sensors at the vertices of the right angles in the three L-shaped sensor clusters respectively comprises:
let the coordinate of the damage N in the plate-like material be (x) N ，y N ) Wherein N =1, 2, \8230, N, three groups of L-shaped sensor clusters are respectively marked as sensor cluster S 1 S 2 S 3 Sensor cluster S 4 S 5 S 6 And a sensor cluster S 7 S 8 S 9 Damage N and sensor S 2 The equation of the line where the connecting line is located is recorded as a straight line L N1 Damage N and sensor S 5 The equation of the line where the connecting line is located is recorded as a straight line L N2 Damage N and sensor S 8 The equation of the straight line where the connecting line is located is expressed as a straight line L N3 ；
Step 4.1.1: calculating a straight line L N1 Angle alpha to the x-axis N1 ，α N1 The expression of (c) is as follows:
Figure BDA0003832602440000031
step 4.1.2: calculating the time difference Deltat of the damage characteristic signal N12 And Δ t N32 ，Δt N12 And Δ t N32 The expression of (a) is as follows:
Figure BDA0003832602440000032
Figure BDA0003832602440000033
in the formula,. DELTA.t N12 Receiving sensor S corresponding to damage N 1 And a receiving sensor S 2 Difference in signal time of impairment characteristic, Δ t, between N32 Receiving sensor S corresponding to damage N 2 And a receiving sensor S 3 The time difference of the damage characteristic signal between, d represents the receiving sensor S 2 And a receiving sensor S 3 And a receiving sensor S 1 Distance therebetween, receiving the sensor S 2 At the right angle vertex of the L-shaped sensor cluster in which it is located, c (α) N1 ) Indicating the direction alpha of the sound source N1 The wave velocity of (1);
step 4.1.3: substituting the expression (2) and the expression (3) into the expression (1) to obtain alpha N1 The expression of (c) is as follows:
Figure BDA0003832602440000041
step 4.1.4: obtaining damage N and receiving sensor S 2 Straight line L of connecting line N1 Slope k of N1 Slope k N1 The expression of (c) is as follows:
Figure BDA0003832602440000042
step 4.1.5: to obtain a straight line L N1 The equation of (c) is as follows:
Figure BDA0003832602440000043
step 4.1.6: obtaining the straight line L by the same method N2 And a straight line L N3 The equation of (a) is as follows:
Figure BDA0003832602440000044
Figure BDA0003832602440000045
in some embodiments, the receiving sensor S is set within a coordinate system 1 Has a longitudinal coordinate greater than that of the receiving sensor S 2 Ordinate of (c), receiving sensor S 5 Has a greater ordinate than the receiving sensor S 6 Ordinate of (2), receiving sensor S 7 Has a longitudinal coordinate greater than that of the receiving sensor S 8 The ordinate of (a); then in step 5, rejecting the damage artifact existing in the possible damage point coordinates according to the time difference of the damage characteristic signal and the relative position of the receiving sensor comprises:
step 5.1: determination of Δ t N12 Magnitude relation with 0, if Δ t N12 If less than 0, go to step 5.2, if Δ t N12 If greater than 0, go to step 5.3, if Δ t N12 Equal to 0, the damage is located at the receiving sensor S 1 And a receiving sensor S 2 On the perpendicular bisector of the connecting line;
and step 5.2: at this time, the receiving sensor S 1 Prior to receiving the sensor S 2 Receiving a signal indicating that the lesion site is located in the sensor cluster S 1 S 2 S 3 Upper, then removing the straight line L N1 At sensor cluster S 1 S 2 S 3 A lower portion;
step 5.3: at this time, the receiving sensor S 2 Prior to receiving the sensor S 1 Receiving a signal indicating that the lesion site is located in the sensor cluster S 1 S 2 S 3 Below, then eliminate the straight line L N1 At sensor cluster S 1 S 2 S 3 An upper portion;
step 5.4: determination of Δ t N65 Magnitude relation with 0, if Δ t N65 If less than 0, go to step 5.5, if Δ t N65 If greater than 0, go to step 5.6, if Δ t N65 Equal to 0, the damage is located at the receiving sensor S 6 And a receiving sensor S 5 On the perpendicular bisector of the connecting line;
step 5.5: at this time, the receiving sensor S 6 Prior to receiving the sensor S 5 Receiving a signal indicating that the lesion site is located in the sensor cluster S 4 S 5 S 6 Below, then the straight line L is eliminated N2 At sensor cluster S 4 S 5 S 6 An upper portion;
step 5.6: at this time, the receiving sensor S 5 Prior to receiving the sensor S 6 Receiving a signal indicating that the damage location is in the sensor cluster S 4 S 5 S 6 Upper, then removing the straight line L N2 At sensor cluster S 4 S 5 S 6 A lower portion;
step 5.7: determination of Δ t N78 Magnitude relation with 0, if Δ t N78 If less than 0, go to step 5.8, if Δ t N78 If greater than 0, go to step 5.9, if Δ t N78 Equal to 0, the damage is located at the receiving sensor S 7 And a receiving sensor S 8 On the perpendicular bisector of the connecting line;
step 5.8: at this time, the receiving sensor S 7 Prior to receiving the sensor S 8 Receiving a signal indicating that the lesion site is located in the sensor cluster S 7 S 8 S 9 Upper, then removing the straight line L N3 At sensor cluster S 7 S 8 S 9 A lower portion;
step 5.9: at this time, the receiving sensor S 8 Prior to receiving sensor S 7 Receiving a signal indicating that the damage location is in the sensor cluster S 7 S 8 S 9 Below, then the straight line L is eliminated N3 At sensor cluster S 7 S 8 S 9 The upper part.
In some embodiments, in step 6, performing damage point relative probability density imaging by a nuclear density estimation method, and screening damage points satisfying a threshold to obtain a damage location includes:
setting step 5 to remove damage artifacts existing in possible damage point coordinates, and then leaving m possible damage coordinate points u v ，u v Is expressed as (x) v ，y v ) Wherein v =1, 2, \8230:;
step 6.1: the density function expression for the kernel density estimate for each possible lesion coordinate point is as follows:
Figure BDA0003832602440000051
in the formula (I), the compound is shown in the specification,
Figure BDA0003832602440000052
is a kernel function, h is a positive number;
step 6.2: obtaining a relative probability density graph of the damage coordinate point through a density function expression of kernel density estimation;
step 6.3: setting a threshold value of the relative probability density, acquiring a region of which the relative probability density is greater than the threshold value in the relative probability density graph, and regarding the damage points in the region meeting the threshold value requirement as real damage points;
step 6.4: and averaging the coordinates of the real damage points in each region meeting the threshold requirement to obtain the predicted position of the damage point.
Compared with the prior art, the technical scheme provided by the disclosure has the following beneficial effects: the acoustic velocity plate can be simultaneously suitable for an acoustic velocity isotropic plate and an acoustic velocity anisotropic plate; the nonlinear equation does not need to be solved, the damage positioning speed is high, the calculated amount is small, and the efficiency of damage positioning is improved; the method has the advantages that the known material properties are not needed, the damage positioning of the plate-shaped material with unknown material can be realized, the application range of the positioning method is expanded, the damage and the potential threat of the plate-shaped material can be found in time, the safety of the structure is further ensured, and the method has good application prospects.
In addition, in the technical solutions of the present disclosure, the technical solutions can be implemented by adopting conventional means in the art, unless otherwise specified.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present disclosure, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a flowchart of a method for positioning multiple damages of a plate-shaped material based on an L-shaped sensor cluster according to an embodiment of the present disclosure.
FIG. 2 is a set of L-shaped sensor clusters S provided in an embodiment of the present disclosure 1 S 2 S 3 Schematic representation of (a).
Fig. 3 is a schematic diagram of a possible damage point after step 4 according to an embodiment of the disclosure.
Fig. 4 is a schematic diagram of a possible damage point after removing the damage artifact through step 5 according to an embodiment of the disclosure.
Fig. 5 is a graph of relative probability density of damage coordinate points according to an embodiment of the disclosure.
Fig. 6 is a schematic diagram of a predicted position of a finally obtained damage point according to an embodiment of the disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without inventive step, are intended to be within the scope of the present disclosure.
Example (b):
referring to the specification and the accompanying drawings 1, a method for positioning multiple damages of a plate-shaped material based on an L-shaped sensor cluster, provided by an embodiment of the disclosure, is shown, and includes the following steps:
step 1: an L-shaped sensor cluster array is arranged on a plate-shaped material to be detected, the L-shaped sensor cluster array comprises three groups of L-shaped sensor clusters, each group of L-shaped sensor clusters comprises three receiving sensors, and an excitation sensor is arranged at the center of the plate-shaped material to be detected.
In an alternative embodiment, arranging an array of L-shaped sensor clusters on a sheet of material to be measured may comprise:
step 1.1: establishing a coordinate system, taking the center of the plate-shaped material to be detected as an original point, taking the long edge of the plate-shaped material to be detected as an x axis, and taking the short edge of the plate-shaped material to be detected as a y axis;
step 1.2: arranging an excitation sensor at the origin of the coordinate system, and recording the excitation sensor as O;
step 1.3: a plurality of groups of L-shaped sensor clusters are arranged in a coordinate system, each group of L-shaped sensor clusters comprises three receiving sensors, the three receiving sensors in each group of L-shaped sensor clusters are distributed in an isosceles right triangle shape, the distance between two adjacent receiving sensors on a right-angle side is d, and the receiving sensors are marked as S i (i =1, 2, 3 \8230; 9), i is the number of the receiving sensor, and the receiving sensor coordinate is expressed as (p) i ，q i )。
In this embodiment, in step 1.3, the setting of the plurality of sets of L-shaped sensor clusters in the coordinate system specifically includes, optionally, three quadrants of the coordinate system, and a set of L-shaped sensor clusters is set in each quadrant. Therefore, when two or more groups of L-shaped sensor clusters are arranged in the same quadrant to cause subsequent calculation, the condition that the slope of the straight line is close to the large positioning error caused by the subsequent calculation is avoided, the positioning error is reduced, and the positioning result is more accurate.
In an alternative embodiment, the right-angle sides of the isosceles right triangle formed by the three receiving sensors in each group of the L-shaped sensor clusters are arranged in parallel with the coordinate axis. Therefore, the linear equation in the subsequent calculation is more convenient to obtain, the complexity of calculation is reduced, and the damage positioning efficiency is improved.
Specifically, piezoelectric sensors are used for both the excitation sensor and the reception sensor.
Referring to FIG. 2 of the specification, FIG. 2 of the specification shows a set of L-shaped sensor clusters S 1 S 2 S 3 Wherein S is 1 、S 2 And S 3 Each representing a receiving sensor, S 1 、S 2 And S 3 Form an isosceles right triangle, wherein S 2 Is positioned at the right-angle vertex of the isosceles right triangle.
Step 2: and obtaining damage characteristic signals of each receiving sensor in the L-shaped sensor cluster array.
In an alternative embodiment, obtaining the lesion signature signal for each receiving sensor in the array of L-shaped sensor clusters may comprise:
step 2.1: applying an excitation signal to the excitation sensor under the healthy state of the plate-shaped material, and sequentially collecting the base line signals fed back by the receiving sensors and recording the base line signals as
Figure BDA0003832602440000081
Step 2.2: keeping the test condition unchanged, applying the same excitation signal as the step 2.1 to the excitation sensor in the damage state of the plate-shaped material, and sequentially collecting detection signals fed back by each receiving sensor, and recording the detection signals as
Figure BDA0003832602440000082
Step 2.3: obtaining a lesion signature of
Figure BDA0003832602440000083
Specifically, a 5-cycle 150kHz sine signal of a hamming window may be used as the excitation signal.
Thus, when an excitation signal is applied to the excitation sensor, if the plate-shaped material is damaged, the damage acts on the excitation signal to generate a damage characteristic signal, and the damage characteristic signal is calculated from the baseline signal of the healthy state and the detection signal of the damaged state.
And step 3: and calculating the time difference of the damage characteristic signals between two adjacent receiving sensors.
Specifically, three groups of L-shaped sensor clusters are respectively set as a sensor cluster S 1 S 2 S 3 Sensor cluster S 4 S 5 S 6 And a sensor cluster S 7 S 8 S 9 In which the sensor S is received 2 、S 5 And S 8 The receiving sensors at the right-angle vertex of the isosceles right triangle are respectively connected with two adjacent right-angle sides in each group of L-shaped sensor clustersCarrying out cross-correlation processing on the damage characteristic signals recorded by the receiving sensors, calculating the time difference of the damage characteristic signals between two adjacent receiving sensors on the right-angle edge, and recording the time difference of the damage characteristic signals as delta t ij (i＝1、3、4、6、7、9，j＝2、5、8，|i-j|≤1)。
And 4, step 4: and determining possible damage point coordinates according to the damage characteristic signal time difference.
In particular, the number of damage signatures obtained on each receiving sensor should be identical, i.e. when there are n damages in the sheet material, n damage signatures should be obtained on each receiving sensor.
When the damage characteristic signals obtained from the receiving sensor are smaller than n, the L-shaped sensor cluster where the current receiving sensor is located is determined to be located on the perpendicular bisector of the two damages, at the moment, the two damage characteristic signals are overlapped, and the L-shaped sensor cluster needs to be moved to obtain the damage characteristic signals again.
When the number of the damage characteristic signals obtained on each receiving sensor is n, judging that n damages exist in the plate-shaped material at the moment. The step 4 of determining possible coordinates of the damage point according to the time difference of the damage characteristic signal may specifically include:
step 4.1: respectively determining a linear equation where a connection line of each damage and a receiving sensor on a right-angle vertex in the three L-shaped sensor clusters is located;
step 4.2: and solving the three linear equations corresponding to each damage pairwise in a simultaneous manner, wherein each damage corresponds to three solutions, namely each damage has three possible damage point coordinates.
In an alternative embodiment, in step 4.1, the equation of the straight line where each lesion is connected with the receiving sensors at the right-angled vertices of the three L-shaped sensor clusters respectively includes:
let the coordinate of the damage N in the plate-like material be (x) N ，y N ) Wherein N =1, 2, \8230, N, three groups of L-shaped sensor clusters are respectively marked as sensor cluster S 1 S 2 S 3 Sensor cluster S 4 S 5 S 6 And a sensor cluster S 7 S 8 S 9 Damage N and sensorS 2 The equation of the line where the connecting line is located is recorded as a straight line L N1 Damage N and sensor S 5 The equation of the straight line where the connecting line is located is expressed as a straight line L N2 Damage N and sensor S 8 The equation of the line where the connecting line is located is recorded as a straight line L N3 ；
Step 4.1.1: calculating a straight line L N1 Angle alpha to the x-axis N1 ，α N1 The expression of (a) is as follows:
Figure BDA0003832602440000091
specifically, in each L-shaped sensor cluster, the distance d between two adjacent receiving sensors on the right-angle side should be as small as possible when the accuracy of the device allows, so as to enlarge the detection area and improve the measurement accuracy and precision. For example, at 150kHz excitation signal, d can be set to 2cm. Because the distance d between two adjacent receiving sensors on the right-angle side of the L-shaped sensor cluster is far smaller than the distance from the damage N to the L-shaped sensor cluster, the slope of the damage N is approximately the same as that of a straight line where the connecting line of each receiving sensor in the same L-shaped sensor cluster is located, and the calculation complexity is reduced.
When the sound wave reaches each receiving sensor in the same L-shaped sensor cluster, the sound wave can be regarded as a plane wave front, so that the wave speed c (alpha) of the sound source to each receiving sensor in the same L-shaped sensor cluster in the direction alpha can be regarded as approximately the same no matter the material is isotropic or anisotropic.
Step 4.1.2: calculating the time difference Deltat of the damage characteristic signal N12 And Δ t N32 ，Δt N12 And Δ t N32 The expression of (a) is as follows:
Figure BDA0003832602440000092
Figure BDA0003832602440000093
in the formula,. DELTA.t N12 Receiving sensor S indicating correspondence of damage N 1 And a receiving sensor S 2 Difference in signal time between the impairment signatures, Δ t N32 Receiving sensor S indicating correspondence of damage N 2 And a receiving sensor S 3 The time difference of the damage characteristic signal between, d represents the receiving sensor S 2 And a receiving sensor S 3 And a receiving sensor S 1 Distance therebetween, receiving the sensor S 2 At the right angle vertex of the L-shaped sensor cluster in which it is located, c (α) N1 ) Indicating the sound source in the direction alpha N1 The wave velocity of (1);
step 4.1.3: substituting the expression (2) and the expression (3) into the expression (1) to obtain alpha N1 The expression of (c) is as follows:
Figure BDA0003832602440000101
step 4.1.4: obtaining damage N and receiving sensor S 2 Straight line L of connecting line N1 Slope k of N1 Slope k N1 The expression of (a) is as follows:
Figure BDA0003832602440000102
step 4.1.5: to obtain a straight line L N1 The equation of (a) is as follows:
Figure BDA0003832602440000103
step 4.1.6: according to the same principle as the receiving sensor S 5 And a receiving sensor S 8 Can obtain a straight line L N2 And a straight line L N3 The equation of (a) is as follows:
Figure BDA0003832602440000104
Figure BDA0003832602440000105
referring to fig. 3 of the specification, a schematic diagram of possible damage points obtained after step 4 is shown.
And 5: and removing damage artifacts existing in possible damage point coordinates according to the damage characteristic signal time difference and the relative position of the receiving sensor.
Description of the drawings fig. 3 shows a schematic representation of the position of each receiving sensor in an L-shaped sensor cluster array consisting of three groups of L-shaped sensor clusters, within a coordinate system, receiving sensors S 1 Has a longitudinal coordinate greater than that of the receiving sensor S 2 Ordinate of (2), receiving sensor S 5 Has a greater ordinate than the receiving sensor S 6 Ordinate of (2), receiving sensor S 7 Has a greater ordinate than the receiving sensor S 8 The ordinate of (a); then, for the 3 × n possible coordinates of the damage points obtained in step 4, removing the existing damage artifacts according to the time difference of the damage feature signals and the relative position of the receiving sensor, which may specifically include the following steps:
step 5.1: determination of Δ t N12 Magnitude relation with 0, if Δ t N12 If less than 0, go to step 5.2, if Δ t N12 If greater than 0, go to step 5.3, if Δ t N12 Equal to 0, the damage is located at the receiving sensor S 1 And a receiving sensor S 2 On the perpendicular bisector of the connecting line;
and step 5.2: at this time, the receiving sensor S 1 Prior to receiving the sensor S 2 Receiving a signal indicating that the damage location is in the sensor cluster S 1 S 2 S 3 Upper, then removing the straight line L N1 At sensor cluster S 1 S 2 S 3 A lower portion;
step 5.3: at this time, the receiving sensor S 2 Prior to receiving the sensor S 1 Receiving a signal indicating that the lesion site is located in the sensor cluster S 1 S 2 S 3 Below, then the straight line L is eliminated N1 At sensor cluster S 1 S 2 S 3 An upper portion;
step 5.4: determination of Δ t N65 And 0 ofIf Δ t is large or small N65 If less than 0, go to step 5.5, if Δ t N65 If greater than 0, go to step 5.6, if Δ t N65 Equal to 0, the damage is located at the receiving sensor S 6 And a receiving sensor S 5 On the perpendicular bisector of the connecting line;
step 5.5: at this time, the receiving sensor S 6 Prior to receiving sensor S 5 Receiving a signal indicating that the lesion site is located in the sensor cluster S 4 S 5 S 6 Below, then the straight line L is eliminated N2 At sensor cluster S 4 S 5 S 6 An upper portion;
step 5.6: at this time, the receiving sensor S 5 Prior to receiving sensor S 6 Receiving a signal indicating that the lesion site is located in the sensor cluster S 4 S 5 S 6 Upper, rejecting straight line L N2 At sensor cluster S 4 S 5 S 6 A lower portion;
step 5.7: determination of Δ t N78 Magnitude relation with 0, if Δ t N78 If less than 0, go to step 5.8, if Δ t N78 If greater than 0, go to step 5.9, if Δ t N78 Equal to 0, the damage is located at the receiving sensor S 7 And a receiving sensor S 8 On the perpendicular bisector of the connecting line;
step 5.8: at this time, the receiving sensor S 7 Prior to receiving sensor S 8 Receiving a signal indicating that the lesion site is located in the sensor cluster S 7 S 8 S 9 Upper, then removing the straight line L N3 At sensor cluster S 7 S 8 S 9 A lower portion;
step 5.9: at this time, the receiving sensor S 8 Prior to receiving sensor S 7 Receiving a signal indicating that the lesion site is located in the sensor cluster S 7 S 8 S 9 Below, then the straight line L is eliminated N3 At sensor cluster S 7 S 8 S 9 The upper part.
Referring to the description of the drawings, fig. 4 shows a schematic diagram of possible lesion sites obtained after removing the lesion artifact through step 5.
And 6: and (4) performing relative probability density imaging on the damage points by a nuclear density estimation method, and screening the damage points meeting the threshold value to obtain the damage positions.
Specifically, after eliminating the damage artifact existing in the possible damage point coordinates in the step 5, m possible damage coordinate points u are left v ，u v Is represented by (x) v ，y v ) Wherein v =1, 2, \8230:;
in step 6, performing relative probability density imaging on the damage points by using a nuclear density estimation method, and screening the damage points meeting the threshold value to obtain the damage position specifically may include:
step 6.1: the density function expression for the kernel density estimate corresponding to each possible lesion coordinate point is as follows:
Figure BDA0003832602440000121
in the formula (I), the compound is shown in the specification,
Figure BDA0003832602440000122
is a kernel function and h is a positive number.
Step 6.2: and obtaining a relative probability density imaging graph of the damage point through a density function expression of kernel density estimation.
Step 6.3: and setting a threshold value of the relative probability density, acquiring a region of which the relative probability density is greater than the threshold value in the relative probability density graph, and regarding the damage points in the region meeting the threshold value requirement as real damage points.
Since real damage points are concentrated at the actual damage position, and damage artifacts are relatively scattered, the relative probability density near the actual damage position in the relative probability density imaging map is large, and the relative probability density of the damage artifacts is small, so when the relative probability density of a certain region in the map is above a threshold, the damage points in the region can be regarded as the real damage points.
In an alternative embodiment, the threshold value for the relative probability density may be set to 0.7. Therefore, the error is small when the real damage point is obtained.
Step 6.4: and averaging the coordinates of the real damage points in each region meeting the threshold requirement to obtain the predicted position of the damage point, namely positioning the damage point.
Referring to the specification, fig. 5, a graph of relative probability density imaging of damage coordinate points is shown; referring to the specification, fig. 6 shows a schematic diagram of the predicted location of the resulting lesion. In the description fig. 5 and the description fig. 6, the five-pointed star indicates a possible damage point, and the circle indicates an area meeting the threshold requirement.
The plate-shaped material multi-damage positioning method based on the L-shaped sensor cluster can be simultaneously suitable for a sound velocity isotropic flat plate and a sound velocity anisotropic flat plate; a nonlinear equation does not need to be solved, the damage positioning speed is high, the calculated amount is small, and the efficiency of damage positioning is improved; the method has the advantages that the known material properties are not needed, the damage positioning of the plate-shaped material with unknown material can be realized, the application range of the positioning method is expanded, the damage and the potential threat of the plate-shaped material can be found in time, the safety of the structure is further ensured, and the method has good application prospects.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solutions of the present disclosure, not to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.

Claims (10)

1. A plate-shaped material multi-damage positioning method based on an L-shaped sensor cluster is characterized by comprising the following steps:
step 1: arranging an L-shaped sensor cluster array on a plate-shaped material to be detected, wherein the L-shaped sensor cluster array comprises three groups of L-shaped sensor clusters, each group of L-shaped sensor clusters comprises three receiving sensors, and an excitation sensor is arranged at the center of the plate-shaped material to be detected;
and 2, step: obtaining a damage characteristic signal of each receiving sensor in the L-shaped sensor cluster array;
and 3, step 3: calculating the time difference of the damage characteristic signals between two adjacent receiving sensors;
and 4, step 4: determining possible damage point coordinates according to the damage characteristic signal time difference;
and 5: removing damage artifacts existing in possible damage point coordinates according to the damage characteristic signal time difference and the relative position of the receiving sensor;
and 6: and (4) performing relative probability density imaging on the damage points by a nuclear density estimation method, and screening the damage points meeting the threshold value to obtain the damage positions.
2. The method for positioning multiple damages of plate-shaped material based on L-shaped sensor clusters according to claim 1, wherein in step 1, the arranging of the L-shaped sensor cluster array on the plate-shaped material to be measured comprises:
step 1.1: establishing a coordinate system, taking the center of the plate-shaped material to be detected as an original point, taking the long edge of the plate-shaped material to be detected as an x axis, and taking the short edge of the plate-shaped material to be detected as a y axis;
step 1.2: arranging an excitation sensor at the origin of the coordinate system, and recording the excitation sensor as O;
step 1.3: a plurality of groups of L-shaped sensor clusters are arranged in a coordinate system, each group of L-shaped sensor clusters comprises three receiving sensors, the three receiving sensors in each group of L-shaped sensor clusters are distributed in an isosceles right triangle shape, the distance between the two receiving sensors on the right-angle side is d, and the receiving sensors are marked as S i (i =1, 2, 3 \ 8230; \82309; 9), receiving a sensor coordinate notation (p) i ，q i )。
3. The method for positioning multiple damages of plate-shaped material based on L-shaped sensor clusters according to claim 2, wherein in step 1.3, the step of arranging multiple sets of L-shaped sensor clusters in the coordinate system specifically comprises, optionally, three quadrants of the coordinate system, and one set of L-shaped sensor clusters is arranged in each quadrant.
4. The method for positioning multiple damages to plate-shaped material based on L-shaped sensor clusters as claimed in claim 2, wherein in step 1.3, the right-angle sides of the isosceles right triangle formed by the three receiving sensors in each group of L-shaped sensor clusters are arranged in parallel with the coordinate axis.
5. The L-shaped sensor cluster-based plate-shaped material multi-damage positioning method according to claim 1, wherein in the step 2, obtaining damage characteristic signals of each receiving sensor in the L-shaped sensor cluster array comprises:
step 2.1: applying an excitation signal to the excitation sensor under the healthy state of the plate-shaped material, and sequentially collecting the base line signals fed back by the receiving sensors and recording the base line signals as
Figure FDA0003832602430000021
Step 2.2: in the damage state of the plate-shaped material, the same excitation signal as the step 2.1 is applied to the excitation sensor, and detection signals fed back by all the receiving sensors are sequentially collected and recorded as
Figure FDA0003832602430000022
Figure FDA0003832602430000023
Step 2.3: obtaining a signal characteristic of the lesion as
Figure FDA0003832602430000024
6. The method for positioning multiple damages of plate-shaped material based on L-shaped sensor cluster as claimed in claim 4, wherein in step 3, the calculating the difference of the damage characteristic signal time between two adjacent receiving sensors comprises:
three groups of L-shaped sensor clusters are respectively set as a sensor cluster S 1 S 2 S 3 A sensor cluster S 4 S 5 S 6 And transmissionSensor cluster S 7 S 8 S 9 In which the sensor S is received 2 、S 5 And S 8 The receiving sensor is arranged at the right-angle vertex of the isosceles right triangle;
respectively carrying out cross-correlation processing on the damage characteristic signals recorded by two adjacent receiving sensors on the right-angle side of each group of L-shaped sensor clusters, calculating the time difference of the damage characteristic signals between the two adjacent receiving sensors on the right-angle side, and recording the time difference of the damage characteristic signals as delta t ij (i＝1、3、4、6、7、9，j＝2、5、8，|i-j|≤1)。
7. The method for positioning multiple damages of plate-shaped material based on L-shaped sensor cluster as claimed in claim 6, wherein in step 4, the determining the possible damage point coordinates according to the damage characteristic signal time difference comprises:
when the number of the damage characteristic signals obtained from each receiving sensor is n, judging that n damages exist in the plate-shaped material at the moment;
step 4.1: respectively determining a linear equation where a connection line of each damage and a receiving sensor on a right-angle vertex in the three L-shaped sensor clusters is located;
and 4.2: and solving the three linear equations corresponding to each damage pairwise in a simultaneous manner, wherein each damage corresponds to three solutions, namely each damage has three possible damage point coordinates.
8. The method for positioning multiple damages of plate-shaped material based on L-shaped sensor cluster according to claim 7, wherein in step 4.1, respectively determining the linear equation of the connection line of each damage and the receiving sensors at the right-angle vertexes of the three L-shaped sensor clusters comprises:
let the coordinate of the damage N in the plate-like material be (x) N ，y N ) Wherein N =1, 2, 8230, N, three groups of L-shaped sensor clusters are respectively marked as sensor clusters S 1 S 2 S 3 A sensor cluster S 4 S 5 S 6 And a sensor cluster S 7 S 8 S 9 Damage N and sensor S 2 The equation of the line where the connecting line is located is recorded asStraight line L N1 Damage N and sensor S 5 The equation of the line where the connecting line is located is recorded as a straight line L N2 Damage N and sensor S 8 The equation of the straight line where the connecting line is located is expressed as a straight line L N3 ；
Step 4.1.1: calculating a straight line L N1 Angle alpha to the x-axis N1 ，α N1 The expression of (a) is as follows:
Figure FDA0003832602430000031
step 4.1.2: calculating the time difference Deltat of the damage characteristic signal N12 And Δ t N32 ，Δt N12 And Δ t N32 The expression of (a) is as follows:
Figure FDA0003832602430000032
Figure FDA0003832602430000033
in the formula,. DELTA.t N12 Receiving sensor S indicating correspondence of damage N 1 And a receiving sensor S 2 Difference in signal time between the impairment signatures, Δ t N32 Receiving sensor S indicating correspondence of damage N 2 And a receiving sensor S 3 The time difference of the damage characteristic signal between, d represents the receiving sensor S 2 And a receiving sensor S 3 And a receiving sensor S 1 Distance between, receiving sensor S 2 At the right-angled vertex of the L-shaped sensor cluster in which it is located, c (α) N1 ) Indicating the direction alpha of the sound source N1 The wave velocity of (3);
step 4.1.3: substituting the expression (2) and the expression (3) into the expression (1) to obtain alpha N1 The expression of (a) is as follows:
Figure FDA0003832602430000034
step 4.1.4: obtaining damage N and receiving sensor S 2 Straight line L of connecting line N1 Slope k of N1 Slope k N1 The expression of (a) is as follows:
Figure FDA0003832602430000035
step 4.1.5: to obtain a straight line L N1 The equation of (a) is as follows:
Figure FDA0003832602430000041
step 4.1.6: obtaining the straight line L by the same method N2 And a straight line L N3 The equation of (a) is as follows:
Figure FDA0003832602430000042
Figure FDA0003832602430000043
9. the method for positioning multiple damages of plate-shaped material based on L-shaped sensor cluster as claimed in claim 8, wherein the receiving sensor S is arranged in a coordinate system 1 Has a greater ordinate than the receiving sensor S 2 Ordinate of (c), receiving sensor S 5 Has a longitudinal coordinate greater than that of the receiving sensor S 6 Ordinate of (2), receiving sensor S 7 Has a greater ordinate than the receiving sensor S 8 The ordinate of (a); then in step 5, said rejecting damage artifacts existing in the coordinates of the possible damage points according to the time difference of the damage characteristic signals and the relative position of the receiving sensor includes:
step 5.1: determination of Δ t N12 Magnitude relation with 0, if Δ t N12 If less than 0, go to step 5.2, if Δ t N12 If greater than 0, go to step 5.3, if Δ t N12 Equal to 0, the damage is located at the receiving sensor S 1 And a receiving sensor S 2 On the perpendicular bisector of the connecting line;
and step 5.2: at this time, the receiving sensor S 1 Prior to receiving sensor S 2 Receiving a signal indicating that the damage location is in the sensor cluster S 1 S 2 S 3 Upper, rejecting straight line L N1 At sensor cluster S 1 S 2 S 3 A lower portion;
step 5.3: at this time, the receiving sensor S 2 Prior to receiving sensor S 1 Receiving a signal indicating that the damage location is in the sensor cluster S 1 S 2 S 3 Below, then eliminate the straight line L N1 At sensor cluster S 1 S 2 S 3 An upper portion;
step 5.4: determination of Δ t N65 Magnitude relation with 0, if Δ t N65 If less than 0, go to step 5.5, if Δ t N65 If greater than 0, go to step 5.6, if Δ t N65 Equal to 0, the damage is located at the receiving sensor S 6 And a receiving sensor S 5 On the perpendicular bisector of the connecting line;
step 5.5: at this time, the receiving sensor S 6 Prior to receiving the sensor S 5 Receiving a signal indicating that the lesion site is located in the sensor cluster S 4 S 5 S 6 Below, then the straight line L is eliminated N2 At sensor cluster S 4 S 5 S 6 An upper portion;
step 5.6: at this time, the receiving sensor S 5 Prior to receiving the sensor S 6 Receiving a signal indicating that the lesion site is located in the sensor cluster S 4 S 5 S 6 Upper, rejecting straight line L N2 At sensor cluster S 4 S 5 S 6 A lower portion;
step 5.7: determination of Δ t N78 Magnitude relation with 0, if Δ t N78 If less than 0, go to step 5.8, if Δ t N78 If greater than 0, go to step 5.9, if Δ t N78 Equal to 0, the damage is located at the receiving sensorS 7 And a receiving sensor S 8 On the perpendicular bisector of the connecting line;
step 5.8: at this time, the receiving sensor S 7 Prior to receiving sensor S 8 Receiving a signal indicating that the damage location is in the sensor cluster S 7 S 8 S 9 Upper, rejecting straight line L N3 At sensor cluster S 7 S 8 S 9 A lower portion;
step 5.9: at this time, the receiving sensor S 8 Prior to receiving the sensor S 7 Receiving a signal indicating that the damage location is in the sensor cluster S 7 S 8 S 9 Below, then the straight line L is eliminated N3 At sensor cluster S 7 S 8 S 9 The upper part.
10. The method for positioning multiple damages to plate-shaped material based on L-shaped sensor cluster according to claim 8, wherein in step 6, damage point relative probability density imaging is performed through a nuclear density estimation method, and screening damage points satisfying a threshold value to obtain a damage position comprises:
setting step 5 to remove damage artifacts existing in possible damage point coordinates, and then leaving m possible damage coordinate points u v ，u v Is represented by (x) v ，y v ) Wherein v =1, 2, \8230 \8230m;
step 6.1: the density function expression for the kernel density estimate corresponding to each possible lesion coordinate point is as follows:
Figure FDA0003832602430000051
in the formula (I), the compound is shown in the specification,
Figure FDA0003832602430000052
is a kernel function, h is a positive number;
step 6.2: obtaining a relative probability density graph of the damage coordinate point through a density function expression of kernel density estimation;
step 6.3: setting a threshold value of the relative probability density, acquiring a region of which the relative probability density is greater than the threshold value in the relative probability density graph, and regarding the damage points in the region meeting the threshold value requirement as real damage points;
step 6.4: and averaging the coordinates of the real damage points in each area meeting the threshold requirement to obtain the predicted position of the damage point.
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