CN114813962A - Acoustic emission source positioning method based on GCLM-grid search algorithm - Google Patents

Acoustic emission source positioning method based on GCLM-grid search algorithm Download PDF

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CN114813962A
CN114813962A CN202210387289.1A CN202210387289A CN114813962A CN 114813962 A CN114813962 A CN 114813962A CN 202210387289 A CN202210387289 A CN 202210387289A CN 114813962 A CN114813962 A CN 114813962A
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acoustic emission
emission source
gclm
iteration
positioning
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代树红
程冠军
王闯
张凯
冯俊鹏
安志奎
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Liaoning Technical 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
    • G01N29/14—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 using acoustic emission techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/18—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using ultrasonic, sonic, or infrasonic waves
    • G01S5/22—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements

Abstract

The invention discloses an acoustic emission source positioning method based on a GCLM-grid search algorithm. The method comprises the steps of firstly arranging a plurality of sensors around an acoustic emission source in a three-dimensional space, then constructing a target function by utilizing time difference between a main sensor and each secondary sensor, carrying out iterative solution on the target function through a GCLM algorithm to obtain an initial positioning result, taking the result as a central point coordinate, and calculating an optimal positioning result in a region adjacent to the point by adopting a grid search method, so that the dependence of the iterative algorithm on an initial value can be solved, the target function is prevented from falling into a local extreme value, and the accurate positioning of the acoustic emission source under the influence of factors such as an iterative initial value and a time measurement error is realized.

Description

Acoustic emission source positioning method based on GCLM-grid search algorithm
Technical Field
The invention belongs to the technical field of nondestructive testing, and particularly relates to an acoustic emission source positioning method based on a GCLM-grid search algorithm.
Background
In recent years, serious coal mine disaster problems caused by deformation and damage of coal and rock due to rock excavation are more prominent, the mine disasters have great threats to life safety of workers and safety production of mines, and special phenomena are generated before the disasters occur.
At present, acoustic emission is a good tool for researching the deformation damage evolution process of the quasi-brittle material, because the acoustic emission can continuously monitor the generation and the expansion of micro-cracks in the quasi-brittle material in real time and realize the positioning of the damage position, the acoustic emission is widely applied to the research of the quasi-brittle materials such as coal rock, concrete and the like. Therefore, the method can accurately monitor the rock deformation damage evolution process and plays an important role in understanding the occurrence mechanism of the mine coal and rock disasters. A plurality of positioning algorithms are provided in the field of acoustic emission positioning, such as a classical least square method, a simplex method, a Geiger algorithm, a Newton iteration method and the like, but the positioning algorithms are sensitive to selection of iteration initial values, and the processing efficiency and the quality of positioning results depend on the initial values.
Disclosure of Invention
The invention provides an acoustic emission source positioning method based on a GCLM-grid search algorithm, which monitors the microscopic change of the internal structure of a material in real time to provide powerful data support for coal and rock dynamic disaster monitoring and early warning and coal mine safety production so as to overcome the defects of the existing positioning algorithm.
In order to achieve the above technical objects, the present invention provides the following technical solutions:
an acoustic emission source positioning method based on a GCLM-grid search algorithm comprises the following steps:
step 1, arranging M sensors for receiving acoustic emission signals emitted by an acoustic emission source for the acoustic emission source on a three-dimensional space structure; one of the sensors is determined as a main sensor, and the other sensors are determined as secondary sensors; a rectangular coordinate system is established in the three-dimensional space, so that the coordinates of the sound emission source are (x, y, z), and the coordinates of the main sensor are (x) 1 ，y 1 ，z 1 ) The coordinates of each sub-sensor are (x) i ，y i ，z i ) (i is 2, 3 … M, M is a positive integer, and M is more than or equal to 4);
step 2, obtaining the time difference t of the signals received by the main sensor and each secondary sensor through a signal processing method i1 Establishing a measurement vectorR；
Step 3, representing the position of the sound emission source and the time of the sound emission signal from the sound emission source to the main sensor by using the state vector X; define state vector X ═ (X, y, z, T) T Wherein (x, y, z) is the coordinates of the acoustic emission source and T is the time for the acoustic emission signal to reach the primary sensor from the acoustic emission source;
step 4, converting the acoustic emission positioning problem into an optimization solving problem, and constructing an objective function to iteratively solve a state vector X, wherein:
the time difference positioning equation set is expressed as:
f(x,y,z,T)＝(x-x i ) 2 +(y-y i ) 2 +(z-z i ) 2 -v 2 (T+t i1 ) 2 ＝0 (1)
the target function expression is:
Figure BDA0003593541580000011
in the formula: f ═ F 1 ，f 2 ，f 3 …f M ] T (x, y, z) is the AE source position; v is the P wave velocity; t is the time of the acoustic emission signal from the acoustic emission source to the primary sensor; t is t i1 Representing the time difference of the acoustic emission signal from the acoustic emission source to the primary sensor and each secondary sensor;
and 5, carrying out iterative solution by adopting a GCLM-grid search algorithm, calculating the optimal solution of the state vector X, and taking the optimal solution of the state vector X which is iterated for the last time and meets the iteration times or the iteration termination condition as the position of the acoustic emission source.
According to the technical scheme, compared with the prior art, the invention has the following advantages:
when the acoustic emission source is positioned, the influence of iteration initial value selection and time measurement errors is considered, the method converts the positioning of the acoustic emission source into an optimization solving problem, establishes a time difference equation set, further constructs an objective function, takes the wave speed and the time difference of signals received by the primary sensor and each secondary sensor as known measurement quantities, and takes the position of the acoustic emission source and the time of the acoustic emission signal from the acoustic emission source to the primary sensor as state variables. Due to the lack of accurate solutions, iterative solution is carried out on unknown state variables by adopting a GCLM-grid search algorithm, and finally global optimal positioning is realized.
Drawings
FIG. 1 is a schematic illustration of three-dimensional spatial acoustic emission source positioning;
FIG. 2 is a three-dimensional spatial acoustic emission sensor position map;
FIG. 3 shows a sensor S 1 And S 2 Received point of lead break P 1 A waveform map of the acoustic emission signal;
fig. 4 is a plot of absolute error for positioning of a simulated acoustic emission source.
Detailed Description
The invention is further described with reference to the accompanying drawings and embodiments:
fig. 1 is a schematic diagram of positioning of an acoustic emission source in three-dimensional space.
The invention relates to an acoustic emission source positioning method based on a GCLM-grid search algorithm, which is used for positioning an acoustic emission source under the influence of iteration initial value selection and time measurement errors and comprises the following steps:
step 1, arranging M sensors for receiving acoustic emission signals emitted by an acoustic emission source for the acoustic emission source on a three-dimensional space structure; one of the sensors is determined as a main sensor, and the other sensors are determined as secondary sensors; a rectangular coordinate system is established in the three-dimensional space, so that the coordinates of the sound emission source are (x, y, z), and the coordinates of the main sensor are (x) 1 ，y 1 ，z 1 ) The coordinates of each sub-sensor are (x) i ，y i ，z i ) (i is 2, 3 … M, M is a positive integer, and M is more than or equal to 4);
step 2, obtaining the time difference t of the signals received by the main sensor and each secondary sensor through a signal processing method i1 Establishing a measurement vector R;
step 3, representing the position of the sound emission source and the time of the sound emission signal from the sound emission source to the main sensor by using the state vector X; the state vector X is defined as (X,y，z，T) T wherein (x, y, z) is the coordinates of the acoustic emission source and T is the time for the acoustic emission signal to reach the primary sensor from the acoustic emission source;
step 4, converting the acoustic emission positioning problem into an optimization solving problem, and constructing an objective function to iteratively solve a state vector X, wherein:
the time difference positioning equation set is expressed as:
f(x,y,z,T)＝(x-x i ) 2 +(y-y i ) 2 +(z-z i ) 2 -v 2 (T+t i1 ) 2 ＝0 (3)
the target function expression is:
Figure BDA0003593541580000021
in the formula: f ═ F 1 ，f 2 ，f 3 …f M ] T (x, y, z) is the acoustic emission source location; v is the P wave velocity; t is the time of the acoustic emission signal from the acoustic emission source to the primary sensor; t is t i1 Representing the time difference of the acoustic emission signal from the acoustic emission source to the primary sensor and each secondary sensor;
step 5, adopting a GCLM-grid search algorithm to carry out iterative solution, calculating the optimal solution of the state vector X, and taking the optimal solution of the state vector X which is iterated for the last time and meets the iteration times or the iteration termination condition as the position of the acoustic emission source;
the method for solving the state vector X by adopting the GCLM-grid search algorithm in the step 5 comprises the following steps:
step one, in order to solve the objective function, an iterative solution d of an iterative formula (5) is utilized k To determine the search direction of the true solution, for the approximate solution X k And correcting, wherein the expression is as follows:
Figure BDA0003593541580000022
in the formula: k is the number of iterations; j. the design is a square k Is the ya of the k iterationA comparable matrix; i is an identity matrix; mu.s k Is a regularization parameter; d k Is a correction value of the iterative solution;
step two, utilizing the radius alpha of the confidence domain k To correct the regularization parameter mu k The expression is as follows:
Figure BDA0003593541580000023
step three, the actual decrease amount Ared of the k step iteration k And predicted decrease amount Pred k The expression is as follows:
Ared k ＝||F k || 2 -||F(X k +d k )|| 2 (7)
Pred k ＝||F k || 2 -||F k +J k d k || 2 (8)
step four, the above formula is taken and substituted into the iterative formula (5) to solve d k And r is calculated using equation (9) k The expression is as follows:
r k ＝Ared k /Pred k (9)
wherein: r is k For deciding whether to accept step size d k And adjusting the factor alpha in the iterative process k The size of (d);
step five, solving r k Then, X is solved using the equations (10) and (11) k+1 And alpha k+1 The expression is as follows:
Figure BDA0003593541580000031
Figure BDA0003593541580000032
judging whether an iteration termination condition or a preset iteration frequency is satisfied, and if so, obtaining an iteration solution; otherwise, returning to the step I to continue the circulation until the iteration termination condition is met;
step seven, determining an initial search area by taking an iteration result of the GCLM algorithm as a central point, and dividing the search area into a plurality of grids to form N grid vertexes; and constructing a cost function for each grid vertex, wherein the position of a grid point corresponding to the minimum value of the cost function is the optimal positioning point.
Description of examples
As shown in FIG. 2, the structure to be monitored was a coal sample having dimensions of 30mm by 220mm by 50mm, and 10 sensors, each designated as S, were arranged on the surface area of the test piece 1 -S 10 As listed in table 1.
The method of breaking lead on the coal sample is adopted to simulate the generation of acoustic emission, and 7 acoustic emission sources are totally named as P 1 -P 7 As listed in table 2.
With S 1 The sensor is a main sensor, the other sensors are secondary sensors, when the voltage value monitored by the sensors exceeds a certain threshold value, it is considered that an acoustic emission event is generated, all the sensors start to acquire acoustic emission signals at the same time, and the method is shown in figure 3 as a sensor S 1 And S 2 Received point of lead break P 1 The acoustic emission signal of (c). And processing the acoustic emission signal by using a DB6 wavelet, extracting a detail component on a 5 th scale, and calculating the time difference between the two sensors by adopting a generalized cross-correlation method.
With P 1 For example, a measurement vector R is established as [21.7, 14.7, 58.7, 46.7, 14.4, 19.0, 13.0, 3.7, 3.4] T The acoustic emission source positioning method based on the GCLM-grid search algorithm is adopted to identify the state vector X, and a table 4 shows the positioning result of each acoustic emission simulation source. Further, as can be seen from fig. 4, the average absolute error of the acoustic emission source positioning method based on the GCLM-grid search algorithm is 3.17 mm.
TABLE 1 sensor location coordinates
Figure BDA0003593541580000033
TABLE 2 position coordinates of lead-breaking point
Figure BDA0003593541580000041
TABLE 3 time differences between the Primary and the Secondary Sensors
Figure BDA0003593541580000042
TABLE 4 positioning results of acoustic emission simulation sources
Figure BDA0003593541580000043
The technical means disclosed by the scheme of the invention are not limited to the technical means disclosed by the technical means, and the technical scheme also comprises the technical scheme formed by any combination of the technical characteristics.

Claims (4)

1. An acoustic emission source positioning method based on a GCLM-grid search algorithm is characterized by comprising the following steps:
step one, arranging M sensors for receiving acoustic emission signals emitted by an acoustic emission source for the acoustic emission source on a three-dimensional space structure; one of the sensors is determined as a main sensor, and the other sensors are determined as secondary sensors; a rectangular coordinate system is established in the three-dimensional space, so that the coordinates of the sound emission source are (x, y, z), and the coordinates of the main sensor are (x) 1 ，y 1 ，z 1 ) The coordinates of each sub-sensor are (x) i ，y i ，z i ) (i is 2, 3 … M, M is a positive integer, and M is more than or equal to 4);
step two, obtaining the time difference t of the signals received by the main sensor and each secondary sensor through a signal processing method i1 Establishing a measurement vector R;
step three, representing the position of the sound emission source and the time of the sound emission signal from the sound emission source to the main sensor by using a state vector X; define state vector X ═ (X, y, z, T) T Where (x, y, z) is the coordinates of the acoustic emission source and T is the acoustic emission signal emitted from the acoustic emission sourceThe time of arrival of the source at the primary sensor;
step four, converting the acoustic emission positioning problem into an optimization solving problem, and constructing an objective function to iteratively solve a state vector X, wherein:
the target function expression is:
Figure FDA0003593541570000011
in the formula: f ═ F 1 ，f 2 ，f 3 …f M ] T Is a function vector;
and step five, carrying out iterative solution by adopting a GCLM-grid search algorithm, calculating the optimal solution of the state vector X, and taking the optimal solution of the state vector X which is iterated for the last time and meets the iteration times or the iteration termination condition as the position of the acoustic emission source.
2. The method for positioning an acoustic emission source based on a GCLM-grid search algorithm according to claim 1, wherein the method for solving the state vector X by using the GCLM-grid search algorithm in the fifth step comprises the following steps:
step one, in order to solve the objective function, an iterative solution d of an iterative formula (2) is utilized k To determine the search direction of the true solution, for the approximate solution X k And correcting, wherein the expression is as follows:
Figure FDA0003593541570000012
in the formula: k is the number of iterations; j. the design is a square k A Jacobian matrix for the kth iteration; i is an identity matrix; mu.s k Is a regularization parameter; d k Is a correction value of the iterative solution;
step two, utilizing the radius alpha of the confidence domain k To correct the regularization parameter mu k The expression is as follows:
Figure FDA0003593541570000013
step three, the actual decrease amount Ared of the k step iteration k And predicted decrease amount Pred k The expression is as follows:
Ared k ＝||F k || 2 -||F(X k +d k )|| 2 (4)
Pred k ＝||F k || 2 -||F k +J k d k || 2 (5)
step four, the above formula is taken and substituted into the iterative formula (2) to solve d k And r is calculated using equation (6) k The expression is as follows:
r k ＝Ared k /Pred k (6)
wherein: r is k For deciding whether to accept step size d k And adjusting the factor alpha in the iterative process k The size of (d);
step five, solving r k Then, X is solved using the equations (7) and (8) k+1 And alpha k+1 The expression is as follows:
Figure FDA0003593541570000014
Figure FDA0003593541570000015
judging whether an iteration termination condition or a preset iteration frequency is satisfied, and if so, obtaining an iteration solution; otherwise, returning to the step I to continue the circulation until the iteration termination condition is met;
step seven, determining an initial search area by taking an iteration result of the GCLM algorithm as a central point, and dividing the search area into a plurality of grids to form N grid vertexes; and constructing a cost function for each grid vertex, wherein the position of a grid point corresponding to the minimum value of the cost function is the optimal positioning point.
3. The method of claim 1 for acoustic emission source localization based on GCLM-grid search algorithm, wherein: the signal processing method is a generalized cross-correlation method.
4. The method of claim 1 for acoustic emission source localization based on GCLM-grid search algorithm, wherein: the iteration times are determined by preset conditions or iteration termination conditions; the iteration termination condition is | J k T F k ‖≤ε。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116754578A (en) * 2023-08-18 2023-09-15 国镓芯科(成都)半导体科技有限公司 Detection system for wafer scratch and detection method of system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116754578A (en) * 2023-08-18 2023-09-15 国镓芯科(成都)半导体科技有限公司 Detection system for wafer scratch and detection method of system
CN116754578B (en) * 2023-08-18 2023-11-03 国镓芯科(成都)半导体科技有限公司 Detection system for wafer scratch and detection method of system

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