Array-based tank acoustic emission detection method and system

Abstract

The present invention discloses an array-based tank acoustic emission detection method and system, which relates to the technical field of tank corrosion positioning test, and includes the following steps: collecting acoustic emission signals; performing noise reduction processing, performing pattern recognition on the acoustic emission signals after noise reduction processing, and determining the number of acoustic emission events that meet the acoustic emission event judgment conditions; whether the number of acoustic emission events is greater than or equal to a preset value, if yes, performing positioning calculation, if not, returning data acquisition; according to the number of acoustic emission event signals, using a triangulation positioning algorithm to perform positioning calculation and determine the location of the acoustic emission source. The present invention adopts a positioning method under an array to better identify the tank bottom center position signal, and has a better improvement effect on the false positioning, repeated positioning, and missed positioning phenomena existing in traditional positioning, and more clearly identifies the location of the acoustic emission source, providing a guarantee for practical engineering applications.

Description

Technical Field

[0001] The invention relates to the technical field of tank corrosion positioning testing, and in particular to an array-based tank acoustic emission detection method and system. Background Art

[0002] As a dynamic nondestructive testing technology, acoustic emission testing technology has low economic cost and small workload. It can also monitor defects in real time, which is difficult to achieve with other nondestructive testing methods. The acoustic emission waves come from the defects themselves rather than from the outside, so it has higher sensitivity and recognition, and there is no need to stop production and open the tank. Therefore, acoustic emission testing technology is widely used in the field of atmospheric pressure vertical storage tank inspection.

[0003] As the key and difficult part of the research on acoustic emission detection technology, the acoustic emission source localization algorithm aims to accurately locate the damage position, so as to further analyze the severity of defects or damage, give clear warnings for potential safety hazards, and provide accurate guidance for maintenance and safe operation. The acoustic emission source localization algorithm has important research and application value.

[0004] There are some problems that need to be solved in the traditional acoustic emission source positioning method. In the application, it was found that as the diameter of the storage tank increases, the sensor is arranged farther away from the center of the tank bottom. The traditional acoustic emission source positioning method does not receive the acoustic emission signal near the center of the tank bottom well, which affects the damage positioning effect near the center of the tank bottom; and the positioning algorithm has poor anti-interference ability, and is prone to repeated positioning, missed positioning and false positioning. The shortcomings are more prominent when the number of sensors increases and the array density increases. These problems cause strong interference to the accurate damage positioning and assessment.

[0005] Therefore, it is an urgent problem for those skilled in the art to propose an array-based tank acoustic emission detection method and system to solve the problems existing in the prior art. Summary of the invention

[0006] In view of this, the present invention provides an array-based tank acoustic emission detection method and system, which can better identify the tank bottom center position signal, and has a better improvement effect on the false positioning, repeated positioning, and missed positioning phenomena existing in traditional positioning, and can more clearly identify the location of the acoustic emission source, providing a guarantee for practical engineering applications.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] The array-based tank acoustic emission detection method comprises the following steps:

[0009] Signal acquisition step: using the arranged sensor array to collect the acoustic emission signal;

[0010] Signal preprocessing step: performing noise reduction processing on the collected acoustic emission signal to obtain the acoustic emission signal after noise reduction processing;

[0011] Pattern recognition step: performing pattern recognition on the acoustic emission signal after noise reduction processing to determine the number of acoustic emission events that meet the acoustic emission event determination conditions;

[0012] Event number determination step: determine whether the number of acoustic emission events is greater than 0, if so, enter the preset value determination step, if not, return to the signal acquisition step;

[0013] Preset value determination step: whether the number of signals of each acoustic emission event is greater than or equal to the preset value, if so, enter the positioning calculation step, if not, enter the final acoustic emission judgment step;

[0014] Positioning calculation steps: According to the number of acoustic emission event signals, the triangulation positioning method is used to perform positioning calculation to determine the positioning point of the acoustic emission signal;

[0015] The last acoustic emission judgment step: judge whether the input acoustic emission event is the last acoustic emission event, if so, end the detection process, if not, return to the preset value judgment step and continue the detection.

[0016] Optionally, the specific contents of the positioning calculation step include:

[0017] When the number of signals from different channels in an acoustic emission event is equal to the preset value, the triangulation positioning algorithm is directly used for positioning calculation. According to the arrival time of the acoustic emission signal, the position coordinates of the channel sensor to which the acoustic emission signal belongs, and the propagation speed of the acoustic emission signal, the unique positioning point can be determined;

[0018] When the number of signals from different channels in an acoustic emission event is greater than the preset value, the multi-sensor data fusion algorithm is used to optimize the selection of positioning channels. According to the amplitude, energy and other parameters of the acoustic emission signal, the positioning channel combination is selected, and the triangulation positioning algorithm is used to perform positioning calculations to obtain a unique positioning point.

[0019] Optionally, multi-sensor data fusion is performed on the acoustic emission events obtained by pattern recognition, specifically: after feature extraction of the acoustic emission events, fusion calculation based on the acoustic emission event feature calculation is performed to obtain the optimal positioning unit.

[0020] Optionally, the amplitude of the acoustic emission signal is used as a feature extraction object.

[0021] Optionally, the sensor array in the signal acquisition step is an 8-4-2-1 umbrella-shaped positioning array.

[0022] Optionally, in the signal preprocessing step, background noise is filtered out by setting a signal reception threshold to obtain an acoustic emission signal after noise reduction processing.

[0023] Optionally, the acoustic emission event determination condition in the pattern recognition step is the acoustic emission signal received within a time window defined by an event, wherein the maximum time of the time window is defined as follows:

[0024]

[0025] Wherein, DL represents the maximum side length of the smallest positioning unit in the array, and C represents the speed of sound.

[0026] Optionally, the specific content of the pattern recognition in the pattern recognition step is: processing the waveform of the acoustic emission signal through cluster analysis, processing the combination of acoustic emission signals from multiple sensors, calculating the correlation between the acoustic emission signals, and judging the acoustic emission signals whose correlation exceeds a set threshold as belonging to the same acoustic emission event;

[0027] x=(x1,x2,x3...x n ), y=(y1,y2,y3...y n ) is the data set to be calculated, x and y represent the data to be measured, and the value of n represents the vector formed by the parameters from different signals, that is, the number of characteristic parameters. The formula for calculating the mutual correlation coefficient is:

[0028]

[0029] R x,y After normalization, the final calculation formula of the mutual correlation coefficient is:

[0030]

[0031] Among them, x(n) and y(n) represent characteristic parameter sequences; the cross-correlation function is the product of the two characteristic parameter sequences x(n) and y(n).

[0032] Optionally, the preset value in the preset value determination step is 3.

[0033] An array-based tank acoustic emission detection system, which applies the above array-based tank acoustic emission detection method, includes a data acquisition module, a preprocessing module, a pattern recognition module, an event number determination module and a positioning calculation module connected in sequence;

[0034] A data acquisition module, used to collect acoustic emission signals using an arranged sensor array;

[0035] The preprocessing module performs noise reduction processing on the collected acoustic emission signal to obtain the acoustic emission signal after noise reduction processing;

[0036] The pattern recognition module performs pattern recognition on the acoustic emission signal after noise reduction processing to determine the number of acoustic emission events that meet the acoustic emission event determination conditions;

[0037] The positioning signal selection module determines whether the number of acoustic emission event signals is greater than or equal to a preset value. If yes, it is input into the positioning calculation module to perform positioning calculation. If no, data acquisition is performed again.

[0038] The positioning calculation module performs positioning calculation based on the number of acoustic emission event signals using a triangulation positioning method to determine the positioning point of the acoustic emission signal.

[0039] It can be seen from the above technical solution that, compared with the prior art, the present invention provides an array-based tank acoustic emission detection method and system: the positioning method under the array can better identify the tank bottom center position signal, and has a better improvement effect on the false positioning, repeated positioning, and missed positioning phenomena existing in traditional positioning, and can more clearly identify the location of the acoustic emission source, providing a guarantee for practical engineering applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0041] Figure 1 A flow chart of the array-based tank acoustic emission detection method provided by the present invention;

[0042] Figure 2 A flow chart of the method for positioning calculation steps provided by the present invention;

[0043] Figure 3 A structural block diagram of the array-based tank acoustic emission detection system provided by the present invention;

[0044] Figure 4 This is a schematic diagram of the sensor array provided by the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Reference Figure 1 As shown, the present invention discloses an array-based tank acoustic emission detection method, comprising the following steps:

[0047] Signal acquisition step: using the arranged sensor array to collect the acoustic emission signal;

[0048] Signal preprocessing step: performing noise reduction processing on the collected acoustic emission signal to obtain the acoustic emission signal after noise reduction processing;

[0049] Pattern recognition step: performing pattern recognition on the acoustic emission signal after noise reduction processing to determine the number of acoustic emission events that meet the acoustic emission event determination conditions;

[0050] Event number determination step: determine whether the number of acoustic emission events is greater than 0, if so, enter the preset value determination step, if not, return to the signal acquisition step;

[0051] Preset value determination step: whether the number of signals of each acoustic emission event is greater than or equal to the preset value, if so, enter the positioning calculation step, if not, enter the final acoustic emission judgment step;

[0052] Positioning calculation steps: According to the number of acoustic emission event signals, the triangulation positioning method is used to perform positioning calculation to determine the positioning point of the acoustic emission signal;

[0053] The last acoustic emission judgment step: judge whether the input acoustic emission event is the last acoustic emission event, if so, end the detection process, if not, return to the preset value judgment step and continue the detection.

[0054] In a specific embodiment, referring to Figure 2 As shown, the specific contents of the positioning calculation steps include:

[0055] When the number of signals from different channels in an acoustic emission event is equal to the preset value, the triangulation positioning algorithm is directly used for positioning calculation. According to the arrival time of the acoustic emission signal, the position coordinates of the channel sensor to which the acoustic emission signal belongs, and the propagation speed of the acoustic emission signal, the unique positioning point can be determined;

[0056] When the number of signals from different channels in an acoustic emission event is greater than the preset value, the multi-sensor data fusion algorithm is used to optimize the selection of positioning channels. According to the amplitude, energy and other parameters of the acoustic emission signal, the positioning channel combination is selected, and the triangulation positioning algorithm is used to perform positioning calculations to obtain a unique positioning point.

[0057] In a specific embodiment, multi-sensor data fusion is performed on the acoustic emission events obtained by pattern recognition. Specifically, after feature extraction of the acoustic emission events, fusion calculation based on the acoustic emission event feature calculation is performed to obtain the optimal positioning unit.

[0058] In a specific embodiment, the amplitude of the acoustic emission signal is used as a feature extraction object.

[0059] In a specific embodiment, referring to Figure 4 As shown, the sensor array in the signal acquisition step is an 8-4-2-1 umbrella-shaped positioning array.

[0060] By arranging 8 sensors on the outer circle of the tank bottom, the sensors are evenly spread out at 45 degrees; then 4 sensors are arranged at a 2 / 3 radius at a 90-degree angle to each other, then two sensors are arranged opposite to each other at a 1 / 3 radius, and finally 1 sensor is arranged at the center of the tank bottom. By arranging sensors on the outer circle of the tank bottom, the array can ensure comprehensive signal acquisition to a certain extent, that is, it can be understood that the signal is an enhancement of the signal acquired by the traditional array. A sensor is arranged at the center, and then the sensors are evenly arranged with the center point according to the determined sensor arrangement spacing. The sensor spacing is uniform and reasonable, and the detection of the center position of the tank bottom is enhanced. This array can avoid unnecessary increase in signal processing difficulty, optimize positioning effects, improve positioning accuracy, and solve the problems existing in traditional arrays while the sensor array can cover the tank bottom and enhance the detection of the center area of ​​the tank bottom.

[0061] In a specific embodiment, in the signal preprocessing step, background noise is filtered out by setting a signal receiving threshold to obtain an acoustic emission signal after noise reduction processing.

[0062] In a specific embodiment, the acoustic emission event determination condition in S103 is the acoustic emission signal received within a time window defined by an event, wherein the maximum time of the time window is defined as follows:

[0063]

[0064] Wherein, DL represents the maximum side length of the smallest positioning unit in the array, and C represents the speed of sound.

[0065] In a specific embodiment, the specific content of the pattern recognition in the pattern recognition step is: processing the waveform of the acoustic emission signal through cluster analysis, processing the combination of acoustic emission signals from multiple sensors, calculating the correlation between the acoustic emission signals, and judging the acoustic emission signals whose correlation exceeds a set threshold as belonging to the same acoustic emission event;

[0066] x=(x1,x2,x3...x n ), y=(y1,y2,y3...y n ) is the data set to be calculated, x and y represent the data to be measured, and the value of n represents the vector formed by the parameters from different signals, that is, the number of characteristic parameters. The formula for calculating the mutual correlation coefficient is:

[0067]

[0068] R x,y After normalization, the final calculation formula of the mutual correlation coefficient is:

[0069]

[0070] Among them, x(n) and y(n) represent characteristic parameter sequences; the cross-correlation function is the product of the two characteristic parameter sequences x(n) and y(n).

[0071] In a specific embodiment, the specific clustering process is as follows:

[0072] Assume that the collision signal sequence obtained within the event definition time is H = {h1, h2, h3...hn}. The method process is:

[0073] (1) First, an initial cluster C1 is established, C1 = {h1}, the signals to be classified form a queue H2, H2 = {h2, h3, ...hn}, the current cluster set CC = {C1}, and a similarity judgment threshold θ is set.

[0074] (2) Take the first signal (defined as hi) from queue H2, and calculate the correlation coefficient ρ(hi, Cx) between hi and each cluster Cx in CC respectively. ρ(hi, Cx) is the average correlation coefficient between hi and each signal in Cx.

[0075] (3) Find the cluster Ck with the largest correlation coefficient with hi. If ρ(hi, Ck) is less than θ, hi is considered not to belong to Ck. A new cluster Cm is created, Cm = {hi}, CC = CC∪{Cm}. Otherwise, hi is included in Ck.

[0076] (4) If queue H2 is empty, execute step (5); otherwise, execute step (2).

[0077] (5) Analyze whether all signals in each cluster in CC are received by more than three sensors. If so, they are retained; otherwise, they are removed from CC.

[0078] In a specific embodiment, the preset value in the preset value determination step is 3.

[0079] Reference Figure 3 As shown, the present invention discloses an array-based tank acoustic emission detection system, which applies the above-mentioned array-based tank acoustic emission detection method, including a data acquisition module, a preprocessing module, a pattern recognition module, an event number determination module and a positioning calculation module connected in sequence;

[0080] A data acquisition module, used to collect acoustic emission signals using an arranged sensor array;

[0081] The preprocessing module performs noise reduction processing on the collected acoustic emission signal to obtain the acoustic emission signal after noise reduction processing;

[0082] The pattern recognition module performs pattern recognition on the acoustic emission signal after noise reduction processing to determine the number of acoustic emission events that meet the acoustic emission event determination conditions;

[0083] The positioning signal selection module determines whether the number of acoustic emission event signals is greater than or equal to a preset value. If yes, it is input into the positioning calculation module to perform positioning calculation. If no, data acquisition is performed again.

[0084] The positioning calculation module performs positioning calculation based on the number of acoustic emission event signals using a triangulation positioning method to determine the positioning point of the acoustic emission signal.

[0085] The above description of the disclosed embodiments is provided in a progressive manner to enable those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An array-based tank acoustic emission detection method, characterized in that: The following steps are involved: Signal acquisition step: using the arranged sensor array to collect the acoustic emission signal; Signal preprocessing step: performing noise reduction processing on the collected acoustic emission signal to obtain the acoustic emission signal after noise reduction processing; Pattern recognition step: performing pattern recognition on the acoustic emission signal after noise reduction processing to determine the number of acoustic emission events that meet the acoustic emission event determination conditions; Event number determination step: determine whether the number of acoustic emission events is greater than 0, if so, enter the preset value determination step, if not, return to the signal acquisition step; Preset value determination step: whether the number of signals of each acoustic emission event is greater than or equal to the preset value, the preset value is 3, if yes, then enter the positioning calculation step, if not, then enter the final acoustic emission judgment step; Positioning calculation steps: According to the number of acoustic emission event signals, the triangulation positioning method is used to perform positioning calculation to determine the location of the acoustic emission source; The last acoustic emission judgment step: judging whether the input acoustic emission event is the last acoustic emission event, if so, ending the detection process, if not, returning to the preset value judgment step and continuing the detection; The specific contents of the positioning calculation steps include: When the number of signals from different channels in an acoustic emission event is equal to the preset value, the triangulation positioning algorithm is directly used for positioning calculation. According to the arrival time of the acoustic emission signal, the position coordinates of the channel sensor to which the acoustic emission signal belongs, and the propagation speed of the acoustic emission signal, the unique positioning point can be determined; When the number of signals from different channels in an acoustic emission event is greater than the preset value, the multi-sensor data fusion algorithm is used to optimize the selection of positioning channels. According to the amplitude and energy parameters of the acoustic emission signal, the positioning channel combination is selected, and the triangulation positioning algorithm is used to perform positioning calculations to obtain a unique positioning point. The sensor array in the signal acquisition step is an 8-4-2-1 umbrella positioning array; Arrange 8 sensors on the outer circle of the tank bottom, and the sensors are evenly distributed at 45 degrees; then arrange 4 sensors at 2 / 3 radius, at 90 degrees to each other, then arrange 2 sensors opposite to each other at 1 / 3 radius, and finally arrange 1 sensor at the center of the tank bottom. The array is arranged by arranging sensors on the outer circle of the tank bottom; The acoustic emission event determination condition in the pattern recognition step is the acoustic emission signal received within a time window defined by an event, where the maximum time of the time window is defined as follows: Wherein, DL represents the maximum side length of the smallest positioning unit in the array, and C represents the speed of sound.

2. The array-based tank acoustic emission detection method according to claim 1 is characterized in that: The multi-sensor data fusion is performed on the acoustic emission events obtained by pattern recognition. Specifically, after the feature extraction of the acoustic emission events, a fusion calculation based on the acoustic emission event feature calculation is performed to obtain the optimal positioning unit.

3. The array-based tank acoustic emission detection method according to claim 2 is characterized in that: The amplitude of the acoustic emission signal is used as the feature extraction object.

4. The array-based tank acoustic emission detection method according to claim 1, characterized in that: In the signal preprocessing step, the background noise is filtered out by setting the signal receiving threshold to obtain the acoustic emission signal after noise reduction processing.

5. The array-based tank acoustic emission detection method according to claim 1, characterized in that: The specific content of pattern recognition in the pattern recognition step is: processing the waveform of the acoustic emission signal through cluster analysis, processing the combination of acoustic emission signals from multiple sensors, calculating the correlation between the acoustic emission signals, and judging the acoustic emission signals whose correlation exceeds the set threshold as belonging to the same acoustic emission event; x=(x1,x2,x3...x n ), y=(y1,y2,y3...y n ) is the data set to be calculated, x and y represent the data to be measured, and the value of n represents the vector formed by the parameters from different signals, that is, the number of characteristic parameters. The formula for calculating the mutual correlation coefficient is: R x,y After normalization, the final calculation formula of the mutual correlation coefficient is: Among them, x(n) and y(n) represent characteristic parameter sequences; the cross-correlation function is the product of the two characteristic parameter sequences x(n) and y(n).

6. Array-based tank acoustic emission detection system, characterized in that: The array-based tank acoustic emission detection method according to any one of claims 1 to 5 is applied, comprising a data acquisition module, a preprocessing module, a pattern recognition module, an event number determination module and a positioning calculation module connected in sequence; A data acquisition module, used to collect acoustic emission signals using an arranged sensor array; The preprocessing module performs noise reduction processing on the collected acoustic emission signal to obtain the acoustic emission signal after noise reduction processing; The pattern recognition module performs pattern recognition on the acoustic emission signal after noise reduction processing to determine the number of acoustic emission events that meet the acoustic emission event determination conditions; The positioning signal selection module determines whether the number of acoustic emission event signals is greater than or equal to a preset value. If yes, it is input into the positioning calculation module to perform positioning calculation. If no, data acquisition is performed again. The positioning calculation module performs positioning calculation based on the number of acoustic emission event signals using a triangulation positioning method to determine the positioning point of the acoustic emission signal.

Images