1. A leakage source positioning method based on a plate-shaped structure gas leakage acoustic emission characteristic is characterized by comprising the following steps of:

s1, collecting vibration displacement of the surface of the plate-shaped structure as a leakage signal, and converting the leakage signal to obtain an acoustic time domain signal

S2, performing signal preprocessing on the time domain signal obtained in the step S1 to obtain a second effective signal segment;

s3, inputting the second effective signal section obtained after preprocessing in the step S2 as a signal of an MUSIC algorithm on a surrounding type sensor array consisting of n sensors, constructing a space spectrum function P (theta) based on array azimuth scanning, and taking an angle meeting the maximum value of the space spectrum function P (theta) as a direction angle theta of the center of the sensor array relative to a leakage source;

s4, establishing a two-dimensional coordinate system by taking the center of the sensor array as an original point and the plane where the sensor array is located as an x-axis plane and a y-axis plane, establishing a plurality of straight lines by taking the coordinates of the center of the sensor array in the two-dimensional coordinate system and the direction angles obtained in the step S3, and carrying out K-means clustering on the intersection points of the established straight lines to obtain the estimated position of the leakage source and realize the positioning of the leakage source.

2. The method according to claim 1, wherein in step S1, the surface vibration displacement is collected by using the surround-type array of ultrasonic transducers as the leakage signal, the leakage signal is converted into an electrical signal, the electrical signal is filtered and amplified, and after analog-to-digital conversion, a digital signal is obtained as the leakage acoustic time-domain signal x (t) which is input into the computer.

3. The method according to claim 1, wherein step S2 is specifically:

s201, intercepting a stable signal in a section of acoustic time domain signal to perform fast Fourier transform, and taking a frequency corresponding to the maximum amplitude in a signal frequency domain in a fixed frequency as a target frequency;

s202, after wavelet packet n-layer decomposition is carried out on the acoustic time domain signal by utilizing a wavelet basis, a signal segment containing the target frequency obtained in the step S201 is selected as a first effective signal segment; and performing Hilbert-yellow transformation on the first effective signal segment, and selecting a first decomposition mode signal of the Hilbert-yellow transformation as a second effective signal segment.

4. The method according to claim 3, wherein in step S201, the fixed frequency is 0-200 kHz.

5. The method according to claim 3, wherein in step S202, the decomposition using wavelet packet n-layer is specifically:

marking a main frequency region range in an original signal frequency domain, and performing n-layer decomposition on a wavelet packet in the main frequency region range; extracting the signals by using a Hilbert-Huang transform method, processing the original signals according to an EMD method, decomposing the original signals into a plurality of IMF components, then performing HT (hyper text transfer) to obtain instantaneous frequency and instantaneous energy, and finally expressing the signals into an energy spectrum form on a time domain-frequency plane.

6. The method of claim 1, wherein in step S3, the signal X received at the i-th sensor in the surround-type array_i(t), the total signal output of the sensor array is a matrix vector X; constructing a covariance matrix R, and calculating n eigenvalues lambda in the covariance matrix R₁≥λ₂≥,…,λ_k,…,≥λ_nAnd decomposing the signal subspace formed by k characteristic values and the noise subspace formed by n-k characteristic values after the resolution is larger than 0 to obtain a space spectrum function P (theta) after simplification, and taking the angle meeting the maximum value of the constructed space spectrum function as the direction angle theta of the center of the sensor array relative to the leakage source when the maximum value of the P (theta) is obtained.

7. The method of claim 6, wherein the spatial spectrum function P (θ) is:

wherein the content of the first and second substances,to form the eigenvectors of the noise subspace, a (θ) is the vector of the delay matrix, and H is the conjugate transposed symbol.

8. The method of claim 6, wherein the signal X is received at the i-th sensor in a wound array_i(t) is represented as follows:

wherein S is_ij(t) represents the signal propagated by the kth leak source to the ith sensor; n (t) represents a noise signal.

9. Method according to claim 7, characterized in that the signal X is a signal X_iThe matrix vector form x of (t) is as follows:

X＝AS+N

wherein A represents a delay matrix of size n × k composed of k sets of column vectors; assuming that each sensor finally receives a signal of length l, S represents a signal matrix of size k × l composed of k row vectors of length l, and N represents a noise matrix of size m × l composed of m colored noises of length l.

10. A leakage source positioning system based on plate-like structure gas leakage acoustic emission characteristics, comprising:

the acquisition module acquires the vibration displacement of the surface of the plate-shaped structure as a leakage signal, and converts the leakage signal to obtain an acoustic time domain signal

The processing module is used for preprocessing the time domain signal obtained by the acquisition module to obtain a second effective signal segment;

the input module is used for inputting the second effective signal section obtained by the processing module as a signal of an MUSIC algorithm on a surrounding type sensor array consisting of n sensors, constructing a spatial spectrum function P (theta) based on array azimuth scanning, and taking an angle meeting the maximum value of the constructed spatial spectrum function P (theta) as a direction angle theta of the center of the sensor array relative to a leakage source;

the positioning module is used for establishing a two-dimensional coordinate system by taking the center of the sensor array as an original point and the plane where the sensor array is located as an x-axis plane and a y-axis plane, establishing a plurality of straight lines by taking the coordinate of the center of the sensor array in the two-dimensional coordinate system and the direction angle obtained by the input module, and carrying out K-mean clustering on the intersection points of the established straight lines to obtain the estimated leakage source position so as to realize the positioning of the leakage source.

Background

With the development of aerospace technology and the increase of aerospace debris, spacecraft health monitoring becomes a hot point of research. Once the surface of the spacecraft is impacted or corroded, gas leakage can be generated on the surface of the structure, so that the structural strength of the spacecraft is influenced, the safety coefficient is reduced, and potential safety hazards, economic loss and the like are increased. The problems of spacecraft structure caused by leakage and the life safety of astronauts are all similar. The surface of the spacecraft structure is mostly of a thin plate-shaped structure, which puts requirements on a leakage detection technology on the surface of the plate-shaped structure. After leakage occurs, the position of the leakage point on the surface of the spacecraft structure needs to be given, and the device is convenient to maintain in real time.

At present, an acoustic emission leakage positioning technology is not researched and matured, and the following difficulties mainly exist:

firstly, a leakage signal is a continuous acoustic emission time domain signal, no obvious signal characteristic can be extracted, and a traditional time difference positioning method is difficult to apply;

secondly, the leaked sound signals are transmitted in a structure in a nonlinear frequency dispersion lamb wave mode, and the transmission speeds are different under different frequencies, so that the positioning difficulty is further increased;

thirdly, when the leakage signal meets the reflection generated by the wall structure, the transmission interferes the positioning result, and a better signal processing method is needed;

and fourthly, the research on the positioning method aiming at a single leakage source is more, and the research on the positioning method aiming at a plurality of leakage sources is not enough and has poorer precision.

Disclosure of Invention

The technical problem to be solved by the present invention is to provide a method and a system for positioning a leakage source based on a plate-shaped structure gas leakage acoustic emission feature, which can perform positioning detection on a gas leakage point on a plate-shaped structure, and have good positioning effect under a single leakage source and multiple leakage sources.

The invention adopts the following technical scheme:

a leakage source positioning method based on a plate-shaped structure gas leakage acoustic emission characteristic comprises the following steps:

s1, collecting vibration displacement of the surface of the plate-shaped structure as a leakage signal, and converting the leakage signal to obtain an acoustic time domain signal

S2, performing signal preprocessing on the time domain signal obtained in the step S1 to obtain a second effective signal segment;

s3, inputting the second effective signal section obtained after preprocessing in the step S2 as a signal of an MUSIC algorithm on a surrounding type sensor array consisting of n sensors, constructing a space spectrum function P (theta) based on array azimuth scanning, and taking an angle meeting the maximum value of the space spectrum function P (theta) as a direction angle theta of the center of the sensor array relative to a leakage source;

s4, establishing a two-dimensional coordinate system by taking the center of the sensor array as an original point and the plane where the sensor array is located as an x-axis plane and a y-axis plane, establishing a plurality of straight lines by taking the coordinates of the center of the sensor array in the two-dimensional coordinate system and the direction angles obtained in the step S3, and carrying out K-means clustering on the intersection points of the established straight lines to obtain the estimated position of the leakage source and realize the positioning of the leakage source.

Specifically, in step S1, the ultrasonic sensor surround array is used to collect surface vibration displacement as a leakage signal, the leakage signal is converted into an electrical signal, the electrical signal is filtered and amplified, and analog-to-digital conversion is performed to obtain a digital signal input to a computer as a leakage sound time domain signal x (t).

Specifically, step S2 specifically includes:

s201, intercepting a stable signal in a section of acoustic time domain signal to perform fast Fourier transform, and taking a frequency corresponding to the maximum amplitude in a signal frequency domain in a fixed frequency as a target frequency;

s202, after wavelet packet n-layer decomposition is carried out on the acoustic time domain signal by utilizing a wavelet basis, a signal segment containing the target frequency obtained in the step S201 is selected as a first effective signal segment; and performing Hilbert-yellow transformation on the first effective signal segment, and selecting a first decomposition mode signal of the Hilbert-yellow transformation as a second effective signal segment.

Further, in step S201, the fixed frequency is 0 to 200 kHz.

Further, in step S202, the decomposition using wavelet packet n layer specifically includes:

marking a main frequency region range in an original signal frequency domain, and performing n-layer decomposition on a wavelet packet in the main frequency region range; extracting the signals by using a Hilbert-Huang transform method, processing the original signals according to an EMD method, decomposing the original signals into a plurality of IMF components, then performing HT (hyper text transfer) to obtain instantaneous frequency and instantaneous energy, and finally expressing the signals into an energy spectrum form on a time domain-frequency plane.

Specifically, in step S3, in the surround type arraySignal X received at the ith sensor_i(t), the total signal output of the sensor array is a matrix vector X; constructing a covariance matrix R, and calculating n eigenvalues lambda in the covariance matrix R₁≥λ₂≥,…,λ_k,…,≥λ_nAnd decomposing the signal subspace formed by k characteristic values and the noise subspace formed by n-k characteristic values after the resolution is larger than 0 to obtain a space spectrum function P (theta) after simplification, and taking the angle meeting the maximum value of the constructed space spectrum function as the direction angle theta of the center of the sensor array relative to the leakage source when the maximum value of the P (theta) is obtained.

Further, the spatial spectrum function P (θ) is:

wherein the content of the first and second substances,to form the eigenvectors of the noise subspace, a (θ) is the vector of the delay matrix, and H is the conjugate transposed symbol.

Further, the signal X received by the ith sensor in the wound array_i(t) is represented as follows:

wherein S is_ij(t) represents the signal propagated by the kth leak source to the ith sensor; n (t) represents a noise signal.

Further, the signal X_iThe matrix vector form X of (t) is as follows:

X＝AS+N

wherein A represents a delay matrix of size n × k composed of k sets of column vectors; assuming that each sensor finally receives a signal of length l, S represents a signal matrix of size k × l composed of k row vectors of length l, and N represents a noise matrix of size m × l composed of m colored noises of length l.

Another technical solution of the present invention is a leakage source positioning system based on a plate-shaped structure gas leakage acoustic emission feature, comprising:

the acquisition module acquires the vibration displacement of the surface of the plate-shaped structure as a leakage signal, and converts the leakage signal to obtain an acoustic time domain signal

The processing module is used for preprocessing the time domain signal obtained by the acquisition module to obtain a second effective signal segment;

the input module is used for inputting the second effective signal section obtained by the processing module as a signal of an MUSIC algorithm on a surrounding type sensor array consisting of n sensors, constructing a spatial spectrum function P (theta) based on array azimuth scanning, and taking an angle meeting the maximum value of the constructed spatial spectrum function P (theta) as a direction angle theta of the center of the sensor array relative to a leakage source;

the positioning module is used for establishing a two-dimensional coordinate system by taking the center of the sensor array as an original point and the plane where the sensor array is located as an x-axis plane and a y-axis plane, establishing a plurality of straight lines by taking the coordinate of the center of the sensor array in the two-dimensional coordinate system and the direction angle obtained by the input module, and carrying out K-mean clustering on the intersection points of the established straight lines to obtain the estimated leakage source position so as to realize the positioning of the leakage source.

Compared with the prior art, the invention has at least the following beneficial effects:

the invention relates to a leakage source positioning method based on a plate-shaped structure gas leakage acoustic emission characteristic, which establishes a positioning method and a system through four modules of acquisition, processing, input and positioning. The method has the advantages that the whole process can be modularized, and the subsequent optimization or improvement of a certain process is facilitated. For example, different input methods or more optimized positioning algorithms may be used for different leakage sources, etc.

Further, in step S1, the advantage of using the surrounding sensor array arrangement is that it can scan a 360 ° region compared to the conventional linear arrangement, and the positioning accuracy in a region other than 0-90 ° can be improved compared to the L-shaped arrangement.

Furthermore, in the processing module, aiming at the fact that the original vibration signal contains multi-mode and dispersion phenomena, a wavelet packet decomposition mode is adopted to extract a main frequency band signal from the original vibration signal; and for the phenomena that incident reflection and the like exist at the structure boundary before reaching the sensor, the Hilbert-Huang transformation is adopted to perform modal adaptive extraction.

Further, in step S201, only the signal in the frequency range of 0 to 200Hz is intercepted because the main frequency of the leakage signal is between 0 to 200Hz, and only the analysis of 0 to 200Hz can use the priori knowledge to filter part of the signal.

Further, in step S202, wavelet packet decomposition may greatly retain information of a high frequency band and a low frequency band of the signal, and n layers are selected as main frequency bands of the selection signal, which is convenient for accuracy of a subsequent positioning algorithm.

Further, in step S3, by constructing an autocorrelation matrix of the input signal and performing feature decomposition on the autocorrelation matrix, and based on a conjugate transpose matrix of the algebraic simplified delay matrix a and a noise subspace orthogonality method, a maximum value of the spatial spectrum function is obtained to find a positioning angle, which is advantageous in that positioning can be performed on the premise that different leakage sources of a composite signal composed of multiple source signals are not correlated in theory.

Further, the spatial spectrum function is to find the azimuth of the leakage source relative to the surrounding array. Based on the reciprocal of the time delay matrix A of the surrounding array orthogonal to the noise subspace under the ideal state. However, due to the fact that the actual situation is not completely ideal, when the spatial spectrum function is scanned within a certain angle range, the spatial spectrum function may take a peak value near the direction angle of the current leakage source.

Further, the purpose of writing the signal xi (t) received at the ith sensor in the wraparound array as a superposition of signal and noise is for subsequent mathematical reasoning.

Further, set X_iThe matrix vector form of (t) is for better illustration of the mathematical derivation and subsequent mathematical reasoning.

In conclusion, the leakage source positioning method and the leakage source positioning device effectively increase the positioning accuracy of the leakage points, realize the automatic detection and the accurate positioning of the leakage points, improve the accuracy of the leakage positioning, not only can aim at the leakage working conditions of different numbers of leakage sources, but also can further improve the positioning accuracy of the leakage sources.

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

Drawings

FIG. 1 is a schematic flow diagram;

FIG. 2 is a schematic diagram of an embodiment;

FIG. 3 is an excitation diagram of an embodiment;

FIG. 4 is a schematic representation of an embodiment after an excitation process;

FIG. 5 is a schematic diagram of a sensor array used in an embodiment;

FIG. 6 is a schematic view of an exemplary positioning azimuth;

FIG. 7 is a diagram illustrating a final positioning result according to an embodiment.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

Various structural schematics according to the disclosed embodiments of the invention are shown in the drawings. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are merely exemplary, and deviations may occur in practice due to manufacturing tolerances or technical limitations, and a person skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions, according to actual needs.

The invention provides a leakage source positioning method based on plate-shaped structure gas leakage acoustic emission characteristics, which comprises the steps of collecting vibration leakage acoustic time domain signals transmitted on the surface of a plate-shaped structure caused by gas leakage by utilizing a displacement sensor array arranged on the surface of the plate-shaped structure; then preprocessing the leaked acoustic time domain signal based on the characteristics of the leaked acoustic emission signal; extracting effective signals in an intercepted time domain by wavelet packet decomposition and Hilbert-Huang transform methods, and removing noise and interference signals as far as possible; and inputting the effective signal as a signal of a surround type sensor array MUSIC algorithm, and obtaining other input parameters by a preprocessing method. Finally obtaining the directional result of the sensor array to the leakage source; using the relative position and orientation of the sensor array, a positioning equation determines the distance of the leak source from the sensor array. The invention can more accurately position a plurality of leakage sources; the influence of noise and interference signals can be effectively eliminated, and therefore the gas leakage positioning of the plate-shaped structure under the complex working condition is realized.

Referring to fig. 1, the present invention provides a method for positioning a leakage source based on a plate-shaped structure gas leakage acoustic emission feature, including the following steps:

s1, collecting surface vibration displacement as a leakage signal by using the surrounding array of the ultrasonic sensor, converting the leakage signal into an electric signal, and obtaining a digital signal input into a computer, namely a leakage sound time domain signal x (t), by filtering and amplifying the electric signal and performing analog-to-digital conversion;

the leakage acoustic signal of the plate-shaped structure is an acoustic signal which is generated by vibration with a leakage opening and is transmitted along the direction parallel to the surface of the structure when the structure generates impact or internal and external pressure difference occurs in other modes when gas leaks out of the structure. The leakage signal of the plate-shaped structure belongs to a high-frequency signal and is influenced by environmental noise and other interference noise. The sensor acquires the displacement vibration data of the surface of the structure to obtain an original leakage signal.

S2, performing signal preprocessing on the time domain signal obtained in the step S1;

s201, performing fast Fourier transform on a section of stable signal intercepted from the signal, and taking the frequency corresponding to the amplitude at the maximum position in a signal frequency domain in a fixed frequency range as a target frequency, wherein the fixed frequency range is 0-200 kHz;

s202, after wavelet packet n-layer decomposition is carried out on the signal by utilizing a wavelet basis, a signal segment containing the target frequency obtained in the step S201 is selected as a first effective signal segment; and performing Hilbert-Huang transform (HHT transform) on the first effective signal segment, and selecting a first decomposition mode signal of the Hilbert-Huang transform as a second effective signal segment.

The original signal, which is in the form of a continuous signal, has fewer features than a burst type signal and is more difficult to extract. In actual conditions, the environmental noise signal is often in a low-frequency region, the frequency domain of the leakage signal is in a higher frequency, and the frequency characteristics of the main frequency and the second harmonic exist.

The invention adopts a wavelet packet decomposition method to carry out the first-step signal preprocessing on the original leakage signal, and the wavelet packet decomposition method can more accurately keep the characteristics of the original signal at high frequency and low frequency respectively. The treatment method comprises the following steps:

firstly, marking a main frequency domain range in an original signal frequency domain, carrying out n-layer decomposition on a wavelet packet in the main frequency domain range, and further extracting signals in the main frequency domain range; the frequency domain of the signal after being lifted is more concentrated.

Secondly, the reflected signal of the leakage signal can affect the signal received by the sensor at the position with more discontinuity on the plate-shaped structure, therefore, the invention adopts a Hilbert-Huang transform method to further extract the signal, the Hilbert-Huang transform is a self-adaptive transform method, the original signal is processed according to an EMD method, and is decomposed into a plurality of IMF components, and then the IMF components are subjected to HT transform to obtain instantaneous frequency and instantaneous energy, thereby greatly improving the precision of frequency transform. The resulting signal can be represented as a spectral form of energy on the time-frequency plane. The method carries out self-adaptive decomposition on the signal by starting from the characteristic time scale of the method without prior signal, and the IMF component obtained by the Hilbert-Huang transformation generally has obvious physical significance. The invention selects the first IMF component after Hilbert-Huang transformation as the processed signal.

S3, taking the second effective signal section preprocessed in the step S2 as a signal input of a surrounding type MUSIC algorithm, wherein an angle meeting the maximum value of a constructed spatial spectrum function is a direction angle of the center of the sensor array relative to a leakage source;

referring to fig. 1, a signal segment X containing k leakage signals is input to a surround array composed of n sensors, and a signal X received by an i-th sensor in the surround array_i(t) is represented as follows:

wherein S is_ij(t) represents the signal propagated by the kth leak source to the ith sensor; n (t) represents a noise signal.

Rewriting to matrix vector form:

X＝AS+N

wherein A represents a delay matrix of size n × k composed of k sets of column vectors; assuming that each sensor finally receives a signal of length l, S represents a signal matrix of size k × l composed of k row vectors of length l, and N represents a noise matrix of size m × l composed of m colored noises of length l.

Covariance matrix R:

R＝E[XX^H]

＝E[(AS+N)(AS+N)^H]

＝AE[SS^H]A^H+E[NN^H]

＝AR_SA^H+R_N

suppose that the noise signal N (t) has a mean value of 0 and a variance of σ²With white noise present, the covariance matrix R is written as:

R＝AR_SA^H+σ²I

n eigenvalues lambda in the covariance matrix R₁≥λ₂≥,…,λ_k,…,≥λ_nAfter decomposition is more than 0, a signal subspace formed by k eigenvalues and a noise subspace formed by n-k eigenvalues are obtained.

From knowledge of the matrix theory, Rv_i＝λ_iv_i

Namely:

Rv_j＝σ²v_j

wherein j is k +1, k +2, …, n, and after algebraic reduction of the above formula, there are:

where j is k +1, k +2, …, n, ideally, the conjugate transpose of the delay matrix a is orthogonal to the noise subspace. Thus, the spatial spectrum function P (θ) is specifically constructed as follows:

wherein the content of the first and second substances,to form the eigenvectors of the noise subspace, a (θ) is the vector of the delay matrix, and H is the conjugate transposed symbol. From the above, when P (θ) is taken as the maximum value, the closer to the ideal case, the angle satisfying the maximum value of the constructed spatial spectrum function is taken as the direction angle θ of the sensor array center with respect to the leak source. .

S4, establishing a two-dimensional coordinate system by taking the center of the sensor array as an origin and the plane where the sensor array is located as an x-axis plane and a y-axis plane, establishing a plurality of straight lines by taking the coordinates of the center of the sensor array in the coordinate system and the direction angles obtained in the step S3, and carrying out K-means clustering on the intersection points of the established straight lines to obtain the estimated position of the leakage source.

The general equation for a number of lines is:

y_i＝tan(θ_i)x_i+b

where i is the number of sensor arrays, (x)_i,y_i) Is the coordinate of the center of the sensor array, θ_iIs the azimuth angle of the sensor array facing the leak source as determined in step S3, and b is the unknown intercept.

If the above equation set is approximately solved through the coordinates and azimuth angles of the centers of the plurality of sensor arrays, the result can be obtainedThe solution is also coordinates which have large errors and account for a few; some errors are very small and majority. And performing K-means clustering on all possible points to obtain the positions of most points with very small errors, namely the estimated leakage source position, and realizing the positioning of the leakage source.

In another embodiment of the present invention, a leakage source positioning system based on a plate-shaped structure gas leakage acoustic emission feature is provided, and the system can be used for implementing the above detection method for the marking information of the radiation image.

The acquisition module acquires vibration displacement of the surface of the plate-shaped structure as a leakage signal, and converts the leakage signal to obtain an acoustic time domain signal

The processing module is used for preprocessing the time domain signal obtained by the acquisition module to obtain a second effective signal segment;

the input module is used for inputting the second effective signal section obtained by the processing module as a signal of an MUSIC algorithm on a surrounding type sensor array consisting of n sensors, constructing a spatial spectrum function P (theta) based on array azimuth scanning, and taking an angle meeting the maximum value of the constructed spatial spectrum function P (theta) as a direction angle theta of the center of the sensor array relative to a leakage source;

the positioning module is used for establishing a two-dimensional coordinate system by taking the center of the sensor array as an original point and the plane where the sensor array is located as an x-axis plane and a y-axis plane, establishing a plurality of straight lines by taking the coordinate of the center of the sensor array in the two-dimensional coordinate system and the direction angle obtained by the input module, and carrying out K-mean clustering on the intersection points of the established straight lines to obtain the estimated leakage source position so as to realize the positioning of the leakage source.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The rationality and accuracy of the positioning technology of the technical scheme of the invention are verified based on finite elements.

A3-dimensional finite element model with the size of 400mm multiplied by 2.5mm is established, and a coordinate system is established by taking the center of the upper surface of the structure as the center of a circle, and a schematic diagram of the coordinate system is shown in FIG. 2. The simulated leakage excitation (red stars) is continuously loaded at the origin, and fig. 3 shows the real domain of the excitation signal. And randomly selecting 72 points with different directions of 0 degrees, 5 degrees, 360 degrees and away from the leakage source on the surface of the structure as the center of the analog sensor array, and checking the method through the azimuth angle and the final positioning result obtained by a positioning algorithm.

In step S2, a signal in the frequency domain of 0 to 200kHz is selected, the number n of wavelet packet decomposition layers is selected to be 7, and after wavelet packet decomposition and HHT conversion are performed on the selected signal, a frequency domain comparison graph of the signal is shown in fig. 4, which shows that the wavelet packet decomposition and HHT method effectively obtains the main frequency information of the signal.

In step S3, a surrounding sensor array is selected to be composed of 5 sensors, and after the signals processed in step 2 are obtained, a spatial spectrum function is constructed as shown in fig. 5And making it the largest, the obtained azimuth angle θ is the angle of each sensor array relative to the leakage source, and the error between the azimuth angle of 72 model sensor arrays and the theoretical azimuth angle thereof is shown in fig. 6, from which it can be seen that the error is very small, and the average error is only 0.47 °.

Finally, by using the relative position and azimuth angle of the center of the sensor array and by using a K-means clustering method, the obtained positioning coordinates are shown in FIG. 7 under the condition of 100 random experiments. From this, the error is very small, only 1.67 mm.

In summary, the leakage source positioning method based on the plate-shaped structure gas leakage acoustic emission features effectively improves the positioning accuracy of the leakage point, utilizes the sensor to replace manual operation, realizes automatic detection and accurate positioning of the leakage point, utilizes wavelet packet decomposition and Hilbert yellowing transform to eliminate interference signals and purify signals, improves the accuracy of leakage positioning, utilizes the surrounding array, MUSIC positioning method and K-means clustering method, can not only aim at the leakage working conditions of different numbers of leakage sources, but also can further improve the positioning accuracy of the leakage sources.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.