CN114526451A - Underground space rock mass pipeline water seepage acoustic emission fluctuation level identification method and device - Google Patents
Underground space rock mass pipeline water seepage acoustic emission fluctuation level identification method and device Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 33
- 239000013598 vector Substances 0.000 claims abstract description 64
- 239000011159 matrix material Substances 0.000 claims abstract description 39
- 238000004364 calculation method Methods 0.000 claims abstract description 23
- 238000012549 training Methods 0.000 claims abstract description 13
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- 238000005259 measurement Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
- G01M3/24—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations
- G01M3/243—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations for pipes
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
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Abstract
The invention discloses a method and a device for identifying water seepage acoustic emission fluctuation levels of underground space rock mass pipelines. In the method, an acoustic emission sensing array is used for acquiring an acoustic emission signal of a rock mass pipeline in monitoring, four time-frequency domain parameters of acoustic emission energy, duration, ringing count and peak frequency are calculated, and a weight vector is constructed by using a parameter array to count fluctuation information; and then training historical data by adopting a Sigmoid function, constructing a membership matrix, and finally carrying out water seepage state identification based on a weight vector and a fuzzy calculation result of the membership matrix. The method has the advantages of simple required hardware, accurate identification result, good real-time performance and advancement, early warning of water seepage and water instability accidents of the rock mass pipeline, and guarantee of the progress of the rock mass pipeline engineering and the safety of constructors.
Description
Technical Field
The invention belongs to the field of safety monitoring of underground rock mass pipeline engineering, and relates to a rock mass pipeline water seepage state identification method based on acoustic emission parameter fluctuation hierarchical analysis.
Background
Moisture can change mechanical parameters such as the elastic modulus and the Poisson ratio of a rock mass, changes macroscopic mechanical properties such as rigidity and compression and shear strength, brings damages such as crack propagation and surface spalling of a rock mass pipeline, and aggravates the unstable cracking accident risk of the rock mass pipeline structure, so that the development of rock mass pipeline water seepage state monitoring and damage early warning work has important scientific significance for guaranteeing engineering progress and personnel safety.
The traditional rock mass pipeline seepage leakage detection method is mainly based on the principle that the dielectric property of rock and soil changes along with moisture, such as a time domain reflection method, a frequency domain reflection method, a neutron method and the like. Although the method can accurately measure the moisture content, the sensitivity of the dielectric property of the pipeline rock mass to moisture can be reflected only when the moisture is completely immersed into the pipeline structure of the rock mass, so that the method has lower hydrological sensitivity during measurement; in addition, the method belongs to a point measurement method, high cost and equipment deployment problems are brought in a wide-area monitoring project, and how to realize low cost and high reliability while ensuring the hydrological state identification sensitivity and the advance of the rock mass pipeline is an urgent problem to be solved.
Rock mass pipeline acoustic emission is the structure through the phenomenon that release transient state elasticity ultrasonic wave is in order to reach steady state under the stress effect, and the acoustic emission incident is produced in pipeline rock mass granule slip in-process, and moisture can soften the rock mass structure, changes the friction law between the granule, and then causes parameter changes such as acoustic emission signal energy, duration, utilizes acoustic emission and structural damage state to be correlated with to develop damage monitoring work and has obtained the extensive acceptance in academic and industrial circles. In addition, the acoustic emission technology is a passive detection method, an excitation signal does not need to be transmitted in real-time monitoring, long-time and continuous damage monitoring can be realized under low power consumption, and the problems of equipment energy consumption and cost can be better controlled; however, no good method for researching the identification of the water seepage state of the rock mass pipeline by utilizing the characteristic exists at present.
Disclosure of Invention
In order to solve the problems, the invention provides a rock mass pipeline water seepage state identification method and device based on acoustic emission parameter fluctuation hierarchical analysis.
The invention relates to a method for identifying the water seepage acoustic emission fluctuation level of a rock mass pipeline in an underground space, which comprises the following steps:
step 1, obtaining acoustic emission signals of rock mass pipelines in different water seepage states, extracting energy, duration, ringing count and peak frequency parameters of the acoustic emission signals, calculating dynamic step characteristics of all parameters in a gradual change hydrological state, and obtaining importance sorting vectors of the parameters to determine parameter weights;
step 2, training an acoustic emission parameter by using a Sigmoid function, and combining Sigmoid output row vectors to construct a membership matrix;
and 3, identifying the water seepage state of the rock mass pipeline by using the weight vector and the calculation result of the membership matrix.
Further, in step 1, the dynamic step characteristics of the acoustic emission energy, the duration, the ringing count and the peak frequency parameter in the gradual change hydrological state are calculated, and the specific method is as follows: recording the energy parameter sequences under different water seepage levels as follows:
the duration parameter sequence is:
the ringing count parameter sequence is:
the peak frequency parameter sequence is:
where m is the water penetration level, the dynamic step characteristic matrix of the parameters is:
Further, in step 1, the importance ranking vector is obtained by accumulating row vector elements of each dynamic step characteristic matrix, and the parameter weight is determined by the ratio of the accumulated values of the row vector elements of the dynamic step characteristic matrix.
Further, in step 2, the Sigmoid output row vector obtaining method includes: taking acoustic emission parameters in a historical database as input, taking every two parameters as a group, training a Sigmoid function to obtain an identification model, inputting acoustic emission signals of unknown water seepage states into the trained model in a test stage, and outputting the function, namely a Sigmoid output row vector; the sequence of the combination of every two parameters is as follows: energy-duration, duration-ringing count, ringing count-peak frequency, peak frequency-energy; the membership matrix is formed by combining a plurality of Sigmoid row vectors, and each Sigmoid row vector is obtained by training and identifying two specific acoustic emission parameters.
Further, in step 3, multiplying the weight vector by the membership matrix, taking the sequence of the maximum element in the result vector, and taking the sequence as the water seepage level state of the rock mass pipeline.
Further, the device comprises an acoustic emission sensing array (1) and a signal processing module (2) which are arranged on the surface of the rock mass pipeline; the acoustic emission perception array (1) is used for perceiving and collecting acoustic emission signals of the rock mass pipeline and is connected to the signal processing module; the signal processing module (2) comprises a weight vector calculation module, a membership matrix calculation module and a fuzzy calculation module, wherein the weight vector calculation module is used for calculating the dynamic step characteristics of each parameter in a gradual change hydrological state to obtain an importance ranking vector of the parameters as a weight vector; the membership matrix calculation module is used for training a Sigmoid function by using historical acoustic emission data and combining Sigmoid row vectors to construct a membership matrix; and the fuzzy calculation module is used for performing fuzzy operation on the weight vector and the membership matrix and outputting the water seepage level state of the rock mass pipeline.
The invention has the beneficial effects that: the method utilizes the fluctuation characteristics and the hierarchical analysis method of the acoustic emission parameters in different water seepage states to identify the water seepage state of the rock mass pipeline, and identifies the water seepage level through the acoustic emission signals intermittently generated at the initial stage of damage of the rock mass pipeline, so that the method has higher hydrological sensitivity; the fluctuation condition of the parameters in the gradual hydrological state is counted to evaluate the influence degree of moisture on the parameters, historical acoustic emission data information is fully mined by utilizing a Sigmoid function, and the constructed water seepage identification model has better anti-interference capability along with the continuous abundance of data in a long-period monitoring project; according to the method, a weight vector is constructed by utilizing the fluctuation state of the acoustic emission parameter, historical data information is mined through a Sigmoid classifier, and the water seepage state of the rock mass is identified based on a hierarchical analysis method. The method has the advantages of simple hardware, high accuracy and good real-time performance of monitoring the water seepage state of the rock mass pipeline, and can early warn and guarantee the progress of the rock mass pipeline engineering in the underground space and the safety of constructors.
Drawings
FIG. 1 is a method flow diagram;
FIG. 2 is acoustic emission signals of different water seepage states;
fig. 3 is the result of importance calculation of each parameter.
Detailed Description
In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
The invention relates to a method for identifying the water seepage acoustic emission fluctuation level of a rock mass pipeline in an underground space, which comprises the following steps:
step 1, obtaining acoustic emission signals of rock mass pipeline structures in different water seepage states, extracting energy, duration, ringing count and peak frequency parameters of the acoustic emission signals, calculating dynamic step characteristics of all parameters in a gradual change hydrological state, and obtaining importance sorting vectors of the parameters to determine parameter weights;
grouping the parameters pairwise, training acoustic emission parameters by using a Sigmoid function, and combining Sigmoid output row vectors to construct a membership matrix;
and 3, carrying out fuzzy operation on the weight vector and the membership degree matrix, and identifying the water seepage state of the rock mass pipeline.
In the step 1, dynamic step characteristics of acoustic emission energy, duration, ringing count and peak frequency parameter in a gradual change hydrological state are calculated, and the specific method is as follows: recording the energy parameter sequence under different water seepage levels as follows:
the duration parameter sequence is:
the ringing count parameter sequence is:
the peak frequency parameter sequence is:
where m is the water penetration level, the dynamic step characteristic matrix of the parameters is:
The importance sorting vector is obtained by accumulating each dynamic step characteristic matrix row vector element, and the parameter weight is determined by the ratio of the accumulated values of the dynamic step characteristic matrix row vector elements.
In step 2, the Sigmoid output line vector obtaining method includes: and (3) taking acoustic emission parameters in a historical database as input, taking every two parameters as a group, training a Sigmoid function to obtain an identification model, inputting acoustic emission signals of unknown water seepage states into the trained model in a test stage, and outputting the function, namely, a Sigmoid output row vector. The sequence of the combination of every two parameters is as follows: energy-duration, duration-ringing count, ringing count-peak frequency, peak frequency-energy; the membership matrix is formed by combining a plurality of Sigmoid output line vectors, and each Sigmoid output line vector is obtained by training and identifying two specific acoustic emission parameters.
In step 3, multiplying the weight vector and the membership matrix in a self-identification mode, taking the sequence of the maximum element in the result vector, and taking the sequence as the water seepage level state of the rock mass pipeline.
Based on the method, the invention also provides a device for identifying the acoustic emission fluctuation level of the water seepage state of the rock mass pipeline, as shown in figure 3, the device comprises an acoustic emission perception array (1) and a signal processing module (2) which are arranged on the surface of the rock mass pipeline; the acoustic emission sensing array (1) is used for sensing and collecting acoustic emission signals of the rock mass pipeline and is connected to the signal processing module; the signal processing module (2) consists of a weight vector calculation module, a membership matrix calculation module and a fuzzy calculation module, wherein the weight vector calculates the dynamic step characteristics of all parameters in a gradual change hydrological state to obtain importance sequencing vectors of the parameters as parameter weights; the membership matrix calculation module is used for training a Sigmoid function by using historical acoustic emission data and combining Sigmoid row vectors to construct a membership matrix; the fuzzy calculation module is used for carrying out fuzzy operation on the weight vector and the membership degree matrix and outputting the water seepage level state of the rock mass pipeline.
The algorithm flow is shown in fig. 1. For example, 5 water seepage states are adopted, and 5 water seepage levels are simulated, and the sample is controlled by a weighing method to have the water content of 0% (dry state), 25%, 50%, 75% and 100% (saturated water content state). And (3) applying pressure by using hydraulic equipment and acquiring acoustic emission signals of samples in different water seepage states, wherein the acoustic emission signals in different water seepage states are shown in figure 2. Four parameters are extracted, a weight vector calculation module is adopted to analyze the dynamic step characteristics of the parameters in the gradual change hydrological state, and the normalized parameter sequence values are shown in table 1.
TABLE 1 parameter sequence values
| Parameter name | Value of sequence of parameters |
| (Energy) | (0.954,0.79,0.60,0.38,0.16) |
| Duration of time | (0.912,0.51,0.24,0.14,0.05) |
| Ringing count | (0.70,0.49,0.35,0.20,0.02) |
| Peak frequency | (0.74,0.67,0.38,0.31,0.21) |
The importance results of the parameters are obtained as shown in fig. 3, and the vector elements are accumulated to construct the weight vector result as (0.40,0.30,0.22, 0.08). And (4) mining historical acoustic emission data, and constructing a membership matrix by adopting a membership matrix calculation module. Taking the 25% water seepage state as an example, the parameters are combined into a Sigmoid function in pairs, and the results of the Sigmoid function on different parameter combinations are shown in table 2
Table 2 Sigmoid function outputs results for different parameter combinations
| Parameter combination | Sigmoid function output line vector |
| Energy-durationBetween | (0.09,061,023,0.04,0.03) |
| Duration-ringing count | (0.05,031,0.10,024,0.30) |
| Ringing count-peak frequency | (0.15,075,0.05,0.02,0.03) |
| Peak frequency-energy | (0.91,002,0.01,0.03,0.03) |
Combining the row vectors to obtain a membership matrix:
multiplying the weight vector by the membership matrix to obtain a result vector as follows: (0.1568,0.5036,0.1338,00948,0.1110), the resulting vector maximum 0.5036 occurs in the second position, indicating that this sample is 25% most likely, which corresponds to the actual sample moisture status.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and all equivalent variations made by using the contents of the present specification and the drawings are within the protection scope of the present invention.
Claims (6)
1. The method for identifying the water seepage acoustic emission fluctuation level of the underground space rock mass pipeline is characterized by comprising the following steps:
step 1, obtaining acoustic emission signals of rock mass pipelines in different water seepage states, extracting energy, duration, ringing count and peak frequency parameters of the acoustic emission signals, calculating dynamic step characteristics of all parameters in a gradual change hydrological state, and obtaining importance sorting vectors of the parameters to determine parameter weights;
step 2, training acoustic emission parameters by using a Sigmoid function, and combining Sigmoid output row vectors to construct a membership matrix;
and 3, identifying the water seepage state of the rock mass pipeline by using the weight vector and the membership matrix calculation result.
2. The method for identifying the water seepage acoustic emission fluctuation hierarchy of the underground space rock mass pipeline according to claim 1, wherein the dynamic step characteristics of acoustic emission energy, duration, ringing count and peak frequency parameters in the gradual hydrological state are calculated in step 1, and the method comprises the following specific steps: recording the energy parameter sequences under different water seepage levels as follows:
the duration parameter sequence is:
the ringing count parameter sequence is:
the peak frequency parameter sequence is:
where m is the water penetration level, the dynamic step characteristic matrix of the parameters is:
3. The underground space rock mass pipeline water seepage acoustic emission fluctuation level identification method according to claim 2, characterized in that: in step 1, the importance sorting vector is obtained by accumulating each dynamic step characteristic matrix row vector element, and the parameter weight is determined by the ratio of the accumulated values of the dynamic step characteristic matrix row vector elements.
4. The underground space rock mass pipeline water seepage acoustic emission fluctuation level identification method according to claim 1, characterized in that: in step 2, the Sigmoid output row vector obtaining method includes: taking acoustic emission parameters in a historical database as input, taking every two parameters as a group, training a Sigmoid function to obtain an identification model, inputting acoustic emission signals of unknown water seepage states into the trained model in a test stage, and outputting the function, namely a Sigmoid output row vector; the sequence of the combination of every two parameters is as follows: energy-duration, duration-ringing count, ringing count-peak frequency, peak frequency-energy; the membership matrix is formed by combining a plurality of Sigmoid row vectors, and each Sigmoid row vector is obtained by training and identifying two specific acoustic emission parameters.
5. The underground space rock mass pipeline water seepage acoustic emission fluctuation hierarchy recognition method according to claim 1, characterized in that: in step 3, multiplying the weight vector by the membership matrix, taking the sequence of the maximum element in the result vector, and taking the sequence as the water seepage level state of the rock mass pipeline.
6. The device for identifying the acoustic emission fluctuation level of the water seepage of the underground space rock mass pipeline according to any one of claims 1 to 5 is characterized in that: the device comprises an acoustic emission sensing array (1) and a signal processing module (2), wherein the acoustic emission sensing array is arranged on the surface of a rock mass pipeline; the acoustic emission perception array (1) is used for perceiving and collecting acoustic emission signals of the rock mass pipeline and is connected to the signal processing module; the signal processing module (2) comprises a weight vector calculation module, a membership matrix calculation module and a fuzzy calculation module, wherein the weight vector calculation module is used for calculating the dynamic step characteristics of each parameter in a gradual change hydrological state to obtain an importance ranking vector of the parameters as a weight vector; the membership matrix calculation module is used for training a Sigmoid function by using historical acoustic emission data and combining Sigmoid row vectors to construct a membership matrix; the fuzzy calculation module is used for carrying out fuzzy operation on the weight vector and the membership degree matrix and outputting the water seepage level state of the rock mass pipeline.
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