A multi-component fiber Bragg grating detection device and method for ice crack positioning

Abstract

A multi-component fiber grating detection device and method for ice crack positioning belongs to the field of fiber optic sensing technology. The multi-component fiber grating detection device includes a fiber grating multi-component detector, a mounting base, and a counterweight, wherein the fiber grating multi-component detector includes a rigid support rod, a columnar fixed base, an arc-shaped mass block, a cantilever beam structure, an FBG, and an annular base. The multi-component fiber grating detection device obtains a vibration signal through the FBG, determines the source of the maximum polarization direction of the vibration signal, and uses a distance positioning algorithm to determine the position of the ice crack in this direction; uses a Bayesian method to optimize the measurement results through multi-path signal feedback information; and uses a distance positioning algorithm to determine the exact position of the ice crack in this direction. The present invention can adapt a multi-component fiber grating detection device to solve the spatial positioning problem of ice cracks, apply the positioning idea of single-point positioning to ice crack positioning, reduce the difficulty of deployment, and provide a new safety guarantee for ice surface operations in extreme environments.

Description

Technical Field

[0001] The present invention belongs to the field of optical fiber sensing technology and relates to a multi-component optical fiber Bragg grating (FBG) detection device and method for ice crack positioning. By real-time monitoring of the stress accumulation effect (vibration) inside the ice body, the direction and magnitude of the sudden change are determined, effectively ensuring the safety of manual operations on the ice surface. Background Art

[0002] Ice cracking refers to the structural fracture or disintegration of an ice sheet caused by natural factors (such as temperature, expansion, and compression) or human factors. Current research on ice crack monitoring often utilizes image recognition methods. For example, the China University of Geosciences (Chinese invention patent CN118832604A) and the Institute of Polar Research of China (Chinese invention patent CN118408536A) have each proposed a detection robot for ice crack detection. By collecting real-time ice crack image data, these robots can timely assess ice conditions and risk levels. While these methods eliminate the need for manual on-site monitoring and can identify surface cracks within a large monitoring range (hundreds of meters), accurate identification of surface cracks is difficult because the expansion of internal ice defects can easily induce ice cracks extending in unknown spatial directions, making accurate identification based on surface cracks difficult.

[0003] Internal fractures in solids typically release energy in the form of elastic waves. Therefore, the location of ice cracks can be indirectly determined by picking up vibration signals (detection). Detection technology is currently widely used in microseismic monitoring of coal mine rock masses. Fractures can be located by deploying multiple geophones (or microseismic sensors). For example, Southwest Jiaotong University (Chinese invention patent CN119393185A) has proposed a multi-microseismic sensor-based method for locating the source of internal fracture propagation in rock masses. By recording microseismic signals from multiple microseismic sensors deployed in advance boreholes, the temporal and spatial distribution of these signals is analyzed to determine the extent of fracture propagation in the rock mass. Shandong University of Science and Technology (Chinese invention patent CN118911775A) has proposed a combined "microseismic + geoacoustic" monitoring system for tunnel rockbursts and its application method. By collecting and analyzing microseismic and geoacoustic signals picked up by multiple geophones, this system enables real-time monitoring, location, and assessment of rockburst events. Existing technologies still rely on a combination of multiple geophone arrays for fracture source location; there are no examples of using a single geophone for locating fracture sources.

[0004] In summary, while multi-component, multi-detector arrays can provide more comprehensive source information for rupture source location, they are difficult to deploy in extreme ice crack identification scenarios. Existing research has yet to demonstrate the use of a single detector for source location. Given the practical needs of ice crack monitoring in extreme environments, there is an urgent need to develop an ice crack detection device and positioning method based on a single detector. By optimizing the sensor structure and positioning algorithm, the density of equipment deployment can be reduced while ensuring monitoring accuracy, thus meeting the engineering needs of long-term unmanned monitoring in harsh environments such as polar regions and glaciers. Summary of the Invention

[0005] In response to the above-mentioned problems existing in the prior art, the present invention proposes a multi-component fiber Bragg grating detection device and method for ice crack positioning. It is an ice crack azimuth detection device with a multi-component fiber Bragg grating detection device as the main body and an adapted spatial positioning method thereof. It can solve the spatial positioning problem of ice cracks with a single detector. At the same time, the fiber Bragg grating device can overcome the inherent problems of the electrical detector itself, such as easy corrosion and susceptibility to electromagnetic interference.

[0006] In order to solve the above problems, the technical solution adopted by the present invention is:

[0007] A multi-component fiber Bragg grating (FBG) detector device for detecting the orientation of ice cracks, the multi-component fiber Bragg grating (FBG) detector device comprising a fiber Bragg grating multi-component detector I, a mounting base II, and a counterweight III. The mounting base II comprises a shell 1, a disc-shaped mounting base 2, an annular limiting structure 3, a cylindrical tubular body 4, a wire outlet 5, and a transmission optical cable 6; the counterweight III is a hemispherical solid counterweight block 7; the fiber Bragg grating multi-component detector I comprises a rigid support rod 8, a columnar fixed base 9, an arc-shaped mass block 10, a cantilever beam structure 11, an FBG 12, and an annular base 13. The multi-component fiber Bragg grating (FBG) detector device is placed into the water during the freeze-thaw period, and the bottom counterweight III is used to keep the multi-component fiber Bragg grating detector device in a critical buoyancy state, so that it is stably embedded in the ice layer during the freezing phase transition. Specifically:

[0008] The fiber Bragg grating (FBG) multi-component detector I comprises three identical, orthogonally arranged main component units. Each unit comprises an annular base 13, six multi-cantilever beam structures 11 evenly distributed along the circumference of the annular base 13 and located in the same horizontal plane, FBGs 12 mounted on each of the six cantilever beams 11, and a curved proof mass 10. Specifically, the bottoms of the annular bases 13 on each of the three main component units are fixedly connected to the tops of rigid support rods 8. The ends of the rigid support rods 8 are embedded at an angle into the sides of a cylindrical fixed base 9. The bottom of the cylindrical fixed base 9 is bolted to a disc-shaped mounting platform 2. The disc-shaped mounting platform 2 can be provided with a transmission hole for optical fiber access. Two positive and negative FBGs 12 are fixed between the annular base 13 and the curved proof mass 10 as vibration sensing units. These FBGs 12 are fiber Bragg gratings. The negative FBG 12 serves as a reference grating to eliminate external temperature interference and amplify the fiber Bragg grating multi-component detector's ability to pick up vibration signals.

[0009] Furthermore, the annular base 13 is a hemispherical arch structure and is provided with six mounting slots for fixing the cantilever beam structure.

[0010] Furthermore, the axis of the rigid support rod 8 coincides with the center normal of the annular base 13. This means that the bottoms of the annular bases 13 on the three main component units are perpendicularly connected to the rigid support rod 8 and secured with bolts. The three rigid support rods 8 are orthogonal to each other and are embedded in the cylindrical fixed base 9 at an angle of 45 degrees.

[0011] Furthermore, the cantilever beam structure 11 is a flat, curved structure, with its fixed end horizontally and non-angledly embedded in a corresponding mounting groove of the annular base 13. The free end extends radially from the annular base 13, with the outermost arc-shaped mass 10 mounted. The cantilever beam structure 11 has grooves on both the front and back sides for embedding the FBG 12, which is fixed by gluing.

[0012] Furthermore, six cantilever beam structures 11 are distributed in the same detection plane in a circular array with equal spacing at an angle of 60°, and the overall petal-shaped radiation topology structure can simultaneously obtain all-round vibration signals in the corresponding plane, and each main component unit structure can simultaneously output 6 channels of low-frequency dynamic response data.

[0013] Furthermore, for each main component unit structure, a total of 12 FBGs 12 fixed on the six cantilever beam structures 11 are connected end to end through optical fibers, used in cascade, and encapsulated into the groove of the annular base 13 by epoxy resin.

[0014] The mounting base II includes a shell 1, a disc-shaped mounting platform 2, an annular limiting structure 3, a cylindrical tubular body 4, a wire outlet hole 5, and a transmission optical cable 6. Specifically: the shell 1 is a hard hemispherical transparent shell, and the inner wall of the bottom is provided with an annular inner protrusion, which serves as an annular limiting structure 3 for fixing the shell 1 on the disc-shaped mounting platform 2, and at the same time, an epoxy resin filling layer is reserved for the packaging of the fiber optic Bragg grating multi-component detector I; the fiber optic Bragg grating multi-component detector I is placed in the shell 1 and is connected to the disc-shaped mounting platform 2 through a cylindrical fixed base 9; the cylindrical tubular body 4 is a structure with a hollow interior and filled at both ends, the upper axial end of which is fixedly connected to the disc-shaped mounting platform 2, and the lower axial end is connected to the hemispherical solid counterweight block 7, and is provided with a wire outlet 5 for leading out a transmission optical cable 6; the optical fiber tail of the cascaded FBG12 on each main component unit structure is fused with the transmission optical cable 6 passing through the center of the disc-shaped mounting platform 2 and the cylindrical tubular body 4. The transmission optical cable 6 is led out from the wire outlet 5, and the far end is connected to the optical fiber demodulation system to collect sensor signals.

[0015] Furthermore, the center of the hemispherical solid counterweight 7 is collinear with the geometric center of the cylindrical fixed base 9 along the direction of gravity. The hemispherical solid counterweight 7 is removably fixed to the bottom of the cylindrical tubular body 4 by bolts. By replacing the hemispherical solid counterweight 7 with a different model, the depth of the multi-component fiber Bragg grating detector device in water can be changed.

[0016] A multi-component fiber Bragg grating detection method for ice crack positioning is implemented based on the above-mentioned multi-component fiber Bragg grating detection device and is used to determine the direction and distance of the ice crack. The multi-component fiber Bragg grating detection device obtains the vibration signal through FBG12 and transmits it to the acquisition system, reads the vibration signal in real time and records it; selects the data in the n-segment time window of different principal component unit structures for coordinate transformation and covariance matrix analysis to determine the source of the maximum polarization direction of the vibration signal; uses the distance positioning algorithm to determine the specific position of the ice crack in this direction; uses the Bayesian method to optimize the measurement results through multi-path signal feedback information; and uses the distance positioning algorithm to determine the specific position of the ice crack in this direction. Specifically, it includes the following steps:

[0017] S1: Multi-component vibration signal acquisition. First, a vibration signal is acquired using a fiber Bragg grating (FBG) multi-component detector. According to the structure of the fiber Bragg grating (FBG) multi-component detector, each principal component unit can acquire 12 vibration signals, for a total of 36 vibration signals, primarily based on three principal components. Excluding the channel corresponding to the reference FBG 12 on the reverse side of the cantilever beam structure 11, 18 vibration signals of different components are ultimately acquired.

[0018] S2: Determine the source propagation direction based on polarization analysis. When a rupture causes the particles in the surrounding medium to vibrate, the trajectory of the generated vibration signal often needs to be represented by a complex spatial curve. This curve can be approximately fitted into an ellipsoid (a wave with an ellipsoidal trajectory is called an ellipsoidal polarized wave). The maximum polarization direction of the ellipsoidal polarized wave is solved by the polarization analysis method to determine the orientation of the source. Polarization analysis is performed on the vibration signal collected by the fiber Bragg grating multi-component detector to determine the direction of the source. The polarization analysis and source propagation direction determination method can be divided into the following sub-steps:

[0019] s200: Detector data correction. The present invention divides the vibration signals of 18 components collected by the three main component unit structures into According to the position of the cantilever beam structure 11, the 18 signals can be set as three types. , , Since it is difficult to ensure that the vertical direction of each main component unit is consistent with the geographic rectangular coordinate system during the structural design and on-site installation of the fiber Bragg grating multi-component detector, The direction is consistent. In order to facilitate the subsequent data processing, the collected 18-channel data needs to be corrected. The corrected three-component data is consistent with the data in the geographic rectangular coordinate system in the picking direction. For the data collected by different FBG12s, the specific rotation correction algorithm is performed according to the principal component unit structure of each location. It can be expressed as follows:

[0020]

[0021] Where, azimuth , pitch angle , roll angle Corresponding to different main component units in fiber Bragg grating multi-component detector 、 、 The angle of rotation about the X-axis, Y-axis, and Z-axis of the geographic rectangular coordinate system. , pitch angle , roll angle All of them are obtained through field measurements. The present invention is installed at 45° when assembling the main component unit structure, so the azimuth angle can be set here. , pitch angle , roll angle is 45°.

[0022] S201: Construct a multi-component data matrix R. Take the data points of each cantilever beam structure 11 in different principal component unit structures within n time windows at the same time interval. According to the cantilever beam structure, the 18 signals collected within n time windows can be combined into a 6n×3 multi-component data matrix R:

[0023]

[0024] in,( , , ) represents the vibration signal picked up by any cantilever beam structure 11 in each principal component unit structure within the first time window; ( , , ) represents the vibration signal picked up by any cantilever beam structure 11 except the cantilever beam structure 11 just collected in each principal component unit structure in the first time window; and so on, ( , , ) indicates that in each principal component unit structure within the nth time window, only the vibration signal picked up by the cantilever beam structure 11 remains uncollected.

[0025] s202: Use the R matrix to construct the covariance matrix P. Calculate the covariance matrix of the matrix R and obtain a 3×3 three-component data matrix P:

[0026]

[0027] Where, 、 、 Represent the data in the tth row and jth column in the R matrix, t, j = 1, 2, 3 respectively.

[0028] S203: Solve the matrix eigenvector to determine the source direction. Use the data points in the n time windows to perform characteristic analysis on the multi-component data matrix R, and obtain the eigenvectors and eigenvalues of the three-component data matrix P, where the largest eigenvalue The corresponding eigenvector is When the vibration signal is linearly polarized, the multi-component data matrix R has only one non-zero eigenvalue, so the corresponding eigenvector can represent the direction of the wave source. In practical applications, the vibration signal is polarized throughout the entire three-dimensional space. In this case, it is believed that the main energy source of the ice crack is concentrated on the largest eigenvalue, thereby determining the azimuth of the earthquake source in space. and incident angle :

[0029]

[0030] in, represents the first term of the eigenvector; represents the second term of the eigenvector; represents the third term of the eigenvector.

[0031] S3: Determine the distance to the earthquake source. The distance is determined by using the time difference between the vibration signals reaching different cantilever beam structures 11, as follows:

[0032] Assume that a certain point source is S. When the vibration signal caused by the source S passes through any principal component unit structure, it will cause the cantilever beam structure 11 to vibrate successively. Therefore, there will be a wave path difference between the cantilever beam structures 11 of any principal component unit structure. , when the wave speed is known, the path difference The relationship between the wave velocity v is as follows:

[0033]

[0034] Among them, the time difference It is obtained by recording the vibration signal using a fiber Bragg grating multi-component detector.

[0035] Since the distance between the earthquake source S and any two FBGs 12 arranged on the cantilever beam structures 11 in any principal component unit structure is much greater than the spacing between any two FBGs 12 arranged on the cantilever beam structures 11, the angle between the line connecting the earthquake source S and the two FBGs 12 is very small. The FBG 12 closer to the earthquake source (set as point A) is taken as its distance , the distance from FBG12 (assuming the location is point B) which is farther from the earthquake source is ,in Indicates the wave path difference. Set a point O on the path between the source S and FBG12 which is far away from the source, so that the distance from point O to the source is also , then the triangle area enclosed by the earthquake source S, point B and point O can be approximately regarded as an isosceles triangle with a very small vertex angle and a base angle of 90° (see Appendix Figure 5 ), which satisfies the following equation:

[0036]

[0037] Therefore, the path difference The distance l between the two FBGs 12 satisfies the following equation (7):

[0038]

[0039] in, It represents the angle between the earthquake source S and the area enclosed by the two FBGs 12 (A, B).

[0040] According to the law of cosines, the triangle formed by the source S and the two FBGs 12 satisfies the following equation (8):

[0041]

[0042] Then through the path difference The distance difference l can determine the source distance For any principal component unit structure, one of the six FBGs 12 embedded in the six cantilever beam structures 11 on it will always pick up the vibration signal first and set it as the reference grating. According to the above principle, five distance results can be obtained through the five distance differences and five wave path differences between the other FBGs 12 on the six cantilever beam structures 11 and the reference grating. The five distance differences can be expressed as (See attached Figure 6 ), the five path differences can be expressed as , the distance results can be expressed as .

[0043] S4: Use probabilistic methods to optimize distance results. Since multiple FBG12s can output multiple results, in order to further determine the reliability of the results, a Bayesian method is used to optimize the results and improve positioning accuracy. The specific method is as follows:

[0044] First, the monitoring area of ice sheet rupture is defined, and the number of ice sheet ruptures in the monitoring area is counted to obtain the prior probability function Then, the distance results measured by each principal component unit of the fiber Bragg grating multi-component detector are compared with the actual ice crack results observed and the likelihood function is constructed according to the statistical law. , and then multiply the likelihood functions obtained from the distance measurements of the 18 cantilever beam structures 11 in the principal component unit structure to obtain the joint likelihood function as shown in formula (9):

[0045]

[0046] Combining the prior probability function and the observed distance results, the latest probability distribution of the earthquake source location can be obtained as shown in formula (10):

[0047]

[0048] When filtering out clutter, the posterior distribution function can be used Generate a probability cloud map related to distance to provide more accurate information for ice cracking, and optimize geometric positioning through probabilistic means to assist decision-making.

[0049] The beneficial effects of the present invention are:

[0050] (1) The multi-component fiber Bragg grating detector designed by the present invention can simultaneously read the vibration signal of the X, Y, and Z components. The polarization characteristics of the vibration signal can be reflected by multiple FBG12s in different directions on the main component unit, providing more azimuth information for vibration signal analysis. At the same time, compared with traditional electrical detectors, it has the advantages of being passive, anti-interference, corrosion-resistant, cascaded and multiplexed, and having a high transmission rate, making it suitable for vibration signal acquisition in extreme environments.

[0051] (2) The positioning method designed in the present invention can adapt to the multi-component fiber grating detection device to solve the spatial positioning problem of ice cracks. At the same time, the positioning idea of single-point positioning is applied to ice crack positioning, which greatly reduces the difficulty of deployment and provides a new safety guarantee for ice surface operations in extreme environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A design diagram of a multi-component fiber Bragg grating detection device designed for the present invention;

[0053] Figure 2 A design diagram of a fiber Bragg grating multi-component detector designed for the present invention;

[0054] Figure 3 A flow chart describing ice crack source location for the present invention;

[0055] Figure 4 The present invention provides a specific step for locating the earthquake source direction using a polarization analysis method;

[0056] Figure 5 A schematic diagram illustrating the principle of earthquake source distance positioning is provided for describing the present invention;

[0057] Figure 6 Simplified diagram for distance positioning of multiple cantilever beams.

[0058] In the figure: Ⅰ fiber Bragg grating multi-component detector, Ⅱ mounting base, Ⅲ counterweight; 1 shell, 2 disc-shaped mounting base, 3 annular limit structure, 4 cylindrical tubular body, 5 outlet hole, 6 transmission optical cable, 7 hemispherical solid counterweight, 8 rigid support rod, 9 columnar fixed base, 10 arc-shaped mass block, 11 cantilever beam structure, 12 fiber Bragg grating FBG, 13 annular base. DETAILED DESCRIPTION

[0059] To make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the following will be combined with the appended drawings of the embodiments of the present invention. Figure 1 To the attached Figure 6 The technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0060] A multi-component fiber Bragg grating (FBG) detector device for detecting the orientation of ice cracks, comprising a fiber Bragg grating (FBG) multi-component detector I, a mounting base II, and a counterweight III; the mounting base II comprises a housing 1, a disc-shaped mounting base 2, an annular limiting structure 3, a cylindrical tubular body 4, a cable outlet 5, and a transmission optical cable 6; the counterweight III is a hemispherical solid counterweight block 7; the fiber Bragg grating (FBG) multi-component detector I comprises a rigid support rod 8, a columnar fixed base 9, an arc-shaped mass block 10, a cantilever beam structure 11, an FBG 12, and an annular base 13. The multi-component fiber Bragg grating (FBG) detector device is placed in water during the freeze-thaw period, and the bottom counterweight III is used to keep the multi-component fiber Bragg grating (FBG) detector device in a critical buoyancy state, allowing it to be stably embedded in the ice layer during the freezing phase transition. Specifically:

[0061] The fiber Bragg grating multi-component detector I comprises three identical and orthogonally distributed main component unit structures. Each main component unit structure comprises an annular base 13, six multi-cantilever beam structures 11 evenly distributed along the circumference of the annular base 13 and located in the same horizontal plane, FBGs 12 mounted on each of the six cantilever beam structures 11, and an arc-shaped proof mass 10. Specifically, the bottoms of the annular bases 13 on the three main component unit structures are fixedly connected to the tops of rigid support rods 8; the ends of the rigid support rods 8 are embedded at a certain angle into the side of a cylindrical fixed base 9; the bottom of the cylindrical fixed base 9 is fixedly connected to a disc-shaped mounting platform 2 via bolts; the disc-shaped mounting platform 2 can be provided with a transmission hole for optical fiber access. Two positive and negative FBGs 12 are fixed between the annular base 13 and the arc-shaped proof mass 10 as vibration sensing units. The FBGs 12 are fiber Bragg gratings. The negative FBG 12 serves as a reference grating to eliminate interference from the external ambient temperature while amplifying the fiber Bragg grating multi-component detector's ability to pick up vibration signals.

[0062] Furthermore, the annular base 13 is a hemispherical arch structure and is provided with six mounting slots for fixing the cantilever beam structure.

[0063] Furthermore, the axis of the rigid support rod 8 coincides with the center normal of the annular base 13. This means that the bottoms of the annular bases 13 on the three main component units are perpendicularly connected to the rigid support rod 8 and secured with bolts. The three rigid support rods 8 are orthogonal to each other and are embedded in the cylindrical fixed base 9 at an angle of 45 degrees.

[0064] Furthermore, the cantilever beam structure 11 is a flat, curved structure, with its fixed end horizontally and non-angledly embedded in a corresponding mounting groove of the annular base 13. The free end extends radially from the annular base 13, with the outermost arc-shaped mass 10 mounted. The cantilever beam structure 11 has grooves on both the front and back sides for embedding the FBG 12, which is fixed by gluing.

[0065] Furthermore, six cantilever beam structures 11 are distributed in the same detection plane in a circular array with equal spacing at an angle of 60°, and the overall petal-shaped radiation topology structure can simultaneously obtain all-round vibration signals in the corresponding plane, and each main component unit structure can simultaneously output 6 channels of low-frequency dynamic response data.

[0066] Furthermore, for each main component unit structure, a total of 12 FBGs 12 fixed on the six cantilever beam structures 11 are connected end to end through optical fibers, used in cascade, and encapsulated into the groove of the annular base 13 by epoxy resin.

[0067] The mounting base II includes a shell 1, a disc-shaped mounting platform 2, an annular limiting structure 3, a cylindrical tubular body 4, a wire outlet hole 5, and a transmission optical cable 6. Specifically: the shell 1 is a hard hemispherical transparent shell, and the inner wall of the bottom is provided with an annular inner protrusion, which serves as an annular limiting structure 3 for fixing the shell 1 on the disc-shaped mounting platform 2, and at the same time, an epoxy resin filling layer is reserved for the packaging of the fiber optic Bragg grating multi-component detector I; the fiber optic Bragg grating multi-component detector I is placed in the shell 1 and is connected to the disc-shaped mounting platform 2 through a cylindrical fixed base 9; the cylindrical tubular body 4 is a structure with a hollow interior and filled at both ends, the upper axial end of which is fixedly connected to the disc-shaped mounting platform 2, and the lower axial end is connected to the hemispherical solid counterweight block 7, and is provided with a wire outlet 5 for leading out a transmission optical cable 6; the optical fiber tail of the cascaded FBG12 on each main component unit structure is fused with the transmission optical cable 6 passing through the center of the disc-shaped mounting platform 2 and the cylindrical tubular body 4. The transmission optical cable 6 is led out from the wire outlet 5, and the far end is connected to the optical fiber demodulation system to collect sensor signals.

[0068] Furthermore, the center of the hemispherical solid counterweight 7 is collinear with the geometric center of the cylindrical fixed base 9 along the direction of gravity. The hemispherical solid counterweight 7 is removably fixed to the bottom of the cylindrical tubular body 4 by bolts. By replacing the hemispherical solid counterweight 7 with a different model, the depth of the multi-component fiber Bragg grating detector device in water can be changed.

[0069] Acceleration is a crucial parameter used by detectors to measure vibration signals. Generally, the center wavelength offset of a standard single-component fiber Bragg grating (FBG) detector exhibits a linear relationship with the acceleration of the measured vibration signal. However, due to interdimensional coupling during vibration signal pickup in multi-component fiber Bragg grating (FBG) detectors, this phenomenon results in a complex nonlinear relationship between the detector's FBG center wavelength offset signal and the measured acceleration. Therefore, an effective nonlinear decoupling method is required to ensure the proper operation of multi-component fiber Bragg grating (FBG) detectors.

[0070] Any main component unit structure of the detector can be fixed on the vibration table according to the original installation position of the detector, and a certain range of acceleration values with the same step length (such as the acceleration value range of , the step size is , the range is limited according to the actual situation of elastic waves generated by ice cracks), and the corresponding relationship is obtained Then, the above experiment is repeated by increasing the number of cantilever beams to obtain the measured acceleration values, and the corresponding relationship is obtained:

[0071]

[0072] Then the obtained measurement value is brought into the BP neural network for training to obtain the decoupling model. Among them, the center wavelength offset value As the input layer of the neural network, the six-component center wavelength offset values in the cantilever beam structure group The six nodes corresponding to the input layer. As the output layer of the BP neural network, the six-dimensional measurement value a corresponds to the six nodes of the output layer. Finally, the three principal component units are increased to two and then three according to the installation position, and the above experimental operation is repeated to complete the inter-dimensional decoupling.

[0073] A multi-component fiber Bragg grating detection method for ice crack positioning is implemented based on the above-mentioned multi-component fiber Bragg grating detection device and is used to determine the direction and distance of the ice crack. The multi-component fiber Bragg grating detection device obtains the vibration signal through FBG12 and transmits it to the acquisition system, reads the vibration signal in real time and records it; selects the data in the n-segment time window of different principal component unit structures for coordinate transformation and covariance matrix analysis to determine the source of the maximum polarization direction of the vibration signal; uses the distance positioning algorithm to determine the specific position of the ice crack in this direction; uses the Bayesian method to optimize the measurement results through multi-path signal feedback information; and uses the distance positioning algorithm to determine the specific position of the ice crack in this direction. Specifically, it includes the following steps:

[0074] S1: Multi-component vibration signal acquisition. First, a vibration signal is acquired using a fiber Bragg grating (FBG) multi-component detector. According to the structure of the fiber Bragg grating (FBG) multi-component detector, each principal component unit can acquire 12 vibration signals, for a total of 36 vibration signals, primarily based on three principal components. Excluding the channel corresponding to the reference FBG 12 on the reverse side of the cantilever beam structure 11, 18 vibration signals of different components are ultimately acquired.

[0075] S2: Determine the source propagation direction based on polarization analysis. When a rupture causes the particles in the surrounding medium to vibrate, the trajectory of the generated vibration signal often needs to be represented by a complex spatial curve. This curve can be approximately fitted into an ellipsoid (a wave with an ellipsoidal trajectory is called an ellipsoidal polarized wave). The maximum polarization direction of the ellipsoidal polarized wave is solved by the polarization analysis method to determine the orientation of the source. Polarization analysis is performed on the vibration signal collected by the fiber Bragg grating multi-component detector to determine the direction of the source. The polarization analysis and source propagation direction determination method can be divided into the following sub-steps:

[0076] s200: Detector data correction. The present invention divides the vibration signals of 18 components collected by the three main component unit structures into According to the position of FBG12, 18 channels of signals can be set as three types. , , Since it is difficult to ensure that the direction of the main component unit of the fiber Bragg grating multi-component detector is consistent with the geographic rectangular coordinate system during structural design and on-site installation, The direction is consistent. In order to facilitate the subsequent data processing, the collected 18-channel data needs to be corrected. The corrected three-component data is consistent with the data in the geographic rectangular coordinate system in the picking direction. For the data collected by different FBG12s, the specific rotation correction algorithm is performed according to the principal component unit structure of each location. It can be expressed as follows:

[0077]

[0078] Where, azimuth , pitch angle , roll angle Corresponding to different main component units in fiber Bragg grating multi-component detector 、 、 The angle of rotation about the X-axis, Y-axis, and Z-axis of the geographic rectangular coordinate system. , pitch angle , roll angle All of them are obtained through field measurements. The present invention is installed at 45° when assembling the main component unit structure, so the azimuth angle can be set here. , pitch angle , roll angle is 45°.

[0079] S201: Construct a multi-component data matrix R. Take the data points of each cantilever beam structure 11 in different principal component unit structures within n time windows at the same time interval. According to the cantilever beam structure, the 18 signals collected within n time windows can be combined into a 6n×3 multi-component data matrix R:

[0080]

[0081] in,( , , ) represents the vibration signal picked up by any cantilever beam structure 11 in each principal component unit structure within the first time window; ( , , ) represents the vibration signal picked up by any cantilever beam structure 11 except the cantilever beam structure 11 just collected in each principal component unit structure in the first time window; and so on, ( , , ) indicates that in each principal component unit structure within the nth time window, only the vibration signal picked up by the cantilever beam structure 11 remains uncollected.

[0082] s202: Use the R matrix to construct the covariance matrix P. Calculate the covariance matrix of the matrix R and obtain a 3×3 three-component data matrix P:

[0083]

[0084] Where, 、 、 Represent the data in the tth row and jth column in the R matrix, t, j = 1, 2, 3 respectively.

[0085] S203: Solve the matrix eigenvector to determine the source direction. Use the data points in the n time windows to perform characteristic analysis on the multi-component data matrix R, and obtain the eigenvectors and eigenvalues of the three-component data matrix P, where the largest eigenvalue The corresponding eigenvector is When the vibration signal is linearly polarized, the multi-component data matrix R has only one non-zero eigenvalue, so the corresponding eigenvector can represent the direction of the wave source. In practical applications, the vibration signal is polarized throughout the entire three-dimensional space. In this case, it is believed that the main energy source of the ice crack is concentrated on the largest eigenvalue, thereby determining the azimuth of the earthquake source in space. and incident angle :

[0086]

[0087] in, represents the first term of the eigenvector; represents the second term of the eigenvector; represents the third term of the eigenvector.

[0088] S3: Determine the distance to the earthquake source. The distance is determined by using the time difference between the vibration signals reaching different cantilever beam structures 11, as follows:

[0089] Assume that a certain point source is S. When the vibration signal caused by the source S passes through any principal component unit structure, it will cause the cantilever beam structure 11 to vibrate successively. Therefore, there will be a wave path difference between the cantilever beam structures 11 of any principal component unit structure. , when the wave speed is known, the path difference The relationship between the wave velocity v is as follows:

[0090]

[0091] Among them, the time difference It is obtained by recording the vibration signal using a fiber Bragg grating multi-component detector.

[0092] According to the geometric relationship, the focal distance and path difference And the distance l between the two FBGs 12 satisfies the following relationship:

[0093]

[0094] Through the path difference The distance difference l can be used to preliminarily determine the focal distance .

[0095] In order to further determine the reliability of the results, the Bayesian method is used to optimize the results and improve the positioning progress.

[0096] For ice cracking events that are random and non-informative with little prior knowledge, the prior information is represented by a uniform distribution to represent the distribution of model parameters (Formula (13)):

[0097]

[0098] Here, since the model parameter is distance, the upper limit and lower limit correspond to the maximum and minimum values of the distance that can be measured by the detector. This parameter is determined through experiments.

[0099] For the same main component unit, since there is a cantilever beam that receives the signal first, according to the distance positioning principle, it can be known that five distance signals can be received within a specific time window. , the likelihood function can be constructed based on the results measured by the detector The energy release or ice loss from ice calving events exhibits a positive right-skewed distribution (i.e., most calving events are small, while a few extreme events are extremely large). The gamma distribution is more consistent with actual observations. The likelihood function can be assumed to be in the following form (Formula (14)):

[0100]

[0101] in, Represents one of the five received distances, i = 1, 2, 3, 4, 5. k is a shape parameter obtained through specific experiments and simulation experiments. Then, the likelihood functions obtained from the distance results measured by multiple FBG12s in the principal component unit are multiplied to obtain the joint likelihood function as shown in formula (15):

[0102]

[0103] Combining prior information and observation data, the latest probability distribution of the earthquake source location is obtained as shown in formula (16):

[0104]

[0105] When filtering out clutter, the posterior distribution function can be used Generate a probability cloud map related to distance to provide more accurate information for ice cracking, and optimize geometric positioning through probabilistic means to assist decision-making.

[0106] The present invention aims to solve the problem of being unable to accurately locate ice cracks with a small number of geophones in extreme environments. It uses a self-designed multi-component geophone structure to solve the problem of ice crack location using a single geophone.

[0107] The above-described embodiments merely express the implementation methods of the present invention, but should not be understood as limiting the scope of the present invention. It should be pointed out that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, which all fall within the scope of protection of the present invention.

Claims

1. A multi-component fiber Bragg grating detector for ice crack location, characterized in that: The multi-component fiber Bragg grating detector device comprises a fiber Bragg grating multi-component detector I, a mounting base II, and a counterweight III; the mounting base II comprises a shell (1), a disc-shaped mounting base (2), an annular limiting structure (3), a cylindrical tubular body (4), a wire outlet (5), and a transmission optical cable (6); specifically, an annular inner protrusion is provided on the inner wall of the bottom of the shell (1), which serves as an annular limiting structure (3) for fixing the shell (1) on the disc-shaped mounting base (2), and an epoxy resin filling layer is reserved for packaging the fiber Bragg grating multi-component detector I; the fiber Bragg grating multi-component detector I is placed in the shell (1) and is connected to the disc-shaped mounting base (2) through a columnar fixing base (9); the cylindrical tubular body (4) is a structure with a hollow interior and filled at both ends, and its axial upper end is fixedly connected to the disc-shaped mounting base (2), and its axial upper end is fixedly connected to the disc-shaped mounting base (2). The lower end is connected to a hemispherical solid counterweight (7), and is provided with a wire outlet (5) for leading out a transmission optical cable (6); the tail of the optical fiber of the cascaded FBG (12) on each main component unit structure is fused with the transmission optical cable (6) passing through the center of the disc-shaped mounting platform (2) and arranged inside the cylindrical tubular body (4); the transmission optical cable (6) is led out from the wire outlet (5), and the far end is connected to the optical fiber demodulation system to collect the sensing signal; the counterweight III is a hemispherical solid counterweight (7); the fiber Bragg grating multi-component detector I includes a rigid support rod (8), a columnar fixed base (9), an arc-shaped mass block (10), a cantilever beam structure (11), an FBG (12), and an annular base (13); when in use, the bottom counterweight III is used to keep the multi-component fiber Bragg grating detector in a critical buoyancy state, and stably embed in the ice layer during the freezing phase transition; The fiber Bragg grating multi-component detector I comprises three main component unit structures of identical structure and orthogonal distribution, each main component unit structure comprising an annular base (13), six multi-cantilever beam structures (11) uniformly distributed along the circumference of the annular base (13) and located on the same horizontal plane, FBGs (12) respectively mounted on the six cantilever beam structures (11), and an arc-shaped mass block (10); The center of the hemispherical solid counterweight (7) and the geometric center of the cylindrical fixed base (9) are arranged collinearly along the direction of gravity.

2. The multi-component fiber Bragg grating detection device for ice crack positioning according to claim 1, characterized in that: In the fiber Bragg grating multi-component detector I: The bottoms of the annular bases (13) on the three main component unit structures are fixedly connected to the tops of the rigid support rods (8); the ends of the rigid support rods (8) are embedded in the side surfaces of the columnar fixed bases (9) at a certain angle; The bottom of the columnar fixed base (9) is fixedly connected to the disc-shaped mounting platform (2); the disc-shaped mounting platform (2) is provided with a transmission hole for optical fiber access; Two positive and negative FBGs (12) are fixed between the annular base (13) and the arc-shaped mass block (10) as vibration sensing units, wherein the FBG (12) is a fiber Bragg grating, and the negative FBG (12) is used as a reference grating to eliminate the interference of the external environment temperature and amplify the ability of the fiber Bragg grating multi-component detector to pick up vibration signals.

3. The multi-component fiber Bragg grating detection device for ice crack positioning according to claim 2, characterized in that: The annular base (13) is a hemispherical arched structure and is provided with six mounting grooves for fixing the cantilever beam structure (11); the cantilever beam structure (11) is an arc-shaped flat structure, the fixed end of which is horizontally and non-angledly embedded in the mounting groove corresponding to the annular base (13), and the free end extends radially from the annular base (13), and the outermost side is provided with an arc-shaped mass block (10); the front and back sides of the cantilever beam structure (11) are both provided with grooves for embedding the FBG (12).

4. The multi-component fiber Bragg grating detection device for ice crack positioning according to claim 2, characterized in that: Six cantilever beam structures (11) are distributed in a same detection plane in a circular array with equal spacing at an angle of 60 degrees, and the overall structure presents a petal-shaped radiation topology, which can simultaneously obtain all-round vibration signals in the corresponding plane, and each main component unit structure can simultaneously output 6 channels of low-frequency dynamic response data.

5. The multi-component fiber Bragg grating detection device for ice crack positioning according to claim 2, characterized in that: The axis of the rigid support rod (8) coincides with the center normal of the annular base (13), and the bottoms of the annular bases (13) on the three main component unit structures are vertically fixedly connected to the rigid support rod (8); the three rigid support rods (8) are orthogonal to each other and are embedded in the columnar fixed base (9) at an angle of 45°.

6. The multi-component fiber Bragg grating detection device for ice crack location according to claim 1, characterized in that: Each main component unit structure comprises six cantilever beam structures (11) on which a total of 12 FBGs (12) are fixed, which are connected end to end via optical fibers, used in cascade, and are encapsulated in a groove of a ring base (13) via epoxy resin.

7. The multi-component fiber Bragg grating detector for ice crack location according to claim 1, characterized in that: The shell (1) is a hard hemispherical transparent shell; the hemispherical solid counterweight (7) is fixed to the bottom of the cylindrical tubular body (4) and is detachable; by replacing the hemispherical solid counterweight (7) with different models, the depth of the multi-component fiber grating detector device in water can be changed.

8. A multi-component fiber Bragg grating detection method implemented based on the multi-component fiber Bragg grating detection device according to any one of claims 1 to 7, for determining the direction and distance of ice cracks, characterized in that: The multi-component fiber Bragg grating detector device acquires a vibration signal through an FBG (12) and transmits it to an acquisition system, reads the vibration signal in real time and records it; selects data in n time windows of different principal component unit structures to perform coordinate transformation and covariance matrix analysis to determine the source of the maximum polarization direction of the vibration signal; uses a distance positioning algorithm to determine the position of the ice crack in the direction; uses a Bayesian method to optimize the measurement result through multi-path signal feedback information; and uses the distance positioning algorithm to determine the determined position of the ice crack in the direction. The method comprises the following steps: S1: Obtain vibration signals through fiber Bragg grating multi-component detector I; S2: Determine the source propagation direction based on polarization analysis method; s200: detector data correction; s201: construct multi-component data matrix R; s202: Use the R matrix to construct the covariance matrix P; s203: Solve the matrix eigenvector to determine the source direction; S3: Determine the distance to the earthquake source; use the time difference between the vibration signal reaching different cantilever beam structures (11) to perform distance positioning; S4: Use probabilistic methods to optimize distance results; use Bayesian methods to optimize results and improve positioning accuracy.

9. A multi-component fiber Bragg grating detection method according to claim 8, characterized in that: The specific steps are: S1: Obtain vibration signals through fiber Bragg grating multi-component detector I; Each main component unit structure of the fiber Bragg grating multi-component detector I can obtain 12 vibration signals, and a total of 36 vibration signals with 3 main components as the main components are obtained. Excluding the channel corresponding to the reference FBG (12) on the back side of the cantilever beam structure (11), 18 vibration signals of different components are finally obtained. S2: Determine the source propagation direction based on polarization analysis method; s200: Detector data correction; the vibration signals of 18 components collected by the three main component unit structures are divided into Three categories, according to the position of different cantilever beam structures (11), 18 signals are set as , , ; The 18 collected data are corrected. The corrected three-component data are consistent with the data in the geographic rectangular coordinate system in the picking direction. For the data collected by different FBGs (12), the specific rotation correction algorithm is expressed as follows according to the principal component unit structure of each data: ， Where, azimuth , pitch angle , roll angle Corresponding to different main component units in fiber Bragg grating multi-component detector 、 、 The angle of rotation about the X, Y, and Z axes of the geographic rectangular coordinate system; azimuth , pitch angle , roll angle All of them are obtained through field measurements. The present invention is installed at 45° when assembling the main component unit structure, so the azimuth angle can be set here. , pitch angle , roll angle is 45°; s201: Construct a multi-component data matrix R; take the data points of each cantilever beam structure (11) in different principal component unit structures within n time windows at the same time interval, and form a 6n×3 multi-component data matrix R with the 18 signals collected within the n time windows: ， in,( , , ) represents the vibration signal picked up by any cantilever beam structure (11) in each principal component unit structure within the first time window; ( , , ) represents the vibration signal picked up by any cantilever beam structure (11) except the cantilever beam structure (11) just collected in each principal component unit structure in the first time window; and so on, ( , , ) indicates that in each principal component unit structure within the nth time window, only the vibration signal picked up by the cantilever beam structure (11) remains uncollected; s202: Use the R matrix to construct the covariance matrix P; calculate the covariance matrix of the matrix R to obtain a 3×3 three-component data matrix P: ， Where, 、 、 Represent the data of the t-th row and j-th column in the R matrix, t, j = 1, 2, 3 respectively; s203: Solve the matrix eigenvector to determine the source direction; use the data points in the n time window to perform characteristic analysis on the multi-component data matrix R, and obtain the eigenvectors and eigenvalues of the three-component data matrix P, where the largest eigenvalue The corresponding eigenvector is When the vibration signal is linearly polarized, the multi-component data matrix R has only one non-zero eigenvalue, so the corresponding eigenvector can represent the direction of the wave source. In practical applications, the main energy source of ice cracks is concentrated on the largest eigenvalue, thereby determining the azimuth of the earthquake source in space. and incident angle : ， in, represents the first term of the eigenvector; represents the second term of the eigenvector; represents the third term of the eigenvector; S3: Determine the distance to the earthquake source; use the time difference between the vibration signal reaching different cantilever beam structures (11) to perform distance positioning, as follows: Assume that a certain point source is S. When the vibration signal caused by the source S passes through any principal component unit structure, it will cause the cantilever beam structure (11) to vibrate successively. Therefore, there will be a wave path difference between the cantilever beam structures (11) of any principal component unit structure. , when the wave speed is known, the path difference The relationship between the wave velocity v is as follows: ， Among them, the time difference It is obtained by recording the vibration signal with a fiber Bragg grating multi-component detector; Since the distance between the earthquake source S and any two FBGs (12) arranged on the cantilever beam structures (11) in any principal component unit structure is much greater than the spacing between the FBGs (12) arranged on any two cantilever beam structures (11), the angle between the earthquake source S and the lines connecting the two FBGs (12) is small. The position of the FBG (12) closer to the earthquake source is taken as point A, and its distance is set to , the location of FBG (12) which is farther from the earthquake source is point B, then its distance is ,in represents the wave path difference; set a point O on the path between the earthquake source S and the FBG (12) far away from the earthquake source, so that the distance from point O to the earthquake source is also , then the triangular area enclosed by the earthquake source S, point B, and point O can be approximately regarded as an isosceles triangle with a very small vertex angle and a base angle of 90°, satisfying the following equation: ， Therefore, the path difference The distance l between the two FBGs (12) satisfies the following equation (7): ， in, represents the angle between the earthquake source S and the area enclosed by the two FBGs (12) (A, B); According to the law of cosines, the triangle formed by the source S and the two FBGs (12) satisfies the following equation (8): ， Then through the path difference The source distance is determined by the distance difference l ; For any principal component unit structure, there is always one FBG (12) embedded in the six cantilever beam structures (11) thereon that first picks up the vibration signal and sets it as the reference grating. Then, five distance results are obtained by the five distance differences and five wave path differences between the other FBGs (12) on the six cantilever beam structures (11) and the reference grating. The five distance differences are expressed as , the five path differences are expressed as , the distance results are expressed as ; S4: Optimize distance results using probabilistic methods; First, the monitoring area of ice sheet rupture is defined, and the number of ice sheet ruptures in the monitoring area is counted to obtain the prior probability function Secondly, the distance results measured by each principal component unit of the fiber Bragg grating multi-component detector are compared with the actual ice crack results observed and a likelihood function is constructed based on statistical laws. Finally, the likelihood functions obtained from the distance measurements of the 18 cantilever beam structures (11) in the principal component unit structure are multiplied to obtain the joint likelihood function, as shown in formula (9): ， Combining the prior probability function and the observed distance results, the latest probability distribution of the earthquake source location is obtained, as shown in formula (10): ， When the clutter is filtered out, the posterior distribution function Generate distance-dependent probability cloud maps to provide accurate information on ice cracking.

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