Multi-source thunder view data fusion method and device for pumped storage power station

Abstract

The invention discloses a multi-source thunder view data fusion method and device for a pumped storage power station, and relates to the technical field of geological disaster monitoring, and the method comprises the steps: obtaining first integrated data, and carrying out the preprocessing of the first integrated data; constructing a cross-physics field coupling model based on the preprocessed first comprehensive data, and extracting a depolarization ratio and echo coherence of a crack region according to the cross-physics field coupling model; generating a crack electromagnetic feature vector set based on the depolarization ratio of the crack region and the echo coherence; and calculating a crack depth parameter according to the first comprehensive data, and adjusting a scanning interval based on the crack depth parameter. According to the method, the cross-physics field coupling model is constructed to quantify and associate the electromagnetic features and the acoustic features, the two-parameter joint judgment rule is adopted, the threshold value is dynamically adjusted to generate the reliable crack electromagnetic feature vector set, and the misjudgment rate is remarkably reduced; and finally, full-process accurate management and control from identification to early warning of the pumped storage power station crack is realized.

Description

Technical Field

[0001] This invention relates to the field of geological disaster monitoring technology, and in particular to a method and device for fusing multi-source lightning and visual data from a pumped storage power station. Background Technology

[0002] The slopes of pumped storage power station reservoirs are affected by periodic water level fluctuations, and the initiation and propagation of rock fissures are highly concealed and sudden. Current monitoring of pumped storage power station reservoir slopes mainly relies on single sensors (such as optical cameras or simple radar scans), which are difficult to capture the propagation behavior of tiny fissures in the environment of rock swelling and shrinking caused by water circulation. Existing technologies have significant shortcomings: traditional millimeter-wave radar imaging cannot distinguish the true scattering characteristics of fissures from the interference of water film reflection on the rock surface; ground acoustic wave monitoring operates in isolation, and the spatiotemporal alignment error with radar data exceeds 500ms; the fissure depth evolution model relies on empirical formulas, and the response to sudden rock mass instability lags by ≥3 hours. Especially under conditions of heavy rainfall or sudden water level changes, the existing methods have a high false negative rate, which seriously threatens the safe operation of the power station.

[0003] However, the common solutions currently available have many drawbacks, including: traditional methods use single-field monitoring, which cannot establish a correlation between electromagnetic scattering and mechanical evolution; existing technologies use fixed threshold triggering, and the scanning cycle of existing technologies is fixed, without being associated with crack risk levels. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the problems existing in the current method and device for multi-source radar visual data fusion of pumped storage power stations, the present invention is proposed.

[0006] Therefore, the purpose of this invention is to provide a multi-source lightning data fusion method and device for pumped storage power stations, which is applicable to solving the problems of traditional methods using single-field monitoring, which cannot establish the correlation between electromagnetic scattering and mechanical evolution, existing technologies using fixed threshold triggering, and existing technologies having fixed scanning cycles and not associating crack risk levels.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a method for fusing multi-source radar-visual data of a pumped storage power station, comprising: acquiring first comprehensive data and preprocessing the first comprehensive data; constructing a cross-physics coupling model based on the preprocessed first comprehensive data, and extracting the depolarization ratio and echo coherence of the crack region according to the cross-physics coupling model; generating a crack electromagnetic feature vector set based on the crack region depolarization ratio and echo coherence; calculating crack depth parameters based on the first comprehensive data, and adjusting the scanning interval based on the crack depth parameters.

[0008] As a preferred embodiment of the multi-source radar and acoustic data fusion method for pumped storage power stations described in this invention, the first integrated data includes radar data and ground acoustic wave data; the radar data includes the horizontal-vertical to polarization scattering coefficient ratio; the ground acoustic wave data includes the crack surface acoustic wave diffraction time series; the radar data is acquired through a 94GHz MIMO radar fully polarized scattering matrix; and the ground acoustic wave data is acquired through a distributed microseismic sensor array.

[0009] As a preferred embodiment of the multi-source radar-visual data fusion method for pumped storage power stations described in this invention, the following steps are taken to construct a cross-physics coupling model based on the preprocessed first comprehensive data: The preprocessed first comprehensive data is aligned to a spatiotemporal reference; the scattering disorder of electromagnetic waves on the rough crack surface is quantified by extracting the depolarization ratio parameter of the crack region; the signal phase instability caused by the crack is characterized by extracting the radar echo coherence parameter; a cross-physics coupling model is constructed by combining the depolarization ratio parameter and the radar echo coherence parameter; and the crack propagation nonlinear index is obtained based on the cross-physics coupling model.

[0010] As a preferred embodiment of the multi-source radar-visual data fusion method for pumped storage power stations described in this invention, the specific content of generating the crack electromagnetic feature vector set is as follows: when the depolarization ratio is greater than a first threshold and the echo coherence is less than a second threshold, it is determined that there is a valid crack in the region, and a crack electromagnetic feature vector set is generated; if the depolarization ratio is less than or equal to the first threshold, or the echo coherence is greater than or equal to the second threshold, it is determined that the region is a non-crack region or invalid interference, and such regions are marked and removed.

[0011] As a preferred embodiment of the multi-source radar-visual data fusion method for pumped storage power stations described in this invention, the calculation of crack depth parameters based on the first comprehensive data includes the following steps: inverting the dielectric constant of the rock mass based on radar data; obtaining the reference acoustic velocity of the rock mass type by combining the rock mass type parameters in the regional geological survey report; correcting the reference acoustic velocity by introducing radar echo coherence; and constructing a nonlinear mapping function by calling the output results of the cross-physics coupling model to obtain the crack depth parameters.

[0012] As a preferred embodiment of the multi-source radar-visual data fusion method for pumped storage power stations described in this invention, the specific content of the crack propagation nonlinear index is as follows: when the crack propagation nonlinear index is greater than the third threshold, it indicates that the crack has entered the nonlinear accelerated propagation stage, the propagation speed increases with time, and the propagation morphology changes abruptly due to rock stress concentration and crack penetration factors; when the crack propagation nonlinear index is less than or equal to the third threshold, it indicates that the crack propagation is in a stable stage, the propagation speed and morphology change slowly with time, the risk of crack damage to the rock mass structure is within a controllable range, and the conventional monitoring mode is maintained.

[0013] As a preferred embodiment of the multi-source radar-visual data fusion method for pumped storage power stations described in this invention, the specific content of adjusting the scanning interval based on the crack depth parameter is as follows: when the crack propagation nonlinearity index is greater than the third threshold, the slope instability coefficient calculation is activated; combining the spatial distribution of the slope instability coefficient and the crack depth parameter, a slope disaster probability cloud map is generated; for high-risk areas, the radar scanning interval is shortened to achieve encrypted monitoring; for low-risk areas, the baseline scanning cycle is maintained, and the monitoring resources are adaptively allocated through the crack depth parameter.

[0014] Secondly, to further solve the above-mentioned technical problems, the present invention provides a multi-source radar-visual data fusion device for a pumped storage power station, comprising: a data acquisition module for acquiring first comprehensive data and preprocessing the first comprehensive data; a model building module for constructing a cross-physics coupling model based on the preprocessed first comprehensive data, and extracting the depolarization ratio and echo coherence of the crack region according to the cross-physics coupling model; a vector set generation module for generating a crack electromagnetic feature vector set based on the crack region depolarization ratio and echo coherence; and an interval adjustment module for calculating crack depth parameters based on the first comprehensive data and adjusting the scanning interval based on the crack depth parameters.

[0015] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements any step of the multi-source radar-visual data fusion method for a pumped storage power station as described in the first aspect of the present invention.

[0016] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the multi-source radar-visual data fusion method for a pumped storage power station as described in the first aspect of the present invention.

[0017] The beneficial effects of this invention are as follows: This invention quantifies and correlates electromagnetic and acoustic features by constructing a cross-physics field coupling model, and improves the accuracy of crack parameter inversion by combining dynamically corrected rock mass sound velocity factors; it adopts a dual-parameter joint judgment rule and dynamically adjusts the threshold to generate a reliable crack electromagnetic feature vector set, which significantly reduces the false judgment rate; it triggers risk assessment by crack propagation nonlinear exponent, and dynamically adjusts the scanning interval by combining the slope instability coefficient, thereby realizing intensified monitoring of high-risk areas and resource optimization of low-risk areas, and can adapt to different geological conditions. Ultimately, it achieves precise control of cracks in pumped storage power stations from identification to early warning, providing high-precision and high-efficiency technical support for the safe operation of the power station. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart illustrating the implementation of the present invention in Example 1.

[0019] Figure 2 This is a flowchart of the cross-physics coupling model in Example 1. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1 Reference Figure 1 and Figure 2 This is the first embodiment of the present invention, which provides a method for fusing multi-source radar and visual data of a pumped storage power station, including the following steps: S1: Obtain the first comprehensive data and preprocess the first comprehensive data.

[0024] Preferably, the first comprehensive data includes radar data and ground acoustic wave data.

[0025] Furthermore, radar data includes the ratio of horizontal to vertical to polarization scattering coefficients; Furthermore, the ground acoustic wave data includes a time series of acoustic wave diffraction on the crack surface; Furthermore, the radar data was acquired using the 94GHz MIMO radar fully polarimetric scattering matrix; Furthermore, the ground acoustic wave data is acquired through a distributed microseismic sensor array.

[0026] It should be noted that the 94GHz MIMO radar fully polarized scattering matrix is ​​the core data foundation for obtaining the electromagnetic characteristics of cracks in the geological disaster monitoring of pumped storage power stations, and it operates in the millimeter wave band with a wavelength of 3.2mm.

[0027] Specifically, the preprocessing of radar data in the first integrated data includes noise removal and interference suppression, scattering matrix calibration, and data format conversion; the preprocessing of ground acoustic wave data in the first data includes filtering and noise reduction, time difference correction, and effective signal extraction.

[0028] For example, in the slope monitoring of a pumped storage power station, radar data containing the horizontal-vertical polarization scattering coefficient ratio is obtained through a 94GHz MIMO radar fully polarized scattering matrix. At the same time, ground acoustic wave data of the crack surface acoustic wave diffraction time series is collected using a distributed microseismic sensor array to form the first comprehensive data. The radar data is subjected to noise removal (removing atmospheric interference signals), scattering matrix calibration (eliminating equipment channel errors), and format conversion (converting to a computable scattering coefficient matrix). The ground acoustic wave data is subjected to filtering and denoising (wavelet denoising to eliminate environmental vibration interference), time difference correction (unifying the sensor time reference), and effective signal extraction (preserving the crack diffraction wave time series) to complete the preprocessing.

[0029] S2: Construct a cross-physics coupling model based on the preprocessed first comprehensive data, and extract the depolarization ratio and echo coherence of the crack region according to the cross-physics coupling model.

[0030] Preferably, a cross-physics coupling model is constructed based on the preprocessed first comprehensive data, and the specific steps are as follows: The preprocessed first composite data is aligned with a spatiotemporal reference. It should be noted that the specific content of the spatiotemporal reference alignment is to use the high-precision GPS clock signal to unify the time reference of the radar and microseismic sensors; and to map the positions of the radar scanning network and acoustic sensor to a unified geological coordinate system through a three-dimensional coordinate transformation matrix.

[0031] The scattering disorder of electromagnetic waves on the rough crack surface is quantified by extracting the depolarization ratio parameter of the crack region. The specific formula is as follows:

[0032] In the formula, The depolarization ratio quantifies the scattering disorder of electromagnetic waves on the crack surface; the larger the value, the more disordered the scattering. The cross-polarization scattering coefficient for horizontal transmission and vertical reception; The same polarization scattering coefficient for horizontal transmission and horizontal reception; The same polarization scattering coefficients for vertical transmission and vertical reception are obtained through the fully polarized scattering matrix of a 94GHz MIMO radar. It should be noted that the depolarization ratio parameter ( The core function of the scattering of electromagnetic waves on the surface of a rough crack is to quantify the degree of disorder in the scattering of electromagnetic waves. The larger the value, the more disordered the scattering of electromagnetic waves in the region, which directly reflects the physical characteristics of the rough surface and disordered polarization state of the crack.

[0033] The degree of signal phase instability caused by the crack is characterized by extracting radar echo coherence parameters. The specific formula is as follows:

[0034] In the formula, Echo coherence characterizes the degree of phase instability caused by cracks; the smaller the value, the more obvious the phase continuity is disrupted. For the first The scattering coefficient of each sampling point reflects the electromagnetic wave scattering intensity at that sampling point; It is the conjugate complex number of the scattering coefficient of the next sampling point, used to calculate the phase correlation between adjacent sampling points, reflecting the phase continuity of the signal; To determine the number of sampling points, the sample size for coherence calculation is determined to ensure the statistical reliability of the results; It should be noted that the radar echo coherence parameters ( The core function of the crack is to characterize the degree of signal phase instability caused by the crack. The smaller the value, the more obvious the signal phase continuity is destroyed, which is consistent with the blocking or disturbance effect of the crack discontinuity on the electromagnetic wave propagation path.

[0035] A cross-physics coupling model is constructed by combining the depolarization ratio parameter and the radar echo coherence parameter. The specific formula is as follows:

[0036] In the formula, The nonlinear index for crack propagation characterizes the nonlinear properties of crack propagation rate and morphology. It is a proportionality constant; The depolarization ratio quantifies the scattering disorder of electromagnetic waves on the crack surface; the larger the value, the more disordered the scattering. Echo coherence characterizes the degree of phase instability caused by cracks; the smaller the value, the more obvious the phase continuity is disrupted. It is a nonlinear exponent, calibrated based on geomechanical test data; The time series of acoustic wave diffraction on the crack surface collected by a distributed microseismic sensor array, representing the time difference of ground acoustic wave propagation. The standard time difference for sound wave propagation in an intact rock mass is the reference propagation time difference.

[0037] It should be noted that the input to the cross-physics coupling model is the preprocessed radar data and ground acoustic wave data; the output of the cross-physics coupling model is the key physical property parameters of the crack.

[0038] Furthermore, the crack propagation nonlinear index The specific details are as follows: When the crack propagation nonlinear exponent When the crack depth exceeds the third threshold, it indicates that the crack has entered the nonlinear accelerated propagation stage. The propagation speed shows a significant increasing trend over time, and the propagation morphology changes abruptly due to factors such as rock mass stress concentration and crack penetration, triggering the slope instability risk assessment process. This indicates that the crack depth has increased significantly in a short period of time, and monitoring needs to be strengthened. When the crack propagation nonlinear exponent When the value is less than or equal to the third threshold, it indicates that the crack propagation is in a stable stage, the propagation speed and morphology change slowly over time, there are no significant nonlinear abrupt changes, the risk of crack damage to the rock mass structure is within a controllable range, and it has not yet reached the level requiring an emergency response. The routine monitoring mode should be maintained, and the trend of crack propagation nonlinear index changes should be continuously tracked.

[0039] It should be noted that the third threshold is obtained by first simulating the propagation of cracks in different rock masses through indoor geomechanical tests to determine... The critical baseline values ​​for the transition from stability to acceleration are calculated (1.2~1.5 for hard rock mass and 0.8~1.0 for soft rock mass); this is then combined with historical disaster cases from similar power plants to invert the pre-disaster values. The value suddenly increases to a critical value, and the base value is adjusted by weighting; finally, the value is adjusted based on the actual field measurement. Dynamic fine-tuning of values ​​and rock mass stability status: If monitoring reveals that a certain area... If the value exceeds the initial third threshold but no significant signs of instability appear, appropriately increase the third threshold in this region (e.g., increase by 0.1~0.2); if If rock mass deformation accelerates when the value approaches the initial threshold, the third threshold is reduced (e.g., by 0.1 to 0.2), ultimately forming a third threshold that adapts to the geological conditions of the specific monitoring area. This ensures that the third threshold conforms to the mechanical evolution law of cracks and is adapted to the actual geological conditions, thereby ensuring the accuracy of the determination that cracks have entered the nonlinear accelerated propagation stage.

[0040] For example, the preprocessed radar and ground acoustic wave data are unified with a GPS high-precision clock as a time reference. Using a three-dimensional coordinate transformation matrix, the radar scanning network and acoustic sensor positions are mapped to a unified geological coordinate system, achieving spatiotemporal alignment. From the radar data, the depolarization ratio of the fracture region (e.g., calculated to be 0.4, quantifying the electromagnetic wave scattering disorder) and echo coherence (e.g., calculated to be 0.5, characterizing the signal phase instability) are extracted. Combined with the ground acoustic wave propagation time difference (e.g., monitored to be 0.6 ms, with a reference propagation time difference of 0.2 ms), a cross-physics coupling model is used to calculate the fracture propagation nonlinearity index (e.g., 1.2), thereby reflecting the nonlinear characteristics of the fracture propagation speed and morphology.

[0041] S3: Generate a set of electromagnetic feature vectors for cracks based on the depolarization ratio and echo coherence of the crack region.

[0042] Preferably, the specific content of generating the crack electromagnetic feature vector set is as follows: When the depolarization ratio is greater than the first threshold and the echo coherence is less than the second threshold, it is determined that there is an effective crack in the region, and a crack electromagnetic feature vector set is generated. If the depolarization ratio is less than or equal to the first threshold, or the echo coherence is greater than or equal to the second threshold, then the region is determined to be a non-crack region or invalid interference. Such regions are marked and removed to avoid interfering with the accuracy of the crack feature vector set.

[0043] Specifically, depolarization ratio ( This is used to quantify the scattering disorder of electromagnetic waves on a rough crack surface. A higher value indicates more disordered scattering of electromagnetic waves in that region, consistent with the characteristics of a rough crack surface that easily leads to disordered polarization states; echo coherence ( The value is used to characterize the degree of signal phase instability caused by cracks. The smaller the value, the more obvious the signal phase continuity is destroyed, which is consistent with the blocking or disturbance effect of crack discontinuity on the electromagnetic wave propagation path.

[0044] Specifically, non-cracked areas refer to areas with intact rock mass structures and no significant cracks, and their electromagnetic scattering characteristics are stable; invalid interference includes reflected signals from non-geological targets within the radar scanning range (such as metal parts of monitoring equipment and temporary construction facilities), or signal distortion caused by atmospheric humidity fluctuations and electromagnetic noise.

[0045] It should be noted that the crack electromagnetic feature vector set includes the real-time calculated value of the depolarization ratio, the real-time calculated value of the echo coherence, the horizontal-to-vertical polarization scattering coefficient ratio (extracted from the 94GHz MIMO radar fully polarized scattering matrix), the three-dimensional geological coordinates of the corresponding region (coordinates in a unified geological coordinate system aligned with a spatiotemporal reference), and key elements in the radar fully polarized scattering matrix. , , (Amplitude and phase information).

[0046] Specifically, the first threshold is determined based on the statistical value of the depolarization ratio of typical fractures in the target monitoring area of ​​the pumped storage power station, and dynamically adjusted in combination with regional geological conditions. For hard rock masses (such as granite and diorite), the background depolarization ratio is generally low (usually below 0.2) because the scattering characteristics of intact rock masses are stable. The first threshold is set to 0.3~0.4. If it is a weak interlayer or weathered rock layer, the background depolarization is relatively high due to the development of natural fractures. The first threshold is set to 0.4~0.5 to avoid misjudging natural stable fractures as effective fractures. The second threshold is determined based on the echo coherence benchmark value of the 94GHz MIMO radar in intact rock mass. It is dynamically adjusted by referring to the measured data of crack areas in similar projects and taking into account the electromagnetic interference in the monitoring environment: if the environment is stable, the second threshold is set to 0.6~0.7; if there is strong electromagnetic interference, the second threshold is set to 0.5~0.6 to eliminate the abnormal reduction in coherence caused by interference.

[0047] For example, for the monitoring area of ​​hard rock mass in a pumped storage power station, a first threshold for depolarization ratio is set to 0.35 and a second threshold for echo coherence is set to 0.6. If a certain area has a calculated depolarization ratio of 0.4 (greater than 0.35) and an echo coherence of 0.5 (less than 0.6), it is determined to be a valid fracture area. A fracture electromagnetic feature vector set is generated, which includes the depolarization ratio, echo coherence, horizontal-to-vertical polarization scattering coefficient ratio, three-dimensional geological coordinates (e.g., X=1200m, Y=800m, Z=500m), and key elements of the radar full polarization scattering matrix. For another area with a depolarization ratio of 0.3 (less than 0.35), it is marked as a non-fracture area and removed.

[0048] S4: Calculate the crack depth parameters based on the first comprehensive data, and adjust the scanning interval based on the crack depth parameters.

[0049] Preferably, the crack depth parameter is calculated based on the first comprehensive data, including the following steps: The dielectric constant of the rock mass is retrieved based on radar data, thereby reflecting the physical properties of the rock mass medium. Based on the rock mass type parameters in the regional geological survey report, the baseline acoustic velocity of this type of rock mass is obtained; Radar echo coherence is introduced to correct the reference acoustic velocity to compensate for the influence of rock mass heterogeneity and fractures on acoustic propagation, resulting in a rock mass acoustic velocity correction factor, the specific formula of which is as follows:

[0050] In the formula, This is a rock mass sound velocity correction factor, used to correct the baseline sound wave velocity to adapt to actual rock mass and fracture conditions. The reference acoustic velocity for similar rock masses was determined based on the regional geological survey report. The relative permittivity of the rock mass is obtained from the radar fully polarized scattering matrix; , The weighting coefficients are dynamically allocated based on the integrity of the rock mass. (Integrity rock mass) Large, cracked area big; The ground acoustic wave propagation correction index is calibrated using regional acoustic wave propagation test data. Depolarization ratio; For echo coherence; This refers to the time difference of sound wave propagation over the ground. Use the base propagation time difference; By calling the output of the cross-physics coupling model, a nonlinear mapping function is constructed to obtain the crack depth parameter, as shown in the following formula:

[0051] In the formula, The fracture depth parameter characterizes the vertical extension depth of the fracture in the rock mass; This is a rock mass sound velocity correction factor, used to correct the baseline sound wave velocity to adapt to actual rock mass and fracture conditions. The nonlinear index for crack propagation characterizes the nonlinear properties of crack propagation rate and morphology. This refers to the time difference of sound wave propagation over the ground. The reference propagation time difference.

[0052] Specifically, the details of adjusting the scanning interval based on the crack depth parameter are as follows: When the crack propagation nonlinearity index exceeds the third threshold, the slope instability coefficient calculation is activated, and the specific formula is as follows:

[0053] In the formula, This is the slope instability coefficient, reflecting the urgency of slope instability; The crack propagation nonlinear index reflects the contribution of crack propagation rate to instability risk; Crack density is the number of effective cracks per unit area, obtained statistically based on the crack electromagnetic feature vector set, reflecting the spatial density of cracks. The higher the density, the greater the risk. By combining the spatial distribution of slope instability coefficient and crack depth parameters, a slope disaster probability cloud map is generated. High-risk areas correspond to areas with large crack depth parameters and small slope instability coefficients. The specific formula for calculating the disaster probability is as follows:

[0054] In the formula, This represents the probability of a catastrophe. This is a proportional parameter; This is the slope instability coefficient; The critical instability coefficient is determined using historical landslide data. For high-risk areas, the radar scanning interval is shortened to achieve encrypted monitoring. The specific formula is as follows:

[0055] In the formula, The monitoring frequency is dynamically adjusted according to the radar scanning interval to achieve adaptive optimization of monitoring resources; The initial scanning interval of the radar system under normal monitoring conditions is used as the reference period and serves as the basic reference value for adjusting the scanning interval. The slope instability coefficient determines the adjustment range of the radar scanning interval. The smaller the interval, the shorter the monitoring frequency (for high-risk areas). For low-risk areas, a baseline scanning cycle is maintained, and monitoring resources are adaptively allocated through crack depth parameters to improve the timeliness of monitoring in high-risk areas.

[0056] It should be noted that the specific content of the adaptive allocation is as follows: the scanning interval for deep fracture zones is shortened to 1 / 3 to 1 / 2 of the baseline cycle, the sampling frequency of distributed microseismic sensors is increased (e.g., from 10Hz to 20Hz), and the priority of data transmission and analysis is improved; for low-risk areas with shallow fracture zones (D≤1m) and slope instability coefficient S≥critical value, the baseline scanning cycle and conventional sampling frequency are maintained to reduce unnecessary consumption of monitoring resources; at the same time, according to the dynamic changes of fracture depth parameters (e.g., the fracture depth in a certain area increases from 2m to 4m in a short period of time), the resource allocation strategy is updated in real time, and some resources originally used for low-risk areas (e.g., redundant sensors, computing power) are allocated to high-risk areas with sudden increases in depth, ensuring that monitoring resources are always focused on the fracture areas that pose the greatest threat to rock mass stability, maximizing resource utilization efficiency while ensuring monitoring accuracy.

[0057] For example, based on radar data, the relative permittivity of the rock mass is inverted (e.g., 5.8). Combined with the regional geological survey report, a baseline acoustic velocity (e.g., 3000 m / s) for similar rock masses is obtained. Radar echo coherence (e.g., 0.5) is introduced to correct the baseline acoustic velocity, resulting in a rock mass acoustic velocity correction factor (e.g., 2900 m / s). The crack propagation nonlinearity index (e.g., 1.2) output by the cross-physics coupling model is called to construct a nonlinear mapping function and calculate the crack depth parameter (e.g., 6.5 m). Because this index is greater than the third threshold (critical value of 1.2 for hard rock masses), slope instability assessment is activated: for high-risk areas, the radar scanning interval is shortened from the baseline 60 minutes to approximately 0.5 minutes according to the strategy (achieving intensified monitoring); for low-risk areas, the baseline scanning cycle is maintained, and monitoring resource allocation is adapted through crack depth parameters.

[0058] In summary, this invention constructs a cross-physics field coupling model to quantitatively correlate electromagnetic and acoustic features, and combines a dynamically corrected rock mass sound velocity factor to improve the accuracy of crack parameter inversion. It adopts a dual-parameter joint judgment rule and dynamically adjusts the threshold to generate a reliable set of crack electromagnetic feature vectors, significantly reducing the false judgment rate. By triggering risk assessment through the nonlinear exponent of crack propagation and dynamically adjusting the scanning interval in combination with the slope instability coefficient, it achieves intensified monitoring of high-risk areas and resource optimization of low-risk areas, and can adapt to different geological conditions. Ultimately, it realizes precise control of cracks in pumped storage power stations from identification to early warning, providing high-precision and high-efficiency technical support for the safe operation of the power station.

[0059] Example 2, an embodiment of the present invention, provides a multi-source radar-visual data fusion device for a pumped storage power station, comprising: a data acquisition module for acquiring first comprehensive data and preprocessing the first comprehensive data; a model building module for constructing a cross-physics coupling model based on the preprocessed first comprehensive data, and extracting the depolarization ratio and echo coherence of the crack region according to the cross-physics coupling model; a vector set generation module for generating a crack electromagnetic feature vector set based on the crack region depolarization ratio and echo coherence; and an interval adjustment module for calculating crack depth parameters based on the first comprehensive data and adjusting the scanning interval based on the crack depth parameters.

[0060] Example 3 is an embodiment of the present invention, which differs from the previous embodiment in that: If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0061] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0062] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0063] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0064] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for fusing multi-source radar visual data of a pumped storage power station, characterized in that: include: Acquire the first comprehensive data and preprocess the first comprehensive data; A cross-physics coupling model is constructed based on the preprocessed first comprehensive data, and the depolarization ratio and echo coherence of the crack region are extracted according to the cross-physics coupling model. A set of electromagnetic feature vectors of the crack is generated based on the depolarization ratio and echo coherence of the crack region. The crack depth parameter is calculated based on the first comprehensive data, and the scanning interval is adjusted based on the crack depth parameter.

2. The multi-source radar-visual data fusion method for pumped storage power stations as described in claim 1, characterized in that: The first integrated data includes radar data and ground acoustic wave data; The radar data includes the horizontal-vertical to polarization scattering coefficient ratio; The geosonic data includes a time series of surface acoustic diffraction patterns from the crack. The radar data was acquired using a 94GHz MIMO radar fully polarized scattering matrix. The ground acoustic wave data was acquired through a distributed microseismic sensor array.

3. The multi-source radar-visual data fusion method for pumped storage power stations as described in claim 2, characterized in that: Based on the preprocessed first comprehensive data, a cross-physics coupling model is constructed. The specific steps are as follows: The preprocessed first composite data is aligned with a spatiotemporal reference. The scattering disorder of electromagnetic waves on the rough crack surface is quantified by extracting the depolarization ratio parameter of the crack region. The degree of signal phase instability caused by cracks is characterized by extracting radar echo coherence parameters. A cross-physics coupling model is constructed by combining the depolarization ratio parameter and the radar echo coherence parameter. The crack propagation nonlinear exponent is obtained based on the cross-physics coupling model.

4. The multi-source radar-visual data fusion method for pumped storage power stations as described in claim 1, characterized in that: The specific details of generating the electromagnetic feature vector set of the crack are as follows: When the depolarization ratio is greater than the first threshold and the echo coherence is less than the second threshold, it is determined that there is an effective crack in the region, and a crack electromagnetic feature vector set is generated. If the depolarization ratio is less than or equal to the first threshold, or the echo coherence is greater than or equal to the second threshold, then the region is determined to be a non-crack region or invalid interference, and such regions are marked and removed.

5. The multi-source radar-visual data fusion method for pumped storage power stations as described in claim 1, characterized in that: The crack depth parameter is calculated based on the first comprehensive data, including the following steps: Dielectric constant of rock mass inverted from radar data; Based on the rock mass type parameters in the regional geological survey report, the baseline acoustic velocity of this type of rock mass is obtained; Radar echo coherence is introduced to correct the reference acoustic velocity; The output of the cross-physics coupling model is used to construct a nonlinear mapping function to obtain the crack depth parameter.

6. The multi-source radar-visual data fusion method for pumped storage power stations as described in claim 3, characterized in that: The specific details of the crack propagation nonlinear index are as follows: When the nonlinearity index of crack propagation is greater than the third threshold, it indicates that the crack has entered the nonlinear accelerated propagation stage. The propagation speed increases with time, and the propagation morphology changes abruptly due to factors such as rock mass stress concentration and crack penetration. When the nonlinear index of crack propagation is less than or equal to the third threshold, it indicates that the crack propagation is in a stable stage, the propagation speed and morphology change slowly over time, the risk of crack damage to the rock mass structure is within a controllable range, and the conventional monitoring mode should be maintained.

7. The multi-source radar-visual data fusion method for pumped storage power stations as described in claim 1, characterized in that: The specific details of adjusting the scanning interval based on the aforementioned crack depth parameter are as follows: When the nonlinear exponent of crack propagation is greater than the third threshold, the calculation of the slope instability coefficient is activated. By combining the spatial distribution of slope instability coefficient and crack depth parameters, a slope disaster probability cloud map is generated. For high-risk areas, shorten the radar scanning interval to achieve encrypted monitoring; For low-risk areas, a baseline scanning cycle is maintained, and monitoring resources are adaptively allocated using crack depth parameters.

8. A multi-source radar-visual data fusion device for a pumped-storage power station, based on the multi-source radar-visual data fusion method for a pumped-storage power station as described in any one of claims 1 to 7, characterized in that: include, The data acquisition module is used to acquire the first comprehensive data and preprocess the first comprehensive data; The model building module is used to construct a cross-physics coupling model based on the preprocessed first comprehensive data, and extract the depolarization ratio and echo coherence of the crack region according to the cross-physics coupling model. The vector set generation module is used to generate a set of electromagnetic feature vectors of the crack based on the depolarization ratio of the crack region and the echo coherence. The interval adjustment module is used to calculate the crack depth parameter based on the first comprehensive data and adjust the scanning interval based on the crack depth parameter.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the multi-source radar-visual data fusion method for a pumped storage power station as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the multi-source radar-visual data fusion method for a pumped storage power station as described in any one of claims 1 to 7.

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