Method and system for discriminating dynamic response and damage evolution of dam structure cracks under seismic action

Abstract

The application discloses a method and system for discriminating crack dynamic response and damage evolution of dam structure under seismic action, and belongs to the technical field of structural health monitoring of water conservancy and hydropower engineering. The method comprises the following steps: a dam shaking table physical model is constructed, acceleration vibration data of a crack area and a crack propagation process are collected; a near-field dynamics numerical model is established, key parameters are calibrated through a physical experiment, and a standard parameter library is constructed; ensemble empirical mode decomposition and Hilbert-Huang transformation are performed on vibration signals, and an energy damage index based on Hilbert spectrum is constructed; crack propagation stages are discriminated according to the damage index, a propagation path is predicted, and multi-stage early warning is triggered. The application combines physical experiments, numerical simulation and signal analysis, realizes accurate simulation of dam crack propagation and quantitative discrimination of damage evolution, and provides reliable technical support for dam seismic safety monitoring and emergency decision-making.

Description

Technical Field

[0001] This invention belongs to the technical field of structural health monitoring and safety assessment of water conservancy and hydropower projects, specifically involving a method and system for dynamic response and damage evolution discrimination analysis of cracks in dam structures under seismic action. Background Technology

[0002] As a crucial water conservancy project, the structural safety of dams directly impacts the safety of life and property downstream and regional flood control. Under dynamic loads such as earthquakes, dam structures are prone to cracking and propagation, leading to accumulated structural damage and performance degradation.

[0003] Currently, the following technical challenges exist in identifying crack propagation and damage evolution in dam structures: (1) Difficulty in simulating crack propagation: Traditional finite element method faces problems such as difficulty in mesh re-division and low computational efficiency when dealing with crack propagation problem, making it difficult to accurately simulate the entire process of crack initiation, propagation and penetration; (2) Lack of basis for numerical model parameter calibration: Peridynamics (PD) method can naturally simulate the whole process of crack initiation, propagation and bifurcation and even breakage, but for the calibration parameters required for crack propagation in dam structures, there is a lack of calibration methods that best represent the actual crack propagation. (3) Inaccurate quantitative identification of damage evolution: Existing online monitoring technology is difficult to establish a quantitative correlation between monitoring signals and the degree of structural damage deterioration, and cannot realize real-time identification and early warning of crack damage evolution.

[0004] Therefore, there is an urgent need to develop an integrated method that combines physical model experiments, numerical simulations, and signal analysis to accurately identify crack propagation and damage evolution in dam structures under seismic action. Summary of the Invention

[0005] To address the aforementioned shortcomings of existing technologies, this invention provides a method and system for analyzing the dynamic response and damage evolution of cracks in dam structures under seismic loading, which solves the problems of difficulty in simulating crack propagation, lack of basis for numerical model parameter calibration, and inaccurate quantitative identification of damage evolution in existing technologies.

[0006] To achieve the above-mentioned technical features, the objective of this invention is as follows: The first aspect of this invention provides a method for analyzing the dynamic response and damage evolution of cracks in dam structures under seismic loading, comprising the following steps: S1: Construct a physical model of the dam structure using a shaking table, and pre-define cracks or crack propagation areas in the model; deploy an array of acceleration sensors to collect acceleration vibration data near the pre-define cracks and in the crack propagation areas, and record the actual development process and final form of crack propagation; S2: Establish a near-field dynamics numerical model that is geometrically similar to the physical model; set the initial values ​​and variation ranges of key near-field dynamics parameters, including near-field range size, micromodulus, and critical elongation; determine the optimal combination of near-field dynamics parameters by comparing the crack propagation path in numerical simulation with the results of physical experiments, and construct a standard parameter library based on the calibrated parameters; S3: Perform ensemble empirical mode decomposition on the acquired acceleration vibration signal to obtain a series of intrinsic mode functions; perform Hilbert-Huang transform on the main intrinsic mode function components to extract instantaneous frequency and instantaneous amplitude; construct an energy damage index based on Hilbert spectrum to establish a quantitative relationship between signal evolution characteristics and damage degradation degree; S4: Based on the changing trend of energy damage indicators, determine the crack propagation stage; combine numerical simulation results to predict the future propagation path and remaining lifetime of the crack; when the damage indicators exceed the preset threshold, trigger a multi-level early warning mechanism.

[0007] Preferably, in step S1, the construction of the dam structure vibration table physical model specifically involves: making a dam model at a geometric scale of 1:50 to 1:200, and using micro-particle concrete or similar materials to simulate the dam concrete.

[0008] Preferably, in step S1, the step of presetting a crack or crack extension area in the model specifically means: presetting an initial crack in the middle of the model, with a crack length of 10-50cm, a width of 1-10cm, a depth penetrating the thickness direction of the dam body, and a crack inclination angle of 30°-75°.

[0009] Preferably, in step S1, the arrangement of the acceleration sensor array specifically involves: arranging a first set of acceleration sensors at intervals of 2-10 cm along the direction extending from the tip of the initial crack into the interior of the dam body; arranging a second set of acceleration sensors symmetrically on both sides of the expected path of crack expansion; and arranging reference measuring points in the intact area of ​​the dam body away from the crack.

[0010] Preferably, in step S2, determining the optimal combination of near-field dynamic parameters specifically involves: establishing a parameter calibration objective function, which is the sum of squared errors between the numerical simulation crack propagation length and angle and the experimental observations; and using a genetic algorithm or particle swarm optimization algorithm to search for the optimal parameters that minimize the objective function within the parameter variation range.

[0011] Preferably, in step S3, the construction of the energy damage index based on the Hilbert spectrum specifically involves: when performing ensemble empirical mode decomposition on the acceleration signal, the amplitude of the added white noise is set to 0.1-0.3 times the standard deviation of the signal, and the number of ensembles is 50-200; the first 3-5 high-frequency intrinsic mode function components are selected for Hilbert-Huang transform to extract the Hilbert spectrum energy in the 200-800Hz frequency band; the energy damage index EDI(t) is calculated, which is the ratio of instantaneous Hilbert spectrum energy to cumulative energy multiplied by the frequency normalization coefficient.

[0012] Preferably, in step S4, the crack propagation determination stage specifically includes: Stable propagation stage: Energy damage index fluctuates slightly within the range of 0.1-0.3, and crack propagation rate is less than 0.5 cm / s; Accelerated propagation phase: Energy damage index continues to rise to 0.3-0.7, crack propagation rate is 0.5-2.0 cm / s; Critical failure stage: The energy damage index rises sharply to above 0.7, and the crack propagation rate is greater than 2.0 cm / s.

[0013] Preferably, in step S4, the prediction of the future propagation path of the crack specifically involves: when the energy damage index enters the accelerated propagation stage, using the current measured crack length and angle as the initial conditions of the near-field dynamic numerical model, calculating the crack propagation trend within a set time period based on the calibrated optimal parameters; and performing Monte Carlo simulation in conjunction with the randomness of material parameters to obtain the propagation path envelope.

[0014] Preferably, in step S4, the multi-level early warning mechanism specifically includes: Blue alert: Energy damage index greater than 0.3, indicating a need to pay attention to crack development; Yellow alert: Energy damage index is greater than 0.5. It is recommended to increase the frequency of monitoring and take preventive measures. Red alert: Energy damage index greater than 0.7. Take emergency measures immediately and activate emergency plan.

[0015] A second aspect of this invention provides a system for analyzing the dynamic response and damage evolution of cracks in dam structures under seismic loading, comprising: The shaking table experimental module is used to construct a physical model of the dam structure shaking table. Cracks or crack propagation areas are preset in the model. An array of acceleration sensors is arranged to collect acceleration vibration data near the preset cracks and in the crack propagation area, and to record the actual development process and final form of crack propagation. The near-field dynamics simulation module is used to establish a near-field dynamics numerical model that is geometrically similar to the physical model; to set the initial values ​​and variation ranges of key near-field dynamics parameters, including near-field range size, micromodulus, and critical elongation; to determine the optimal combination of near-field dynamics parameters by comparing the numerical simulation crack propagation path with the physical experimental observation results; and to construct a standard parameter library based on the calibrated parameters. The signal analysis module is used to perform ensemble empirical mode decomposition on the acquired acceleration vibration signal to obtain a series of intrinsic mode functions; perform Hilbert-Huang transform on the main intrinsic mode function components to extract instantaneous frequency and instantaneous amplitude; construct an energy damage index based on Hilbert spectrum to establish a quantitative relationship between signal evolution characteristics and damage degradation degree; The damage assessment and early warning module is used to determine the crack propagation stage based on the changing trend of energy damage indicators; predict the future propagation path and remaining lifetime of the crack by combining numerical simulation results; and trigger a multi-level early warning mechanism when the damage indicators exceed the preset threshold.

[0016] Preferably, the shaking table experimental module includes a shaking table surface, a physical model of the dam structure, an acceleration sensor array, and a data acquisition system; the shaking table surface is used to support the physical model of the dam structure, the acceleration sensor array is used to collect acceleration vibration data near the preset crack and in the crack propagation area, and the data acquisition system is used to record the actual development process and final form of crack propagation.

[0017] Preferably, in the shaking table test module, the physical model of the dam structure is made at a geometric scale of 1:50 to 1:200, and micro-particle concrete or similar materials are used to simulate the dam concrete; an initial crack is preset in the middle of the model, with a crack length of 10-50cm, a width of 1-10cm, a depth that penetrates the thickness direction of the dam, and a crack inclination angle of 30°-75°.

[0018] Preferably, the near-field dynamics simulation module is specifically used for: establishing a parameter calibration objective function, which is the sum of squared errors between the numerical simulation crack propagation length and angle and the experimental observation values; and using a genetic algorithm or particle swarm optimization algorithm to search for the optimal parameters that minimize the objective function within the parameter variation range.

[0019] Preferably, the signal analysis module is specifically used for: when performing ensemble empirical mode decomposition on the acceleration signal, adding white noise with an amplitude of 0.1-0.3 times the signal standard deviation, and performing ensemble decomposition 50-200 times; selecting the first 3-5 high-frequency intrinsic mode function components for Hilbert-Huang transform to extract the Hilbert spectrum energy in the 200-800Hz frequency band; and calculating the energy damage index EDI(t), which is the ratio of instantaneous Hilbert spectrum energy to cumulative energy multiplied by the frequency normalization coefficient.

[0020] Preferably, the damage detection and early warning module is specifically used to detect the crack propagation stage according to the following rules: Stable propagation stage: Energy damage index fluctuates slightly within the range of 0.1-0.3, and crack propagation rate is less than 0.5 cm / s; Accelerated propagation phase: Energy damage index continues to rise to 0.3-0.7, crack propagation rate is 0.5-2.0 cm / s; Critical failure stage: The energy damage index rises sharply to above 0.7, and the crack propagation rate is greater than 2.0 cm / s.

[0021] According to the seismic motion-induced dynamic response and damage evolution discrimination analysis system for dam structure cracks under seismic action as described in claim 10, the multi-level early warning mechanism of the damage discrimination and early warning module specifically includes: Blue alert: Energy damage index greater than 0.3, indicating a need to pay attention to crack development; Yellow alert: Energy damage index is greater than 0.5. It is recommended to increase the frequency of monitoring and take preventive measures. Red alert: Energy damage index greater than 0.7. Take emergency measures immediately and activate emergency plan.

[0022] The present invention has the following beneficial effects: 1. This invention uses the near-field dynamics (PD) method to avoid the mesh dependence of the traditional finite element method, and can naturally simulate the arbitrary path propagation and bifurcation of cracks. At the same time, the PD parameters are calibrated by physical experiments on a shaking table to ensure that the numerical model truly reflects the crack propagation characteristics of the dam body, realizes the accurate simulation of crack propagation, and solves the uncertainty problem of pure numerical simulation parameters.

[0023] 2. Based on the EEMD-HHT signal analysis method, this invention extracts the damage-sensitive Hilbert spectrum energy features, establishes a quantitative mapping relationship between signal evolution and damage degradation, and then constructs a quantitative damage discrimination index.

[0024] 3. This invention establishes an integrated system of experiment-simulation-signal analysis, forming a widely applicable engineering method. The calibrated PD parameter library can be applied to similar dam structures, and the signal damage index can be used for real-time damage identification in online monitoring systems, demonstrating significant engineering practical value. Attached Figure Description

[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0026] Figure 1 This is an overall flowchart of a method for analyzing the dynamic response and damage evolution of cracks in dam structures under seismic loading, according to the present invention.

[0027] Figure 2 This is a schematic diagram of the physical model experimental setup for a shaking table.

[0028] Figure 3 Flowchart for calibrating near-field dynamic parameters.

[0029] Figure 4 A flowchart for signal feature extraction and damage index construction.

[0030] Figure 5 This is a schematic diagram of the energy change curves of the Hilbert spectrum at different damage stages. Detailed Implementation

[0031] To make the technical problems, solutions, and advantages of this invention clearer, a detailed description will be provided below with reference to specific embodiments and accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0032] Example 1: This embodiment uses a concrete gravity dam as a prototype to describe in detail the implementation process of the method of the present invention. The overall process of the method is as follows: Figure 1 As shown.

[0033] Step S1: Shaking table physical model experiment and data acquisition S1.1 Model Design and Production A concrete gravity dam was selected as the prototype, and a shaking table physical model was constructed at a geometric scale of 1:100. The model used micro-particle concrete to simulate the dam body concrete, and the model dimensions were: dam height 85cm, dam top width 12cm, dam bottom width 65cm, and dam axial length 28cm.

[0034] An initial crack is pre-set in the middle of the upstream face of the model dam. The crack is 15cm long, 2cm wide, and penetrates the thickness of the dam body. The crack angle is 60° (the angle with the horizontal plane). The crack is made by pre-embedding thin steel sheets and then pulling them out to ensure that the crack surface is flat.

[0035] S1.2 Sensor Arrangement An array of acceleration sensors is arranged on the surface of the model, as shown in the diagram. Figure 2 As shown in Table 1, the specific layout plan is as follows: Measuring points A1-A3: arranged at 3cm intervals along the direction extending from the tip of the initial crack into the interior of the dam body, used to capture the vibration response in the stress concentration area at the crack tip; Measurement points B1-B4: symmetrically arranged on both sides of the expected crack propagation path, used to monitor energy release during crack propagation; Measuring points C1-C2: Arranged in the intact area of ​​the dam body away from the cracks, as reference measuring points.

[0036] The sensor uses a triaxial piezoelectric accelerometer.

[0037] Table 1 Accelerometer Sensor Array Arrangement Scheme

[0038] S1.3 Data Acquisition A three-dimensional, six-DOF shaking table was used for loading. The input seismic wave was an El Centro wave (1940, NS component), compressed at a time similarity ratio of 1 / 10. Peak ground acceleration (PGA) was applied at six levels: 0.05g, 0.1g, 0.2g, 0.4g, 0.6g, and 0.8g, each lasting 5.3 seconds, with a 1-second interval for crack morphology observation and recording. The crack propagation process was recorded using a high-speed camera to obtain the crack propagation path and morphology under different seismic intensities. Specific working conditions are shown in Table 2.

[0039] Table 2 Data Acquisition Operating Conditions Setting Scheme

[0040] Step S2: Near-field dynamic parameter calibration The parameter calibration process is as follows: Figure 3 As shown.

[0041] S2.1 Establishing a numerical model Using conventional basis peridynamics (OSB-PD), a peridynamic numerical model that is geometrically consistent with the physical model is established, with the bond constitutive relations as follows: ; Where c is the micromodulus, s is the bond elongation, ξ is the initial bond vector, and η is the relative displacement vector.

[0042] When the bond elongation s exceeds the critical elongation s0, the bond breaks: ; Local damage is defined as the ratio of the number of broken bonds to the total number of bonds: ; Step S2.2 Calibrate key PD parameters Key parameters of the PD model include micromodulus c, critical elongation s0, and near-field size δ. Among these, the micromodulus c is related to the material's elastic modulus, and its theoretical value is... The critical elongation s0 controls the damage initiation; there is no theoretical formula, and it needs to be calibrated experimentally. The near-field range dimension δ is fixed at 3Δx and is not calibrated separately.

[0043] Establish the objective function for parameter calibration: Define the crack morphology error between numerical simulation and physical experiment: ; in, Let be the crack propagation length in the numerical simulation and experiment at the i-th loading level; The crack propagation angle at the j-th observation point; N=6 (6 loading levels), M=12 (12 angle observation points).

[0044] A genetic algorithm was used to search for the optimal s0. The population size was 50, the search range was s0∈[0.0001,0.001], the crossover probability was 0.8, the mutation probability was 0.1, and the termination condition was that the objective function change was <0.1% for 20 consecutive generations. The final s0 was then determined. * =0.00042 (corresponding to strain 0.042%), minimum value of objective function: Fmin = 0.083 (8.3% average error).

[0045] Step S2.3 Verify calibration parameters Using calibration parameter s0 * =0.00042 The three key operating conditions EQ-3, EQ-5, and EQ-6 were recalculated. The error between the simulated and experimental values ​​of crack propagation length was less than 10%, verifying the reliability of the calibration parameters. Based on this, a standard parameter library for PD analysis was established.

[0046] Step S3: Signal Feature Extraction and Damage Index Construction Step S3.1 Acceleration signal preprocessing Acceleration signals at various measuring points under different operating conditions are preprocessed. First, the least squares method is used to eliminate the linear trend term. Then, the Butterworth bandpass filter is used to eliminate high-frequency noise and low-frequency drift. Finally, normalization is performed.

[0047] Step S3.2 Ensemble Empirical Mode Decomposition (EEMD) Ensemble Empirical Mode Decomposition (EEMD) was performed on the acceleration signals of each measuring point under seismic loading. EEMD addresses the mode aliasing problem of traditional EMD by adding white noise with a finite amplitude. Specifically, the amplitude of the added white noise was set to 0.2 times the standard deviation of the signal, the ensemble number was 100, and each IMF order was filtered a maximum of 10 times. The process was stopped when the remaining signal was a monotonic function or had fewer than two extreme points.

[0048] The decomposition yielded eight IMF components (IMF1-IMF8) and one residual component. Among them, IMF1-IMF3 are high-frequency components (>100Hz), mainly reflecting the transient characteristics of local damage and crack propagation; IMF4-IMF6 are mid-frequency components (10-100Hz), related to the overall dynamic response of the structure; and IMF7-IMF8 are low-frequency components (<10Hz), reflecting rigid body motion and foundation vibration.

[0049] Step S3.3 Hilbert-Huang Transform (HHT) Perform Hilbert-Huang transform on the IMF1-IMF3 components containing the main damage information to obtain the instantaneous frequency and instantaneous amplitude: ; Analytical signal construction: ; Where: instantaneous amplitude is The instantaneous phase is Instantaneous frequency is .

[0050] Constructing the Hilbert spectrum: ; This represents the distribution of signal energy in the time-frequency plane. The total Hilbert spectrum is obtained by superimposing the calculations for IMF1-IMF3 separately. .

[0051] Step S3.4 Constructing the Energy Damage Index (EDI) Define an energy damage index based on the Hilbert spectrum: ; Instantaneous energy Integration limits ω1 = 2π × 200 rad / s, ω2 = 2π × 800 rad / s (damage characteristic frequency band); Accumulated energy ; Average instantaneous frequency ; The fundamental frequency of the structure is f0 = 28.5 Hz (determined through frequency domain analysis).

[0052] Example of calculation results: For EQ-5 operating condition, the EDI time history curve shows: 0-1.2s: EDI fluctuated between 0.08 and 0.15, and the crack did not propagate; 1.2-2.8s: EDI gradually increases to 0.25-0.35, and the crack propagates stably; 2.8-4.0s: EDI rapidly rises to 0.45-0.65, entering the accelerated expansion phase; 4.0-5.3s: EDI reaches 0.75-0.88, approaching critical failure.

[0053] Step S4: Damage Evolution Identification and Early Warning Step S4.1 Quantitative identification of damage stage Based on the EDI index, a three-level damage discrimination criterion was established, as shown in Table 3: Table 3 Criteria for Determining Grade III Injury

[0054] The effectiveness of the EDI index was verified by comparing the EDI discrimination results with the actual experimental observations, as shown in Table 4: Table 4. Results of EDI Validity Verification

[0055] Step S4.2 Predict the crack propagation path When EDI enters the accelerated propagation phase (>0.3), the real-time update prediction of the PD numerical model is initiated: the current measured crack length and angle are used as the initial conditions for the PD model; based on the calibration parameter s0 * The crack propagation trend within the next Δt = 10 seconds is calculated. Considering the randomness of material parameters (s0 is taken as mean ± 10%), 100 Monte Carlo simulations are performed to obtain the propagation path envelope.

[0056] Step S4.3 Triggers a multi-level early warning mechanism Based on the calibration experimental data, three levels of early warning thresholds were set, as shown in Table 5: Table 5. Level 3 Early Warning Setting Scheme

[0057] EQ-5 operating condition warning triggering process: t=2.1s: EDI exceeds 0.3 (0.32) for the first time, triggering a blue alert, which is recorded and marked by the system; t=3.8s: EDI reaches 0.51, triggering a yellow alert, and sending SMS and APP push notifications to the management platform; t=4.5s: EDI reaches 0.73, triggering a red alert, activating the audible and visual alarm, and automatically dialing the emergency number; In actual engineering, the interval between yellow and red alerts is 0.7 seconds (7 seconds in the prototype), providing a time window for emergency response.

[0058] This embodiment demonstrates the effectiveness and engineering applicability of the proposed integrated method of "shaking table experiment - PD numerical simulation - EEMD - HHT signal analysis" by conducting a full-process test and analysis of a concrete gravity dam shaking table model under a magnitude 6 earthquake loading of 0.05g to 0.80g. The near-field dynamic parameter calibration based on genetic algorithm optimization yielded the optimal solution for the critical elongation s0, controlling the errors in crack propagation length and propagation angle between numerical simulation and physical experiment within a certain range. A standard parameter library that can be widely applied to similar dam structures was established. The constructed energy damage index (EDI) was analyzed using an empirical model. State decomposition and Hilbert-Huang transform effectively extracted crack damage characteristic information, achieving accurate differentiation of the three stages of stable propagation, accelerated propagation, and critical failure. The differentiation results were completely consistent with the actual crack development state observed by high-speed cameras. The multi-level early warning mechanism successfully achieved step-by-step triggering from blue to yellow and then to red warnings in the EQ-5 working condition, providing an emergency response time window for the prototype project. It solved technical problems such as the difficulty in simulating crack propagation in dam structures, the lack of basis for parameter calibration, and the inaccurate quantitative identification of damage evolution, providing reliable technical support for online monitoring and emergency decision-making for dam seismic safety.

[0059] Example 2: This embodiment provides an analysis system for implementing the above method, including a shaking table experiment module, a near-field dynamics simulation module, a signal analysis module, and a damage discrimination and early warning module.

[0060] Vibration table test module The system includes a shaking table, a physical model of the dam structure, an accelerometer array, and a data acquisition system. The shaking table is a three-axis, six-degree-of-freedom shaking table used to support the physical model of the dam structure and apply seismic loads. The physical model of the dam structure is fabricated according to a geometric similarity scale and has pre-set initial cracks. The accelerometer array is arranged according to the aforementioned scheme to collect three-axis acceleration signals in the crack area. The data acquisition system simultaneously collects vibration signals and high-speed camera data to record the entire process of crack propagation.

[0061] Near-field dynamics simulation module It features a built-in normal-state basis near-field dynamics solver, which can import geometric parameters from physical models to establish numerical models; it provides a parameter setting interface, allowing users to set initial values ​​and search ranges for micromodulus, critical elongation, and near-field range size; it integrates genetic algorithms and particle swarm optimization algorithms to automatically compare crack morphology errors between numerical simulations and experiments, and outputs the optimal parameter combination; it supports the storage and retrieval of parameter libraries, allowing calibration parameters to be directly applied to simulation calculations of similar dam structures.

[0062] Signal Analysis Module It incorporates a signal preprocessing unit, an EEMD decomposition unit, and an HHT transformation unit. The preprocessing unit performs trend term elimination, filtering, and normalization; the EEMD decomposition unit can be configured with parameters such as white noise amplitude, ensemble number, and screening number, and automatically outputs IMF components of each order; the HHT transformation unit transforms the selected high-frequency IMF components, extracting the instantaneous frequency, instantaneous amplitude, and Hilbert spectrum; it automatically calculates the energy impairment index (EDI) and outputs the time history curve and characteristic frequency band energy distribution.

[0063] Damage detection and early warning module It has a built-in three-level damage discrimination model that determines the current crack propagation stage in real time based on EDI values; it is coupled with a near-field dynamics simulation module that automatically starts crack propagation path prediction during the accelerated propagation stage and outputs the path envelope and remaining life estimation results; it is configured with multi-level early warning triggers that automatically push early warning information to the corresponding level of personnel and systems when preset trigger conditions are met, and supports multiple early warning methods such as audible and visual alarms, SMS push, APP notifications and emergency telephone linkage.

[0064] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for discriminant analysis of dynamic response and damage evolution of cracks in dam structures under seismic loading, characterized in that, Includes the following steps: S1: Construct a physical model of the dam structure using a shaking table, and pre-define cracks or crack propagation areas in the model; deploy an array of acceleration sensors to collect acceleration vibration data near the pre-define cracks and in the crack propagation areas, and record the actual development process and final form of crack propagation; S2: Establish a near-field dynamics numerical model that is geometrically similar to the physical model; set the initial values ​​and variation ranges of key near-field dynamics parameters, including near-field range size, micromodulus, and critical elongation; determine the optimal combination of near-field dynamics parameters by comparing the crack propagation path in numerical simulation with the results of physical experiments, and construct a standard parameter library based on the calibrated parameters; S3: Perform ensemble empirical mode decomposition on the acquired acceleration vibration signal to obtain a series of intrinsic mode functions; perform Hilbert-Huang transform on the main intrinsic mode function components to extract instantaneous frequency and instantaneous amplitude; construct an energy damage index based on Hilbert spectrum to establish a quantitative relationship between signal evolution characteristics and damage degradation degree; S4: Based on the changing trend of energy damage indicators, determine the crack propagation stage; combine numerical simulation results to predict the future propagation path and remaining lifetime of the crack; when the damage indicators exceed the preset threshold, trigger a multi-level early warning mechanism.

2. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S1, the construction of the physical model of the dam structure vibration table specifically involves: making a dam model at a geometric scale of 1:50 to 1:200, and using micro-particle concrete or similar materials to simulate the dam concrete.

3. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S1, the step of presetting cracks or crack extension areas in the model specifically means: presetting initial cracks in the middle of the model, with a crack length of 10-50cm, a width of 1-10cm, a depth penetrating the thickness direction of the dam body, and a crack inclination angle of 30°-75°.

4. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S1, the arrangement of the acceleration sensor array specifically involves: arranging a first set of acceleration sensors at intervals of 2-10cm along the direction of extension from the tip of the initial crack into the interior of the dam body; arranging a second set of acceleration sensors symmetrically on both sides of the expected path of crack expansion; and arranging reference measuring points in the intact area of ​​the dam body away from the crack.

5. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S2, determining the optimal combination of near-field dynamic parameters specifically involves: establishing a parameter calibration objective function, which is the sum of squared errors between the numerical simulation crack propagation length and angle and the experimental observations; and using a genetic algorithm or particle swarm optimization algorithm to search for the optimal parameters that minimize the objective function within the parameter variation range.

6. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S3, the construction of the energy damage index based on the Hilbert spectrum specifically involves: when performing ensemble empirical mode decomposition on the acceleration signal, the amplitude of the added white noise is set to 0.1-0.3 times the standard deviation of the signal, and the number of ensembles is 50-200; the first 3-5 high-frequency intrinsic mode function components are selected for Hilbert-Huang transform to extract the Hilbert spectrum energy in the 200-800Hz frequency band; The energy damage index EDI(t) is calculated, which is the ratio of instantaneous Hilbert spectrum energy to cumulative energy multiplied by the frequency normalization coefficient.

7. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S4, the crack propagation determination stage specifically includes: Stable propagation stage: Energy damage index fluctuates slightly within the range of 0.1-0.3, and crack propagation rate is less than 0.5 cm / s; Accelerated propagation phase: Energy damage index continues to rise to 0.3-0.7, crack propagation rate is 0.5-2.0 cm / s; Critical failure stage: The energy damage index rises sharply to above 0.7, and the crack propagation rate is greater than 2.0 cm / s.

8. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S4, the prediction of the future propagation path of the crack is specifically as follows: when the energy damage index enters the accelerated propagation stage, the current measured crack length and angle are used as the initial conditions of the near-field dynamic numerical model, and the crack propagation trend within a set time period is calculated based on the calibrated optimal parameters; Monte Carlo simulation is performed in combination with the randomness of material parameters to obtain the propagation path envelope.

9. The method for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 1, characterized in that, In step S4, the multi-level early warning mechanism specifically includes: Blue alert: Energy damage index greater than 0.3, indicating a need to pay attention to crack development; Yellow alert: Energy damage index is greater than 0.

5. It is recommended to increase the frequency of monitoring and take preventive measures. Red alert: Energy damage index greater than 0.

7. Take emergency measures immediately and activate the emergency plan.

10. A system for discriminant analysis of dynamic response and damage evolution of cracks in dam structures under seismic loading, characterized in that, include: The shaking table test module is used to construct a physical model of the dam structure using a shaking table, and to pre-define cracks or crack propagation areas in the model. An array of accelerometers was deployed to collect acceleration vibration data near the pre-set crack and in the crack propagation area, and to record the actual development process and final shape of the crack propagation. The near-field dynamics simulation module is used to establish a near-field dynamics numerical model that is geometrically similar to the physical model; to set the initial values ​​and variation ranges of key near-field dynamics parameters, including near-field range size, micromodulus, and critical elongation; to determine the optimal combination of near-field dynamics parameters by comparing the numerical simulation crack propagation path with the physical experimental observation results; and to construct a standard parameter library based on the calibrated parameters. The signal analysis module is used to perform ensemble empirical mode decomposition on the acquired acceleration vibration signal to obtain a series of intrinsic mode functions; perform Hilbert-Huang transform on the main intrinsic mode function components to extract instantaneous frequency and instantaneous amplitude; construct an energy damage index based on Hilbert spectrum to establish a quantitative relationship between signal evolution characteristics and damage degradation degree; The damage assessment and early warning module is used to determine the crack propagation stage based on the changing trend of energy damage indicators; Based on numerical simulation results, the future propagation path and remaining life of the crack are predicted; when the damage index exceeds the preset threshold, a multi-level early warning mechanism is triggered.

11. The system for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 10, characterized in that, The shaking table experimental module includes a shaking table surface, a physical model of the dam structure, an acceleration sensor array, and a data acquisition system. The shaking table surface is used to support the physical model of the dam structure, the acceleration sensor array is used to collect acceleration vibration data near the preset crack and in the crack propagation area, and the data acquisition system is used to record the actual development process and final form of crack propagation.

12. The system for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 10, characterized in that, In the shaking table test module, the physical model of the dam structure is made at a geometric scale of 1:50 to 1:200, and micro-particle concrete or similar materials are used to simulate the dam concrete. An initial crack is preset in the middle of the model, with a crack length of 10-50cm, a width of 1-10cm, a depth that penetrates the thickness direction of the dam, and a crack inclination angle of 30°-75°.

13. The system for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 10, characterized in that, The near-field dynamics simulation module is specifically used to: establish a parameter calibration objective function, which is the sum of squared errors between the numerical simulation crack propagation length and angle and the experimental observations; and use a genetic algorithm or particle swarm optimization algorithm to search for the optimal parameters that minimize the objective function within the parameter variation range.

14. The system for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 10, characterized in that, The signal analysis module is specifically used for: when performing ensemble empirical mode decomposition on the acceleration signal, adding white noise with an amplitude of 0.1-0.3 times the signal standard deviation, and performing ensemble decomposition 50-200 times; selecting the first 3-5 high-frequency intrinsic mode function components for Hilbert-Huang transform, and extracting the Hilbert spectrum energy in the 200-800Hz frequency band; The energy damage index EDI(t) is calculated, which is the ratio of instantaneous Hilbert spectrum energy to cumulative energy multiplied by the frequency normalization coefficient.

15. The system for discriminant analysis of dynamic response and damage evolution of dam structure cracks under seismic loading as described in claim 10, characterized in that, The damage detection and early warning module is specifically used to determine the crack propagation stage according to the following rules: Stable propagation stage: Energy damage index fluctuates slightly within the range of 0.1-0.3, and crack propagation rate is less than 0.5 cm / s; Accelerated propagation phase: Energy damage index continues to rise to 0.3-0.7, crack propagation rate is 0.5-2.0 cm / s; Critical failure stage: The energy damage index rises sharply to above 0.7, and the crack propagation rate is greater than 2.0 cm / s; The multi-level early warning mechanism of the damage detection and early warning module specifically includes: Blue alert: Energy damage index greater than 0.3, indicating a need to pay attention to crack development; Yellow alert: Energy damage index is greater than 0.

5. It is recommended to increase the frequency of monitoring and take preventive measures. Red alert: Energy damage index greater than 0.

7. Take emergency measures immediately and activate the emergency plan.

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