A method and system for identifying scouring of calcareous sand slopes based on fiber Bragg grating monitoring

Abstract

The present invention discloses a method and system for identifying erosion of a calcareous sand bank slope based on fiber Bragg grating (FBG) monitoring. The method comprises the following steps: arranging a fiber Bragg grating (FBG) displacement sensor on the top of the calcareous sand bank slope, and obtaining real-time deformation parameters of the calcareous sand bank slope through the fiber Bragg grating (FBG) displacement sensor; replacing a modified Cambridge elastoplastic constitutive model in an original calcareous sand cumulative deformation elastoplastic explicit calculation model (HCA) with a state-dependent soil constitutive model, and using the improved HCA model to simulate the deformation parameters of the calcareous sand bank slope under different erosion parameter combinations; fitting the mapping relationship between the erosion parameters and the deformation parameters of the calcareous sand bank slope to obtain an erosion identification model; training the erosion identification model based on historical deformation parameters of the calcareous sand bank slope and corresponding erosion conditions, and inputting the real-time deformation parameters into the trained erosion identification model to obtain the real-time erosion conditions of the calcareous sand bank slope.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to a method and system for identifying calcareous sand bank erosion based on fiber grating monitoring. Background Art

[0002] Calcareous sand is widely distributed in my country's South China Sea and other tropical and subtropical waters, and is an important basic material for the construction of hydraulically reclaimed islands and reefs. In island and reef construction, calcareous sand banks are usually artificial slopes formed by artificial accumulation on the basis of the original reef. Engineers build concrete revetments on top of them and place twisted blocks to reduce wave erosion and maintain the stability of the land area of the island and reef. However, because the toe of the slope is not completely within the protection range of the concrete revetment structure, the calcareous sand banks are very prone to erosion disasters under the long-term action of ocean dynamic factors such as waves and tides. Erosion disasters will not only reduce the stability of the slope and cause the slippage of the revetment structure, threatening the safety of island and reef infrastructure, but may also cause serious engineering problems such as the disappearance of large-scale land areas of hydraulically reclaimed islands and reefs.

[0003] Currently, the monitoring methods for calcareous sand bank erosion hazards mainly include direct observation and geophysical detection. Direct observation relies on manual on-site observations on a regular basis. Although intuitive, it is inefficient and cannot achieve real-time monitoring. Geophysical detection uses technical means such as monitoring technology based on measurement data and acoustic impact fusion, microseismic technology, and multi-beam mobile monitoring technology to obtain bank morphology and geological information, which can compensate for the shortcomings of direct observation to a certain extent. However, these methods generally have problems such as high equipment cost, complex operation, limited monitoring range, and cannot achieve real-time detection around the clock.

[0004] Although existing monitoring technologies can provide a certain degree of information on bank slope morphology and geology, they still have significant limitations in practical application. First, neither direct observation nor geophysical detection methods can achieve real-time, continuous monitoring of erosion disasters, resulting in a lag in disaster identification. Second, existing technologies have difficulty accurately extracting effective information related to erosion disasters from large amounts of monitoring data, resulting in a high error rate and inability to meet engineering requirements. These issues make it difficult for existing monitoring technologies to effectively address the complexity and dynamic nature of calcareous sand bank erosion disasters. Summary of the Invention

[0005] The present invention proposes a method and system for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring, which solves the problem that the existing technology is difficult to effectively deal with the complexity and dynamics of calcareous sand bank erosion disasters.

[0006] To solve the above technical problems, the present invention provides a method for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring, comprising the following steps:

[0007] Step S1: arranging a fiber Bragg grating displacement sensor on the top of the calcareous sand bank slope, and obtaining real-time deformation parameters of the calcareous sand bank slope through the fiber Bragg grating displacement sensor;

[0008] Step S2: Using the state-dependent constitutive model of soil to replace the modified Cambridge elastoplastic constitutive model in the original calcareous sand cumulative deformation explicit calculation model HCA, the improved HCA model is used to simulate the deformation parameters of the calcareous sand bank under different erosion parameter combinations;

[0009] Step S3: fitting the mapping relationship between the erosion parameters and the deformation parameters of the calcareous sand bank slope to obtain an erosion identification model;

[0010] Step S4: training an erosion recognition model based on historical deformation parameters of the calcareous sand bank slope and corresponding erosion conditions, inputting the real-time deformation parameters into the trained erosion recognition model to obtain the real-time erosion conditions of the calcareous sand bank slope.

[0011] Preferably, the dilatancy equation of the state-dependent constitutive model of the soil in step S2 is expressed as:

[0012] ;

[0013] ;

[0014] ;

[0015] Where, is the dilatancy ratio; is the plastic body strain increment; Plastic shear strain increment; and are all model parameters with positive values; is the state parameter; is the stress ratio; is the critical stress ratio; is the porosity ratio; is the critical porosity ratio; 、 and All by - Material constants determined by the plane critical state line; is the average normal stress of the soil; It is a value normalized to atmospheric pressure.

[0016] Preferably, the deformation parameters in step S1 include horizontal displacement and vertical displacement of the calcareous sand bank slope.

[0017] Preferably, after the deformation parameters of the calcareous sand bank slope are monitored in real time by the fiber Bragg grating displacement sensor in step S1, data preprocessing is performed on the deformation parameters obtained by monitoring, including the following steps:

[0018] Step S11: using the exponential sliding average method to remove environmental data noise in the deformation parameters;

[0019] Step S12: setting abnormal parameter thresholds based on historical deformation parameters to identify and remove abnormal deformation parameters;

[0020] Step S13: using linear interpolation to identify and interpolate deformation parameter data containing missing values.

[0021] Preferably, the etching parameters in step S2 include: etching depth and etching area.

[0022] Preferably, when training the erosion recognition model based on historical monitoring data and corresponding erosion conditions in step S4, a 10-fold cross validation method is used to evaluate the accuracy of the erosion recognition model, and the parameters of the erosion recognition model are adjusted according to the evaluation results.

[0023] Preferably, after obtaining the real-time erosion situation of the calcareous sand bank slope in step S4, a graded warning is performed according to the real-time erosion situation. If there is no erosion, a green signal is output and monitoring continues; if there is slight erosion, a yellow warning is output and the operation and maintenance personnel are notified by SMS; if there is severe erosion, a red alarm is output, an audible and visual alarm is issued, and an emergency response is carried out.

[0024] The present invention also provides a calcareous sand bank erosion identification system based on fiber Bragg grating monitoring, which is implemented based on the above-mentioned calcareous sand bank erosion identification method based on fiber Bragg grating monitoring, and includes: a fiber Bragg grating monitoring module, a data preprocessing module, a model building module and an erosion identification module;

[0025] The fiber Bragg grating monitoring module collects the horizontal and vertical displacements of the calcareous sand bank in real time through a fiber Bragg grating displacement sensor arranged on the top of the calcareous sand bank, converts the optical signal into a digital signal through a demodulator, and transmits it to the data preprocessing module via a communication cable;

[0026] The data preprocessing module is used to perform denoising, outlier removal and data interpolation on the data collected by the fiber grating monitoring module;

[0027] The model construction module simulates the deformation parameters of the calcareous sand bank slope under different erosion parameter combinations based on the improved HCA model, fits the mapping relationship between the erosion parameters and the deformation parameters, constructs an erosion recognition model, and trains the erosion recognition model using historical monitoring data and corresponding erosion conditions;

[0028] The erosion identification module inputs the pre-processed fiber Bragg grating deformation monitoring data into the trained erosion identification model, and outputs the erosion risk level of the current calcareous sand bank slope.

[0029] Preferably, the system also includes an early warning module, and the early warning and visualization module: performs graded early warning according to the erosion risk level output by the erosion identification module. If there is no erosion, a green signal is output and monitoring continues; if there is slight erosion, a yellow early warning is output and an SMS message is notified to the operation and maintenance personnel; if there is severe erosion, a red alarm is output, an audible and visual alarm is sounded, and an emergency response is carried out.

[0030] Preferably, the system further comprises a power supply and communication module, which supplies power to the fiber Bragg grating displacement sensor and demodulator, and uploads data to a cloud processing center via a communication cable or a 4G / 5G module.

[0031] The benefits of the present invention include at least:

[0032] 1. By placing fiber grating displacement sensors on the top of the calcareous sand bank slope, the deformation parameters of the bank slope can be monitored in real time, eliminating the need for manual periodic measurements. This improves monitoring efficiency and data timeliness. Once abnormal changes in deformation parameters are detected, erosion can be quickly detected and appropriate measures can be taken in a timely manner to effectively prevent further deterioration of the erosion problem and reduce potential losses.

[0033] 2. The modified Cambridge elastoplastic constitutive model in the HCA (elastic-plastic explicit calculation model for cumulative deformation of calcareous sand) is replaced by a state-dependent constitutive model of soil. The improved HCA model can more accurately reflect the mechanical behavior of calcareous sand slopes under different erosion conditions under cyclic wave loading, making the simulation results closer to actual engineering conditions and improving the accuracy of erosion identification.

[0034] 3. By fitting the mapping relationship between erosion parameters and calcareous sand bank deformation parameters, an erosion identification model is obtained, which provides a scientific quantitative analysis basis for erosion identification. Erosion identification no longer relies on empirical judgment or qualitative analysis, but is based on objective evaluation of data and models, thereby improving the accuracy and reliability of erosion identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Schematic diagram of a method flow in an embodiment of the present invention;

[0036] Figure 2 This is a flowchart of a real-time disaster identification technology according to an embodiment of the present invention;

[0037] Figure 3 Schematic diagram of the arrangement of the fiber Bragg grating displacement sensor according to an embodiment of the present invention;

[0038] Figure 4 Schematic diagram of the installation structure of the fiber Bragg grating displacement sensor according to an embodiment of the present invention;

[0039] Figure 5 Schematic diagram of the system structure of an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following is a clear and complete description of the technical solutions in the embodiments of the present invention, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts are within the scope of protection of the present invention.

[0041] like Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a method for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring, comprising the following steps:

[0042] Step S1: arranging a fiber Bragg grating displacement sensor on the top of the calcareous sand bank slope, and obtaining real-time deformation parameters of the calcareous sand bank slope through the fiber Bragg grating displacement sensor.

[0043] Specifically, in accordance with the requirements of the "Code for Building Deformation Measurement," "JTS304-2019 Technical Standard Specification for Inspection and Evaluation of Water Transport Engineering Structures," and the "Code for Breakwater and Bank Protection Design," this embodiment of the present invention designed a monitoring point layout for the calcareous sand bank slope of a revetment, as shown in Table 1. Fiber Bragg grating (FBG) displacement sensors were deployed on the crest of the calcareous sand bank slope of a typical sloped revetment on a reef. The fiber Bragg grating (FBG) displacement sensors used in this embodiment of the present invention were corrosion-resistant, premium-grade FBGs with a 50 cm grating spacing.

[0044] Table 1 Layout plan of monitoring points on calcareous sand bank slope

[0045]

[0046] like Figure 3 As shown, taking the geometric characteristics of a representative actual calcareous sand bank slope section as an example, the horizontal distance between the fiber Bragg grating displacement sensor and the breast wall is about 1500 mm, and the burial depth is about 500 mm. During installation, first dig an installation pit of appropriate depth of about 500 mm on the top surface of the bank slope; take two 600 mm long HPB335Φ6 steel bars, and insert them into the prefabricated holes of a PVC pipe with an outer diameter of 50 mm, an inner diameter of 40 mm, and a wall thickness of 5 mm in sequence to prevent the PVC pipe from shaking. The connection method uses glue bonding or pipe clamp connection to form a tight connection body, and the whole is placed in the installation pit; use a fixing device to fix the two fiber Bragg grating sensors around the vertical steel bars and horizontal steel bars respectively, and the fixing force is moderate to avoid damaging the sensor, forming a structure as shown below. Figure 4 The installation structure shown.

[0047] Next, the fiber Bragg grating (FBG) interrogator, wired transmission module, and photovoltaic independent power supply were connected, and the sensor was debugged to ensure proper collection and transmission of deformation data. Finally, the wired transmission module connected the interrogator to the data processing center. The data processing center includes a data receiving and processing platform equipped with appropriate data processing software and analysis tools. The communication cables in the wired transmission module were paired and configured to ensure accurate transmission of the deformation monitoring data generated by the interrogator to the data processing center.

[0048] After the fiber Bragg grating displacement sensor is set up, it collects bank slope deformation data every 5 minutes at a set time interval and sends it to the data processing center in real time via a wired transmission module. The data processing center's software system automatically stores and classifies the received bank slope deformation data and performs data preprocessing on the received deformation data, including:

[0049] 1. Use data smoothing algorithms, such as the exponential moving average algorithm (EMA), to denoise the collected data, remove noise caused by environmental interference and other factors, and improve data stability.

[0050] 2. Set an abnormal threshold based on historical deformation parameter data to identify and correct abnormal data. For example, if the deformation data of a certain monitoring point shows a large mutation in a short period of time and exceeds the set abnormal threshold, the data is judged as abnormal data and corrected through the data interpolation algorithm.

[0051] 3. Use data interpolation algorithms such as linear interpolation method LI or nearest neighbor interpolation method NNI to identify and interpolate deformation parameter data with missing values, restore the original statistical information of the data, and ensure the continuity and reliability of the data.

[0052] Data analysis programs are used to extract characteristic parameters related to erosion hazards, such as the displacement rate of the bank slope, the cumulative displacement, and the periodic displacement, from the preprocessed deformation data. For example, by calculating the ratio of the displacement difference between adjacent time points to the time interval, the displacement rate (e.g., the displacement rate in the first hour and the displacement rate in the second hour) is obtained. By accumulating the displacement changes over a period of time, the cumulative displacement (e.g., the displacement in the first hour, the displacement in the second hour, and the displacement in the sixth hour) is obtained. Periodic displacement (e.g., daily / weekly displacement) can be calculated based on the cumulative displacement of the bank slope.

[0053] Step S2: The modified Cambridge elastoplastic constitutive model in the original calcareous sand cumulative deformation explicit elastoplastic calculation model HCA is replaced by the state-dependent constitutive model of soil, and the deformation parameters of the calcareous sand bank slope under different erosion parameter combinations are simulated using the improved HCA model.

[0054] Specifically, erosion parameters include erosion depth and erosion area, while calcareous sand bank deformation parameters include horizontal displacement and settlement of the slope crest. Applying two-dimensional finite element numerical calculation theory and based on the High Cycle Accumulation (HCA) explicit elastic-plastic calculation model for calcareous sand cumulative deformation, numerical simulations were conducted to generate bank deformation data for different wave cycles, different erosion parameter combinations, and different slope height / slope length combinations. The erosion severity of the bank slope was also scored, ranging from mild to severe.

[0055] The improvement of the High Cycle Accumulation (HCA) model for the cumulative deformation of calcareous sand over traditional elastoplastic constitutive calculation theory lies primarily in its direct use of explicit calculation modules instead of implicit calculations over a wide range of time scales, significantly reducing computational costs and the cumulative errors caused by multiple implicit calculations. At the same time, the implicit calculation module of the HCA model can comprehensively and objectively reflect the impact of various factors on the long-term cumulative deformation of the soil, with advantages such as clear parameters, rich data, and high reliability. The HCA model in the embodiment of the present invention is an explicit elastoplastic calculation model for the cumulative deformation of sand, constructed and improved based on the original HCA model. The original HCA model consists of two parts: implicit and explicit calculation. The implicit calculation part uses a quasi-static elastoplastic constitutive model instead of a dynamic elastoplastic constitutive model for calculation. On short time scales, the elastoplastic constitutive model is used to implicitly calculate the stress-strain relationship within a single control cycle, and the soil state parameters such as soil stiffness are updated by updating the soil strain amplitude changes. The explicit calculation part includes the flow law and a series of function formulas that consider various independent influencing factors. On a long time scale, the cumulative deformation of the soil within a certain number of cycles is calculated through a large-step explicit integration algorithm, and the stress and strain of the soil within a single cycle are not calculated. The implicit calculation part of the original HCA model introduces the modified Cambridge elastoplastic constitutive model. Since the modified Cambridge elastoplastic constitutive model adopts the associated flow law, it can only consider the influence of stress ratio on shear dilatancy, but cannot consider the influence of soil porosity and confining pressure on shear dilatancy. As a result, the original HCA model can only consider the stress loading history and simulate the strain hardening of sand, but cannot directly simulate the strain softening of sand, and cannot consider the state correlation of sand. Therefore, in the embodiment of the present invention, the implicit calculation part of the HCA model is improved, and the state-related constitutive model of soil is used instead of the modified Cambridge elastoplastic constitutive model. The expression of the dilatancy equation adopted by the elastoplastic constitutive model is:

[0056] ;

[0057] ;

[0058] ;

[0059] Where, is the dilatancy ratio; is the plastic body strain increment; Plastic shear strain increment; and are all model parameters with positive values; is the state parameter; is the stress ratio; is the critical stress ratio; is the porosity ratio; is the critical porosity ratio; 、 and All by - Material constants determined by the plane critical state line; is the average normal stress of the soil; It is a value normalized to atmospheric pressure.

[0060] From the above formula, we can see that When shear dilatancy occurs, The shear dilatancy of sand is not only related to the stress ratio Related to and Therefore, this constitutive model is particularly suitable for simulating the mechanical response of cohesiveless sands such as calcareous sand.

[0061] By replacing the modified Cambridge elastoplastic constitutive model with the state-dependent constitutive model of soil, the improved HCA model can comprehensively consider the combined effects of stress ratio, porosity ratio and confining pressure on the dilatancy of calcareous sand.

[0062] Specifically, in this embodiment of the present invention, the wave loading frequency is set to 0.1 Hz, and the number of cycles is selected to be 3600, 7200, 10800, 21600, 43200, and 86400, corresponding to time spans of 1 hour, 2 hours, 3 hours, 6 hours, 12 hours, and 24 hours. The erosion condition is achieved by deleting the grid cells at the toe of the finite element slope numerical model. Through the above numerical simulation calculations, based on the HCA numerical calculation model, the slope deformation data when erosion occurs is obtained.

[0063] Similarly, by applying the two-dimensional finite element numerical calculation theory and carrying out numerical simulation calculations based on the HCA model, the slope deformation data when no erosion occurs can be obtained.

[0064] Based on the deformation data of slopes without erosion, the deformation data of slopes with erosion, and the corresponding erosion parameters, a numerical database of erosion disasters for calcareous sand slopes was constructed, as shown in Table 2. The erosion degree scores include no erosion, slight erosion, and severe erosion.

[0065] Table 2 Numerical database of erosion hazards on calcareous sandy slopes

[0066]

[0067] Step S3: fitting the mapping relationship between the erosion parameters and the deformation parameters of the calcareous sand bank slope to obtain an erosion identification model.

[0068] Specifically, machine learning algorithms with excellent nonlinear learning performance, such as support vector machines (SVM), neural networks, random forests, and gradient boosting decision trees, are used. The numerical database of calcareous sand bank erosion disasters is used as the training set, the deformation parameters of the calcareous sand bank in the training set are used as input, and the corresponding erosion disaster occurrence is used as output. The model is trained to fit the mapping relationship between the bank deformation parameters and the erosion parameters, and an erosion recognition model for calcareous sand bank is constructed. During the training process, the optimal parameters of the erosion recognition model are obtained through the 10-fold cross-validation method, where the adjustable parameters of the support vector machine are the penalty parameters. c and kernel function parameters; the adjustable parameters of the neural network are the learning rate, the number of hidden layer neurons and the number of layers; the adjustable parameters of the random forest are the number of decision trees, the maximum depth and the minimum number of sample splits; the adjustable parameters of the gradient boosting tree are the learning rate, the number of decision trees, the maximum depth and the subsampling ratio.

[0069] Step S4: training an erosion recognition model based on historical deformation parameters of the calcareous sand bank slope and corresponding erosion conditions, inputting the real-time deformation parameters into the trained erosion recognition model to obtain the real-time erosion conditions of the calcareous sand bank slope.

[0070] Specifically, the trained model is evaluated using the test set to calculate model accuracy, recall, and other evaluation metrics. If the model performance does not meet the expected requirements, further adjustments are made to the model parameters or additional training data is added, and retraining and evaluation are performed until the model performance meets the requirements.

[0071] At the same time, historical deformation monitoring data of the calcareous sand bank slopes in the area over the past five years and the corresponding records of erosion disasters were collected to form a database of actual erosion cases of calcareous sand bank slopes, to supplement the numerical database of erosion disasters of calcareous sand bank slopes and to calibrate the parameters of the erosion identification model of calcareous sand bank slopes, to further optimize the performance of the erosion identification model of calcareous sand bank slopes and improve the recognition accuracy of the erosion identification model.

[0072] Combined with the numerical database of erosion disasters on calcareous sand banks, the database of actual erosion cases on calcareous sand banks, relevant specifications, and the survey results of erosion disasters on calcareous sand banks, three levels of erosion disaster warning levels are set, with the warning for no erosion risk set as a green signal warning, the warning for minor erosion disasters set as a yellow signal warning, and the warning for severe erosion disasters set as a red signal warning, as well as corresponding three-dimensional disposal methods.

[0073] The deformation monitoring data of the calcareous sand bank slope collected in real time is transmitted to the data processing center for data processing to obtain deformation parameters. The deformation parameters are input into the erosion identification model, and the erosion identification model quickly determines whether the current calcareous sand bank slope is at risk of erosion disaster based on the deformation parameters. In the embodiment of the present invention, the erosion disaster label for no erosion is set to 0, the erosion disaster label for slight erosion is set to 1, and the erosion disaster label for severe erosion is set to 2. If the erosion disaster label predicted by the model is 0, it is judged that the current calcareous sand bank slope is safe to operate; if the erosion disaster label predicted by the model is 1, it is judged that the current calcareous sand bank slope is at risk of slight erosion disaster; if the erosion disaster label predicted by the model is 2, it is judged that the current calcareous sand bank slope is at risk of severe erosion disaster.

[0074] Based on the prediction results of minor and severe erosion, the system will send warning text messages to the staff of the coastal management department through the SMS platform according to the pre-set warning level, and at the same time issue sound and light alarm signals on the monitoring interface of the data processing center to remind relevant personnel to take timely response measures.

[0075] like Figure 5 As shown, an embodiment of the present invention also provides a calcareous sand bank erosion identification system based on fiber Bragg grating monitoring, which is implemented based on the above-mentioned calcareous sand bank erosion identification method based on fiber Bragg grating monitoring, and includes: a fiber Bragg grating monitoring module, a data preprocessing module, a model building module, an erosion identification module, an early warning module and a power supply and communication module.

[0076] Fiber Bragg grating monitoring module: The fiber Bragg grating displacement sensor installed on the top of the calcareous sand bank slope collects the horizontal and vertical displacements of the calcareous sand bank slope in real time. The optical signal is converted into a digital signal by a demodulator and transmitted to the data preprocessing module via a communication cable.

[0077] Data preprocessing module: performs denoising, outlier removal and data interpolation processing on the data collected by the fiber Bragg grating monitoring module.

[0078] Model construction module: Based on the improved HCA model, the deformation parameters of the calcareous sand bank under different erosion parameter combinations are simulated, the mapping relationship between the erosion parameters and the deformation parameters is fitted, and an erosion identification model is constructed. The erosion identification model is trained using historical monitoring data and the corresponding erosion conditions.

[0079] Erosion identification module: The pre-processed fiber Bragg grating data is input into the trained erosion identification model to output the erosion risk level of the current calcareous sand bank slope.

[0080] Early warning and visualization module: Provides graded early warning based on the erosion risk level output by the erosion identification module. If there is no erosion, a green signal is output and monitoring continues; if there is slight erosion, a yellow warning is output and an SMS message is notified to the operation and maintenance personnel; if there is severe erosion, a red alarm is output, an audible and visual alarm is issued, and an emergency response is carried out.

[0081] Power supply and communication module: Provides power to the fiber Bragg grating displacement sensor and demodulator, and uploads data to the cloud processing center via communication cables or 4G / 5G modules.

[0082] The embodiments of the present invention disclose a method and system for identifying erosion of calcareous sand bank slopes based on fiber Bragg grating monitoring. By real-time acquisition and processing of deformation monitoring data by a data processing center and a fiber Bragg grating demodulator, abnormal changes in deformation of calcareous sand bank slopes can be detected in a timely manner, and the erosion disaster risk warning level can be identified in the first place, thereby realizing real-time monitoring and warning of disasters.

[0083] Based on the numerical database of erosion disasters on calcareous sandbanks and the monitoring data of precise fiber Bragg grating displacement sensors, an extensively trained erosion recognition model was obtained using advanced data processing algorithms. This model can accurately extract characteristic information related to erosion disasters from deformation monitoring data, effectively reducing the misjudgment and missed detection rates of disaster identification.

[0084] Furthermore, compared to traditional geophysical detection methods, the present invention's technical solution, which primarily relies on sensors such as fiber Bragg gratings and data processing algorithms, offers low equipment cost, simple operation, and the ability to monitor large areas of bank slopes, making it highly cost-effective. It is also applicable to calcareous sand bank slopes in diverse geological conditions and marine environments, demonstrating strong versatility and adaptability.

[0085] The technical features of the above embodiments may be combined in any manner. To simplify the description, not all possible combinations of the technical features in the above embodiments are described. Only preferred embodiments of the present invention are presented. While the description is relatively specific and detailed, it should not be construed as limiting the scope of the present invention. As long as there are no conflicts in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] It should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the scope of the present invention, and these modifications and improvements fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A method for identifying erosion of calcareous sand bank slope based on fiber Bragg grating monitoring, characterized in that: The following steps are involved: Step S1: arranging a fiber Bragg grating displacement sensor on the top of the calcareous sand bank slope, and obtaining real-time deformation parameters of the calcareous sand bank slope through the fiber Bragg grating displacement sensor; Step S2: Using the state-dependent constitutive model of soil to replace the modified Cambridge elastoplastic constitutive model in the original calcareous sand cumulative deformation explicit calculation model HCA, the improved HCA model is used to simulate the deformation parameters of the calcareous sand bank under different erosion parameter combinations; The dilatancy equation of the state-dependent constitutive model of soil is expressed as: ψ=ee c ; Where D is the dilatancy ratio; is the plastic body strain increment; Plastic shear strain increment; d0 and m are model parameters with positive values; ψ is the state parameter; η is the stress ratio; M is the critical stress ratio; e is the porosity ratio; e c is the critical porosity ratio; e Γ , λ and ξ are all material constants determined by the critical state line of the ep plane; p is the average normal stress of the soil; p a It is the value after normalization of atmospheric pressure; Step S3: fitting the mapping relationship between the erosion parameters and the deformation parameters of the calcareous sand bank slope to obtain an erosion identification model; Step S4: training an erosion recognition model based on historical deformation parameters of the calcareous sand bank slope and corresponding erosion conditions, inputting the real-time deformation parameters into the trained erosion recognition model to obtain the real-time erosion conditions of the calcareous sand bank slope.

2. The method for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring according to claim 1, characterized in that: The deformation parameters in step S1 include the horizontal displacement and vertical displacement of the calcareous sand bank slope.

3. The method for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring according to claim 1, characterized in that: After the real-time deformation parameters of the calcareous sand bank slope are obtained by the fiber Bragg grating displacement sensor in step S1, the real-time deformation parameters are preprocessed, including the following steps: Step S11: using the exponential sliding average method to remove environmental noise information in the deformation parameters; Step S12: setting an abnormal threshold value based on historical deformation parameters to identify and remove abnormal deformation parameters; Step S13: using linear interpolation to identify and interpolate deformation parameter data containing missing values.

4. The method for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring according to claim 1, characterized in that: The etching parameters in step S2 include: etching depth and etching area.

5. The method for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring according to claim 1, characterized in that: In step S4, when training the erosion recognition model based on the historical monitoring data and the corresponding erosion conditions, a 10-fold cross-validation method is used to evaluate the accuracy of the erosion recognition model, and the parameters of the erosion recognition model are adjusted according to the evaluation results.

6. The method for identifying calcareous sand bank erosion based on fiber Bragg grating monitoring according to claim 1, characterized in that: After obtaining the real-time erosion situation of the calcareous sand bank slope in step S4, a graded warning is issued according to the real-time erosion situation. If there is no erosion, a green warning is output and monitoring continues; if there is slight erosion, a yellow warning is output and the operation and maintenance personnel are notified by SMS; if there is severe erosion, a red alarm is output, an audible and visual alarm is issued, and an emergency response is carried out.

7. A calcareous sand bank erosion identification system based on fiber Bragg grating monitoring, implemented based on a calcareous sand bank erosion identification method based on fiber Bragg grating monitoring according to any one of claims 1 to 6, characterized in that: include: Fiber Bragg grating monitoring module, data preprocessing module, model building module, erosion identification module, early warning and visualization module, power supply and communication module; The fiber Bragg grating monitoring module collects the horizontal and vertical displacements of the calcareous sand bank in real time through a fiber Bragg grating displacement sensor arranged on the top of the calcareous sand bank, converts the optical signal into a digital signal through a demodulator, and transmits it to the data preprocessing module via a communication cable; The data preprocessing module is used to perform denoising, outlier removal and data interpolation on the data collected by the fiber grating monitoring module; The model construction module simulates the deformation parameters of the calcareous sand bank slope under different erosion parameter combinations based on the improved HCA model, fits the mapping relationship between the erosion parameters and the deformation parameters, constructs an erosion recognition model, and trains the erosion recognition model using historical monitoring data and corresponding erosion conditions; The erosion identification module inputs the pre-processed fiber Bragg grating data into a trained erosion identification model and outputs the erosion risk level of the current calcareous sand bank slope.

8. The calcareous sand bank erosion identification system based on fiber Bragg grating monitoring according to claim 7 is characterized by: The early warning and visualization module provides graded early warning according to the erosion risk level output by the erosion identification module. If there is no erosion, a green signal is output and monitoring continues; if there is slight erosion, a yellow warning is output and an SMS message is notified to the operation and maintenance personnel; if there is severe erosion, a red alarm is output, an audible and visual alarm is issued, and an emergency response is carried out.

9. The calcareous sand bank erosion identification system based on fiber Bragg grating monitoring according to claim 7, characterized in that: The power supply and communication module provides power to the fiber Bragg grating demodulator and uploads data to the cloud processing center via a communication cable or a 4G / 5G module.

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