Real-time stress analysis and early warning system for wharf breakwater

Abstract

The invention relates to the technical field of breakwater structure monitoring, in particular to a wharf breakwater real-time stress analysis and early warning system which comprises a stress data acquisition module, a data processing module, a stress analysis module, an early warning module, a display and interaction module and a data storage module. The stress data acquisition module is used for acquiring stress data of each structural part of the breakwater in real time, the data processing module is used for analyzing and preprocessing the acquired data, and the stress analysis module is used for establishing a stress distribution model and dynamically predicting a stress change trend through a finite element analysis method and a long-short-term memory network algorithm; the early warning module generates early warning information based on a preset threshold value and a dynamic adjustment mechanism, the display and interaction module is used for visually displaying a monitoring result and the early warning information, and the data storage module has compression and encryption functions and guarantees the integrity and security of data. According to the invention, accurate real-time monitoring and intelligent early warning of the breakwater can be realized, and the safety and reliability of the breakwater are improved.

Description

Technical Field

[0001] The invention relates to the technical field of breakwater structure monitoring, and in particular to a real-time stress analysis and early warning system for a wharf breakwater. Background Art

[0002] With the rapid development of global ports and coastal infrastructure construction, dock breakwaters, as important offshore protective structures, are widely used to resist the invasion of external forces such as waves and storm surges on port facilities and ensure the safe operation of ports. Breakwaters are subjected to repeated effects of natural forces for a long time, which can easily lead to structural fatigue, local damage or even structural failure. In order to ensure the safety and reliability of breakwaters, real-time monitoring of their stress changes and timely warning of potential structural abnormalities have become important research directions in structural health monitoring technology.

[0003] Existing breakwater structure monitoring technology mainly relies on regular manual inspections and offline data analysis methods, which have problems with lack of real-time and accuracy. Traditional monitoring systems are often based on simple stress data collection and static threshold warnings, and cannot dynamically respond to complex external environmental changes, making it difficult to make comprehensive and accurate predictions of the long-term health status of the structure. In addition, the existing technology lacks an intelligent early warning adjustment mechanism, which makes the system prone to false alarms or missed alarms. At the same time, in terms of data management, existing systems usually lack effective data compression and encryption functions, making it difficult to ensure the integrity and security of data in long-term storage, affecting the stable operation of the system and data utilization. Summary of the invention

[0004] The invention provides a real-time stress analysis and early warning system for a wharf breakwater.

[0005] The real-time stress analysis and early warning system for the wharf breakwater includes a stress data acquisition module, a data processing module, a stress analysis module, an early warning module, a display and interaction module and a data storage module, wherein; The stress data acquisition module is used to collect stress data of various structural parts of the wharf breakwater in real time, and the stress data acquisition module includes stress sensors installed in different areas of the breakwater; The data processing module is used to analyze and preprocess the stress data collected in real time to ensure the accuracy and timeliness of data processing; The stress analysis module is used to establish a stress distribution model of the breakwater based on the processed stress data by using a finite element analysis method, simulate the stress distribution of the breakwater under different load conditions, and combine a long short-term memory network algorithm based on a time series to predict future stress change trends based on real-time stress data and historical stress data; The early warning module is used to detect abnormal stress points in real time according to the analysis results of the stress analysis module, and the early warning module generates early warning information based on a preset threshold and a dynamic adjustment mechanism; The display and interaction module is used to visualize the monitoring results and warning information. The display and interaction module supports multi-dimensional data display, stress history trend chart and abnormal point highlighting, and provides user interaction function; The data storage module is used to store stress data, analysis results and warning information, and the data storage module has data compression and encryption functions.

[0006] Optionally, the stress data acquisition module specifically includes: Sensor layout planning: Plan the installation location of stress sensors based on the structural characteristics of the wharf breakwater and the stress distribution in different areas; Sensor type selection: Select a suitable stress sensor according to the type of stress to be monitored. Sensors used for stress acquisition include strain gauges, fiber grating sensors or piezoelectric sensors. Different types of sensors are selected according to environmental conditions and monitoring requirements. Sensor installation: The stress sensor is installed at various stress locations of the breakwater through a fixed bracket; Data transmission method: The stress sensor is connected to the data processing module via wired or wireless means; Real-time data acquisition: The stress sensor continuously acquires stress data of each stress position in real time, and the acquisition frequency is adjusted according to the stress change rate of the breakwater.

[0007] Optionally, the data processing module specifically includes: Data reception: The data processing module receives real-time stress data from the stress data acquisition module through a wired or wireless network; Data cleaning: The data processing module performs preliminary processing on the received stress data, including removing outliers, filling missing data, and filtering noise; Data analysis: The data processing module analyzes the cleaned data and converts it into a format suitable for the stress analysis module, including unit conversion, coordinate system mapping and data format standardization of stress data; Data preprocessing: After data parsing, the data processing module performs further preprocessing, including noise reduction, interpolation, and downsampling operations; Data verification: After completing preprocessing, the data processing module performs consistency verification on the processed data.

[0008] Optionally, the stress analysis module establishes a stress distribution model of the breakwater by a finite element analysis method based on the processed stress data, specifically including: Data input: receiving processed stress data from the data processing module; Establish stress distribution model: Based on the geometric structure, material properties and boundary conditions of the breakwater, the stress distribution model is established by finite element analysis method; Meshing: Adaptive meshing technology is used to mesh the stress distribution model of the breakwater; Stress distribution calculation: Based on the input processed stress data, the finite element analysis method is used to calculate the stress distribution of the stress distribution model under different external forces; Model verification and adjustment: Compare and verify the calculated stress distribution results with the actual measured stress data.

[0009] Optionally, the stress analysis module combines a long short-term memory network algorithm based on time series to predict future stress change trends based on real-time stress data and historical stress data, specifically including: Data input: A long short-term memory network model is constructed through a long short-term memory network algorithm, and real-time stress data and historical stress data from the data processing module are used as inputs of the long short-term memory network model; Data normalization: normalize the input stress data; Model training: Train the long-short-term memory network model through historical stress data to learn the law of stress data changing over time; Real-time prediction: The long short-term memory network model predicts future stress change trends by inputting real-time stress data; Error optimization: The difference between the model prediction results and the actual stress values ​​is evaluated through the loss function, and the model parameters are adjusted using the back propagation algorithm to improve the prediction accuracy.

[0010] Optionally, the early warning module detects abnormal stress points in real time through a preset threshold mechanism, specifically including: Determination of preset thresholds: Based on historical stress data and breakwater design specifications, set stress safety thresholds for each part; Real-time stress data monitoring: The early warning module uses the real-time stress data provided by the stress analysis module and compares it with the corresponding safety threshold; Abnormal detection: If the real-time stress value of a certain structural part exceeds the preset safety threshold, the early warning module automatically detects the abnormal stress point and activates the early warning mechanism; Warning information generation: When an abnormal stress point is detected, the warning module generates warning information, which includes the abnormal location, stress value and the degree of exceeding the threshold.

[0011] Optionally, the warning module optimizes the warning threshold through a dynamic adjustment mechanism, specifically including: Dynamic threshold adjustment mechanism: The early warning module automatically adjusts the stress threshold of each part based on the change trend of real-time stress data and the statistical results of historical data; Stress trend analysis: Based on the stress change trend predicted by the stress analysis module, the system dynamically adjusts the threshold; Threshold adaptive update: The system continuously collects and analyzes the long-term stress data of the breakwater, adaptively adjusts the warning threshold, and reduces the false alarm rate and missed alarm rate; Real-time warning optimization: After dynamically adjusting the threshold, the system continues to monitor stress data in real time. When the stress exceeds the dynamically adjusted threshold, the warning module automatically issues a warning.

[0012] Optionally, the display and interaction module specifically includes: Data visualization processing: The display and interaction module obtains real-time stress data, historical data and warning information from the data processing module and stress analysis module, and performs visualization processing; Multi-dimensional data display: The display and interaction module supports the comprehensive display of multi-dimensional data, and users can view stress data of multiple dimensions simultaneously in the same interface; Stress history trend chart: The display and interaction module supports the time series display of stress history data. The stress change process of each part of the breakwater structure is displayed through the stress history trend chart; Abnormal point highlighting: When the early warning module detects stress abnormality, the display and interaction module will automatically display the abnormal point in the interactive interface; User interaction function: The display and interaction module provides user interaction function. Users can select different time periods and different parts of the breakwater through the interface to view the corresponding stress data and warning information.

[0013] Optionally, the data storage module specifically includes: Data classification storage: The data storage module classifies and stores data according to data types, including real-time stress data, historical stress data, stress analysis results, and early warning information; Data compression processing: The data storage module uses data compression algorithm to compress the stress data stored for a long time; Data encryption storage: To ensure the security of stress data, the data storage module encrypts all data before storage; Data backup: The data storage module supports automatic backup function and regularly backs up multiple copies of important data; Data access permission control: The data storage module controls the access permission of stored data.

[0014] Beneficial effects of the present invention: The present invention can realize real-time stress monitoring of various structural parts of the breakwater, and combine finite element analysis and long short-term memory network algorithm to accurately analyze and dynamically predict stress data. The stress analysis module models the time series of stress data through the long short-term memory network, which can accurately predict future stress change trends and discover potential structural abnormalities in advance, effectively improving the early warning capability of the system.

[0015] In the present invention, the early warning module is based on preset thresholds and dynamic adjustment mechanisms. When stress exceeds the safety threshold or an abnormality is detected in trend prediction, it can automatically generate early warning information and remind the user. By dynamically adjusting the early warning threshold, the system can adaptively adjust the early warning strategy according to the changes in real-time stress data and historical data, reduce false alarms and missed alarms, and further improve the accuracy and timeliness of early warnings. This intelligent early warning mechanism ensures the safe operation of the breakwater in a long-term complex environment.

[0016] In the present invention, the data storage module has data compression and encryption functions to ensure the integrity and security of stress data, analysis results and warning information in long-term storage. At the same time, the display and interaction module provides functions such as multi-dimensional data display, stress history trend chart and abnormal point highlighting, which helps users intuitively understand the stress distribution and warning information of the breakwater. Users can also customize and adjust the operating parameters of the system through the interactive interface, which further improves the operability of the system and the flexibility of data management, and ensures all-round monitoring of the health status of the breakwater. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the composition of system function modules of an embodiment of the present invention; Figure 2 The figure is a schematic diagram of the early warning module flow in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0020] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0021] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0022] like Figure 1-Figure 2 As shown, the real-time stress analysis and early warning system for the wharf breakwater includes a stress data acquisition module, a data processing module, a stress analysis module, an early warning module, a display and interaction module and a data storage module, wherein; The stress data acquisition module is used to collect stress data of various structural parts of the wharf breakwater in real time. The stress data acquisition module includes stress sensors installed in different areas of the breakwater; The data processing module is used to analyze and preprocess the stress data collected in real time to ensure the accuracy and timeliness of data processing; The stress analysis module is used to establish the stress distribution model of the breakwater based on the processed stress data through the finite element analysis method, simulate the stress distribution of the breakwater under different load conditions, and combine the long short-term memory network algorithm based on time series to predict the future stress change trend according to the real-time stress data and historical stress data, and continuously optimize the model parameters to improve the prediction accuracy; The early warning module is used to detect abnormal stress points in real time based on the analysis results of the stress analysis module. The early warning module generates early warning information based on preset thresholds and dynamic adjustment mechanisms to remind users of possible structural abnormalities; The display and interaction module is used to visualize the monitoring results and warning information. The display and interaction module supports multi-dimensional data display, stress history trend chart and abnormal point highlighting, and provides user interaction function; The data storage module is used to store stress data, analysis results and warning information. The data storage module has data compression and encryption functions to ensure the integrity and security of stress data stored for a long time.

[0023] The stress data acquisition module specifically includes: Sensor layout planning: According to the structural characteristics of the wharf breakwater and the stress distribution in different areas, the installation location of the stress sensor is planned. The sensor is preferably installed at the key stress parts of the breakwater, including the foundation area, side wall area and top area, to ensure full coverage of the entire breakwater structure; Sensor type selection: Select a suitable stress sensor according to the type of stress to be monitored. Sensors used for stress acquisition include strain gauges, fiber grating sensors or piezoelectric sensors. Different types of sensors are selected according to environmental conditions and monitoring requirements to ensure the accuracy and stability of data acquisition; Sensor installation: The stress sensor is installed at various stress locations of the breakwater through a fixed bracket. The installation should ensure that the sensor is in close contact with the breakwater surface to avoid the influence of environmental noise and external interference on the stress data. The sensor installation ensures long-term stability and is easy to maintain and replace; Data transmission method: The stress sensor is connected to the data processing module by wired or wireless means. The wireless transmission method is suitable for areas with complex environments and inconvenient wiring, while the wired transmission method can ensure high reliability and low latency of data transmission. The stress sensor has anti-interference ability to ensure that the data transmission process is not affected by factors such as electromagnetic interference; Real-time data acquisition: The stress sensor continuously collects stress data of each stress part in real time. The acquisition frequency is adjusted according to the stress change rate of the breakwater, usually ranging from 1Hz to 100Hz, to ensure that the dynamic and real-time nature of stress changes can be captured; Through reasonable sensor arrangement, selection of appropriate sensor types and data transmission methods, the stress data acquisition module can comprehensively and accurately collect stress data of the wharf breakwater, ensuring a reliable real-time data basis for subsequent stress analysis and early warning.

[0024] The data processing module specifically includes: Data reception: The data processing module receives real-time stress data from the stress data acquisition module through a wired or wireless network. The data processing module has a multi-channel data reception function, supports multiple sensors to send data simultaneously, and performs time synchronization processing on the data during the reception process to ensure the time consistency of each stress data; Data cleaning: The data processing module performs preliminary processing on the received stress data, including removing outliers, filling missing data and filtering noise. The data cleaning process adopts a sliding window-based filtering algorithm, which can be expressed as: ; in, After filtering at time The stress data represents the stress value at the current moment after sliding window filtering. For at the moment The collected stress data indicates that the sensor is in front The original stress data collected in each time step, the sensor collects stress values ​​at different positions in real time, and records the stress value at each moment through this variable. is the size of the sliding window, expressed as the current time and the previous The number of data points in a time step, which determines the data range for smoothing; Data analysis: The data processing module analyzes the cleaned data and converts it into a format suitable for the stress analysis module, including unit conversion, coordinate system mapping and data format standardization of stress data. For multi-source stress data, the data processing module converts the data uniformly to ensure consistent standards in subsequent analysis steps; Data preprocessing: After data parsing, the data processing module performs further preprocessing, including noise reduction, interpolation, and downsampling operations to ensure the accuracy and timeliness of the data. The downsampling operation is expressed as: ; in, After downsampling at time The stress data represents the stress data at the current moment after downsampling, which is used to reduce data redundancy and reduce processing load. is the downsampling rate, which indicates the number of sampling data points involved in the calculation. For at the moment The original stress data indicates that the sensor is The stress data collected in each time step can be downsampled to reduce data redundancy, storage and processing pressure, while keeping the overall trend unchanged; Data verification: After completing preprocessing, the data processing module performs consistency verification on the processed data to ensure the validity and integrity of each stress data. The verification mechanism includes integrity check of the data packet and verification of fields such as timestamp and sensor identification; The data processing module uses a multi-step data processing process, including data reception, cleaning, analysis, preprocessing and verification, to ensure that the stress data collected in real time is accurate, complete and timely, providing high-quality data input for the stress analysis module.

[0025] The stress analysis module establishes the stress distribution model of the breakwater based on the processed stress data through the finite element analysis method, including: Data input: receiving processed stress data from the data processing module, the stress data including stress values ​​at different parts of the breakwater; Establishing stress distribution model: Based on the geometric structure, material properties and boundary conditions of the breakwater, the stress distribution model is established by finite element analysis method. The geometric structure is generated according to the design of the actual breakwater. The material parameters include Young's modulus, Poisson's ratio, etc. The boundary conditions are set as the fixed support of the breakwater and the external force. Meshing: The stress distribution model of the breakwater is meshed using adaptive meshing technology, and denser meshes are used at stress concentration locations (such as the joints and corners of the breakwater) to improve calculation accuracy; Stress distribution calculation: Based on the input processed stress data, the finite element analysis method is used to calculate the stress distribution of the stress distribution model under different external forces. The calculation includes static analysis and dynamic analysis to simulate the stress changes of the breakwater under dynamic loads such as waves and wind; Model verification and adjustment: Compare and verify the calculated stress distribution results with the actual measured stress data, and calibrate the model by adjusting material parameters and boundary conditions to ensure that the model can accurately reflect the stress state of the breakwater; Through the finite element analysis method, the stress distribution model can accurately simulate the stress distribution of the breakwater structure under the action of external forces, providing a reliable basis for stress prediction and early warning.

[0026] The stress analysis module combines the long short-term memory network algorithm based on time series to predict future stress change trends based on real-time stress data and historical stress data, including: Data input: A long short-term memory network model is constructed through the long short-term memory network algorithm. The real-time stress data and historical stress data from the data processing module are used as the input of the long short-term memory network model. The data includes stress values ​​and time series data of different parts of the breakwater. Data normalization: Normalize the input stress data and scale all feature data to the range of [0,1] to ensure the stability of model training and reduce the impact of dimensional differences on the model; Model training: The long short-term memory network model is trained through historical stress data to learn the law of stress data changing over time. The long short-term memory network model can capture the long-term dependency in stress changes and predict future stress changes through hidden state updates, which can be expressed as: ; in, is the hidden layer state at the current moment, is the input data at the current moment, and are the input and hidden layer weight matrices, respectively, is the bias term, is the activation function; Real-time prediction: The long short-term memory network model predicts future stress change trends by inputting real-time stress data, and updates model parameters based on real-time data to ensure the accuracy and timeliness of the prediction results; Error optimization: The difference between the model prediction result and the actual stress value is evaluated through the loss function (such as mean square error), and the model parameters are adjusted using the back propagation algorithm to improve the prediction accuracy, which is expressed as: ; in, is the loss function, is the actual stress value, is the model prediction value, is the sample size; The stress analysis module can dynamically update the stress distribution model, accurately predict the stress change trend of the breakwater, and adapt to changes in environmental and stress conditions in real time, thereby improving the accuracy of the early warning system.

[0027] The early warning module detects abnormal stress points in real time through a preset threshold mechanism, including: Preset threshold determination: Based on historical stress data and breakwater design specifications, the stress safety threshold of each part is set. The threshold range is calculated according to the material properties, structural design and environmental conditions (such as wave height, wind speed, etc.) of the breakwater. Each structural part (such as foundation, side wall, top) is set with an independent stress threshold to reflect the bearing capacity of different parts; Real-time stress data monitoring: The early warning module continuously monitors the stress status of each structural part of the breakwater through the real-time stress data provided by the stress analysis module. The system regularly obtains the real-time stress value of each part and compares it with the corresponding safety threshold; Abnormal detection: If the real-time stress value of a certain structural part exceeds the preset safety threshold, the early warning module automatically detects the abnormal stress point. At this time, the system will mark the abnormal point as a potential structural abnormal area and activate the early warning mechanism; Warning information generation: When an abnormal stress point is detected, the warning module immediately generates warning information, which includes the abnormal location, stress value and the degree of exceeding the threshold; Through a detection mechanism based on preset thresholds, the early warning module can detect stress anomalies in various structural parts of the breakwater in real time, effectively identify possible structural safety issues, and generate early warning information in a timely manner to ensure the safe operation of the breakwater.

[0028] The early warning module optimizes the early warning threshold through a dynamic adjustment mechanism, including: Dynamic threshold adjustment mechanism: The early warning module automatically adjusts the stress threshold of each part based on the change trend of real-time stress data and the statistical results of historical data. The dynamic adjustment mechanism calculates the stress fluctuation range and optimizes the threshold according to the stress change law monitored over a long period of time, so that the early warning system can sensitively respond to environmental changes and structural fatigue. Stress trend analysis: Through the stress change trend predicted by the stress analysis module, the early warning module detects possible future stress peaks or stress concentration areas in advance. According to the prediction results, the system dynamically adjusts the threshold to ensure that efficient early warning performance can be maintained even when the stress fluctuates greatly; Threshold adaptive update: The system continuously collects and analyzes the long-term stress data of the breakwater, adaptively adjusts the warning threshold, reduces the false alarm rate and missed alarm rate, and appropriately relaxes the threshold for stress changes that fluctuate frequently but do not affect the safety of the structure, and tightens the threshold for sudden stress fluctuations; Real-time warning optimization: After dynamically adjusting the threshold, the system continues to monitor stress data in real time. When the stress exceeds the dynamically adjusted threshold, the warning module automatically issues a high-priority warning to remind users of the upcoming structural abnormality risk; Through the dynamic adjustment mechanism, the early warning module can automatically optimize the early warning threshold according to the changes in real-time stress data, making the system more sensitive and accurate, effectively responding to long-term structural fatigue and sudden stress fluctuations, and improving the effectiveness of the early warning.

[0029] The display and interaction modules specifically include: Data visualization processing: The display and interaction module obtains real-time stress data, historical data and warning information from the data processing module and stress analysis module, and performs visualization processing. The system presents the monitoring results to the user through charts, three-dimensional models and color coding. The stress data of different parts are displayed in different colors and graphics, so that users can understand the stress distribution of the breakwater at a glance; Multi-dimensional data display: The display and interaction module supports the comprehensive display of multi-dimensional data. Users can view stress data of multiple dimensions at the same time in the same interface. For example, users can choose to display the real-time stress, historical stress change trend and warning information of different parts of the breakwater. The system provides multiple view switching functions, which allows users to choose two-dimensional plane diagrams, three-dimensional stereo diagrams or time series diagrams according to their needs. Stress history trend chart: The display and interaction module supports the time series display of stress history data. Through the stress history trend chart, the stress change process of each part of the breakwater structure is displayed, and the time and frequency of the stress peak are displayed. The system provides zooming and sliding functions, and users can flexibly adjust the time window to view long-term or short-term stress changes; Highlighting of abnormal points: When the early warning module detects stress abnormalities, the display and interaction module will automatically highlight the abnormal points in the interactive interface. The highlighted parts include the parts where the stress exceeds the threshold, the stress value and the degree of excess. The abnormal points will be marked in eye-catching colors. Users can click on the highlighted area to view detailed abnormal information and recommended disposal measures. User interaction function: The display and interaction module provides user interaction function. Users can select different time periods and different parts of the breakwater through the interface to view the corresponding stress data and warning information. In addition, the system supports users to set thresholds, adjust display modes (such as switching between 3D and 2D views), and export data reports. Through linkage with the warning module, users can also actively view historical warning records and adjust warning threshold settings according to needs; The display and interaction module intuitively displays the stress distribution and warning information of the breakwater structure through visual display, multi-dimensional data presentation, stress history trend chart and abnormal point highlighting function. Its interactive function further improves the user's operability and control over the system, and provides users with comprehensive stress monitoring support.

[0030] The data storage module specifically includes: Data classification storage: The data storage module classifies and stores data according to data types, including real-time stress data, historical stress data, stress analysis results, and early warning information. Each type of data is indexed and archived according to time and breakwater location to ensure the efficiency of subsequent query and analysis. The system adopts a hierarchical storage strategy for stress data and analysis results based on the importance and access frequency of the data. Real-time data is preferentially stored in high-speed storage devices, and historical data is archived to large-capacity storage devices; Data compression processing: The data storage module uses a data compression algorithm to compress the stress data stored for a long time. The compression algorithm performs lossless compression based on the characteristics of the stress data to ensure data integrity; Data encryption storage: To ensure the security of stress data, the data storage module encrypts all data before storage; Data backup: The data storage module supports automatic backup function, and regularly backs up multiple copies of important data (such as historical stress data, warning information, etc.). The backup is stored in an off-site server or cloud storage to prevent data loss or damage. The system also provides data recovery function. When the storage device fails, the stress data and analysis results can be quickly restored from the backup to ensure the continuous and stable operation of the system. Data access permission control: The data storage module controls access permissions for stored data. Users must pass identity authentication before they can access specific data types. The system supports different levels of access permission configuration to ensure that key data (such as analysis results and warning information) can only be accessed and modified by authorized personnel. Through data classification storage, compression and encryption processing, the data storage module can effectively manage the long-term storage of breakwater stress data, ensure the integrity and security of the data, and also have backup and recovery functions to prevent data loss and ensure the continuous operation of the system.

[0031] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0032] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. Real-time stress analysis and early warning system for wharf breakwater, characterized by: It includes stress data acquisition module, data processing module, stress analysis module, early warning module, display and interaction module and data storage module, among which; The stress data acquisition module is used to collect stress data of various structural parts of the wharf breakwater in real time, and the stress data acquisition module includes stress sensors installed in different areas of the breakwater; The data processing module is used to analyze and preprocess the stress data collected in real time; The stress analysis module is used to establish a stress distribution model of the breakwater based on the processed stress data by using a finite element analysis method, simulate the stress distribution of the breakwater under different load conditions, and combine a long short-term memory network algorithm based on a time series to predict future stress change trends based on real-time stress data and historical stress data; The early warning module is used to detect abnormal stress points in real time according to the analysis results of the stress analysis module, and the early warning module generates early warning information based on a preset threshold and a dynamic adjustment mechanism; The display and interaction module is used to visualize the monitoring results and warning information. The display and interaction module supports multi-dimensional data display, stress history trend chart and abnormal point highlighting, and provides user interaction function; The data storage module is used to store stress data, analysis results and warning information, and the data storage module has data compression and encryption functions.

2. The real-time stress analysis and early warning system for dock breakwater according to claim 1 is characterized in that: The stress data acquisition module specifically includes: Sensor layout planning: Plan the installation location of stress sensors based on the structural characteristics of the wharf breakwater and the stress distribution in different areas; Sensor type selection: Select a stress sensor based on the type of stress to be monitored. Sensors used for stress acquisition include strain gauges, fiber grating sensors, or piezoelectric sensors. Different types of sensors are selected based on environmental conditions and monitoring requirements. Sensor installation: The stress sensor is installed at various stress locations of the breakwater through a fixed bracket; Data transmission method: The stress sensor is connected to the data processing module via wired or wireless means; Real-time data acquisition: The stress sensor continuously acquires stress data of each stress position in real time, and the acquisition frequency is adjusted according to the stress change rate of the breakwater.

3. The real-time stress analysis and early warning system for dock breakwater according to claim 2 is characterized in that: The data processing module specifically includes: Data reception: The data processing module receives real-time stress data from the stress data acquisition module through a wired or wireless network; Data cleaning: The data processing module performs preliminary processing on the received stress data, including removing outliers, filling missing data, and filtering noise; Data analysis: The data processing module analyzes the cleaned data, including unit conversion, coordinate system mapping and data format standardization of stress data; Data preprocessing: After data parsing, the data processing module performs further preprocessing, including noise reduction, interpolation, and downsampling operations; Data verification: After completing preprocessing, the data processing module performs consistency verification on the processed data.

4. The real-time stress analysis and early warning system for dock breakwater according to claim 3 is characterized in that: The stress analysis module establishes a stress distribution model of the breakwater based on the processed stress data by using a finite element analysis method, specifically including: Data input: receiving processed stress data from the data processing module; Establish stress distribution model: Based on the geometric structure, material properties and boundary conditions of the breakwater, the stress distribution model is established through finite element analysis method; Meshing: Adaptive meshing technology is used to mesh the stress distribution model of the breakwater; Stress distribution calculation: Based on the input processed stress data, the finite element analysis method is used to calculate the stress distribution of the stress distribution model under different external forces; Model verification and adjustment: Compare and verify the calculated stress distribution results with the actual measured stress data.

5. The real-time stress analysis and early warning system for dock breakwater according to claim 4 is characterized in that: The stress analysis module combines the long short-term memory network algorithm based on time series to predict future stress change trends based on real-time stress data and historical stress data, specifically including: Data input: A long short-term memory network model is constructed through a long short-term memory network algorithm, and real-time stress data and historical stress data from the data processing module are used as inputs of the long short-term memory network model; Data normalization: normalize the input stress data; Model training: Train the long-short-term memory network model through historical stress data to learn the law of stress data changing over time; Real-time prediction: The long short-term memory network model predicts future stress change trends by inputting real-time stress data; Error optimization: The difference between the model prediction results and the actual stress values ​​is evaluated through the loss function, and the model parameters are adjusted using the back propagation algorithm to improve the prediction accuracy.

6. The real-time stress analysis and early warning system for dock breakwater according to claim 5 is characterized in that: The early warning module detects abnormal stress points in real time through a preset threshold mechanism, specifically including: Determination of preset thresholds: Based on historical stress data and breakwater design specifications, set stress safety thresholds for each part; Real-time stress data monitoring: The early warning module uses the real-time stress data provided by the stress analysis module and compares it with the corresponding safety threshold; Abnormal detection: If the real-time stress value of a certain structural part exceeds the preset safety threshold, the early warning module automatically detects the abnormal stress point and activates the early warning mechanism; Warning information generation: When an abnormal stress point is detected, the warning module generates warning information, which includes the abnormal location, stress value and the degree of exceeding the threshold.

7. The real-time stress analysis and early warning system for dock breakwater according to claim 6 is characterized in that: The early warning module optimizes the early warning threshold through a dynamic adjustment mechanism, specifically including: Dynamic threshold adjustment mechanism: The early warning module automatically adjusts the stress threshold of each part based on the change trend of real-time stress data and the statistical results of historical data; Stress trend analysis: Based on the stress change trend predicted by the stress analysis module, the system dynamically adjusts the threshold; Threshold adaptive update: The system continuously collects and analyzes the long-term stress data of the breakwater, adaptively adjusts the warning threshold, and reduces the false alarm rate and missed alarm rate; Real-time warning optimization: After dynamically adjusting the threshold, the system continues to monitor stress data in real time. When the stress exceeds the dynamically adjusted threshold, the warning module automatically issues a warning.

8. The real-time stress analysis and early warning system for dock breakwater according to claim 7 is characterized in that: The display and interaction module specifically includes: Data visualization processing: The display and interaction module obtains real-time stress data, historical data and warning information from the data processing module and stress analysis module, and performs visualization processing; Multi-dimensional data display: The display and interaction module supports the comprehensive display of multi-dimensional data, and users can view stress data of multiple dimensions simultaneously in the same interface; Stress history trend chart: The display and interaction module supports the time series display of stress history data. The stress change process of each part of the breakwater structure is displayed through the stress history trend chart; Abnormal point highlighting: When the early warning module detects stress abnormality, the display and interaction module will automatically display the abnormal point in the interactive interface; User interaction function: The display and interaction module provides user interaction function. Users can select different time periods and different parts of the breakwater through the interface to view the corresponding stress data and warning information.

9. The real-time stress analysis and early warning system for dock breakwater according to claim 8, characterized in that: The data storage module specifically includes: Data classification storage: The data storage module classifies and stores data according to data types, including real-time stress data, historical stress data, stress analysis results, and early warning information; Data compression processing: The data storage module uses data compression algorithm to compress stress data; Data encryption storage: The data storage module encrypts the data before storage; Data backup: The data storage module supports automatic backup function and regularly backs up multiple copies of important data; Data access permission control: The data storage module controls the access permission of stored data.

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