Wind tower structure health monitoring system and method, electronic equipment and medium

Abstract

The embodiment of the invention provides a wind tower structure health monitoring system and method, electronic equipment and a medium, and the system comprises an end layer which is used for sensing the physical quantity change of a specific part of a wind tower in real time, generating a sensor analog signal, converting the sensor analog signal into a sensor digital signal, obtaining preprocessed sensor data, and transmitting the preprocessed sensor data to an edge layer; the edge layer is used for analyzing the sensor data, providing an analysis result for operation and maintenance personnel, sending local early warning information when abnormality is detected, and sending the corresponding analysis result and related data as operation and maintenance data to the cloud layer; the cloud layer is used for storing the operation and maintenance data of each wind tower structure health monitoring system, and comprehensively evaluating and predicting the health condition of the wind tower structure by adopting a structure health evaluation and damage prediction model based on big data analysis and an artificial intelligence algorithm according to a large amount of historical operation and maintenance data; and remote management and work coordination are carried out on the equipment of the end layer and the edge layer.

Description

Technical Field

[0001] This document relates to the field of computer technology, and more particularly to a wind tower structure health monitoring system, method, electronic equipment and medium. Background Art

[0002] As the global demand for renewable energy increases, wind power generation has gradually become one of the important ways to obtain energy. As the core infrastructure of wind power generation, wind turbines bear huge wind loads, tower weight and equipment loads. During long-term operation, the wind tower structure will be affected by various external environmental factors, which may cause structural fatigue of the wind tower, loose bolts, tower deformation, increased concrete stress around the door, and other problems, thereby affecting the safety of the wind tower. At present, wind tower structural health monitoring mainly relies on traditional sensors and simple data processing methods. The existing technology has the following problems:

[0003] 1. The data collection accuracy is limited, and it is difficult to fully and accurately reflect the actual status of the wind tower;

[0004] 2. Lack of efficient data processing capabilities, unable to analyze and process large amounts of data in a timely manner;

[0005] 3. The level of intelligence is low, making it difficult to accurately predict and warn of potential problems with wind towers.

[0006] Therefore, due to the problems of limited data collection accuracy, lack of efficient data processing capabilities, and low intelligence in the existing wind tower structure monitoring methods, it is of great practical significance to develop a wind tower structure health monitoring system that can achieve high-precision data collection, efficient data processing, and intelligent analysis and prediction. Summary of the invention

[0007] The object of the present invention is to provide a wind tower structure health monitoring system, method, electronic equipment and medium, aiming to solve the above-mentioned problems in the prior art.

[0008] The present invention provides a wind tower structure health monitoring system, comprising:

[0009] The end layer is used to sense the physical quantity changes of specific parts of the wind tower in real time through sensors and generate sensor analog signals, collect the sensor analog signals through data acquisition equipment, convert them into sensor digital signals, pre-process the sensor data signals, obtain the pre-processed sensor data and send them to the edge layer;

[0010] The edge layer is used to analyze the sensor data, provide analysis results to the operation and maintenance personnel, and issue local warning information when an abnormality is detected, and send the corresponding analysis results and related data as operation and maintenance data to the cloud layer;

[0011] The cloud layer is used to store the operation and maintenance data of each wind tower structure health monitoring system. Based on a large amount of historical operation and maintenance data, big data analysis and artificial intelligence algorithms, it uses structural health assessment and damage prediction models to comprehensively assess and predict the health status of wind tower structures, and remotely manages and collaborates on end-layer and edge-layer equipment.

[0012] The present invention provides a wind tower structure health monitoring method, which is used in the wind tower structure health monitoring system, comprising:

[0013] The sensors at the end layer sense the physical quantity changes at specific parts of the wind tower in real time and generate sensor analog signals, the sensor analog signals are collected by data acquisition equipment, converted into sensor digital signals, the sensor data signals are preprocessed, the preprocessed sensor data are obtained and sent to the edge layer;

[0014] The sensor data is analyzed through the edge layer, and the analysis results are provided to the operation and maintenance personnel. When an abnormality is detected, a local warning message is issued, and the corresponding analysis results and related data are sent to the cloud layer as operation and maintenance data;

[0015] The operation and maintenance data of each wind tower structure health monitoring system are stored in the cloud. Based on a large amount of historical operation and maintenance data, big data analysis and artificial intelligence algorithms, structural health assessment and damage prediction models are used to comprehensively assess and predict the health status of wind tower structures, and remotely manage and coordinate work on end-layer and edge-layer equipment.

[0016] An embodiment of the present invention further provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the above-mentioned wind tower structure health monitoring method when executed by the processor.

[0017] An embodiment of the present invention further provides a computer-readable storage medium, on which a program for implementing information transmission is stored, and when the program is executed by a processor, the steps of the above-mentioned wind tower structure health monitoring method are implemented.

[0018] By adopting the embodiment of the present invention, a wind tower structural health monitoring system based on edge-cloud configuration and multi-technology collaboration is introduced. Real-time data collection by sensors is used to realize automatic monitoring, reducing the impact of human factors; comprehensive monitoring is realized through the collaboration of multiple sensors and various layers; real-time analysis of the edge layer and comprehensive judgment of the cloud layer are used to strengthen structural health assessment and early warning, damage prediction model, remote management and collaboration. It can realize real-time data collection, intelligent analysis and timely early warning, improve the operational safety and maintenance efficiency of wind towers, and ensure the long-term safe operation of wind towers in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate one or more embodiments of this specification or the technical solutions in 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 described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0020] Figure 1 is a schematic diagram of a wind tower structure health monitoring system according to an embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of the detailed structure of a wind tower structure health monitoring system according to an embodiment of the present invention;

[0022] Figure 3 is a flow chart of a method for monitoring the health of a wind tower structure according to an embodiment of the present invention;

[0023] Figure 4 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the following will be combined with the drawings in one or more embodiments of this specification to clearly and completely describe the technical solutions in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this document.

[0025] System Example

[0026] According to an embodiment of the present invention, a wind tower structure health monitoring system is provided. Figure 1 Schematic diagram of a wind tower structure health monitoring system according to an embodiment of the present invention. Figure 1 As shown, the wind tower structure health monitoring system according to an embodiment of the present invention specifically includes:

[0027] The end layer 10 is used to sense the physical quantity changes of specific parts of the wind tower in real time through sensors and generate sensor analog signals, collect the sensor analog signals through data acquisition equipment, convert them into sensor digital signals, pre-process the sensor data signals, obtain the pre-processed sensor data and send them to the edge layer; the sensor specifically includes at least one of the following: strain sensor, displacement sensor, acceleration sensor, inclination sensor and pressure sensor, wherein the strain sensor is used to monitor the tension of the prestressed steel strand, the displacement sensor is used to monitor the displacement caused by the stress change of concrete around the tower door, the inclination sensor is used to monitor the tilt displacement of the tower, and the pressure sensor is used to monitor the opening and closing state of the steel transition section and the transition pad. The sensor is connected to the data acquisition equipment by wire.

[0028] For the end layer sensor, the strain sensor can use a high-precision fiber Bragg grating stress sensor, which is based on fiber Bragg grating technology and has high precision, high sensitivity and anti-electromagnetic interference capability. It can achieve second-level data acquisition and analysis and is used to monitor the tension of prestressed steel strands. The displacement sensor can use a fiber Bragg grating displacement meter to monitor the opening and closing state of the steel transition section and the transition pad, and can accurately measure the displacement change and provide real-time feedback.

[0029] The edge layer 12 is used to analyze the sensor data, provide the analysis results to the operation and maintenance personnel, and issue a local warning message when an abnormality is detected, and send the corresponding analysis results and related data to the cloud layer as operation and maintenance data; it is used to: upload the sensor data to the edge computing node device through the communication device, perform real-time analysis of the strain data through the edge computing node device to determine whether there is local stress concentration, perform trend analysis on the displacement data to predict the structural deformation trend, and upload the analysis results and related data as operation and maintenance data to the cloud layer, and issue a local warning message through the alarm module when an abnormality is detected.

[0030] The cloud layer 14 is used to store the operation and maintenance data of each wind tower structure health monitoring system. Based on a large amount of historical operation and maintenance data, big data analysis and artificial intelligence algorithms, the structural health assessment and damage prediction model is used to comprehensively assess and predict the health status of the wind tower structure, and remotely manage and coordinate the equipment of the end layer and edge layer. The body is used to classify and store the operation and maintenance data according to the dimensions of structure type, monitoring time, and monitoring location.

[0031] The system of the embodiment of the present invention collects data in real time through sensors to achieve automated monitoring and reduce the impact of human factors; achieves comprehensive monitoring through the collaboration of multiple sensors and various layers; and strengthens structural health assessment and early warning, damage prediction model, remote management and collaboration through real-time analysis of the edge layer and comprehensive judgment of the cloud layer.

[0032] The technical solution of the embodiment of the present invention is described in detail below with reference to the accompanying drawings.

[0033] like Figure 3 As shown, the wind tower structure health monitoring system of the embodiment of the present invention includes an end layer, an edge layer and a cloud layer. Among them, between the end layer and the edge layer, the sensor sends the processed digital data to the edge layer through the data acquisition device. Between the edge layer and the cloud layer, the edge layer uploads the analysis results and valuable data to the cloud layer for storage and in-depth analysis. At the same time, the cloud layer can send instructions to the edge layer to perform operations such as device management and algorithm update. Although the cloud layer and the end layer are not directly connected, they are indirectly associated through the edge layer. The cloud layer can remotely manage the end layer equipment according to the wind tower structure information reflected by the data uploaded by the edge layer, such as adjusting the sensor acquisition frequency.

[0034] Specifically:

[0035] The end layer is the equipment layer, which consists of sensors and data acquisition equipment. The sensors include strain, displacement, acceleration, inclination, pressure sensors, etc., which are used to sense the physical quantity changes of key parts of the wind tower in real time, such as the tension of prestressed steel strands, the concrete stress around the tower door, the tilt displacement of the tower, and the opening and closing status of the steel transfer section and the transition pad. The data acquisition equipment is connected to the sensor, responsible for collecting the analog signal from the sensor and converting it into a digital signal, while performing simple filtering, amplification and other pre-processing operations.

[0036] For sensors, high-precision, high-sensitivity and strong anti-interference sensors can be further used, such as fiber Bragg grating stress sensors for prestressed steel strand tension monitoring, which can achieve second-level data collection and analysis; fiber Bragg grating displacement meters are used for monitoring the opening and closing status of steel transition sections and transition pads, which can accurately measure displacement changes and provide real-time feedback. Sensors and data acquisition equipment are connected by wire to ensure the accuracy and reliability of data collection. Data acquisition equipment, such as data acquisition instruments, have the function of collecting sensor analog signals and converting them into digital signals, and also have simple filtering, amplification and other pre-processing functions.

[0037] The edge layer is composed of edge computing node devices (such as small servers, smart gateways, edge computing boxes, etc.) and devices with communication capabilities (such as modules or devices with wireless communication functions). Its function is to further screen, analyze and preprocess the data transmitted from the end layer, such as real-time analysis of strain data to determine whether there is local stress concentration, trend analysis of displacement data to predict structural deformation trends, etc. At the same time, it can analyze data in real time, provide key warnings and preliminary processing suggestions to operation and maintenance personnel in real time, issue local warnings immediately when structural abnormalities are detected, and upload relevant data and preliminary analysis results to the cloud. For edge computing node devices, more powerful computing chips and storage devices can be equipped to improve data processing capabilities and speed. At the same time, its built-in analysis algorithm can be customized according to the structural characteristics of the wind tower and monitoring needs to improve the accuracy and pertinence of the analysis.

[0038] For edge computing node devices at the edge layer, small servers, smart gateways or edge computing boxes can be used. For example, small servers can be equipped with more powerful computing chips and storage devices to improve data processing capabilities and speed. Its built-in analysis algorithm can be customized according to the structural characteristics of the wind tower and monitoring requirements to improve the accuracy and pertinence of the analysis.

[0039] For devices with communication capabilities at the edge layer, devices that should have communication capabilities can use modules or devices with wireless communication functions, such as wireless communication modules using different protocols such as LoRa, NBIOT or ZigBee, which are used for data transmission with the end layer and cloud layer.

[0040] The cloud layer consists of multiple high-performance cloud servers and related data management and analysis software. It has data storage and management functions, and can store massive operation and maintenance data from different structural monitoring systems for a long time, and store them in categories according to dimensions such as structure type, monitoring time, and monitoring location. It also has the function of structural health assessment and damage prediction model. Based on a large amount of historical data, it uses big data analysis and artificial intelligence algorithms to comprehensively evaluate and predict the health status of wind tower structures. For example, it uses the analysis of tower tilt displacement data combined with environmental factors to establish a structural stability assessment model, and uses machine learning algorithms to analyze prestressed steel strand tension and other data to establish a structural damage prediction model. In addition, the cloud layer also has the function of remote equipment management and coordination, which can remotely manage the end layer and edge layer equipment, such as remotely updating the edge layer equipment analysis algorithm, adjusting the end layer sensor acquisition frequency, etc., and coordinating the work between the layers, receiving the working condition information and processing results from each layer for further analysis and decision-making. For the data analysis and management software of the cloud layer, the algorithm model can be continuously updated and optimized to meet the monitoring needs under different wind tower structures and environmental conditions. For example, for wind towers in different regions, the structural health assessment and damage prediction models are optimized by considering local climate, geology and other factors.

[0041] For the cloud layer, high-performance cloud servers are used to store large amounts of wind tower structure monitoring data and provide powerful computing power to support data analysis and processing.

[0042] For cloud-related data management and analysis software, the relevant data management and analysis software is used to classify and store wind tower structure monitoring data, conduct structural health assessment and damage prediction. For example, by analyzing the tower tilt displacement data combined with environmental factors, a structural stability assessment model is established, and a structural damage prediction model is established by using machine learning algorithms to analyze prestressed steel strand tension and other data.

[0043] It should be noted that in the embodiments of the present invention, in addition to the above-mentioned protocols such as LoRa, NBIOT or ZigBee, the communication module may also adopt 5G, LoRaWAN and other protocols to adapt to different application scenarios and data transmission requirements. A storage module may be added to the end layer or edge layer, such as a small solid-state hard drive or memory card, for temporary storage of collected data to prevent data loss or to ensure data continuity in the event of a network failure. A solution module may be added to the edge layer or cloud layer to perform more complex mathematical operations and analysis on the collected data, such as an in-depth analysis of the stress-strain relationship of the structure to improve the accuracy of the structural health assessment.

[0044] The system can be flexibly configured according to different wind tower structures and environmental conditions. For example, different types and quantities of sensors can be selected according to the height and complexity of the wind tower; appropriate communication protocols and equipment can be selected according to the local communication environment; and module configurations can be added or adjusted at different levels according to data processing requirements, such as adding storage modules or solution modules.

[0045] It can be seen from the above technical aspects that the technical solution of the embodiment of the present invention realizes the automation and intelligence of the health monitoring of the wind tower structure. Through the collaborative work of sensors and data acquisition equipment, data can be collected in real time without human intervention, which greatly reduces the workload of operation and maintenance personnel. The setting of the edge layer effectively reduces the burden on the cloud layer. Through the preliminary screening and analysis of the data, only valuable data is uploaded to the cloud layer, which improves the efficiency of data transmission and processing. The cloud layer uses its powerful computing power and storage resources to comprehensively evaluate and predict the health status of the wind tower structure, discover potential structural safety hazards in advance, and provide maintenance personnel with accurate decision-making basis, effectively improving the structural safety and maintenance efficiency of the wind tower. The overall collaborative work of the system enables data collection, transmission, analysis and early warning to form a complete closed loop, ensuring the continuity and reliability of wind tower structure monitoring.

[0046] like Figure 2 As shown, the specific functions and processes of the system are as follows:

[0047] The data collection process is as follows: the sensors at the end layer include strain, displacement, acceleration, inclination, pressure sensors, etc. For example, strain sensors are used to monitor the tension of prestressed steel strands, displacement sensors are used to monitor the displacement caused by the stress change of concrete around the tower door, inclination sensors are used to monitor the tilt displacement of the tower, and pressure sensors are used to monitor the opening and closing status of the steel transition section and the transition pad. These sensors transmit the collected physical quantity data to the data acquisition device, which converts the analog signal into a digital signal and performs simple filtering, amplification and other preprocessing operations.

[0048] The data transmission and processing process is as follows: the pre-processed data is uploaded to the edge computing node device through the communication device of the edge layer. The edge computing node device further screens, analyzes and pre-processes the data, such as real-time analysis of strain data to determine whether there is local stress concentration, trend analysis of displacement data to predict structural deformation trends, etc. At the same time, the edge computing node device uploads the analysis results and valuable data to the cloud layer. The server in the cloud layer stores and manages the data, and uses related software to perform structural health assessment and damage prediction. When a structural abnormality is detected, an early warning is issued in conjunction with the alarm module.

[0049] In summary, the technical solution of the embodiment of the present invention has the following beneficial effects:

[0050] Reduce labor costs: Through the automation of sensors and data acquisition equipment, data can be collected in real time without human intervention, greatly reducing the workload of operation and maintenance personnel. Improve monitoring accuracy: The accuracy of wind tower structural health monitoring is improved by adopting high-precision sensors, customized analysis algorithms, and comprehensive evaluation and prediction of cloud layers. Improve construction efficiency: The overall collaborative work of the system forms a complete closed loop of data collection, transmission, analysis and early warning, ensuring the continuity and reliability of wind tower structure monitoring, thereby improving construction efficiency. Intelligent features: The system has an automatic early warning function, which can promptly detect potential structural safety hazards, provide maintenance personnel with accurate decision-making basis, and embody intelligent features.

[0051] Method Embodiment

[0052] According to an embodiment of the present invention, a wind tower structural health monitoring method is provided for structural safety monitoring of a wind power tower, and is used for the above-mentioned wind tower structural health monitoring and repair. Figure 3 is a flow chart of a method for monitoring the health of a wind tower structure according to an embodiment of the present invention. Figure 3 As shown, the wind tower structure health monitoring method according to an embodiment of the present invention specifically includes:

[0053] Step S301, using sensors at the end layer to sense the physical quantity changes at specific parts of the wind tower in real time and generate sensor analog signals, collecting the sensor analog signals through data acquisition equipment, converting them into sensor digital signals, preprocessing the sensor data signals, obtaining preprocessed sensor data and sending them to the edge layer;

[0054] Step S302, analyzing the sensor data through the edge layer, providing the analysis results to the operation and maintenance personnel, and issuing local warning information when an abnormality is detected, and sending the corresponding analysis results and related data as operation and maintenance data to the cloud layer; specifically including:

[0055] The sensor data is uploaded to the edge computing node device through the communication device of the edge layer, and the strain data is analyzed in real time by the edge computing node device to determine whether there is local stress concentration, and the displacement data is trend analyzed to predict the structural deformation trend. The analysis results and related data are uploaded to the cloud layer as operation and maintenance data. When an abnormality is detected, a local warning message is issued through the alarm module.

[0056] Step S303, the operation and maintenance data of each wind tower structure health monitoring system are stored through the cloud. Based on a large amount of historical operation and maintenance data, based on big data analysis and artificial intelligence algorithms, a structural health assessment and damage prediction model is used to comprehensively assess and predict the health status of the wind tower structure, and remote management and work collaboration are carried out on the end layer and edge layer equipment.

[0057] The storage of the operation and maintenance data of each wind tower structure health monitoring system through the cloud layer specifically includes: classifying and storing the operation and maintenance data according to the dimensions of structure type, monitoring time, and monitoring location.

[0058] The embodiment of the present invention is a method embodiment corresponding to the above-mentioned system embodiment. The specific operation of each step can be understood by referring to the description of the system embodiment, which will not be repeated here.

[0059] Device Example 1

[0060] An embodiment of the present invention provides an electronic device, such as Figure 4 As shown, it includes: a memory 40, a processor 42, and a computer program stored in the memory 40 and executable on the processor 42. When the computer program is executed by the processor 42, the steps described in the method embodiment are implemented.

[0061] Device Example 2

[0062] An embodiment of the present invention provides a computer-readable storage medium, on which a program for implementing information transmission is stored. When the program is executed by the processor 42, the steps described in the method embodiment are implemented.

[0063] The computer-readable storage medium in this embodiment includes, but is not limited to, ROM, RAM, magnetic disk or optical disk, etc.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wind tower structural health monitoring system, characterized in that: include: The end layer is used to sense the physical quantity changes of specific parts of the wind tower in real time through sensors and generate sensor analog signals, collect the sensor analog signals through data acquisition equipment, convert them into sensor digital signals, pre-process the sensor data signals, obtain the pre-processed sensor data and send them to the edge layer; The edge layer is used to analyze the sensor data, provide analysis results to the operation and maintenance personnel, and issue local warning information when an abnormality is detected, and send the corresponding analysis results and related data as operation and maintenance data to the cloud layer; The cloud layer is used to store the operation and maintenance data of each wind tower structure health monitoring system. Based on a large amount of historical operation and maintenance data, big data analysis and artificial intelligence algorithms, it uses structural health assessment and damage prediction models to comprehensively assess and predict the health status of wind tower structures, and remotely manages and collaborates on end-layer and edge-layer equipment.

2. The system according to claim 1, characterized in that The sensor specifically includes at least one of the following: a strain sensor, a displacement sensor, an acceleration sensor, an inclination sensor and a pressure sensor, wherein the strain sensor is used to monitor the tension of the prestressed steel strand, the displacement sensor is used to monitor the displacement caused by the stress change of the concrete around the tower door, the inclination sensor is used to monitor the tilt displacement of the tower, and the pressure sensor is used to monitor the opening and closing status of the steel transition section and the transition pad.

3. The system according to claim 1, characterized in that The sensor is connected to the data acquisition device via a wired connection.

4. The system according to claim 1, characterized in that The edge layer is specifically used to: upload the sensor data to the edge computing node device through the communication device, perform real-time analysis on the strain data through the edge computing node device to determine whether there is local stress concentration, perform trend analysis on the displacement data to predict the structural deformation trend, and upload the analysis results and related data as operation and maintenance data to the cloud layer. When an abnormality is detected, a local warning message is issued through the alarm module.

5. The system according to claim 4, characterized in that The cloud layer is specifically used to classify and store the operation and maintenance data according to the dimensions of structure type, monitoring time, and monitoring location.

6. A method for monitoring the health of a wind tower structure, characterized in that: A wind tower structural health monitoring system for use in any one of claims 1 to 5, wherein the method specifically comprises: The sensors at the end layer sense the physical quantity changes at specific parts of the wind tower in real time and generate sensor analog signals, the sensor analog signals are collected by data acquisition equipment, converted into sensor digital signals, the sensor data signals are preprocessed, the preprocessed sensor data are obtained and sent to the edge layer; The sensor data is analyzed through the edge layer, and the analysis results are provided to the operation and maintenance personnel. When an abnormality is detected, a local warning message is issued, and the corresponding analysis results and related data are sent to the cloud layer as operation and maintenance data; The operation and maintenance data of each wind tower structure health monitoring system are stored in the cloud. Based on a large amount of historical operation and maintenance data, big data analysis and artificial intelligence algorithms, structural health assessment and damage prediction models are used to comprehensively assess and predict the health status of wind tower structures, and remotely manage and coordinate work on end-layer and edge-layer equipment.

7. The method according to claim 6, characterized in that The sensor data is analyzed through the edge layer, and the analysis results are provided to the operation and maintenance personnel. When an abnormality is detected, a local warning message is issued, and the corresponding analysis results and related data are sent to the cloud layer as operation and maintenance data. Specifically, it includes: The sensor data is uploaded to the edge computing node device through the communication device of the edge layer, and the strain data is analyzed in real time by the edge computing node device to determine whether there is local stress concentration, and the displacement data is trend analyzed to predict the structural deformation trend. The analysis results and related data are uploaded to the cloud layer as operation and maintenance data. When an abnormality is detected, a local warning message is issued through the alarm module.

8. The method according to claim 6, characterized in that Storing the operation and maintenance data of each wind tower structure health monitoring system through the cloud layer specifically includes: classifying and storing the operation and maintenance data according to the dimensions of structure type, monitoring time, and monitoring location.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the steps of the wind tower structure health monitoring method according to any one of claims 6 to 8 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an implementation program for information transmission, and when the program is executed by a processor, the steps of the wind tower structure health monitoring method according to any one of claims 6 to 8 are implemented.

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