Power tower status detection equipment, method, medium and program product

Abstract

The present application provides a power tower mechanical state detection device, method, medium and program product. The power tower mechanical state detection device includes a control device, a collection device and a flight device. The control device is configured to: control the flight device to move to the corresponding position of the target power tower, and control the collection device to collect hyperspectral images of multiple steel structures at different positions; analyze the corrosion condition of the steel structures based on the hyperspectral images of the steel structures, and use a pre-built post-corrosion mechanical property model to predict the residual bearing capacity of the steel structures; perform mechanical property simulation based on the residual bearing capacity of each steel structure to predict the health status of the target power tower; when it is predicted that the target power tower has a safety risk, perform a safety risk classification warning on the target power tower, greatly reduce the detection time, and reduce problems such as missed detection and misjudgment, thereby improving the accuracy and efficiency of power tower state detection.

Description

Technical Field

[0001] The present invention relates to the field of power safety technology, and in particular to a power tower status detection device, method, medium and program product. Background Art

[0002] Power towers operate in a complex environment. During their service, their steel components are exposed to environmental factors such as corrosive media, air, and temperature and humidity fluctuations. This can cause surface coatings to degrade and fail, leading to corrosion of the steel components. As corrosion progresses, the structure and morphology of the corroded steel components change, affecting their mechanical properties and force transmission mechanisms, jeopardizing the safety and reliability of the tower's overall structure. Therefore, to ensure the safety and operational reliability of power towers, it is necessary to inspect and assess the tower's structural health so that timely structural maintenance can be performed.

[0003] At present, the inventors have found that the inspection work of power towers mainly relies on manual inspections of some points on the power towers. Due to the dangers of high-altitude operations, the limitations of inspection cycles, and the subjective errors of manual judgment, the accuracy and efficiency of traditional workers' inspections are not high. In particular, there is a lack of scientific operation and maintenance decisions based on the overall safety of the structure, which makes it difficult to meet the preventive and precise maintenance needs of infrastructure such as transmission towers in the context of high-quality development needs of the large-scale power industry. Summary of the Invention

[0004] The present invention provides a power tower status detection device, method, medium and program product to solve the operation and maintenance difficulties of traditional manual inspections, such as low accuracy, poor timeliness, and low objective scientificity due to the main experience, which makes it difficult to meet the preventive and precision maintenance needs of large-scale power towers.

[0005] In a first aspect, an embodiment of the present application provides a power tower status detection device, comprising:

[0006] An acquisition device, used for acquiring hyperspectral images of a target;

[0007] A flying device, used to respond to control and drive the collection device to move to a corresponding position;

[0008] The control device connected to the acquisition device and the flight device is configured as follows:

[0009] Controlling the flight device to move to a corresponding position of the target power tower, and controlling the acquisition device to acquire hyperspectral images to acquire hyperspectral images of multiple steel structures at different positions in the target power tower;

[0010] Based on the hyperspectral images of steel structures, the corrosion status of steel structures is analyzed to obtain the corrosion status of steel structures;

[0011] According to the corrosion condition of steel structures, the residual bearing capacity of steel structures is predicted using a pre-built post-corrosion mechanical property model. The post-corrosion mechanical property model is constructed based on the measured corrosion data of steel specimens under different corrosion conditions.

[0012] Based on the residual bearing capacity of each steel structure, the mechanical properties of the target power tower are simulated to predict the health status of the target power tower based on the mechanical properties simulation data;

[0013] When the health status of the target power tower is predicted to be a safety risk for the target power tower, a safety risk classification warning is issued for the target power tower.

[0014] In one embodiment, after performing mechanical performance simulation on the target power tower based on the residual bearing capacity of each steel structure, the control device is further configured to:

[0015] Generate maintenance recommendations for the target power tower based on the mechanical performance simulation data of the target power tower and the remaining bearing capacity of each steel structure component;

[0016] Maintenance recommendations for target power towers are displayed.

[0017] In a second aspect, an embodiment of the present application provides a power tower status detection method, which is applied to a power tower status detection device, including:

[0018] Controlling the flight device of the power tower status detection device to operate so as to drive the power tower status detection device to move to the corresponding position of the target power tower, and controlling the acquisition device of the power tower status detection device to perform hyperspectral image acquisition to acquire hyperspectral images of multiple steel structures at different positions in the target power tower;

[0019] Based on the hyperspectral images of steel structures, the corrosion status of steel structures is analyzed to obtain the corrosion status of steel structures;

[0020] According to the corrosion condition of steel structures, the residual bearing capacity of steel structures is predicted using a pre-built post-corrosion mechanical property model. The post-corrosion mechanical property model is constructed based on the measured corrosion data of steel specimens under different corrosion conditions.

[0021] Based on the residual bearing capacity of each steel structure, the mechanical properties of the target power tower are simulated to predict the health status of the target power tower based on the mechanical properties simulation data;

[0022] When the health status of the target power tower is predicted to indicate that the target power tower has a safety risk, a safety risk classification warning is issued to the target power tower.

[0023] In a third aspect, an embodiment of the present application provides an electronic device that stores a computer program. When the computer program is executed by a processor, it implements the functions of the above-mentioned power tower status detection device or the steps of the above-mentioned power tower status detection method.

[0024] In a fourth aspect, an embodiment of the present application provides a readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the functions of the above-mentioned power tower status detection device or the steps of the above-mentioned power tower status detection method.

[0025] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the functions of the above-mentioned power tower status detection device or the steps of the above-mentioned power tower status detection method.

[0026] In one solution provided by the above-mentioned power tower status detection equipment, method, medium and program product, the power tower status detection equipment includes a control device, a collection device for collecting hyperspectral images of a target, and a flying device for responding to control of the control device to drive the collection device to move to a corresponding position. The control device is configured to: control the flying device to move to the corresponding position of the target power tower, and control the collection device to collect hyperspectral images to collect hyperspectral images of multiple steel structures at different positions in the target power tower; based on the hyperspectral images of the steel structures, analyze the corrosion status of the steel structures to obtain the corrosion status of the steel structures; predict the residual bearing capacity of the steel structures based on the corrosion status of the steel structures using a pre-constructed post-corrosion mechanical property model of the steel structures, the post-corrosion mechanical property model being constructed based on measured corrosion data of steel specimens under different corrosion conditions; based on the residual bearing capacity of each steel structure, simulate the mechanical properties of the target power tower to predict the health status of the target power tower based on the mechanical property simulation data; and when it is predicted that there is a safety risk in the health status of the target power tower, issue a safety risk classification warning for the target power tower. On the one hand, hyperspectral imaging technology collects high-dimensional spectral information about steel structures, enabling the capture of subtle differences in materials across different wavelengths. Compared to manual visual inspection or conventional image recognition techniques, it offers higher sensitivity and resolution for corrosion identification, effectively improving the accuracy and efficiency of corrosion product identification. This provides an accurate data foundation for subsequent mechanical property analysis of individual structural components, thereby improving the accuracy of predicting the health of the entire power tower structure. On the other hand, power tower status monitoring equipment boasts flexible flight positioning capabilities, enabling rapid access to various monitoring points on the power tower. This allows for comprehensive, high-frequency, and multi-angle data collection on multiple steel structures at different locations on the tower, replacing inefficient and even dangerous manual tower climbing. This significantly reduces detection time and mitigates issues such as missed inspections and misjudgments during manual inspections due to limited viewing angles or complex environments, thereby improving the accuracy and efficiency of power tower status monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0028] Figure 1 This is a structural diagram of a power tower status detection system according to one embodiment of the present invention;

[0029] Figure 2 This is a schematic structural diagram of a power tower status detection device according to one embodiment of the present invention;

[0030] Figure 3 This is a flow chart of a method for detecting the status of a power tower according to an embodiment of the present invention;

[0031] Figure 4 yes Figure 3 A schematic diagram of an implementation flow of step S20;

[0032] Figure 5 yes Figure 3 A schematic diagram of an implementation flow of step S30;

[0033] Figure 6 yes Figure 3 A schematic diagram of an implementation flow of step S40;

[0034] Figure 7 is an original simulation model diagram of a target power tower in one embodiment of the present invention;

[0035] Figure 8 This is another flowchart of a method for detecting a power tower status according to an embodiment of the present invention;

[0036] Figure 9 yes Figure 2 A structural diagram of the control device;

[0037] Figure 10 FIG. 1 is a structural diagram of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following will clearly and completely describe 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 them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0039] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or their collections. It should also be understood that the term "and / or" used in the present specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0040] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0041] References to "one embodiment" or "some embodiments" in the present specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present invention. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in yet other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0042] It should be understood that the order of execution of the steps in the following embodiments does not necessarily mean the order in which they are executed. The order in which each process is executed should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0043] In order to illustrate the technical solution of the present invention, specific embodiments are provided below.

[0044] Power towers operate in a complex environment. During their service, their steel structures are subject to environmental factors such as corrosive media, air, and temperature and humidity fluctuations. This can cause surface coatings to degrade and fail, leading to corrosion and degradation of the steel components. As corrosion progresses, the morphology of the corroded steel components changes significantly, affecting their mechanical properties and force transmission capacity, thereby endangering the safety and operational reliability of the power towers. Therefore, accurately assessing the mechanical properties of the individual steel components of an in-service power tower, as well as the overall structural mechanical properties of the tower, is a prerequisite and key basis for evaluating the structural safety of the tower and formulating scientific operation and maintenance strategies.

[0045] However, the current inspection work of power towers mainly relies on manual inspections of some points on the power towers. Due to the dangers of high-altitude operations, the limitations of inspection cycles, and the subjective errors of manual judgment, the accuracy and efficiency of traditional workers' inspections are not high, and it is difficult to meet the precise maintenance needs of large-scale power towers.

[0046] In addition, in related technologies, in order to understand the changes in mechanical properties of steel structures caused by corrosion and to evaluate the structural performance status, electrochemical measurement methods are usually used to monitor the corrosion of steel structures. However, this method cannot detect structural parts on a large scale. At the same time, it has poor on-site adaptability, is insensitive to local corrosion, and can only monitor the corrosion rate, making it difficult to accurately monitor the degree of corrosion. Therefore, this method has low efficiency and poor coverage in determining the corrosion status of real engineering structures, and lacks mechanical performance status determination, making it difficult to meet daily operation and maintenance needs such as determining the health status of engineering structures and making maintenance decisions.

[0047] Based on the above-mentioned problems, a power tower status detection device, method, medium, and program product are provided. The power tower status detection device includes a control device, a collection device for collecting hyperspectral images of a target, and a flying device for responding to control of the control device to drive the collection device to a corresponding position. The control device is configured to: control the flying device to move the power tower status detection device to a corresponding position on a target power tower, and control the collection device to collect hyperspectral images, thereby collecting hyperspectral images of multiple steel structures at different positions on the target power tower; analyze the corrosion status of the steel structures based on the hyperspectral images of the steel structures; predict the residual bearing capacity of the steel structures based on the corrosion status of the steel structures using a pre-constructed post-corrosion mechanical property model constructed based on measured corrosion data of steel specimens under different corrosion conditions; simulate the mechanical properties of the target power tower based on the residual bearing capacity of each steel structure, and predict the health status of the target power tower based on the mechanical property simulation data; and issue a safety risk classification warning for the target power tower when the health status of the target power tower is predicted to be a safety risk.

[0048] On the one hand, hyperspectral imaging technology collects high-resolution spectral information from steel structures, capturing subtle differences in materials across different wavelengths. Compared to manual visual inspection or conventional image recognition technology, it offers higher corrosion identification sensitivity and resolution, effectively improving the accuracy and efficiency of corrosion product identification. This provides an accurate data foundation for subsequent mechanical property analysis of individual structural components, thereby improving the accuracy of predicting the health of the entire power tower structure. On the other hand, power tower status detection equipment boasts flexible flight positioning capabilities, enabling rapid access to various detection points on the tower. It can perform all-round, high-frequency, and multi-angle data collection on multiple steel structures at different locations on the tower, replacing inefficient and even dangerous manual tower climbing. This significantly reduces detection time and mitigates issues like missed inspections and misjudgments during manual inspections due to limited viewing angles or complex environments, thereby improving the accuracy and efficiency of power tower status detection.

[0049] In addition, a post-corrosion mechanical properties model is constructed based on the measured data of steel structural parts under different corrosion conditions, making the post-corrosion mechanical properties model closer to actual engineering conditions and accurately reflecting the degradation of the mechanical properties of structural parts after corrosion. It has better prediction ability and application universality of mechanical property changes, improves the prediction accuracy of the residual bearing capacity of steel structural parts, and provides an accurate data basis for subsequent judgment of the health status of power tower structures, thereby reducing the judgment error of manual visual judgment and improving the health detection accuracy and structural safety of power towers.

[0050] The power tower status detection method provided by the embodiment of the present invention can be applied in the following situations: Figure 1In the power tower status detection system shown, the power tower status detection system includes a power tower status detection device and a user's terminal device, wherein the terminal device communicates with the power tower status detection device via a network.

[0051] Among them, such as Figure 2 As shown, the power tower status detection device includes a collection device, a flight device, and a control device. The collection device is used to acquire hyperspectral images of a target. The flight device is used to respond to control from the control device and move the collection device to a corresponding position. The control device is used to execute the power tower status detection method provided in the embodiments of this application; that is, the control device of the power tower status detection device is the main body of the execution of the power tower status detection method.

[0052] In actual applications, when a user needs to monitor the structural health of a power tower, such as during routine tower maintenance, they send a monitoring command for the target tower via a handheld terminal device to the tower status monitoring device. This command may include location information such as the target tower's latitude and longitude coordinates, tower height, and basic structural information.

[0053] The control device of the power tower status detection device receives a detection instruction for a target power tower from a terminal device and, in response to the detection instruction, executes a detection process on the target power tower. Upon detecting that the power tower status detection device is located at the target power tower, the control device controls the flight device to move the power tower status detection device to the corresponding position of the target power tower and controls the acquisition device to acquire hyperspectral images of steel structures at different locations on the target power tower. Based on the hyperspectral images of the steel structures, the control device performs a corrosion analysis on each steel structure to determine the corrosion status of each steel structure. Based on the corrosion status of the steel structure, the control device uses a pre-constructed post-corrosion mechanical property model constructed based on measured corrosion data of steel specimens under different corrosion conditions to predict the residual bearing capacity of the steel structure. Based on the residual bearing capacity of each steel structure, the control device modifies the target power tower model built into the control device and further performs a mechanical property state simulation on the model to predict the health status of the target power tower based on the mechanical property simulation data. If the health status of the target power tower is predicted to be a safety risk, a safety risk classification warning is issued for the target power tower.

[0054] In this embodiment, the power tower status detection equipment uses hyperspectral imaging technology to collect hyperspectral information from steel structural components. This technology can capture subtle differences in materials across different wavelengths. Compared to manual visual inspection or conventional image recognition techniques, it offers higher corrosion identification sensitivity and resolution, effectively improving the accuracy and efficiency of corrosion product identification. This provides an accurate data foundation for subsequent mechanical property analysis of individual components, thereby enhancing the accuracy of the overall health assessment of the power tower structure. Furthermore, the power tower status detection equipment possesses flexible flight positioning capabilities, enabling rapid access to various inspection points on the power tower. This equipment is capable of performing comprehensive, high-frequency, and multi-angle data collection on various steel structural components at different locations on the tower, replacing inefficient and even dangerous manual tower climbing and scrambling operations. This significantly reduces detection time and mitigates issues such as missed inspections and misjudgments caused by limited viewing angles or complex environments during manual inspections, thereby improving the accuracy and efficiency of power tower status detection.

[0055] Terminal devices include, but are not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The power tower status detection device can be an unmanned aerial vehicle equipped with hyperspectral imaging and computing capabilities. It can predict the health status of a target power tower based on mechanical performance simulation data, thereby determining the health status of the target power tower.

[0056] In one embodiment, if Figure 3 As shown, a method for detecting the status of a power tower is provided, which is applied in Figure 1 The power tower status detection device in the example is used for explanation. The power tower status detection device includes a collection device, a flight device, and a control device. The collection device is used to collect hyperspectral images of the target; the flight device is used to respond to the control to drive the collection device to move to the corresponding position; the control device is configured to perform the following steps:

[0057] S10: Control the flying device to move to the corresponding position of the target power tower, and control the acquisition device to acquire hyperspectral images to acquire hyperspectral images of various steel structures at different positions in the target power tower.

[0058] In actual applications, when a user needs to perform a structural health check on a power tower, such as during routine operation and maintenance of a power tower, the user sends a detection instruction for the target power tower to the power tower status detection device via a handheld terminal device. This detection instruction can be sent while the user is at the actual location of the target power tower. That is, during routine power tower inspections, the user carries the terminal device and the power tower status detection device. Upon arriving at the target power tower for inspection, the user sends a detection instruction for the target power tower to the power tower status detection device via the handheld terminal device. This detection instruction triggers the power tower status detection device to execute the power tower status detection process. In this case, the detection instruction can include the collection locations of multiple steel structures at different locations on the target power tower. The collection location of the steel structure is the location where the power tower status detection device can capture a hyperspectral image of the corresponding steel structure; this collection location corresponds to the installation location of the steel structure on the power tower status detection device.

[0059] In other embodiments, the detection instruction can also be sent remotely via a terminal device from a location far from the target power tower. That is, during power tower operation and maintenance, a user can use a terminal device to send a detection instruction for a target power tower to a power tower status detection device. The power tower status detection device responds to the detection instruction and inspects one or more target power towers. The device then remotely sends the detection results of the target power towers to the terminal device, allowing the user to promptly perform maintenance on the target power towers based on the detection results. In this case, the detection instruction can include the coordinate information of different target power towers, as well as the locations of steel structures within the target power towers for which data is to be collected.

[0060] The control device of the power tower status detection device receives a detection instruction for a target power tower sent by the terminal device, and executes a detection process for the target power tower in response to the detection instruction.

[0061] The control device controls the flight device to move the power tower status detection equipment to the corresponding location on the target power tower, i.e., the steel structure's collection location, according to the collection locations for each steel structure at different locations on the target power tower specified in the detection instruction. For each steel structure, after the power tower status detection equipment has moved to the collection location corresponding to the steel structure on the target power tower, the control device controls the collection device of the power tower status detection equipment to collect a hyperspectral image of the steel structure, thereby obtaining a hyperspectral image of the steel structure. By traversing all the collection locations for the steel structures specified in the detection instruction, hyperspectral images of each steel structure at different locations on the target power tower can be collected.

[0062] The steel structure of the target power tower may include at least one of angle steel, steel sheet, steel pipe and other structural members.

[0063] S20: Based on the hyperspectral image of the steel structure, the corrosion state of the steel structure is analyzed to obtain the corrosion status of the steel structure.

[0064] After obtaining a hyperspectral image of the steel structure, the control device can analyze the composition and distribution of corrosion products on the surface of the steel structure based on the hyperspectral image of the steel structure to determine the corrosion condition of the steel structure. The corrosion condition of the steel structure includes at least the corrosion products present on the surface of the steel structure. In other embodiments, the corrosion condition may also include the area ratio of the corrosion products present on the surface of the steel structure (i.e., the corrosion area ratio) and the corrosion grade of the surface of the steel structure.

[0065] S30: Based on the corrosion condition of steel structures, the residual bearing capacity of steel structures is predicted using a pre-built post-corrosion mechanical property model.

[0066] The control device stores a pre-built post-corrosion mechanical property model. After analyzing the corrosion status of the steel structure, the control device uses the pre-built post-corrosion mechanical property model to predict the residual bearing capacity of the steel structure based on the corrosion status of the steel structure, thereby determining the residual bearing capacity of the steel structure.

[0067] The post-corrosion mechanical properties model is pre-constructed based on measured corrosion data of steel specimens under different corrosion conditions. Corrosion tests are conducted on multiple representative steel specimens from power towers under different corrosion conditions to obtain measured corrosion data. Based on this data, the post-corrosion mechanical properties of the steel structures are analyzed. A direct functional relationship between the corrosion condition and the mechanical properties (such as ultimate strength, yield strength, elastic modulus, and elongation) of the steel structures is obtained. This allows the construction of a predictive model for the post-corrosion mechanical properties of the steel structures, also known as the post-corrosion mechanical properties model. The representative steel specimens from power towers can be angle steel, sheet steel, or pipe steel structures of varying sizes.

[0068] In this embodiment, a post-corrosion mechanical property model is constructed based on the measured data of steel specimens under different corrosion conditions, so that the post-corrosion mechanical property model is closer to actual engineering conditions, can accurately reflect the degradation of the mechanical properties of structural parts after corrosion, and has better predictive ability and application universality of mechanical property changes. The power tower status detection equipment uses this model to predict the residual bearing capacity, which can improve the prediction accuracy of the residual bearing capacity of steel, and provide an accurate data basis for the subsequent judgment of the health status of the power tower structure, thereby reducing the judgment error of manual visual judgment and improving the health detection accuracy and structural safety of the power tower.

[0069] S40: Performing mechanical property simulation on the target power tower according to the residual bearing capacity of each steel structure component, so as to predict the health status of the target power tower according to the mechanical property simulation data.

[0070] After acquiring hyperspectral images of each steel structure and analyzing its corrosion status to determine its remaining bearing capacity, the control device modifies the built-in mechanical simulation model of the target power tower based on the corrosion status and mechanical performance parameters of each steel structure, and performs a mechanical performance simulation prediction to determine the target tower's mechanical performance simulation data. The control device then predicts the health status of the target power tower based on this mechanical performance simulation data to determine its health status. The health status of the target power tower is used to indicate whether the target power tower poses a safety risk.

[0071] For example, an initial simulation model of a target power tower can be obtained. This initial simulation model is constructed based on the specific structure of the target power tower upon completion and simulates information about all structural components of the target power tower. The control device can then modify the initial simulation model based on the corrosion status and mechanical performance parameters of each steel structure. The loads on each steel structure in the modified simulation model of the target power tower can then be simulated and analyzed to determine mechanical performance simulation data for the target power tower. This mechanical performance simulation data for the target power tower can include data characterizing the overall mechanical performance of the target power tower, such as the bearing capacity of key steel structures of the target power tower, the base load of the target power tower, and the vertex displacement of the target power tower. Based on the overall mechanical performance data of the target power tower and at least one of the post-corrosion working loads of the steel structures of the target power tower, a health status prediction can be performed for the target power tower to determine the health status of the target power tower, that is, to determine whether the target power tower poses a safety risk.

[0072] S50: When it is predicted that the health status of the target power tower is a safety risk, a safety risk classification warning is issued to the target power tower.

[0073] After analyzing and predicting the health status of the target power tower based on mechanical performance simulation data, if the target power tower's health status is determined to present a safety risk, the control device issues a graded safety risk warning for the target power tower, alerting the user to different levels of safety risk and requiring different risk-level treatment measures for the target power tower's structural components. For example, if the safety risk level is low, one or more steel components on the target power tower may be treated with paint (such as galvanizing). If the safety risk level is medium, the corresponding steel components may be replaced or repaired. If the safety risk level is high, measures such as overall structural reinforcement or foundation reinforcement may be implemented to ensure the stability of the target power tower's overall structure or foundation.

[0074] For example, the mechanical properties simulation data for a target power tower may include the post-corrosion working load of each steel structure. Based on the post-corrosion working load and the corresponding residual bearing capacity of each steel structure, it can be determined whether the target power tower contains any steel structure with a potential safety hazard. If the target power tower contains any steel structure with a potential safety hazard, then the target power tower is determined to have a corresponding level of safety risk. Whether a steel structure presents a potential safety hazard can be determined based on the post-corrosion working load and the corresponding residual bearing capacity of the steel structure. When the ratio (or difference) of the residual bearing capacity of a steel structure to its post-corrosion working load is less than a preset value, it can be determined that the steel structure presents a potential safety hazard and may need to be replaced. This indicates that the target power tower contains any steel structure with a potential safety hazard.

[0075] In this embodiment, the power tower status detection equipment uses hyperspectral imaging technology to collect hyperspectral information from steel structures. This technology can capture subtle differences in material properties across different wavelengths. Compared to manual visual inspection or conventional image recognition techniques, it offers higher corrosion identification sensitivity and resolution, effectively improving the accuracy and efficiency of corrosion product identification. This provides an accurate data foundation for subsequent mechanical property analysis of individual components, thereby enhancing the accuracy of predicting the overall health of the power tower structure. Furthermore, the power tower status detection equipment possesses flexible flight positioning capabilities, enabling rapid access to various inspection points on the power tower. This equipment is capable of comprehensive, high-frequency, and multi-angle data collection on multiple steel structures at different locations on the tower, replacing inefficient and even dangerous manual tower climbing and scrambling operations. This significantly reduces detection time and mitigates issues such as missed inspections and misjudgments during manual inspections due to limited viewing angles or complex environments, thereby improving the accuracy and efficiency of power tower status detection.

[0076] In some embodiments, as Figure 4As shown, in step S20, the control device performs corrosion status analysis on the steel structure based on the hyperspectral image of the steel structure to obtain the corrosion status of the steel structure, and is configured to perform the following steps:

[0077] S21: Based on the hyperspectral image of the steel structure, the corrosion product composition of the steel structure is identified to determine the corrosion products on the surface of the steel structure and the corrosion area of ​​the corrosion products on the steel structure.

[0078] The control device can identify the corrosion product components on the surface of the steel structure based on the hyperspectral image of the steel structure to determine the corrosion products on the surface of the steel structure, and determine the corrosion area of ​​the corrosion products on the steel structure based on the corrosion product identification structure.

[0079] Specifically, the steps include:

[0080] S211: extracting spectral features from the hyperspectral image of the steel structure to obtain hyperspectral feature data of the steel structure. The hyperspectral feature data includes hyperspectral vectors of different pixels in the hyperspectral image.

[0081] The control can first perform denoising on the hyperspectral image, then extract the corresponding hyperspectral vector from each pixel of the denoised hyperspectral image to obtain a hyperspectral vector for each pixel. Each hyperspectral vector corresponds to a high-dimensional spectral reflectance data. In other words, the hyperspectral vector of each pixel contains the spectral response values ​​of the pixel in multiple bands, which reflects the reflectance of the pixel in different bands.

[0082] S212: performing clustering processing of hyperspectral vectors on the hyperspectral feature data of the steel structure to obtain at least one target cluster data.

[0083] The control device may use a preset clustering algorithm (such as a K-means clustering algorithm) to perform clustering processing of the hyperspectral vectors on the hyperspectral feature data of the steel structure to obtain at least one target cluster data through clustering.

[0084] Specifically, the distance between the hyperspectral vector of each pixel in the hyperspectral feature data and the cluster center (such as the initial cluster center) is calculated to classify the pixel into the nearest cluster, thereby initially clustering to obtain multiple clusters, that is, to obtain multiple initial cluster data; for each initial cluster data, the cluster center of the cluster data (that is, the centroid of the hyperspectral vector of each pixel in the cluster data) is calculated, and the distance between the hyperspectral vector of each pixel and the cluster center of each cluster data is recalculated to classify the pixel into the nearest cluster, thereby re-clustering to obtain multiple clusters, that is, to obtain multiple new cluster data; the cluster center and pixel classification process is repeated until the change in the cluster center is less than a threshold, or until the number of clustering iterations reaches the maximum number of iterations, and the current at least one target cluster data can be obtained.

[0085] S213: Based on the pre-generated preset hyperspectral data of multiple types of corrosive substances, hyperspectral feature matching is performed on the target cluster data to determine the calibration substance corresponding to the matched preset hyperspectral data as a corrosion product existing on the surface of the steel structure.

[0086] The control device can perform hyperspectral feature matching on the target cluster data based on pre-generated preset hyperspectral data of multiple types of corrosive substances, so as to determine the corrosive substances corresponding to the matched preset hyperspectral data as corrosion products existing on the surface of the steel structure.

[0087] For example, the control device may perform hyperspectral curve conversion on the target cluster data to obtain a target hyperspectral curve. Then, the control device may obtain pre-generated preset hyperspectral curves for multiple types of corrosive substances and curve fit the target hyperspectral curve with the preset hyperspectral curve to obtain a curve fitting error between the target hyperspectral curve and the preset hyperspectral curve. Finally, the preset hyperspectral curve with a curve fitting error less than a preset error value is regarded as the matched preset hyperspectral curve (i.e., the matched preset hyperspectral data). The corrosive substances corresponding to the preset hyperspectral curve with a curve fitting error less than the preset error value are regarded as corrosion products present on the surface of the steel structure.

[0088] In this embodiment, by clustering hyperspectral feature data, pixels with similar spectral characteristics are automatically grouped together, effectively reducing misjudgments caused by noise, background interference, or uneven illumination, and improving the accuracy of corrosion product identification. The resulting target cluster data is then matched with the hyperspectral features of multiple types of corrosive substances to automatically identify corrosion products on the surface of steel structures. This improves detection efficiency and reduces subjective judgment errors, thereby increasing the accuracy of calibration substance identification.

[0089] S214: The pixel area formed by each pixel in the target cluster data in the hyperspectral image is used as the corrosion area of ​​the corrosion product corresponding to the target cluster data.

[0090] The control device determines the total pixel area formed by each pixel in the target cluster data as the corrosion area of ​​the corrosion product corresponding to the target cluster data. By clustering the hyperspectral vectors of different pixels in the hyperspectral image and then determining the total pixel area of ​​each target cluster data based on the clustering results, the corrosion area of ​​different corrosion products on steel structures can be quickly and accurately identified.

[0091] S22: Determine the corrosion grade of the steel structure based on the corrosion products on the surface of the steel structure and the corrosion area of ​​the corrosion products to obtain the corrosion condition of each steel structure.

[0092] After determining the corrosion products on the surface of the steel structure and the corrosion area of ​​the corrosion products, the control device can determine the corrosion grade of the steel structure based on the corrosion products on the surface of the steel structure and the corrosion area of ​​the corrosion products, so as to characterize the corrosion condition of the steel structure by the corrosion grade, thereby obtaining the corrosion condition of each steel structure.

[0093] The control device can obtain pre-calibrated corrosion grade data, which includes the types of corrosion products corresponding to different corrosion grades and the corrosion area ratios of the corresponding corrosion products. This corrosion grade data is pre-calibrated based on measured corrosion data of steel specimens. Simultaneously, the control device can determine the ratio of the area of ​​the corrosion products to the surface area of ​​the steel structure as the corrosion area ratio of the corrosion products. The control device can then match the types of corrosion products and the corrosion area of ​​the corrosion products on the surface of the steel structure with the types and corrosion area ratios of the corrosion products for different corrosion grades in the corrosion grade data, and use the matched corrosion grade as the corrosion grade of the steel structure. This is simple, convenient, and highly accurate.

[0094] In this embodiment, based on hyperspectral images of steel structures, corrosion product composition is identified on the steel structures to determine the corrosion products on the surface of the steel structures and the corrosion area of ​​the corrosion products on the steel structures. The corrosion grade of the steel structures is then determined based on the corrosion products on the surface of the steel structures and the corrosion area of ​​the corrosion products, thereby obtaining the corrosion status of each steel structure. Different corrosion products have different corrosion damage mechanisms and have different effects on structural performance. By combining the type of corrosion product and its proportion of the corrosion area on the surface of the steel structure, and matching them in a pre-calibrated multi-dimensional corrosion grade database, the corrosion grade of the steel structure is determined, improving the accuracy of the corrosion grade so that it can more accurately reflect the actual corrosion status of the steel structure.

[0095] In some embodiments, the corrosion condition of the steel structure is characterized by the corrosion grade; the post-corrosion mechanical property model includes a structural strength model. Figure 5As shown, in step S30, the control device predicts the residual bearing capacity of the steel structure using a pre-built post-corrosion mechanical property model based on the corrosion condition of the steel structure, and is configured to perform the following steps:

[0096] S31: Determine the cross-sectional loss rate of the steel structure according to the corrosion grade of the steel structure.

[0097] After determining the corrosion level of the steel structure, that is, determining the corrosion condition of the steel structure, the control device determines the cross-sectional loss rate of the steel structure according to the corrosion level of the steel structure.

[0098] Specifically, a pre-calibrated cross-sectional loss rate model is obtained. This cross-sectional loss rate model is obtained by fitting and analyzing the cross-sectional loss rate of steel structures at different corrosion levels based on measured corrosion data of steel specimens. The cross-sectional loss rate model can be represented by a fitting relationship between corrosion level and cross-sectional loss rate.

[0099] Among them, the pre-calibrated cross-sectional loss rate model can be expressed by the following least squares fitting formula:

[0100] ;

[0101] in, Indicates the section loss rate of steel structure; Indicates the corrosion grade of steel structures, that is, the numerical value of the corrosion grade, such as corrosion grades 1-4 correspond to the numerical values ​​1, 2, 3, and 4 respectively.

[0102] The control device can then input the steel structure's corrosion grade into the cross-sectional loss rate model to calculate the cross-sectional loss rate, quickly and accurately obtaining the cross-sectional loss rate of the steel structure. Calculating the cross-sectional loss rate based on the steel structure's corrosion grade eliminates the need for tedious data labeling, making it simple, convenient, and widely adaptable.

[0103] S32: According to the cross-sectional loss rate of the steel structure component, the mechanical performance parameters of the steel structure component are predicted using a component mechanical performance parameter prediction model to obtain mechanical performance parameter information of the steel structure component.

[0104] After determining the section loss rate of the steel structure, the mechanical performance parameters of the steel structure are predicted using the component mechanical performance parameter prediction model to obtain the mechanical performance parameter information of the steel structure.

[0105] The component mechanical properties prediction model can be a mechanical properties parameter information model derived from analyzing field-measured corrosion data of steel components (i.e., steel test specimens) under different corrosion conditions. Accordingly, the mechanical properties parameter information can include the ultimate strength and yield strength of the steel components. Specifically, by directly inputting the cross-sectional loss rate of the steel component into the steel mechanical properties parameter prediction model to predict mechanical properties (e.g., ultimate strength, yield strength, etc.), the ultimate strength or yield strength of the steel component can be obtained, thereby obtaining the mechanical properties parameter information of the steel component. In other embodiments, the mechanical properties parameter can also be at least one of ultimate strength and yield strength.

[0106] Among them, based on the cross-sectional loss rate of the steel structure, the yield strength of the steel structure can be predicted using a pre-built yield strength model of the steel structure to serve as the mechanical performance parameter information of the steel structure. The yield strength model of the steel structure can be expressed by the following least squares fitting formula:

[0107] ;

[0108] in, Indicates the section loss rate of steel structure; Indicates the yield strength of steel structures.

[0109] S33: Calculate the residual bearing capacity of each steel structure member according to the mechanical property parameter information of the steel structure member to obtain the residual bearing capacity of the steel structure member.

[0110] After obtaining the mechanical property parameter information of the steel structure, the residual bearing capacity of the steel structure is calculated respectively using the residual bearing capacity model according to the mechanical property parameter information of the steel structure to obtain the residual bearing capacity of the steel structure.

[0111] Taking the yield strength as an example, the residual bearing capacity of steel structures can be calculated using the following residual bearing capacity model:

[0112] ;

[0113] in, Indicates the residual bearing capacity of steel structure; Indicates the yield strength of steel structures; Indicates the original cross-sectional area of ​​the steel structure.

[0114] Compared with using ultimate strength to calculate the residual bearing capacity of steel structures, this scheme uses the yield strength of steel structures to calculate the residual bearing capacity of steel structures, which provides a certain margin for the strength calculation of steel structures, can obtain a more reliable residual bearing capacity, and provides a more reliable data basis for the simulation prediction of the mechanical properties of the entire power tower.

[0115] In this embodiment, the corrosion condition of the steel structure is characterized by the corrosion grade. The control device determines the cross-sectional loss rate of the steel structure based on the corrosion grade of the steel structure. Then, based on the cross-sectional loss rate of the steel structure, the mechanical property parameters of the steel structure are predicted using mechanical property parameters to obtain mechanical property parameter information of the steel structure. Finally, based on the mechanical property parameter information of the steel structure, the residual bearing capacity of each steel structure is calculated to obtain the residual bearing capacity of the steel structure. Based on the original cross-sectional area of ​​the steel structure and the actual identified cross-sectional loss rate, a prediction of cross-sectional loss rate, yield strength, and residual bearing capacity can be completed in combination with a mechanical property prediction model. By quantitatively correlating the corrosion state of the steel structure with the mechanical properties, the scientific nature of the overall residual bearing capacity assessment is improved, and the accuracy of the residual bearing capacity prediction based on the corrosion condition is improved.

[0116] In some embodiments, before step S30, the control device needs to obtain a pre-built post-corrosion mechanical property model and store it in the power tower status detection device. After determining the corrosion status of each steel structure, the post-corrosion mechanical property model can be used to predict the remaining bearing capacity. The post-corrosion mechanical property model can be constructed by the control device or by a terminal device outside the power tower status detection device.

[0117] Among them, the post-corrosion mechanical properties model is constructed in the following way:

[0118] S01: Obtaining measured corrosion data of steel specimens under different corrosion conditions obtained by performing corrosion tests on multiple steel specimens. The measured corrosion data of the steel specimens include the composition and content of corrosion products of each steel specimen after corrosion. At least one of the placement angle, working environment, and corrosion time of the steel specimens under different corrosion conditions is different.

[0119] The control device can obtain measured corrosion data of steel specimens under different corrosion conditions. The measured corrosion data of the steel specimens under different corrosion conditions is obtained by performing corrosion tests on multiple steel specimens under different corrosion conditions. The measured corrosion data of the steel specimens under different corrosion conditions includes the composition and content of corrosion products of each steel specimen after corrosion under different corrosion conditions. The steel specimens under different corrosion conditions vary in at least one of their placement angle, operating environment, and corrosion duration.

[0120] A pre-set corrosion testing system can be used to conduct corrosion tests on multiple steel specimens under different corrosion conditions. The pre-set corrosion testing system includes a working environment simulation device and a control device. The control device can be the control device of the power tower status detection device in the embodiment of this application, or other terminal equipment. The working environment simulation device is used to simulate the working environment (corrosive environment) of the power tower and monitor the corrosion conditions of each steel specimen (and steel sheet sample) under different working conditions.

[0121] The process of controlling the device to perform corrosion tests on multiple steel specimens, i.e., obtaining measured corrosion data of the steel specimens under different corrosion conditions, specifically includes the following steps:

[0122] S011: Fix multiple steel specimens at the test station in the working environment simulation device according to different preset placement angles. The preset angles are determined according to the installation angles of the steel on the power tower after the power tower is assembled.

[0123] The preset angle (i.e., installation angle) is the angle between the steel and the vertical direction, and can be 90°, 45°, or 15°. Different steel installation angles in power towers directly affect stress, moisture accumulation, and contaminant deposition. This solution accounts for these differences by setting multiple installation angles for the samples. This allows the collected corrosion data to reflect the impact of the actual installation position on corrosion rate and morphology, improving the accuracy of the measured corrosion data for steel specimens.

[0124] S012: Based on the working environment data of the power tower, control the operation of the working environment simulation device to simulate the working environment of the power tower and conduct accelerated corrosion experiments on each steel specimen to obtain the actual corrosion data of each steel specimen under different test durations as the actual corrosion data of the steel specimens under the current corrosion conditions.

[0125] The operating environment data for power towers includes at least altitude, UV radiation, airborne media (such as salt and heavy metal contaminants), and air humidity. The test duration can be customized, ranging from 6 hours, 12 hours, 24 hours, to 600 hours, and so on. By utilizing the actual operating environment data of power towers (such as altitude, UV intensity, type and concentration of corrosive media in the air, and humidity), the simulation device accurately reproduces the corrosion behavior under actual service conditions, improving the reliability and engineering applicability of the experimental results.

[0126] S013: Replace multiple new steel test pieces and update the working environment data of the power tower, and repeat steps S011-S012 to obtain actual corrosion data of the steel test pieces under different corrosion conditions.

[0127] After obtaining the measured corrosion data of multiple steel specimens under one corrosion condition, multiple new steel specimens can be replaced and the working environment data of the power tower can be updated. Then, steps S011-S012 can be repeated for multiple iterations to obtain the measured corrosion data of the steel specimens under different corrosion conditions.

[0128] In this scheme, by conducting highly simulated accelerated corrosion tests on multiple steel specimens under different preset angles and corrosion conditions, and combining a working environment simulation device constructed with real environmental parameters, it is possible to systematically obtain actual corrosion data of power tower steel structures under various corrosion conditions. Compared with conventional experimental methods, this scheme can more comprehensively reflect the corrosion evolution process in the actual service environment, thereby improving the representativeness of corrosion data and the accuracy of the prediction model.

[0129] S02: Based on the steel specimens after corrosion under different corrosion conditions, as well as the composition and content of the corrosion products of each steel specimen after corrosion, the mechanical properties of the steel structure under different corrosion conditions are analyzed to construct a performance prediction model for predicting the steel structure.

[0130] After obtaining the measured corrosion data of steel specimens under different corrosion conditions, the control device can analyze the mechanical properties (such as yield strength, ultimate strength, ductility, etc.) of the steel structures under different corrosion conditions based on the steel specimens after corrosion under different corrosion conditions and the composition and content of the corrosion products of each steel specimen after corrosion, so as to construct a performance prediction model for predicting the steel structures.

[0131] In this embodiment, corrosion test data of steel specimens under different corrosion conditions is obtained by performing corrosion tests on multiple steel specimens. The corrosion test data includes the composition and content of corrosion products of each steel specimen after corrosion. At least one of the placement angle, working environment, and corrosion duration of the steel specimens under different corrosion conditions is different. Based on the corrosion test data of each steel specimen under different corrosion conditions, as well as the composition and content of corrosion products of each steel specimen after corrosion, the mechanical properties of the steel structure under different corrosion conditions are analyzed to construct a performance prediction model for predicting the performance of the steel structure. By performing corrosion tests on multiple steel specimens under different corrosion conditions, collecting the corrosion test data of the steel specimens, including the composition and content of corrosion products, and combining the changes in the mechanical properties of the steel after corrosion, a correlation model between corrosion conditions and performance degradation is constructed, thereby achieving accurate prediction of the mechanical properties of steel structures under complex service environments.

[0132] In some embodiments, as Figure 6 As shown, in step S40, the control device performs mechanical property simulation on the target power tower according to the residual bearing capacity of each steel structure, so as to predict the health status of the target power tower according to the mechanical property simulation data, and is configured to perform the following steps:

[0133] S41: Acquire an original simulation model of the target power tower, where the original simulation model is a structural simulation model established according to the specific structure of the target power tower after it is built.

[0134] After determining the remaining bearing capacity of each steel structure, the control device obtains the original simulation model of the target power tower. The original simulation model is a structural simulation model established based on the specific structure of the target power tower after it is built. The original simulation model includes the nodes corresponding to each steel structure and the nodes of other structures (such as steel sheets), as well as information such as the geometric connection between each node, boundary conditions, and load conditions. Among them, the original simulation model established based on the specific structure of the target power tower after it is built can be found in Figure 7 As shown; Figure 7 The Z direction is the vertical direction.

[0135] Specifically, the control device can obtain the structural design information of the specific structure of the target power tower after it is built, including modeling CAD data, structural layout drawings, connection methods, component models, etc.; then, the structural design information of the target power tower is called to generate an original simulation model of the target power tower. The original simulation model is the structural simulation state of the target power tower after it is built and before it is corroded.

[0136] S42: According to the corrosion conditions of each steel structure, the parameters of the original simulation model are updated to obtain a target simulation model of the target power tower.

[0137] The control device can map the corrosion conditions of each steel structure to the corresponding steel structure in the original simulation model to update the effective cross-sectional area, material strength, boundary conditions and other parameters of the steel structure to obtain a target simulation model after corrosion, which more realistically reflects the structural status of the current target power tower.

[0138] In addition, in one embodiment, the control device updates the parameters of the original simulation model according to the corrosion conditions of each steel structure to obtain a target simulation model of the target power tower, and is configured to: determine the cross-sectional area, yield strength, ultimate strength and elastic modulus of each steel structure after corrosion according to the corrosion conditions of each steel structure; input the cross-sectional area, yield strength, ultimate strength and elastic modulus of each steel structure after corrosion into the original simulation model to update the parameters to obtain a target simulation model of the target power tower.

[0139] Based on measured corrosion data from steel specimens under different corrosion conditions, the relationship between the corrosion status of steel components and their cross-sectional area and mechanical properties (yield strength, ultimate strength, and elastic modulus) can be analyzed to construct a corrosion stress model. In practical applications, after determining the corrosion status of each steel component, a correlation model between the corrosion grade, cross-sectional loss rate, and mechanical properties is used to predict the post-corrosion cross-sectional and mechanical properties of the steel component. These post-corrosion cross-sectional and mechanical properties parameters are then input into the original simulation model for parameter update, resulting in a target simulation model of the target power tower. By replacing the idealized material parameters in the original simulation model with the post-corrosion cross-sectional and mechanical properties parameters, a target simulation model reflecting the actual corrosion state is constructed. This improves the target simulation model's fit to the current state of the target power tower, thereby enhancing the accuracy and reliability of subsequent simulation results.

[0140] S43: Using the target simulation model, a simulation analysis is performed on the mechanical properties of the target power tower after corrosion to obtain mechanical property simulation data of the target power tower.

[0141] After updating the target simulation model, the control device uses the target simulation model to simulate and analyze the mechanical properties of the target power tower after corrosion, thereby obtaining simulation data for the target power tower's mechanical properties. This data includes the post-corrosion working loads of each steel structure, the stress conditions of the steel structures after corrosion, the overall base load (i.e., the load on the lowest structure), and the vertex displacement of the tower.

[0142] That is, the target simulation model can be used to simulate and analyze the working loads of each structure in the target power tower after corrosion to obtain the working loads of each steel structure after corrosion, and the target simulation model can be used to simulate and analyze the base load and vertex displacement of the target power tower to obtain the base load and vertex displacement of the target power tower after corrosion.

[0143] For example, one or more preset working conditions can be applied to the target simulation model to simulate and solve the simulated working load of each steel structure, that is, the working load of each steel structure after corrosion, as well as the mechanical performance data such as the base load of the target power tower after corrosion and the vertex displacement of the target power tower after corrosion.

[0144] S44: Determine the health status of the target power tower based on the residual bearing capacity and mechanical property simulation data of each steel structure component.

[0145] After obtaining the mechanical performance simulation data for the target power tower, the control device can determine the health status of the target power tower based on the residual bearing capacity of each steel structure and the mechanical performance simulation data. Specifically, the control device can determine whether any of the multiple steel structures of the target power tower presents a safety hazard based on the post-corrosion working load of each steel structure and the corresponding residual bearing capacity in the mechanical performance simulation data, thereby determining the health status of the target power tower. For example, the structural safety of the steel structures can be assessed based on the post-corrosion working load and the corresponding residual bearing capacity. If one or more steel structures are determined to present a safety hazard, the health status of the target power tower can be determined as presenting a safety risk.

[0146] In other embodiments, the health status of the target power tower can also be determined using other methods. For example, the health status of the target power tower can be determined based on the base load and vertex displacement of the target power tower after corrosion in the mechanical performance simulation data. When the base load is less than the calibration load, indicating that the current base load of the target power tower is below the risk value, the health status of the target power tower is determined to be a safety risk. When the vertex displacement of the target power tower after corrosion is greater than the calibration displacement, indicating that the target power tower has a large displacement and may have insufficient overall lateral resistance or local instability, the health status of the target power tower is determined to be a safety risk.

[0147] In one embodiment, a control device obtains an original simulation model of a target power tower, where the original simulation model is a structural simulation model established based on the specific structure of the target power tower after construction. Based on the corrosion conditions of each steel structure, the control device updates parameters in the original simulation model to obtain a target simulation model of the target power tower. The target simulation model is used to simulate and analyze the mechanical properties of the target power tower after corrosion to obtain mechanical property simulation data of the target power tower. Based on the residual bearing capacity and mechanical property simulation data of each steel structure, the health status of the target power tower is determined. This solution, based on the original simulation model, introduces the actual corrosion conditions of the steel structures and constructs a target simulation model after corrosion through parameter updates. This allows the simulation results to more realistically reflect the current structural performance status of the power tower, avoids misjudgments caused by ignoring corrosion damage, and significantly improves the accuracy of health status assessments.

[0148] In some embodiments, the mechanical properties simulation data of the target power tower includes the post-corrosion working load of each steel structure. In step S44, the control device determines the health status of the target power tower based on the residual bearing capacity of each steel structure and the mechanical properties simulation data, and is configured to perform the following steps:

[0149] S441: Determine the health status of the steel structure based on its post-corrosion working load and corresponding residual bearing capacity. The health status of the steel structure is used to indicate whether the steel structure is a structural component with safety hazards.

[0150] In this embodiment, the mechanical performance simulation data of the target power tower includes the post-corrosion working load of each steel structure.

[0151] After obtaining the target power tower's mechanical performance simulation data, the control device can determine the health of the steel structure based on its post-corrosion working load and corresponding residual load-bearing capacity. This health status is used to indicate whether the steel structure poses a safety hazard.

[0152] For example, the ratio of a steel component's residual bearing capacity to its post-corrosion working load can be determined, and based on this ratio, it can be determined whether the steel component presents a safety hazard. If the ratio is less than a threshold, the steel component is considered safe. Conversely, if the ratio is greater than or equal to the threshold, the steel component presents a safety hazard. Based on the simulated working load to residual bearing capacity ratio, it can be determined whether the steel component has reached a critical failure state, thereby assessing the health of the power tower. This provides operations and maintenance personnel with accurate maintenance recommendations, component replacement priorities, and operational risk levels, thereby improving the operational safety of the power tower and the overall power network.

[0153] S442: When it is determined that the plurality of steel structures include a steel structure with a potential safety hazard based on the health status of each steel structure, the health status of the target power tower is determined to be a safety risk.

[0154] After determining the health status of each steel structure, the control device determines, based on the health status of each steel structure, whether a steel structure with a safety hazard is included among the multiple steel structures; when it is determined that a steel structure with a safety hazard is included among the multiple steel structures, the health status of the target power tower is determined to be a safety risk.

[0155] In other embodiments, other specific methods can be used to determine whether a steel structure is a steel structure with a safety hazard. For example, the steel structure can be scored or graded based on its residual bearing capacity and post-corrosion working load. Indicators such as safety margin coefficient and safety level can be used. The health status of the target power tower can then be determined based on the number of steel structures in different states or grades within the target power tower.

[0156] In this embodiment, the control device determines the health of the steel components based on their post-corrosion working loads and corresponding residual load-bearing capacity. The health of the steel components is used to indicate whether they pose a safety hazard. If the health of each steel component indicates that any of them pose a safety hazard, the target power tower's health status is determined to be a safety risk. By comparing the actual post-corrosion load-bearing condition of each steel component with its residual load-bearing capacity, it is possible to quantitatively determine whether an individual component is in an overloaded, critical, or safe state, achieving fine-grained structural health analysis and improving detection accuracy.

[0157] In some embodiments, as Figure 8 As shown, after step S50, the control device performs mechanical performance simulation on the target power tower according to the residual bearing capacity of each steel structure, and is further configured to perform the following steps:

[0158] S60: Generate maintenance recommendations for the target power tower based on the mechanical performance simulation data of the target power tower and the residual bearing capacity of each steel structure component.

[0159] After performing mechanical performance simulation on the target power tower according to the residual bearing capacity of each steel structure, the control device generates maintenance recommendations for the target power tower based on the mechanical performance simulation data of the target power tower and the residual bearing capacity of each steel structure.

[0160] Among them, maintenance recommendations for the entire target power tower can be generated based on the base load and vertex displacement of the target power tower after corrosion in the mechanical performance simulation data. For example, when the displacement of the highest point of the target power tower after corrosion is greater than the calibration displacement, it means that the target power tower has a large displacement and may have insufficient lateral resistance or local instability. The target power tower poses a safety risk. At this time, maintenance recommendations for strengthening the target power tower can be generated, such as strengthening the foundation of the target power tower, providing additional structural support for the target power tower, etc. When the base load is less than the calibration load, it means that the current base load of the target power tower is lower than the risk value. The target power tower poses a safety risk. At this time, maintenance recommendations for strengthening the base structure of the target power tower can be generated.

[0161] Among them, the health status of the steel structure parts can also be determined based on the post-corrosion working load of the steel structure parts in the mechanical performance simulation data, and the post-corrosion working load of the steel structure parts, so as to generate maintenance recommendations for the steel structure parts based on the health status of the steel structure parts.

[0162] S70: Displaying maintenance suggestions for the target power tower.

[0163] After generating maintenance recommendations for the target power tower based on the mechanical properties simulation data of the target power tower and the remaining bearing capacity of each steel structure, the control device can send the maintenance recommendations for the target power tower to the user's terminal device, and visualize the maintenance recommendations for the target power tower through the terminal device so that the target power tower can be maintained in a timely manner subsequently.

[0164] In one embodiment, after performing a mechanical performance simulation on a target power tower based on the residual bearing capacity of each steel structure, the control device is further configured to: generate maintenance recommendations for the target power tower based on the mechanical performance simulation data of the target power tower and the residual bearing capacity of each steel structure; and display the maintenance recommendations for the target power tower. Based on the mechanical performance simulation data of the target power tower and the residual bearing capacity of each steel structure, this solution can accurately locate problematic components and high-risk areas, thereby generating scientific, reasonable, and highly targeted personalized maintenance recommendations to ensure the structural safety of the power tower. Furthermore, the introduction of a maintenance recommendation generation step after the mechanical simulation achieves a complete closed loop from data analysis to executable operation and maintenance instructions, effectively improving the automation and intelligence level of the system.

[0165] In some embodiments, the mechanical performance simulation data of the target power tower includes the post-corrosion working load of each steel structure. In step S60, the control device generates maintenance recommendations for the target power tower based on the mechanical performance simulation data of the target power tower and the remaining load-bearing capacity of each steel structure. The control device is configured to perform the following steps:

[0166] S61: Obtaining the health status of each steel structure component, where the health status of the steel structure component is determined based on the post-corrosion working load and the corresponding residual bearing capacity of the steel structure component;

[0167] After simulating the mechanical properties of the target power tower based on the residual bearing capacity of each steel component, the control device can determine the health status of each steel component. The health status of each steel component is determined based on its post-corrosion working load and the corresponding residual bearing capacity. The determination process is described above and will not be further elaborated here.

[0168] S62: When the steel structure is determined to be a target steel structure with potential safety hazards based on the health condition of the steel structure, a replacement suggestion for the target steel structure is generated to obtain a maintenance suggestion for the target power tower.

[0169] Then, when the steel structure is determined to be a target steel structure with potential safety hazards based on the health condition of the steel structure, a replacement suggestion for the target steel structure is generated to obtain a maintenance suggestion for the target power tower.

[0170] In other embodiments, the health of a steel structure can also be used to indicate the safety level or safety score of the steel structure. Different maintenance recommendations are generated for different safety levels or safety scores of steel structures. For example, when the safety level or safety score of a steel structure is high (e.g., greater than a preset level, greater than or equal to a preset score value), it indicates that the corrosion of the steel structure has no or only a minor impact on its performance. In this case, a maintenance recommendation is generated for the steel structure to remove corrosion products and re-coat. When the safety level or safety score of a steel structure is low (e.g., less than a preset level or score value), it indicates that the corrosion of the steel structure has seriously affected its performance. In this case, a maintenance recommendation is generated for replacing the steel structure.

[0171] In this embodiment, the mechanical properties simulation data includes the post-corrosion working load of each steel component. The control device determines the health of the steel component based on the post-corrosion working load and the corresponding residual load capacity. If a steel component is identified as a target steel component with a safety hazard based on the steel component's health, a replacement recommendation for the target steel component is generated to provide maintenance recommendations for the target power tower. Based on the ratio of each steel component's post-corrosion working load to its residual load capacity, the system determines whether it poses a safety hazard. This effectively reduces information fragmentation and manual judgment bias, improving the systematic and standardized nature of maintenance work. Furthermore, by generating clear replacement recommendations for target steel components identified as having safety hazards, targeted replacement of hazardous components allows intervention before corrosion degradation leads to serious failure, significantly reducing the risk of safety incidents such as sudden fracture and structural collapse. This improves the long-term stability and reliability of the power tower and avoids the waste of resources associated with wholesale replacement or untargeted repairs, thereby enhancing the accuracy and cost-effectiveness of operation and maintenance decisions.

[0172] In some embodiments, the acquisition device is further used to acquire light intensity images of the steel structure to obtain light intensity images of each steel structure. In step S70, the control device displays maintenance recommendations for the target power tower and is configured to perform the following steps:

[0173] S71: When the maintenance suggestion for the target power tower includes a suggestion for replacing a target steel structure component with a potential safety hazard, obtain installation location and model information of the target steel structure component in the target power tower.

[0174] In this embodiment, the acquisition device is also used to acquire light intensity images of the steel structures to obtain light intensity images of each steel structure. That is, when the acquisition device is controlled to acquire hyperspectral information from the steel structures, the acquisition device is also controlled to simultaneously acquire light intensity images of the steel structures to obtain both hyperspectral and light intensity images of each steel structure.

[0175] When a steel structure is identified as a target steel structure with a safety hazard based on its health and a replacement recommendation is generated for the target steel structure, the control device can obtain the installation location and model information of the target steel structure on the target power tower and retrieve a captured light intensity image of the target steel structure. This light intensity image can reflect the appearance and corrosion surface characteristics of the target steel structure.

[0176] S72: The replacement suggestion and light intensity image for the target steel structure, as well as the corrosion condition, installation location and model information of the target steel structure are sent to the terminal device for interface display.

[0177] The control device can send replacement recommendations and light intensity images for the target steel structure parts, as well as the corrosion conditions, installation locations and model information of the target steel structure parts, to the terminal device for interface display, so that users can clearly understand the actual status and specific replacement requirements of the target steel structure parts, reduce the difficulty of understanding, and improve the efficiency of the execution of maintenance measures.

[0178] In this embodiment, when the maintenance recommendations for a target power tower include replacement recommendations for target steel components posing safety hazards, the control device obtains the installation location and model information of the target steel components within the target power tower. The control device then transmits the replacement recommendations, along with the light intensity image of the target steel components captured by the acquisition device, along with the corrosion status, installation location, and model information of the target steel components, to the terminal device for display. By synchronously transmitting and centrally displaying the light intensity image (reflecting the appearance and corroded surface characteristics of the target steel components) along with the replacement recommendations, corrosion status, installation location, and model information, users can quickly locate the target components and accurately understand their true condition and specific replacement requirements. This reduces complexity, avoids missed repairs or delays due to incomplete information, and effectively improves the efficiency and accuracy of maintenance work.

[0179] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0180] In one embodiment, a control device is provided. The control device may be a controller in a power tower status detection device, such as an electronic control unit. The control device corresponds to the power tower status detection method in the above embodiment and is used to implement the functions of the control device in the power tower status detection device. Figure 9 As shown, the parameter aggregation device includes a control module 901, an analysis module 902, a prediction module 903 and an early warning module 904. The functional modules are described in detail as follows:

[0181] Control module 901 is used to control the flight device of the power tower status detection device to move to the corresponding position of the target power tower, and control the acquisition device of the power tower status detection device to perform hyperspectral image acquisition to acquire hyperspectral images of various steel structural components at different positions in the target power tower;

[0182] An analysis module 902 is configured to analyze the corrosion state of the steel structure based on the hyperspectral image of the steel structure to obtain the corrosion status of the steel structure;

[0183] Prediction module 903 is used to predict the residual bearing capacity of steel structures based on the corrosion conditions of the steel structures using a pre-established post-corrosion mechanical property model. Based on the residual bearing capacity of each steel structure, a mechanical property simulation is performed on the target power tower to predict the health status of the target power tower based on the mechanical property simulation data. The post-corrosion mechanical property model is constructed based on measured corrosion data of steel specimens under different corrosion conditions.

[0184] The early warning module 904 is configured to issue a safety risk classification early warning to the target power tower when it is predicted that the health status of the target power tower indicates that the target power tower has a safety risk.

[0185] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0186] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0187] The embodiment of the present application also provides an electronic device, which can be a power tower status detection device or a user's terminal device. Figure 10As shown, the electronic device 10 includes: at least one processor 101, a memory 102, and a computer program 103 stored in the memory 102 and executable on the at least one processor 101. When the processor 101 executes the computer program 103, the steps in any of the above-mentioned method embodiments are implemented, or when the processor 101 executes the computer program 103, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0188] Exemplarily, the computer program 103 may be divided into one or more modules / units, which are stored in the memory 102 and executed by the processor 101 to implement the present application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 103 in the electronic device 10.

[0189] Those skilled in the art will understand that Figure 10 These are merely examples of the electronic device and do not constitute a limitation of the electronic device. The electronic device may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0190] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0191] The memory may be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device. The memory may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Furthermore, the memory may include both an internal storage unit of the electronic device and an external storage device.

[0192] An embodiment of the present application further provides a readable storage medium, wherein the readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0193] An embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0194] If the integrated unit is implemented as a software functional unit and sold or used as a standalone product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the process steps in the above-mentioned method embodiments by using a computer program to instruct the relevant hardware. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a camera / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunication signals, and software distribution media. Examples include USB flash drives, removable hard drives, magnetic disks, or optical disks. In some jurisdictions, based on legislation and patent practice, computer-readable media cannot be electric carrier signals or telecommunication signals.

[0195] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0196] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0197] In the embodiments provided in this application, it should be understood that the disclosed devices / equipment and methods can be implemented in other ways. For example, the device / equipment embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0198] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0199] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application 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 make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A power tower status detection device, characterized in that: include: An acquisition device, used for acquiring hyperspectral images of a target; A flying device, used for responding to control to drive the collecting device to move to a corresponding position; The control device connected to the collection device and the flying device is configured to: Controlling the flight device to move to a corresponding position of a target power tower, and controlling the acquisition device to acquire hyperspectral images to acquire hyperspectral images of a plurality of steel structures at different positions of the target power tower; Based on the hyperspectral image of the steel structure, a corrosion state analysis is performed on the steel structure to obtain the corrosion condition of the steel structure, including: Based on the hyperspectral image of the steel structure, identifying the components of the corrosion products of the steel structure to determine the corrosion products on the surface of the steel structure and determining the corrosion area of ​​the corrosion products on the steel structure, including: Extract spectral features from the hyperspectral image of the steel structure to obtain hyperspectral feature data of the steel structure, wherein the hyperspectral feature data includes hyperspectral vectors of different pixels in the hyperspectral image. performing a hyperspectral vector clustering process on the hyperspectral feature data of the steel structure to obtain at least one target cluster data; Based on pre-generated preset hyperspectral data of multiple types of corrosive substances, hyperspectral feature matching is performed on the target cluster data to determine the calibration substance corresponding to the matched preset hyperspectral data as the corrosion product existing on the surface of the steel structure; Using the pixel area formed by each pixel in the target cluster data in the hyperspectral image as the corrosion area of ​​the corrosion product corresponding to the target cluster data; Determining the corrosion grade of the steel structure according to the corrosion products on the surface of the steel structure and the corrosion area of ​​the corrosion products to obtain the corrosion condition of the steel structure; According to the corrosion condition of the steel structure, a pre-built post-corrosion mechanical property model is used to predict the residual bearing capacity of the steel structure, wherein the pre-built post-corrosion mechanical property model is constructed based on measured corrosion data of steel specimens under different corrosion conditions; performing a mechanical property simulation on the target power tower according to the residual bearing capacity of each of the steel structures, so as to predict the health status of the target power tower according to the mechanical property simulation data; When it is predicted that the health status of the target power tower indicates that the target power tower has a safety risk, a safety risk classification warning is issued to the target power tower.

2. The power tower status detection device according to claim 1, characterized in that: After performing mechanical performance simulation on the target power tower according to the residual bearing capacity of each of the steel structural members, the control device is further configured to: generating maintenance recommendations for the target power tower based on the mechanical performance simulation data of the target power tower and the remaining bearing capacity of each of the steel structural members; A maintenance suggestion for the target power tower is displayed.

3. The power tower status detection device according to claim 2, characterized in that: The mechanical property simulation data includes the post-corrosion working load of each of the steel structures. The control device generates a maintenance recommendation for the target power tower based on the mechanical property simulation data of the target power tower and the residual bearing capacity of each of the steel structures, and is configured to: Obtaining the health status of each of the steel structural members, where the health status of the steel structural members is determined based on the post-corrosion working load of the steel structural members and the corresponding residual bearing capacity; When the steel structure is determined to be a target steel structure with potential safety hazards based on the health condition of the steel structure, a replacement suggestion for the target steel structure is generated to obtain a maintenance suggestion for the target power tower.

4. The power tower status detection device according to claim 2, characterized in that: The acquisition device is further used to acquire light intensity images of the steel structures to obtain light intensity images of each of the steel structures; The control device displays maintenance suggestions for the target power tower and is configured to: When the maintenance suggestion for the target power tower includes a suggestion for replacing a target steel structure member with a potential safety hazard, obtaining installation location and model information of the target steel structure member in the target power tower; The replacement suggestion for the target steel structure and the light intensity image, as well as the corrosion condition of the target steel structure, the installation location and model information are sent to the terminal device for interface display.

5. The power tower status detection device according to claim 1, characterized in that: The control device performs mechanical property simulation on the target power tower according to the residual bearing capacity of each of the steel structures, so as to predict the health status of the target power tower according to the mechanical property simulation data, and is configured to: Obtaining an original simulation model of the target power tower, where the original simulation model is a structural simulation model established according to the specific structure of the target power tower after it is completed; According to the corrosion conditions of each of the steel structures, parameters in the original simulation model are updated to obtain a target simulation model of the target power tower; Using the target simulation model to perform simulation analysis on the mechanical properties of the target power tower after corrosion to obtain mechanical property simulation data of the target power tower; The health status of the target power tower is determined according to the residual bearing capacity of each of the steel structural members and the mechanical property simulation data.

6. The power tower status detection device according to claim 5, characterized in that: The mechanical property simulation data includes the post-corrosion working load of each of the steel structures. The control device determines the health status of the target power tower based on the remaining bearing capacity of each of the steel structures and the mechanical property simulation data, and is configured to: determining the health condition of the steel structure according to the post-corrosion working load of the steel structure and the corresponding residual bearing capacity, wherein the health condition is used to indicate whether the steel structure is a structure with potential safety hazards; When it is determined based on the health status of each of the steel structures that the plurality of steel structures include the steel structure with potential safety hazards, the health status of the target power tower is determined to be a safety risk.

7. The power tower status detection device according to any one of claims 1 to 6, characterized in that: The post-corrosion mechanical properties model is constructed in the following way: Obtaining measured corrosion data of steel specimens under different corrosion conditions obtained by performing corrosion tests on multiple steel specimens, wherein the measured corrosion data of the steel specimens include the composition and content of corrosion products of each of the corroded steel specimens, and at least one of the placement angle, working environment, and corrosion duration of the steel specimens under the different corrosion conditions is different; According to the steel specimens after corrosion under different corrosion conditions, and the composition and content of the corrosion products of each steel specimen after corrosion, the mechanical properties of the steel structure under different corrosion conditions are analyzed to construct a performance prediction model for predicting the steel structure.

8. A method for detecting the status of a power tower, characterized in that: Applied to power tower status detection equipment, including: Controlling the flight device of the power tower status detection device to move to a corresponding position of a target power tower, and controlling the acquisition device of the power tower status detection device to perform hyperspectral image acquisition to acquire hyperspectral images of a plurality of steel structures at different positions in the target power tower; Based on the hyperspectral image of the steel structure, a corrosion state analysis is performed on the steel structure to obtain the corrosion condition of the steel structure, including: Based on the hyperspectral image of the steel structure, identifying the components of the corrosion products of the steel structure to determine the corrosion products on the surface of the steel structure and determining the corrosion area of ​​the corrosion products on the steel structure, including: Extract spectral features from the hyperspectral image of the steel structure to obtain hyperspectral feature data of the steel structure, wherein the hyperspectral feature data includes hyperspectral vectors of different pixels in the hyperspectral image. performing a hyperspectral vector clustering process on the hyperspectral feature data of the steel structure to obtain at least one target cluster data; Based on pre-generated preset hyperspectral data of multiple types of corrosive substances, hyperspectral feature matching is performed on the target cluster data to determine the calibration substance corresponding to the matched preset hyperspectral data as the corrosion product existing on the surface of the steel structure; Using the pixel area formed by each pixel in the target cluster data in the hyperspectral image as the corrosion area of ​​the corrosion product corresponding to the target cluster data; Determining the corrosion grade of the steel structure according to the corrosion products on the surface of the steel structure and the corrosion area of ​​the corrosion products to obtain the corrosion condition of the steel structure; According to the corrosion condition of the steel structure, a pre-built post-corrosion mechanical property model is used to predict the residual bearing capacity of the steel structure, wherein the pre-built post-corrosion mechanical property model is constructed based on measured corrosion data of steel specimens under different corrosion conditions; performing a mechanical property simulation on the target power tower according to the residual bearing capacity of each of the steel structures, so as to predict the health status of the target power tower according to the mechanical property simulation data; When it is predicted that the health status of the target power tower indicates that the target power tower has a safety risk, a safety risk classification warning is issued to the target power tower.

9. A readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the computer program implements the functions of the power tower status detection device according to any one of claims 1 to 7, or implements the steps of the power tower status detection method according to claim 8.

10. A computer program product, characterized in that The computer program product includes a computer program, which, when executed by a processor, implements the functions of the power tower status detection device according to any one of claims 1 to 7, or implements the steps of the power tower status detection method according to claim 8.

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