Method and device for determining maintenance cost of tower drum, storage medium and electronic device

Abstract

The invention discloses a method and a device for determining the maintenance cost of a tower drum, a storage medium, an electronic device and a computer program product. The method comprises the following steps: acquiring deformation data of the tower drum; according to the deformation data, determining at least one problem point location of the tower drum; according to the position parameters of the at least one problem point location and a pre-established maintenance map, the maintenance budget of the at least one problem point location is determined, and the maintenance map is used for indicating the maintenance budget of the problem point locations with different position parameters; and according to the maintenance budget of the at least one problem point location, the operation data of the tower drum and the life cycle of the tower drum, the maintenance cost of the whole life cycle of the tower drum is determined. Through accurate deformation data acquisition and efficient problem point location determination, the maintenance budget is quickly determined based on the maintenance atlas, and then the maintenance cost of the whole life cycle of the tower drum is estimated in combination with the operation data of the tower drum and the life cycle of the tower drum, so that more accurate investment measurement and calculation by a user are facilitated.

Description

Technical Field

[0001] The present application relates to the field of wind power technology, and in particular, to a method and device for determining the maintenance cost of a tower, a storage medium, an electronic device, and a computer program product. Background Art

[0002] In the field of wind power generation, wind turbine towers are key structural components that support wind turbine generator sets. Their health status and maintenance strategies are directly related to the economic benefits and safe operation of the entire wind power project. As wind turbines develop towards larger and taller towers, the complexity and height of towers continue to increase, placing higher requirements on tower inspection and maintenance.

[0003] In the related art, the tower is inspected through static monitoring of load sensors and manual inspections, and then the maintenance needs of the tower are evaluated based on the inspection results, thereby determining the maintenance cost.

[0004] However, the related technical methods cannot determine the potential risks of the tower and the estimation of maintenance costs is not accurate enough. Summary of the invention

[0005] Embodiments of the present application provide a method and device for determining the maintenance cost of a tower, a storage medium, an electronic device, and a computer program product.

[0006] According to one aspect of an embodiment of the present application, a method for determining the maintenance cost of a tower is provided, the method comprising: acquiring deformation data of the tower; determining at least one problem point of the tower based on the deformation data; determining a maintenance budget of at least one problem point based on location parameters of the at least one problem point and a pre-established maintenance map, wherein the maintenance map is used to indicate maintenance budgets for problem points with different location parameters; determining the maintenance cost of the tower over its entire life cycle based on the maintenance budget of at least one problem point, operating data of the tower, and the life cycle of the tower.

[0007] In an exemplary embodiment, the life of the tower is determined based on the tower's usage time and maintenance records; the problems of the tower over its entire life cycle are determined based on the tower's life, the maintenance budget of at least one problem point, and a pre-established tower life cycle model; and the maintenance cost of the tower over its entire life cycle is determined based on the problems of the tower over its entire life cycle and a maintenance map.

[0008] In an exemplary embodiment, before determining the problem conditions of the tower throughout its life cycle based on the life of the tower, the maintenance budget of at least one problem point, and a pre-established tower life cycle model, the method also includes: obtaining historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower, wherein the historical maintenance data includes problem points, problem time, and maintenance costs; establishing a sample library based on the historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower; and using the sample library to train a preset neural network model to obtain a tower life cycle model.

[0009] In an exemplary embodiment, before determining the maintenance budget of at least one problem point based on the location parameters of at least one problem point and a pre-established maintenance map, the method also includes: determining maintenance plans for points with multiple different location parameters of the tower when problems occur; determining maintenance budgets corresponding to points with multiple different location parameters of the tower based on the maintenance plans for points with multiple different location parameters of the tower when problems occur; and associating and recording the location parameters, maintenance plans, and maintenance budgets of multiple points to establish a maintenance map.

[0010] In an exemplary embodiment, at least one problem point of a tower is determined based on deformation data, including: mapping the deformation data onto a three-dimensional model of the tower; analyzing the three-dimensional model of the tower to determine problem points where the degree of deformation exceeds a preset range, and determining location parameters of the problem points based on the three-dimensional model.

[0011] In an exemplary embodiment, deformation data of a tower is obtained, including: obtaining scanning data of different areas of the tower by means of multiple radars arranged within a preset range of the tower, wherein different radars have different scanning areas; obtaining image data of different areas of the tower by means of a drone; and determining deformation data of the tower based on the scanning data and the image data.

[0012] Another aspect of the present application provides a device for determining the maintenance cost of a tower, the device comprising: a data acquisition module for acquiring deformation data of the tower; a point determination module for determining at least one problem point of the tower based on the deformation data; a budget determination module for determining the maintenance budget of at least one problem point based on location parameters of at least one problem point and a pre-established maintenance map; and a cost determination module for determining the maintenance cost of the tower over its entire life cycle based on the maintenance budget of at least one problem point, the operating data of the tower, and the life cycle of the tower.

[0013] According to another aspect of the embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned method for determining the maintenance cost of the tower when running.

[0014] According to another aspect of an embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the method for determining the maintenance cost of the tower through the computer program.

[0015] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps of the method described in each embodiment of the present application are implemented.

[0016] The above-mentioned tower maintenance cost determination method and device first obtains the deformation data of the tower. Then, based on the deformation data, at least one problem point of the tower is determined, and potential problem points can be discovered in time, avoiding the inefficiency and misjudgment of manual inspections, and significantly improving the detection efficiency and accuracy. According to the location parameters of at least one problem point and a pre-established maintenance map, the maintenance budget of at least one problem point is determined, wherein the maintenance map is used to indicate the maintenance budget of problem points with different location parameters. Through the maintenance map, the maintenance budget can be quickly determined according to the specific location and nature of the problem point, reducing the decision-making time, improving the pertinence and efficiency of maintenance work, and reducing the risk of over-maintenance or under-maintenance. According to the maintenance budget of at least one problem point, the operation data of the tower, and the life cycle of the tower, the maintenance cost of the tower throughout its life cycle is determined. Through the calculation of the maintenance budget and the prediction of the maintenance cost throughout its life cycle, the maintenance cost can be more accurately determined. In summary, the present application accurately collects deformation data, efficiently determines problem points, and quickly determines the maintenance budget based on the maintenance map, and then estimates the maintenance cost of the tower throughout its life cycle, which is convenient for users to make more accurate investment calculations. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1 It is a hardware structure block diagram of a method for determining the maintenance cost of a tower according to an embodiment of the present application;

[0020] Figure 2is a flow chart of a method for determining tower maintenance cost according to an embodiment of the present application;

[0021] Figure 3 This is a second flow chart of a method for determining tower maintenance cost according to an embodiment of the present application;

[0022] Figure 4 is a flowchart of a method for determining tower maintenance cost according to an embodiment of the present application;

[0023] Figure 5 This is a fourth flow chart of a method for determining tower maintenance cost according to an embodiment of the present application;

[0024] Figure 6 is a fifth flow chart of a method for determining tower maintenance cost according to an embodiment of the present application;

[0025] Figure 7 is a sixth flow chart of a method for determining tower maintenance cost according to an embodiment of the present application;

[0026] Figure 8 It is a structural block diagram of a device for determining tower maintenance cost according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, method, system, product or equipment comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0029] The method embodiments provided in the embodiments of the present application can be executed in a computer terminal or a similar computing device. Taking running on a computer terminal as an example, Figure 1 1 is a hardware structure block diagram of a computer terminal for determining the tower maintenance cost of an embodiment of the present application. Figure 1 As shown, the computer terminal may include one or more ( Figure 1 The computer terminal includes a processor 102 (only one is shown) (the processor 102 may include but is not limited to a microprocessor (Microprocessor Unit, MPU for short) or a programmable logic device (PLD for short)) and a memory 104 for storing data. In an exemplary embodiment, the computer terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 1 More or fewer components as shown, or with Figure 1 Equivalent functions or comparisons shown Figure 1 A different configuration with more features is shown.

[0030] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for determining the maintenance cost of the tower in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0031] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0032] In this embodiment, a method for determining the maintenance cost of a tower is provided. Figure 2 : is a flow chart of an optional method for determining tower maintenance cost according to an embodiment of the present application, the process includes the following steps S200-S230:

[0033] Step S200, obtaining deformation data of the tower.

[0034] Among them, detection means (such as millimeter wave radar) can be used to collect deformation information of the tower during operation in order to detect possible structural damage or abnormal conditions. By monitoring the deformation of the tower under different loads and environmental conditions, potential problems can be identified earlier, tower problems can be predicted, and maintenance can be performed when the problem is minor, avoiding high maintenance costs caused by intervention when the problem deteriorates to the point where maintenance is necessary.

[0035] For example, high-precision millimeter-wave radar sensors can be deployed to perform non-contact deformation monitoring of the tower. Millimeter-wave radar can work stably under severe weather conditions and is not affected by environmental factors such as dust and rain. By collecting tiny displacement data on the surface of the tower, the structural health of the tower can be monitored in real time.

[0036] Step S210: determining at least one problem point of the tower according to the deformation data.

[0037] After obtaining the deformation data of the tower, it is necessary to analyze it to determine the specific problem points. This can be done by comparing historical data with the standard deformation range to identify deformations that exceed the normal range, thereby locating the problem area on the tower. Accurate problem location is the basis for formulating a reasonable maintenance plan later.

[0038] For example, data processing software can be used to analyze the data collected by the millimeter wave radar, and by comparing it with the three-dimensional model of the tower and historical data, abnormal deformation areas can be identified. Combined with drone inspections and ground observation results, the specific location and potential damage of the problem points can be further confirmed.

[0039] Step S220, determining a maintenance budget of at least one problem point according to location parameters of at least one problem point and a pre-established maintenance map.

[0040] Among them, the maintenance map is used to indicate the maintenance budget of problem points with different location parameters. The maintenance map is a maintenance plan and material demand database based on location parameters, which associates different problem points of the tower with corresponding maintenance strategies. By querying the maintenance map, the maintenance budget of the problem point can be quickly determined, including direct material cost, labor cost and indirect downtime loss, etc., providing a basis for cost control and resource allocation.

[0041] For example, the maintenance map stores maintenance plans based on different tower location parameters and problem types, as well as corresponding material lists and cost budgets. By querying the maintenance map, you can quickly call up maintenance strategies that match the problem points, including detailed lists of required tools, materials, and consumables, as well as estimated labor and time costs, so as to conduct accurate maintenance budget analysis.

[0042] Step S230, determining the maintenance cost of the tower over its entire life cycle based on the maintenance budget of at least one problem point, the operation data of the tower, and the life cycle of the tower.

[0043] Specifically, the full life cycle maintenance cost analysis is a comprehensive estimate of the maintenance cost of the tower from construction to decommissioning. It not only considers the repair cost of the current problem points, but also combines the tower's operating data (such as load, wind speed, etc.) and its expected remaining service life to predict and calculate the maintenance costs that may occur in the future, providing a comprehensive cost perspective for project investment decisions.

[0044] For example, a life cycle cost model for a tower is constructed by using data analysis and prediction models, combined with the tower's operating data, such as load history, wind farm environment, and maintenance frequency, as well as the tower's design life and current usage status. The model takes into account potential future maintenance needs and cost changes, such as material price fluctuations and labor cost increases, as well as maintenance efficiency improvements that may be brought about by technological advances, to obtain a total maintenance cost forecast for the tower from construction to decommissioning.

[0045] In this embodiment, the deformation data of the tower is first obtained. Then, based on the deformation data, at least one problem point of the tower is determined, so that potential problem points can be discovered in time, the inefficiency and misjudgment of manual inspections are avoided, and the detection efficiency and accuracy are significantly improved. According to the location parameters of at least one problem point and a pre-established maintenance map, the maintenance budget of at least one problem point is determined, wherein the maintenance map is used to indicate the maintenance budget of problem points with different location parameters. Through the maintenance map, the maintenance budget can be quickly determined according to the specific location and nature of the problem point, which reduces the decision-making time, improves the pertinence and efficiency of maintenance work, and reduces the risk of over-maintenance or under-maintenance. According to the maintenance budget of at least one problem point, the operation data of the tower, and the life cycle of the tower, the maintenance cost of the tower over its entire life cycle is determined. Through the calculation of the maintenance budget and the prediction of the maintenance cost over its entire life cycle, the maintenance cost can be more accurately determined. In summary, the present application collects deformation data accurately, determines problem points efficiently, and quickly determines the maintenance budget based on the maintenance map, and then estimates the maintenance cost of the tower over its entire life cycle, so that users can make more accurate investment calculations.

[0046] In one embodiment, Figure 3 As shown, step S230 determines the maintenance cost of the tower over its entire life cycle based on the maintenance budget of at least one problem point, the tower operation data, and the tower life cycle. It includes: steps S300-S320:

[0047] Step S300, determining the life of the tower according to the tower's usage time and maintenance records.

[0048] Specifically, by analyzing the service history and maintenance data of the tower, the current health status and remaining service life of the tower are evaluated. As the tower is used, its structure will experience natural aging and the effects of external forces such as wind loads. The maintenance record can reflect the actual damage and repair of the tower during its service life, and is an important basis for evaluating the life of the tower.

[0049] For example, a life assessment system can be built, which collects the service time of the tower, detailed information on previous maintenance (such as maintenance time, location, cost, and maintenance measures taken), and combines the tower's design life, material properties, and wind farm environmental data to use machine learning algorithms or life prediction models to assess the health status and remaining service life of the tower. For example, an algorithm based on an artificial neural network can be used to train the model to input the tower's maintenance history and operating environment, and output a prediction of the tower's remaining service life.

[0050] Step S310, determining the problem conditions of the entire life cycle of the tower according to the life of the tower, the maintenance budget of at least one problem point, and a pre-established tower life cycle model.

[0051] Specifically, by combining the tower life assessment results, the maintenance requirements and costs of current problem points, and the tower life cycle model, the types, frequency, and severity of problems that may occur during the entire tower life cycle can be predicted. The life cycle model is based on a large amount of historical data and statistics, and can reflect the typical maintenance requirements of the tower at different stages and the changing laws of its costs.

[0052] For example, a complete tower life cycle problem prediction model can be established. Based on the tower's service life, maintenance records, and current maintenance budget, the model uses time series analysis, fault tree analysis, and other methods to predict the types, frequencies, and costs of problems that may occur in the tower's subsequent use. Specifically, the tower's service life can be used as the input of the time series, combined with the historical problem records and the characteristics of the current problem points, to predict potential problems that may occur in the future and their maintenance needs, thereby providing data support for the formulation of maintenance strategies.

[0053] Step S320, determining the maintenance cost of the tower over its entire life cycle based on the problems in the tower over its entire life cycle and the maintenance map.

[0054] Specifically, after predicting the problems of the tower throughout its life cycle, the maintenance plan and cost budget for each problem point can be obtained by querying the maintenance map. The maintenance map not only contains the immediate maintenance cost of each problem point, but also takes into account the possible trend of maintenance costs over time. Based on this information, a comprehensive tower maintenance cost model for the entire life cycle can be established, and then the maintenance cost of the tower throughout its life cycle can be calculated.

[0055] For example, the maintenance map can be queried to obtain the maintenance budget of each problem point at different time points, including the cost of materials, labor, tools, etc. The system can further combine the tower's operating efficiency and downtime losses, as well as possible equipment updates and upgrade costs, to comprehensively calculate the total maintenance cost of the tower's entire life cycle. For example, an algorithm can be designed to calculate the cumulative maintenance cost of each problem point separately, and combine it with the tower's operating cost, depreciation cost, etc. to derive the total cost of the entire life cycle.

[0056] In this embodiment, through accurate life assessment and problem prediction, preventive maintenance measures can be taken in advance to prevent small problems from turning into major failures, thereby extending the service life of the tower and improving the overall operating efficiency and economy of the wind turbine. The combined use of maintenance maps and life cycle problem prediction models provides comprehensive data support for maintenance decisions, can accurately evaluate the long-term effects and costs of different maintenance plans, and help decision makers choose the best plan. By establishing a full life cycle maintenance cost model, the long-term maintenance cost of the tower can be predicted and controlled, which helps to optimize financial planning, reduce the overall risk of the project, and improve the return on investment of wind power projects. Accurate assessment of the problem situation and maintenance cost of the tower throughout its life cycle provides a reliable basis for the investment decision of the project, helps owners and investors to reasonably anticipate costs at the beginning of the project, reduce investment risks, and improve the quality of feasibility analysis of the project.

[0057] In one embodiment, Figure 4 As shown, in step S310, before determining the problem conditions of the whole life cycle of the tower according to the life condition of the tower, the maintenance budget of at least one problem point, and the pre-established tower life cycle model, the method further includes steps S400-S420:

[0058] Step S400, obtaining the historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower.

[0059] Among them, historical maintenance data includes problem locations, problem time, and maintenance costs.

[0060] Specifically, historical maintenance data contains detailed records of all maintenance events encountered by the tower during its service life, including specific problem locations, the time when the problem was discovered and solved, and the cost of each maintenance. The tower life cycle information reflects the expected service life of the tower, that is, the time span from construction to decommissioning. Geographic environment data includes the topography and climate conditions of the wind farm where the tower is located, which have a direct impact on the health status and maintenance needs of the tower.

[0061] For example, relevant data can be collected from tower monitoring systems, maintenance reports, financial records, and environmental monitoring systems, and stored and managed in a unified manner.

[0062] Step S410, establishing a sample library according to the historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower.

[0063] Specifically, the collected data is converted into a sample library that can be used for model training. The sample library integrates historical maintenance data, life cycle information, and geographic environment data to provide a complete sample of tower status before and after maintenance, geographical conditions, and maintenance costs for each maintenance event.

[0064] Exemplarily, the collected raw data is preprocessed and feature extracted to convert the problem location, problem time, maintenance cost, current life cycle stage of the tower, and geographic environment parameters into standardized numerical or categorical features to form a structured sample set. The sample library should contain a sufficient number of samples to cover various maintenance situations that may occur in towers in different geographic environments and life cycle stages. It can also include the tower manufacturer, model, height, type, wind farm characteristics, wind turbine type, transmission chain conditions, as well as problem analysis, maintenance period investment, construction period investment and other information.

[0065] Step S420: Using the sample library, train a preset neural network model to obtain a tower life cycle model.

[0066] Specifically, through machine learning technology, especially neural network models, the data in the sample library are deeply learned to establish a predictive model that can predict the maintenance conditions and costs that may occur in towers in different geographical environments and life cycle stages.

[0067] For example, a neural network architecture suitable for time series prediction can be selected, such as a recurrent neural network or a long short-term memory network, and the data in the sample library can be used for model training. During the training process, the model will learn the complex relationship between tower maintenance events and the geographical environment, life cycle stages, and the intrinsic relationship between the probability of problem occurrence, problem locations, and maintenance costs. Cross-validation, regularization and other techniques can be used to optimize model parameters and improve prediction accuracy.

[0068] In this embodiment, by comprehensively collecting the maintenance data and environmental information of the tower, a solid foundation is laid for establishing an effective tower life cycle model. The integrity of the data ensures the accuracy and reliability of model training, and helps to improve the accuracy of prediction and maintenance decisions. The established sample library not only provides sufficient training data for the training of the neural network model, but also improves the training efficiency and prediction accuracy of the model through data preprocessing. The structured design of the sample library enables the model to learn the inherent laws of tower maintenance more effectively, providing a solid data foundation for subsequent predictions. The trained tower life cycle model can predict possible maintenance events and their costs in the future based on the current state, geographical environment and life cycle stage of the tower, providing a scientific basis for the formulation of tower maintenance strategies and cost budgeting. Through continuous optimization and updating of the model, the accuracy and reliability of the prediction can be further improved, and the intelligent and refined management of tower maintenance can be realized, thereby reducing maintenance costs, extending the service life of the tower, and improving the economic benefits of wind power projects.

[0069] In one embodiment, Figure 5As shown, before determining the maintenance budget of at least one problem point according to the location parameters of at least one problem point and the pre-established maintenance map in step S220, the method further includes steps S500-S520:

[0070] Step S500, determining a maintenance plan for points of a plurality of different position parameters of the tower when a problem occurs.

[0071] Specifically, analyze the types of problems that may occur at points on the tower under different location parameters (such as height, angle, area, etc.), and determine the corresponding maintenance strategy based on the nature and location characteristics of the problem. The maintenance plan should cover various situations from minor damage to serious failures to ensure that the tower has corresponding response measures when various problems occur.

[0072] For example, an expert system or problem analysis database can be established, which includes detailed descriptions of common tower problems under different position parameters, possible cause analysis, and recommended maintenance measures. A maintenance plan can be developed by an experienced team of engineers based on the tower's structural design, material properties, and historical maintenance records, or machine learning technology can be used to train models to automatically recommend maintenance strategies based on a large number of historical maintenance cases. The maintenance plan should include detailed information such as the specific location of the problem point, the degree of damage, the recommended repair method, the tools and materials required, etc.

[0073] Step S510, determining maintenance budgets corresponding to the multiple points with different position parameters of the tower according to maintenance plans when problems occur at the multiple points with different position parameters of the tower.

[0074] Specifically, the financial cost of each maintenance plan is quantified, including direct costs (such as materials, labor, tools, etc.) and indirect costs (such as downtime losses, logistics costs, etc.). The determination of the maintenance budget is an important part of cost control and project financial planning.

[0075] For example, a maintenance material and labor cost database can be established, and the material list and labor hours in the maintenance plan can be input to automatically calculate the direct cost. The estimation of indirect costs may need to be calculated by combining the tower operation data, market price information and historical cost records through a prediction algorithm. The calculation of the maintenance budget should be comprehensive, including all possible expenses, and leaving a certain margin to deal with unforeseen additional expenses.

[0076] Step S520, the location parameters, maintenance plans, and maintenance budgets of multiple points are associated and recorded to establish a maintenance map.

[0077] Specifically, all the information previously collected and analyzed is integrated into a visual and queryable maintenance map, which records in detail the maintenance plans and budgets of the problem points under each position parameter of the tower, providing an intuitive and systematic tool for tower maintenance management. It has functions such as data query, plan matching and budget calculation, and can quickly retrieve the corresponding maintenance plan and maintenance budget based on the input problem point location parameters. The maintenance map should be updated regularly to reflect new maintenance cases, cost changes and improvements to the tower structure.

[0078] In this embodiment, by formulating a specific maintenance plan for each potential problem point of the tower, the decision-making time after the problem occurs can be greatly shortened, and the maintenance response speed and efficiency can be improved. At the same time, the maintenance plan based on location parameters helps to plan maintenance resources in advance, ensuring that appropriate maintenance strategies can be quickly called when problem points occur, thereby reducing maintenance costs. A clear maintenance budget can provide a financial planning basis for tower maintenance and ensure the rationality of maintenance costs. The establishment of a maintenance map realizes the systematic and visual management of tower maintenance information, greatly improving the efficiency and accuracy of maintenance decisions. Through the maintenance map, maintenance personnel can quickly understand the problem handling methods and estimated costs at any location of the tower, avoiding blind decision-making and waste of resources, reducing maintenance costs, and improving the quality and efficiency of maintenance work.

[0079] In one embodiment, Figure 6 As shown, step S210, determining at least one problem point of the tower according to the deformation data. It includes: steps S600-S610:

[0080] Step S600, mapping the deformation data onto the three-dimensional model of the tower.

[0081] Specifically, the tower deformation data obtained from millimeter-wave radar and other detection equipment is integrated with the 3D model of the tower to intuitively display the deformation status of each part of the tower. By mapping the deformation data onto the 3D model, the structural health of the tower can be more clearly understood and analyzed.

[0082] For example, data processing software or customized algorithms can be used to match the deformation data collected by the millimeter wave radar with the three-dimensional model of the tower. A data mapping system can be created that can automatically identify the location information in the deformation data and correspond it to specific parts in the three-dimensional model. In addition, the system should also have data visualization capabilities, which can intuitively display the degree of deformation on the three-dimensional model in the form of color coding or contour maps, making it easier to identify areas with abnormal deformation.

[0083] Step S610: Analyze the three-dimensional model of the tower to determine the problem points where the deformation degree exceeds a preset range, and determine the position parameters of the problem points based on the three-dimensional model.

[0084] Specifically, using the 3D model with mapped deformation data, the problem points whose deformation exceeds the preset safety range are determined through analysis algorithms, and the 3D position parameters of these problem points are accurately recorded. The determination of position parameters is crucial for subsequent maintenance work, ensuring the accuracy and efficiency of maintenance work.

[0085] In this embodiment, by mapping the deformation data to the three-dimensional model, the deformation of the tower can be clearly visualized, which improves the accuracy and efficiency of problem detection. This intuitive display method helps maintenance personnel quickly locate abnormal deformation sites and provides more intuitive data support for subsequent analysis and maintenance decisions. By analyzing and identifying problem points with abnormal deformation through algorithms, the automation level of tower maintenance is greatly improved, and the errors and time consumption of manual analysis are reduced. Accurate location parameter records ensure the pertinence and effectiveness of maintenance work, help to quickly locate problems, reduce unnecessary maintenance costs, and improve the safety and efficiency of maintenance work. In summary, by deeply integrating deformation data with the three-dimensional model of the tower, an intuitive display of the health status of the tower structure and automatic identification of problem points are achieved, providing strong technical support for the refined maintenance and cost control of the tower. This process not only improves the efficiency and accuracy of problem detection, but also ensures the pertinence and effectiveness of maintenance work.

[0086] In one embodiment, Figure 7 As shown, step S200, obtaining the deformation data of the tower. It includes: steps S700-S720:

[0087] Step S700, acquiring scanning data of different areas of the tower by arranging a plurality of radars within a preset range of the tower.

[0088] Different radars have different scanning areas. Multiple radar devices are used to scan different areas of the tower to obtain comprehensive deformation data. Radars at different locations can capture deformation information at different angles and heights of the tower to ensure the integrity and accuracy of data coverage.

[0089] For example, millimeter-wave radar sensors can be arranged at key locations such as the base, middle and top of the tower. The scanning angle and height range of each radar should be planned in advance to ensure that the deformation data of the entire tower surface can be effectively captured. The radar can be installed in a fixed or rotating manner to meet the scanning needs of different areas. Radar data collection should be carried out in real time to reflect the deformation changes of the tower under different operating conditions and environmental conditions.

[0090] Step S710: acquiring image data of different areas of the tower through a drone.

[0091] Specifically, drone technology can be used to take aerial photos of the tower, aiming to obtain high-definition images of the tower surface to assist in the analysis of deformation data and identify possible external damage or abnormal conditions. Specifically, drones equipped with high-definition camera equipment can be used to collect images of the tower regularly or in real time according to a preset flight path and altitude. The drone should have automatic flight and image stabilization functions to ensure that clear images can be obtained under different weather conditions. The collected image data should be transmitted back to the ground control center for storage and preliminary analysis.

[0092] Step S720, determining the deformation data of the tower according to the scanning data and the image data.

[0093] Specifically, the deformation of the tower is comprehensively analyzed by combining the scanning data of the radar and the image data of the drone to determine the deformation data of the tower. The deformation data should include key information such as the location, degree and trend of the deformation.

[0094] In this embodiment, through the data collection of multiple radars, comprehensive monitoring of the tower deformation data can be achieved, and the accuracy and reliability of deformation detection can be improved. This all-round monitoring method can timely discover potential structural problems of the tower, help to take maintenance measures in advance, avoid small problems from turning into major failures, reduce maintenance costs, and improve the availability and safety of the tower. The image acquisition of the drone not only provides intuitive information on the surface of the tower, but also helps to verify and supplement the radar scanning data, improving the comprehensiveness and accuracy of the deformation analysis. Image data can assist in identifying details such as the peeling of the anti-corrosion layer and damage to the sealant, ensuring the accuracy of maintenance decisions. By integrating and analyzing radar scanning data and drone image data, more comprehensive and accurate tower deformation data can be obtained.

[0095] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0096] In this embodiment, a device for determining the maintenance cost of the tower is also provided. The device for determining the maintenance cost of the tower is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0097] Figure 8 is a structural block diagram of an optional tower maintenance cost determination device according to an embodiment of the present application. Figure 8 As shown, including:

[0098] The data acquisition module 801 is used to acquire the deformation data of the tower.

[0099] The point determination module 802 is used to determine at least one problematic point of the tower according to the deformation data.

[0100] The budget determination module 803 is used to determine the maintenance budget of at least one problem point according to the location parameters of at least one problem point and a pre-established maintenance map, wherein the maintenance map is used to indicate the maintenance budget of problem points with different location parameters.

[0101] The cost determination module 804 is used to determine the maintenance cost of the tower over its entire life cycle based on the maintenance budget of at least one problem point, the operation data of the tower, and the life cycle of the tower.

[0102] Through the above device, the deformation data of the tower is first obtained. Then, based on the deformation data, at least one problem point of the tower is determined, and potential problem points can be discovered in time, avoiding the inefficiency and misjudgment of manual inspections, and significantly improving the detection efficiency and accuracy. According to the location parameters of at least one problem point and a pre-established maintenance map, the maintenance budget of at least one problem point is determined, wherein the maintenance map is used to indicate the maintenance budget of problem points with different location parameters. Through the maintenance map, the maintenance budget can be quickly determined according to the specific location and nature of the problem point, reducing the decision-making time, improving the pertinence and efficiency of maintenance work, and reducing the risk of over-maintenance or under-maintenance. According to the maintenance budget of at least one problem point, the operation data of the tower, and the life cycle of the tower, the maintenance cost of the tower throughout its life cycle is determined. Through the calculation of the maintenance budget and the prediction of the maintenance cost throughout its life cycle, the maintenance cost can be more accurately determined. In summary, the present application collects deformation data accurately, determines problem points efficiently, and quickly determines the maintenance budget based on the maintenance map, and then estimates the maintenance cost of the tower throughout its life cycle, so that users can make more accurate investment calculations.

[0103] In an exemplary embodiment, the cost determination module 804 is further used to: determine the life of the tower according to the service time and maintenance records of the tower. Determine the problem situation of the tower in its entire life cycle according to the life of the tower, the maintenance budget of at least one problem point, and the pre-established tower life cycle model. Determine the maintenance cost of the tower in its entire life cycle according to the problem situation of the tower in its entire life cycle and the maintenance map.

[0104] In an exemplary embodiment, the above device further includes:

[0105] The parameter acquisition module is used to obtain the historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower. The historical maintenance data includes problem points, problem time, and maintenance costs.

[0106] The sample library establishment module is used to establish a sample library based on the historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower.

[0107] The model determination module is used to adopt the sample library to train the preset neural network model to obtain the tower life cycle model.

[0108] In an exemplary embodiment, the above device further includes:

[0109] The solution determination module is used to determine the maintenance solution for points with multiple different position parameters of the tower when problems occur.

[0110] The budget determination module is used to determine the maintenance budget corresponding to the points of the multiple position parameters of the tower according to the maintenance plan when problems occur at the points of the multiple position parameters of the tower.

[0111] The map creation module is used to associate and record the location parameters, maintenance plans, and maintenance budgets of multiple points to create a maintenance map.

[0112] In an exemplary embodiment, the point determination module 802 is used to: map the deformation data onto the three-dimensional model of the tower, analyze the three-dimensional model of the tower, determine the problem points where the deformation degree exceeds the preset range, and determine the position parameters of the problem points based on the three-dimensional model.

[0113] In an exemplary embodiment, the data acquisition module 801 is used to: acquire scanning data of different areas of the tower by using multiple radars arranged within a preset range of the tower, wherein different radars have different scanning areas. Acquire image data of different areas of the tower by using a drone. Determine deformation data of the tower based on the scanning data and the image data.

[0114] An embodiment of the present application further provides a storage medium, which includes a stored program, wherein the program executes any of the above methods when it is run.

[0115] Optionally, in this embodiment, the storage medium may be configured to store program codes for executing the following steps:

[0116] S1, obtain the deformation data of the tower.

[0117] S2: Determine at least one problem point of the tower according to the deformation data.

[0118] S3, determining a maintenance budget of at least one problem point according to location parameters of at least one problem point and a pre-established maintenance map, wherein the maintenance map is used to indicate maintenance budgets of problem points with different location parameters.

[0119] S4, determining the maintenance cost of the tower over its entire life cycle based on a maintenance budget of at least one problem point, operation data of the tower, and the life cycle of the tower.

[0120] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0121] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0122] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0123] S1, obtain the deformation data of the tower.

[0124] S2: Determine at least one problem point of the tower according to the deformation data.

[0125] S3, determining a maintenance budget of at least one problem point according to location parameters of at least one problem point and a pre-established maintenance map, wherein the maintenance map is used to indicate maintenance budgets of problem points with different location parameters.

[0126] S4, determining the maintenance cost of the tower over its entire life cycle based on a maintenance budget of at least one problem point, operation data of the tower, and the life cycle of the tower.

[0127] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store program codes.

[0128] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores the computer program product, and when the computer program is executed by a processor, the steps of the method in each embodiment of the present application are implemented.

[0129] Optionally, in this embodiment, the above computer program may be configured to implement the following steps when executed by a processor:

[0130] S1, obtain the deformation data of the tower.

[0131] S2: Determine at least one problem point of the tower according to the deformation data.

[0132] S3, determining a maintenance budget of at least one problem point according to location parameters of at least one problem point and a pre-established maintenance map, wherein the maintenance map is used to indicate maintenance budgets of problem points with different location parameters.

[0133] S4, determining the maintenance cost of the tower over its entire life cycle based on a maintenance budget of at least one problem point, operation data of the tower, and the life cycle of the tower.

[0134] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0135] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0136] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining the maintenance cost of a tower, characterized in that: The method comprises: Obtaining deformation data of the tower; Determining at least one problem point of the tower according to the deformation data; Determining a maintenance budget for the at least one problem point according to the location parameters of the at least one problem point and a pre-established maintenance map, wherein the maintenance map is used to indicate the maintenance budgets for problem points with different location parameters; The maintenance cost of the tower over its entire life cycle is determined according to the maintenance budget of the at least one problem point, the operation data of the tower, and the life cycle of the tower.

2. The method for determining the tower maintenance cost according to claim 1, characterized in that: The determining the maintenance cost of the tower over its entire life cycle according to the maintenance budget of the at least one problem point, the operation data of the tower, and the life cycle of the tower includes: Determine the life of the tower according to the service time and maintenance record of the tower; Determining the problem conditions of the tower throughout its life cycle according to the life of the tower, the maintenance budget of the at least one problem point, and a pre-established tower life cycle model; The maintenance cost of the tower during its entire life cycle is determined based on the problems in the tower during its entire life cycle and the maintenance map.

3. The method for determining the tower maintenance cost according to claim 2, characterized in that: Before determining the problem conditions of the whole life cycle of the tower according to the life condition of the tower, the maintenance budget of the at least one problem point, and the pre-established tower life cycle model, the method further includes: Acquire historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower, wherein the historical maintenance data includes problem locations, problem time, and maintenance costs; Establishing a sample library according to the historical maintenance data of the tower, the life cycle of the tower, and the geographical environment of the tower; The sample library is used to train a preset neural network model to obtain the tower life cycle model.

4. The method for determining the tower maintenance cost according to claim 1, characterized in that: Before determining the maintenance budget of the at least one problem point according to the location parameters of the at least one problem point and the pre-established maintenance map, the method further includes: Determine a maintenance plan for points of multiple different position parameters of the tower when problems occur; Determine maintenance budgets corresponding to the points with different position parameters of the tower according to maintenance plans when problems occur at the points with different position parameters of the tower; The location parameters, maintenance plans, and maintenance budgets of multiple points are associated and recorded to establish the maintenance map.

5. The method for determining the tower maintenance cost according to claim 1, characterized in that: Determining at least one problem point of the tower according to the deformation data includes: Mapping the deformation data onto the three-dimensional model of the tower; The three-dimensional model of the tower is analyzed to determine the problem points where the deformation degree exceeds a preset range, and based on the three-dimensional model, the position parameters of the problem points are determined.

6. The method for determining the tower maintenance cost according to claim 1, characterized in that: The step of obtaining the deformation data of the tower comprises: Acquire scanning data of different areas of the tower by arranging a plurality of radars within a preset range of the tower, wherein different radars have different scanning areas; Acquiring image data of different areas of the tower by using a drone; Deformation data of the tower is determined based on the scanning data and the image data.

7. A device for determining the maintenance cost of a tower, characterized in that: The device comprises: A data acquisition module, used to acquire the deformation data of the tower; A point determination module, used to determine at least one problematic point of the tower according to the deformation data; A budget determination module, configured to determine a maintenance budget for the at least one problem point according to location parameters of the at least one problem point and a pre-established maintenance map, wherein the maintenance map is configured to indicate maintenance budgets for problem points with different location parameters; The cost determination module is used to determine the maintenance cost of the tower over its entire life cycle based on the maintenance budget of the at least one problem point, the operation data of the tower, and the life cycle of the tower.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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