Method and device for determining installation point of anti-falling device, computer program, computer program product and computer readable storage medium

Abstract

The invention discloses a method and device for determining an installation point of an anti-falling device, a computer program, a computer program product and a computer readable storage medium. The method comprises the following steps: acquiring point cloud data of installation candidate points of an anti-falling device; based on the point cloud data, multiple evaluation indexes of the installation candidate points are evaluated, multiple index evaluation results of the installation candidate points are obtained, and the multiple evaluation indexes at least comprise one of the following indexes: the important component level, the wind load, the weather safety index, the working point selection distance and the working activity range; comprehensively evaluating the plurality of index evaluation results to obtain a comprehensive evaluation result of the installation candidate points; and under the condition that the comprehensive evaluation result meets a preset evaluation condition, determining that the installation candidate point is an installation point of the anti-falling device. According to the invention, the technical problems of low selection efficiency of installation points of anti-falling devices and unreasonable point selection positions in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the field of aerial work safety technology, and in particular to a method, device, computer program, computer program product and computer-readable storage medium for determining an installation point of a fall prevention device. Background Art

[0002] The rapid development of the power industry is inseparable from the process of urbanization. The expansion of the scale of the power grid, especially the construction of UHV and EHV power grids, has put forward higher requirements for the construction and maintenance of transmission towers. The increase in the number of transmission towers and the increase in height have made the workers on the towers face increasing risks of high-altitude operations. In order to ensure the safety of workers on the towers, anti-fall devices have become an indispensable measure and means. The installation point of the anti-fall device refers to the fixed point or node used to install and connect safety equipment (such as safety belts, safety ropes, etc.) in high-altitude operations. The anti-fall device can provide timely and effective protection when the operator loses balance or an accident occurs, preventing the operator from falling from a height. Through the scientific and reasonable installation and use of anti-fall devices, the incidence of high-altitude falling accidents can be significantly reduced, and the life safety of the operators can be guaranteed.

[0003] Nowadays, the selection of installation points for fall protection devices mainly depends on the intuitive judgment and experience accumulation of operators. This selection method has the following problems:

[0004] 1) Lack of unified standards: In actual operations, existing methods rely on the experience of operators, and the choices made by different operators may vary greatly, lacking unified evaluation standards.

[0005] 2) Difficulty in quantification: Existing evaluation indicators are mostly qualitative descriptions. There is a lack of effective quantitative tools and methods, making it difficult to conduct quantitative evaluation, resulting in inaccurate evaluation results.

[0006] 3) Low global screening efficiency: For complex tower structures, manual comprehensive screening of all possible installation points is not only time-consuming and labor-intensive, but also inefficient in meeting the needs of modern power operations and making it difficult to quickly find the optimal installation point.

[0007] Therefore, how to quickly and accurately select the installation point of the anti-fall device in the prior art has become a key issue. Currently, no effective solution has been proposed for the above-mentioned problem. Summary of the invention

[0008] The embodiments of the present invention provide a method, device, computer program, computer program product and computer-readable storage medium for determining the installation point of a fall prevention device, so as to at least solve the technical problems of low efficiency and unreasonable point selection of the installation point of the fall prevention device in the related art.

[0009] According to one aspect of an embodiment of the present invention, a method for determining an installation point of a fall prevention device is provided, the method comprising the following steps: acquiring point cloud data of candidate installation points of the fall prevention device; based on the point cloud data, evaluating multiple evaluation indicators of the candidate installation points to obtain multiple indicator evaluation results of the candidate installation points, the multiple evaluation indicators including at least one of the following: important component level, wind load, weather safety index, work point selection distance, working activity range; comprehensively evaluating the multiple indicator evaluation results to obtain a comprehensive evaluation result of the candidate installation points; and determining the candidate installation point as the installation point of the fall prevention device when the comprehensive evaluation result meets preset evaluation conditions.

[0010] Optionally, a comprehensive evaluation is performed on multiple indicator evaluation results to obtain a comprehensive evaluation result of the installation candidate point, including the following steps: obtaining multiple evaluation weights, and setting the evaluation weights and evaluation indicators in a one-to-one correspondence; based on the evaluation weights and indicator evaluation results, obtaining a comprehensive evaluation result of the installation candidate point.

[0011] Optionally, before obtaining multiple evaluation weights, the method further includes the following steps: using a hierarchical analysis method to obtain relative weights of multiple evaluation indicators; using a comprehensive judgment method to convert the relative weights of multiple evaluation indicators into evaluation weights.

[0012] Optionally, evaluating multiple evaluation indicators of the installation candidate points to obtain multiple indicator evaluation results of the installation candidate points also includes the following steps: using an inverse distance weighted method to evaluate multiple evaluation indicators of the installation candidate points to obtain multiple indicator evaluation results of the installation candidate points.

[0013] Optionally, the inverse distance weighting method is used to evaluate multiple evaluation indicators of the installation candidate point to obtain multiple indicator evaluation results of the installation candidate point, including the following steps: obtaining environmental parameters and spatial coordinate information of the transmission tower, and generating an environmental parameter point cloud based on the environmental parameters and spatial coordinate information, the environmental parameter point cloud including multiple known parameter points, and the environmental parameters at least including temperature parameters, wind parameters, and humidity parameters; constructing a buffer zone centered on the installation candidate point, and screening out the known parameter points in the buffer zone; calculating the distance between the installation candidate point and the known parameter points in each buffer zone, and using the inverse distance weighting method, determining the influence weight of each known parameter point in each buffer zone on the installation candidate point; determining the environmental condition estimation value of the installation candidate point based on the influence weight and the environmental parameter attribute value of the known parameter point; based on the environmental condition estimation value, evaluating multiple evaluation indicators of the installation candidate point to obtain multiple indicator evaluation results of the installation candidate point.

[0014] Optionally, before obtaining the point cloud data of the candidate installation points of the anti-fall device, the method also includes the following steps: collecting point cloud data of the transmission tower; performing voxel grid processing on the point cloud data of the transmission tower to obtain multiple voxels, each voxel containing multiple points; using the voxel intra-point data processing method to process each voxel to obtain a representative point of each voxel; selecting some representative points to form candidate installation points for the anti-fall device.

[0015] According to another aspect of an embodiment of the present invention, there is also provided a device for determining an installation point of an anti-fall device, comprising: an acquisition module, the acquisition module being used to acquire point cloud data of candidate installation points of an anti-fall device; an evaluation module, the evaluation module being used to evaluate multiple evaluation indicators of the candidate installation points based on the point cloud data, and obtain multiple indicator evaluation results of the candidate installation points, wherein the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range; a comprehensive evaluation module, the comprehensive evaluation module being used to comprehensively evaluate multiple indicator evaluation results, and obtain a comprehensive evaluation result of the candidate installation points; and a determination module, the determination module being used to determine that the candidate installation point is the installation point of the anti-fall device when the comprehensive evaluation result meets a preset evaluation condition.

[0016] According to yet another aspect of an embodiment of the present invention, a computer program is provided, which, when executed by a processor, implements the steps of the method for determining the installation point of the anti-fall device.

[0017] According to another aspect of an embodiment of the present invention, there is further provided a computer program product, comprising a computer program, which implements the steps of the above-mentioned method for determining the installation point of the anti-fall device when executed by a processor.

[0018] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, which includes a stored program, wherein when the program is running, the computer-readable storage medium is controlled and the device executes the above-mentioned method for determining the installation point of the anti-fall device.

[0019] In an embodiment of the present invention, point cloud data of candidate installation points of a fall prevention device are obtained; based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, and the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range; the multiple indicator evaluation results are comprehensively evaluated to obtain a comprehensive evaluation result of the candidate installation points; when the comprehensive evaluation result meets the preset evaluation conditions, the candidate installation point is determined to be the installation point of the fall prevention device. Among them, by selecting multiple evaluation indicators such as important component level, wind load, weather safety index, work point selection distance, and work activity range for preliminary evaluation, a comprehensive evaluation of the installation point is achieved. At the same time, by evaluating the installation point based on point cloud data, specific values ​​can be obtained, and the quantitative evaluation of the installation point is achieved, ensuring the accuracy of the evaluation results. By comprehensively evaluating the evaluation results of multiple indicators of the installation point, the evaluation results of multiple indicators can be integrated into a unified comprehensive evaluation result, making the comparison of each installation point more convenient, which is conducive to quickly selecting the installation point that meets the requirements from multiple installation points. Finally, when the comprehensive evaluation result meets the preset evaluation conditions, the installation candidate point is determined to be the installation point of the anti-fall device, that is, a clear preset evaluation condition is established for the selection of the final installation point, making the selection of the installation point more efficient. The technical solution of this embodiment achieves the purpose of quantitatively evaluating the installation point and comprehensively evaluating the installation point by obtaining point cloud data, multi-dimensional indicator evaluation, and comprehensive evaluation, thereby achieving the technical effect of quickly and reasonably determining the installation point of the anti-fall device, and then solving the technical problems of low efficiency and unreasonable point selection of the installation point of the anti-fall device in the related technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0021] Figure 1 is a hardware structure block diagram of a computer terminal according to one embodiment of the present invention;

[0022] Figure 2 is a flow chart of a method for determining an installation point of a fall prevention device according to one optional embodiment of the present invention;

[0023] Figure 3 is a structural block diagram of a device for determining an installation point of a fall prevention device according to one optional embodiment of the present invention;

[0024] Figure 4 is a flow chart of a method for determining an installation point of a fall prevention device according to one optional embodiment of the present invention;

[0025] Figure 5 is a schematic diagram of an evaluation system for a fall protection device installation point according to one of the optional embodiments of the present invention;

[0026] Figure 6 is a schematic diagram of an evaluation index selection system for installation points of a fall prevention device according to one optional embodiment of the present invention;

[0027] Figure 7 is a schematic diagram of evaluating candidate installation points using an inverse distance weighting method according to one optional embodiment of the present invention;

[0028] Figure 8 1 is a schematic diagram of an evaluation process of candidate installation points according to one optional embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention 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 interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] According to one embodiment of the present invention, an embodiment of a method for determining the installation point of a fall protection device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0032] The method embodiment can be executed in a computer terminal or a similar computing device. For example, if the method is executed in a computer terminal, Figure 1As shown, the computer terminal may include one or more processors 102 (the processor may include but is not limited to a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microprocessor (MCU), a field programmable logic device (FPGA), a neural network processor (NPU), a tensor processor (TPU), an artificial intelligence (AI) type processor, etc.) and a memory 104 for storing data. Optionally, the above-mentioned computer terminal may also include a transmission device 106 for communication functions, an input and output device 108, and a display 110. 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. For example, the computer terminal may also include more or fewer components than the above-mentioned structure description, or have a configuration different from the above-mentioned structure description.

[0033] 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 installation point of the anti-fall device in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above-mentioned method for determining the installation point of the anti-fall device is realized. 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 can be connected to the mobile 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 a combination thereof.

[0034] 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 the mobile terminal. In one embodiment, 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.

[0035] The display 110 may be, for example, a touch screen liquid crystal display (LCD). The liquid crystal display may enable a user to interact with a user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), and a user may interact with the GUI by finger contact and / or gestures on a touch-sensitive surface, wherein the human-computer interaction functions here may optionally include the following interactions: creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music, and / or web browsing, etc. The executable instructions for executing the above human-computer interaction functions are configured / stored in a computer program product or a readable storage medium executable by one or more processors.

[0036] This embodiment provides a method for determining the installation point of the anti-fall device running on the above-mentioned computer terminal, Figure 2 is a flow chart of a method for determining an installation point of a fall prevention device according to one embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0037] Step S201, obtaining point cloud data of candidate installation points of the anti-fall device;

[0038] Step S202, based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, where the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range;

[0039] Step S203, comprehensively evaluating the multiple indicator evaluation results to obtain a comprehensive evaluation result of the installation candidate point;

[0040] Step S204: when the comprehensive evaluation result meets the preset evaluation conditions, determine the candidate installation point as the installation point of the anti-fall device.

[0041] Specifically, when the comprehensive evaluation result is a certain value, the preset evaluation condition may be a specific value threshold or value range.

[0042] Through the above steps, the point cloud data of the candidate installation points of the anti-fall device is obtained; based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, and the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity scope; the multiple indicator evaluation results are comprehensively evaluated to obtain the comprehensive evaluation results of the candidate installation points; when the comprehensive evaluation results meet the preset evaluation conditions, the candidate installation point is determined to be the installation point of the anti-fall device. Among them, by selecting multiple evaluation indicators such as important component level, wind load, weather safety index, work point selection distance, and work activity range for preliminary evaluation, a comprehensive evaluation of the installation point is achieved. At the same time, by evaluating the installation point based on point cloud data, specific values ​​can be obtained, and the quantitative evaluation of the installation point is achieved, ensuring the accuracy of the evaluation results. By comprehensively evaluating the evaluation results of multiple indicators of the installation point, the evaluation results of multiple indicators can be integrated into a unified comprehensive evaluation result, making the comparison of each installation point more convenient, which is conducive to quickly selecting the installation point that meets the requirements from multiple installation points. Finally, when the comprehensive evaluation result meets the preset evaluation conditions, the installation candidate point is determined to be the installation point of the anti-fall device, that is, a clear preset evaluation condition is established for the selection of the final installation point, making the selection of the installation point more efficient. The technical solution of this embodiment achieves the purpose of quantitatively evaluating the installation point and comprehensively evaluating the installation point by obtaining point cloud data, multi-dimensional indicator evaluation, and comprehensive evaluation, thereby achieving the technical effect of quickly and reasonably determining the installation point of the anti-fall device, and then solving the technical problems of low efficiency and unreasonable point selection of the installation point of the anti-fall device in the related technology.

[0043] In the technical solution of the embodiment of the present application, through the collection of point cloud data and the evaluation of multiple evaluation indicators such as the level of important components, wind load, weather safety index, work point selection distance, and work activity range, the environmental conditions and structural safety of the installation point can be accurately analyzed to ensure that the installation position of the anti-fall device effectively protects the workers. It is suitable for high-altitude work scenarios such as transmission towers, bridges, and buildings in various complex environments.

[0044] Optionally, in step S203, a comprehensive evaluation is performed on multiple indicator evaluation results to obtain a comprehensive evaluation result of the installation candidate point, including the following execution steps:

[0045] Step S2031, obtaining multiple evaluation weights, and setting the evaluation weights and evaluation indicators in one-to-one correspondence;

[0046] Step S2032: Obtain a comprehensive evaluation result of the candidate installation points based on the evaluation weights and the index evaluation results.

[0047] Through step S2031 and step S2032, by setting the evaluation weight, the influence of different evaluation indicators can be clarified, the influence of key indicators in comprehensive evaluation can be highlighted, the comprehensive evaluation results can be closer to actual needs, and the accuracy of the final evaluation results can be improved. In actual applications, the evaluation weight can be adjusted according to the different heights and structures of the installation points, so that the evaluation results of the installation points are more accurate.

[0048] Optionally, in step S203, before obtaining multiple evaluation weights, the method further includes the following steps:

[0049] Step S20301, using the analytic hierarchy process to obtain relative weights of multiple evaluation indicators;

[0050] Step S20302: using a comprehensive judgment method, convert the relative weights of multiple evaluation indicators into evaluation weights.

[0051] Through step S20301 and step S20302, the combined use of the analytic hierarchy process and the comprehensive judgment method can comprehensively evaluate the safety of candidate installation points from multiple dimensions. While quantifying the importance of evaluation indicators, the weights of multiple evaluation indicators can be adjusted according to specific needs and scenarios to ensure the comprehensiveness and applicability of the evaluation system, overcome the limitations of a single method, provide more objective and fair evaluation weights, and thus improve the accuracy and efficiency of installation point evaluation, making the selection of the final installation point more reasonable and rapid, and suitable for high-altitude working environments that need to comprehensively consider multiple factors, such as transmission towers, wind power towers, communication towers, etc.

[0052] Among them, the Analytic Hierarchy Process (AHP) is a multi-criteria decision analysis method that decomposes complex decision problems into multiple levels, compares the factors at the same level to determine their relative importance relative to the goals at the previous level, and then calculates the weight of each factor. In step S20301, the AHP is first used to construct a judgment matrix, which is used to quantify the relative importance of evaluation indicators. The specific steps are as follows:

[0053] Step S203011, establish a hierarchical model: divide multiple evaluation indicators into different levels, for example, the highest level is the goal, the next level is different evaluation criteria (such as safety, convenience), and the next level is specific evaluation indicators (such as important component level, wind load assessment, etc.).

[0054] Step S203012, construct a judgment matrix: for each level, construct a judgment matrix by comparing two by two. Compare the relative importance of each evaluation indicator, and use a 1-9 scale (or its reciprocal) to quantify this importance. For example, if indicator A is more important than indicator B, it can be assigned a value of 5, and if B is more important than A, it can be assigned a value of 1 / 5.

[0055] Step S203013, calculate weights: that is, by solving the maximum eigenvector of the judgment matrix, the relative weights of each indicator in the same level are obtained.

[0056] Step S203014, consistency check: Use the consistency index CI and consistency ratio CR to check the consistency of the judgment matrix. If CR≤0.1, the judgment matrix is ​​considered to have good consistency, otherwise the judgment matrix needs to be adjusted and the weight calculation is re-performed until the consistency requirements are met.

[0057] Through steps S203011 to S203014, the relative weights of various evaluation indicators can be obtained, and these weights reflect the relative importance of the indicators in the evaluation system.

[0058] Furthermore, after obtaining the relative weights of the evaluation indicators, it is necessary to further convert these relative weights into evaluation weights, i.e., weight values ​​used in the actual evaluation process. The comprehensive judgment method usually combines the relative weights obtained by the hierarchical analysis method and other information (such as expert judgment, empirical data, etc.) to adjust and determine the final evaluation weights. Optionally, step S20302 can be performed using the method in the following embodiment:

[0059] Method implementation example 1, establishing an evaluation factor set and an evaluation set: establishing a primary and secondary factor set, and defining evaluation levels and their values.

[0060] Method implementation example 2 comprehensively considers multiple factors: considers the relative weight obtained by the hierarchical analysis method and possible other factors, such as actual operation requirements, risk preference, etc., to determine the evaluation weight of each indicator.

[0061] Method Example 3, fuzzy comprehensive evaluation: Use fuzzy mathematical methods, such as fuzzy comprehensive judgment, to combine the weights of the hierarchical analysis method with other qualitative or quantitative factors to form the final evaluation weights. Fuzzy comprehensive judgment uses fuzzy set theory to handle the fuzziness and uncertainty between indicators, thereby obtaining a weight value that is closer to the actual situation.

[0062] Method Example 4: Weight adjustment and optimization: According to the actual situation and evaluation results, the weights are adjusted and optimized to achieve more accurate and reasonable results.

[0063] It should be understood that method embodiments 1 to 4 may be used one by one or in any combination.

[0064] Optionally, in step S202, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, and the following steps are also included:

[0065] Step S2021, using the inverse distance weighted method, multiple evaluation indicators of the installation candidate points are evaluated to obtain multiple indicator evaluation results of the installation candidate points.

[0066] Inverse Distance Weighting (IDW) is a geospatial interpolation method that estimates the attribute values ​​of unknown points based on the data of nearby known points. Through step S2021, the multiple evaluation indicators of the candidate installation points are evaluated using the inverse distance weighting method, which can handle the unevenness of spatial distribution, effectively utilize the real-time data and historical data of the surrounding environment, ensure the accuracy and reliability of the evaluation results, and overcome the problems of missing and incomplete data. The method of this embodiment evaluates the impact of environmental parameters on the candidate installation points based on the distance, so that the indicator evaluation results of the candidate installation points are more accurate, which is suitable for scenes where accurate evaluation of environmental impacts is required, such as transmission towers in mountainous areas and by the sea.

[0067] Optionally, in step S2021, using the inverse distance weighted method to evaluate multiple evaluation indicators of the candidate installation points, and obtaining multiple indicator evaluation results of the candidate installation points includes the following steps:

[0068] Step S20211, obtaining environmental parameters and spatial coordinate information of the transmission tower, and generating an environmental parameter point cloud based on the environmental parameters and spatial coordinate information, wherein the environmental parameter point cloud includes a plurality of known parameter points, and the environmental parameters include at least temperature parameters, wind parameters, and humidity parameters;

[0069] Specifically, in step S20211, the transmission tower and its surrounding environment can be scanned and detected by drones or other sensor devices to collect environmental parameter data such as temperature, wind force, humidity, etc. At the same time, drones and other sensor devices also provide their own spatial coordinate information, that is, the precise position in three-dimensional space. Based on the collected environmental parameters and spatial coordinate information, an environmental parameter point cloud can be generated, in which each point not only contains its spatial coordinates, but also has the corresponding environmental parameter value.

[0070] Step S20212, constructing a buffer zone centered on the candidate installation point, and filtering out known parameter points in the buffer zone;

[0071] Specifically, in step S20212, after obtaining the environmental parameter point cloud, for each position as a candidate point for the installation of the fall protection device, a three-dimensional buffer zone centered on the candidate point is constructed. The size and shape of the buffer zone can be adjusted according to actual needs and the accuracy requirements of the evaluation, in order to ensure that the screened known parameter points can have a significant impact on the environmental condition evaluation of the candidate point. By screening the known parameter points in the buffer zone, the amount of calculation can be reduced, the evaluation efficiency can be improved, and the accuracy and reliability of the evaluation results can be ensured.

[0072] Step S20213, calculating the distance between the candidate installation point and the known parameter point in each buffer zone, and using the inverse distance weighting method to determine the influence weight of each known parameter point in each buffer zone on the candidate installation point;

[0073] Specifically, in step S20213, for each known parameter point in the buffer zone, the straight-line distance between it and the candidate installation point is calculated. Then, the influence weight of the known parameter point on the candidate installation point is calculated by applying the inverse distance weight formula. The closer the point is to the candidate installation point, the greater its influence weight is, and the farther the point is, the smaller its influence weight is, thereby quantifying the attenuation degree of the influence of distance on environmental parameters.

[0074] Step S20214, determining an estimated value of the environmental condition of the candidate installation point based on the influence weight and the environmental parameter attribute value of the known parameter point;

[0075] Specifically, in step S20214, the influence weights can be used to perform weighted averaging on the environmental parameter attribute values ​​of the known parameter points in the buffer zone. Through this step, the influence of multiple surrounding known parameter points can be comprehensively considered to obtain an accurate estimate of the environmental conditions near the candidate installation point.

[0076] Step S20215, based on the estimated value of the environmental condition, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points.

[0077] Specifically, in step S20215, during the evaluation, the estimated value of the environmental condition can be compared with the evaluation criteria of each evaluation indicator, and the evaluation score of each installation candidate point under different evaluation indicators can be calculated to obtain multiple indicator evaluation results of the installation candidate point.

[0078] Through steps S20211 to S20215, by constructing a buffer zone and calculating influence weights, the complexity and variability of the environment around the candidate installation points are fully considered, and the inverse distance weighted method is used to effectively extract relevant information from the environment. A comprehensive evaluation is conducted to effectively evaluate the environmental conditions around the candidate installation points, ensuring that the installation points of the anti-fall device can adapt to various weather conditions, making the evaluation process of the candidate installation points more reasonable, and the evaluation results more consistent with the actual environment, thereby selecting anti-fall device installation points that are more in line with actual environmental requirements and improving the safety of operators.

[0079] Optionally, in step S201, before acquiring the point cloud data of the candidate installation points of the anti-fall device, the method further comprises the following steps:

[0080] Step S2011, collecting point cloud data of transmission towers;

[0081] Specifically, in step S2011, the point cloud data of the transmission tower can be collected by the laser radar or other three-dimensional scanning equipment carried by the drone. These devices can perform high-precision scanning of the transmission tower and its surrounding environment to generate a large amount of point cloud data. The point cloud data contains the spatial coordinate information of each point, which can accurately reflect the structural characteristics of the transmission tower and the surrounding terrain and environmental details.

[0082] Step S2012, voxelizing and meshing the point cloud data of the transmission tower to obtain a plurality of voxels, each of which contains a plurality of points;

[0083] Specifically, in step S2012, voxelization grid processing is to divide the point cloud data space into many three-dimensional grids (i.e., voxels), and each voxel may contain several points. This processing method helps to reduce the complexity of the point cloud data while maintaining the continuity and integrity of the spatial data. The selection of voxel size needs to be determined based on the density and required accuracy of the point cloud data to ensure that the number of points in the voxel is sufficient to represent the spatial characteristics of the area.

[0084] Step S2013, processing each voxel using a voxel interior point data processing method to obtain a representative point of each voxel;

[0085] Specifically, in step S2013, the method for processing the point data in the voxel may be averaging or weighted averaging. Specifically, for all points in each voxel, the average value or weighted average value of their spatial coordinates may be calculated to obtain the representative point of the voxel. The selection of the representative point should be able to effectively reflect the distribution characteristics of the points in the voxel, while reducing the amount of calculation and improving the efficiency of subsequent processing steps.

[0086] Step S2014: select some representative points to form candidate installation points for the anti-fall device.

[0087] Specifically, in step S2014, after obtaining the representative point set, a portion of the representative points can be selected as candidate installation points for the anti-fall device by random sampling or a specific screening strategy. The screening strategy can be determined based on factors such as the density of the point cloud data, the size of the voxel, and the distance from the key parts of the transmission tower structure. The selection of the installation candidate points should ensure that they are evenly distributed on the tower and can fully cover all parts of the tower.

[0088] Through step S2011 to step S2014, voxelized grid processing and voxel internal point data processing methods are used to extract useful and representative information from the original point cloud data, effectively reducing the amount of data processing, reducing the dimension and complexity of the data, and improving the data processing efficiency, making the subsequent evaluation and decision-making process more efficient and accurate. The above steps are suitable for processing large-scale point cloud data, for example, they can be applied to the installation point selection process in high-altitude working environments such as urban high-rise buildings and large bridges, effectively improving the efficiency of installation point selection.

[0089] In this embodiment, a device for determining the installation point of a fall prevention device is also provided, and the device is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0090] Figure 3 is a structural block diagram of a device for determining an installation point of a fall prevention device according to one embodiment of the present invention. Figure 3 As shown, the device includes: an acquisition module 30, the acquisition module 30 is used to acquire point cloud data of candidate installation points of the anti-fall device; an evaluation module 32, the evaluation module 32 is used to evaluate multiple evaluation indicators of the candidate installation points based on the point cloud data, and obtain multiple indicator evaluation results of the candidate installation points, and the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range; a comprehensive evaluation module 34, the comprehensive evaluation module 34 is used to comprehensively evaluate multiple indicator evaluation results and obtain a comprehensive evaluation result of the candidate installation points; a determination module 36, the determination module 36 is used to determine that the candidate installation point is the installation point of the anti-fall device when the comprehensive evaluation result meets the preset evaluation conditions.

[0091] Through the above-mentioned device, point cloud data of candidate installation points of the anti-fall device are obtained; based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, and the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity scope; the multiple indicator evaluation results are comprehensively evaluated to obtain a comprehensive evaluation result of the candidate installation point; when the comprehensive evaluation result meets the preset evaluation conditions, the candidate installation point is determined to be the installation point of the anti-fall device. Among them, by selecting multiple evaluation indicators such as important component level, wind load, weather safety index, work point selection distance, and work activity range for preliminary evaluation, a comprehensive evaluation of the installation point is achieved. At the same time, by evaluating the installation point based on point cloud data, specific values ​​can be obtained, and the quantitative evaluation of the installation point is achieved, ensuring the accuracy of the evaluation results. By comprehensively evaluating the evaluation results of multiple indicators of the installation point, the evaluation results of multiple indicators can be integrated into a unified comprehensive evaluation result, making the comparison of each installation point more convenient, which is conducive to quickly selecting the installation point that meets the requirements from multiple installation points. Finally, when the comprehensive evaluation result meets the preset evaluation conditions, the installation candidate point is determined to be the installation point of the anti-fall device, that is, a clear preset evaluation condition is established for the selection of the final installation point, making the selection of the installation point more efficient. The technical solution of this embodiment achieves the purpose of quantitatively evaluating the installation point and comprehensively evaluating the installation point by obtaining point cloud data, multi-dimensional indicator evaluation, and comprehensive evaluation, thereby achieving the technical effect of quickly and reasonably determining the installation point of the anti-fall device, and then solving the technical problems of low efficiency and unreasonable point selection of the installation point of the anti-fall device in the related technology.

[0092] 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 can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, 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, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0093] It should be noted that the above modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0094] Figure 4is a schematic diagram of a method for determining an installation point of a fall prevention device according to one optional embodiment of the present invention. Specifically, the method comprises the following steps:

[0095] S10: Scan the transmission tower to obtain point cloud data, grid the point cloud space, average the point values ​​in the grid to obtain a point, and use it to replace all the points in the original grid to obtain the candidate point for the tower top installation of the fall protection device.

[0096] S20: Based on the existing standards and specifications, starting from the structural characteristics of the transmission tower, high-altitude environmental factors and the need for convenient operation, important components of the transmission tower, wind effects, weather factors, point selection distance and working range are selected as evaluation indicators for the top installation point of the fall protection device.

[0097] S30: Divide the evaluation index levels based on the hierarchical analysis method, determine the evaluation index weights based on the comprehensive judgment method, and construct an index system for evaluating the installation point on the top of the tower of the fall protection device.

[0098] S40: According to the candidate point evaluation system, the inverse distance weighted method is used to calculate the candidate point scores using the collected data and its weights, and the candidate point with the highest score is selected. If the score reaches the threshold, it is determined as the installation point. If the threshold is not reached, the candidate point sampling and iterative calculation is re-performed until a suitable installation point is obtained.

[0099] Specifically, step S10 includes:

[0100] S101: Scan the transmission tower to obtain point cloud data, which can accurately reflect the terrain and environment around the transmission tower.

[0101] S102: Perform voxel grid processing on the point cloud data to divide the point cloud space into multiple voxels, each of which contains a certain number of points.

[0102] S103: In each voxel, the points contained therein are averaged or weighted averaged to obtain a representative point, and all points in the original voxel are replaced by the representative point, thereby reducing the data volume of the point cloud data.

[0103] S104: selecting uniformly distributed candidate points from the point cloud data after voxelized grid processing by random sampling as candidate points for installing the tower top of the fall prevention device.

[0104] Specifically, Figure 6 is a schematic diagram of an evaluation index selection system for installation points of a fall prevention device according to one of the optional embodiments of the present invention, combined with Figure 6 As shown, step S20 includes:

[0105] Based on the existing standards and specifications, the evaluation indicators for the installation point of the top of the anti-fall device are selected from the structural characteristics of the transmission tower, high-altitude environmental factors and the need for convenient operation:

[0106] Among them, the safety evaluation indicators of the tower top installation point of the fall prevention device include: the level of important components of the transmission tower, wind load assessment and weather safety index.

[0107] 1. Level of important components of transmission towers

[0108] The high-altitude mounting point of the transmission tower anti-fall device needs to bear the weight of the anti-fall device. When an accident occurs, it also needs to be able to bear the weight of the operator. Therefore, the selection of the installation point needs to be able to bear a large weight. At the same time, the structure of the transmission tower is complex and there are many components. The cost of testing all components is high, and the stress state of components at different positions has different sensitivities to the overall safety indicators of the tower structure. Reasonable classification and ranking of the importance of the transmission tower components is of great significance to ensure the rationality of the selection of the installation point of the anti-fall device.

[0109] In response to the above problems and needs, the transmission tower structure data obtained by the UAV operation environment monitoring system was used, and a multi-parameter combined discrimination method was used to classify the importance of the transmission tower components. After classification, the importance of the transmission tower components was ranked. The top three structures in the importance ranking were obtained as the evaluation content for the selection of the mounting point of the transmission tower anti-fall device.

[0110] The multi-parameter combined discrimination method for the importance classification of transmission tower components comprehensively considers the influence of beam-column sections on structural performance, the reliability of the structure and the two evaluation indicators of stress mean change rate, and proposes an importance coefficient for calculating the relative importance of nodes in the structure based on the TOPSIS method. The weights of the evaluation indicators are objectively calculated using the entropy weight method, and the component importance coefficient is expressed as:

[0111] λ i =s i

[0112] Among them, λ i represents the component importance coefficient of component i; s i It represents the comprehensive evaluation value of component i in the entropy weight-TOPSIS comprehensive evaluation model. The component importance coefficient is normalized to obtain:

[0113]

[0114] Among them, α is the normalization coefficient, which makes the component importance coefficient λ iThe value range of is between [0,1]. The component importance coefficient uses the entropy weight method to calculate the evaluation index, thereby avoiding the interference of subjective factors on the evaluation index and making the evaluation process more objective. For different structural components, if the structural stability drops significantly after failure and can no longer resist external loads, the safety performance of the overall structure will be greatly affected, and the corresponding component importance coefficient will also be large. Therefore, the component importance coefficient is reasonable. According to the component importance coefficient λ i The criteria for distinguishing important components are as follows: 0.5<λ i ≤1 means extremely important, 0<λ i ≤0.5 indicates important, λ i =0 means not important.

[0115] Calculating the importance coefficient of a component is to calculate the comprehensive evaluation value of the reliability of the remaining structure of the tower and the stress mean change rate after the component fails. The component importance coefficient is obtained after the comprehensive evaluation value is normalized. The steps for constructing a classification framework for important components of transmission towers combining multi-parameter discrimination methods are as follows:

[0116] 1) Establish the finite element model of the transmission tower;

[0117] 2) Then determine the random variables and their statistical parameters in the structure and select a suitable finite element probabilistic design method and sample size to generate structural analysis samples to obtain evaluation indicators;

[0118] 3) Perform positive processing on the evaluation indicators, calculate the standardized matrix, and calculate the entropy weights of the evaluation indicators to obtain the weighted standardized matrix, so as to construct a comprehensive evaluation model and obtain the comprehensive evaluation value;

[0119] 4) Calculate the importance coefficient of the component based on the comprehensive evaluation value;

[0120] 5) Rank and classify the transmission tower components according to their importance.

[0121] 2. Wind load assessment

[0122] In the environment of high-altitude power operations, there are often strong winds, and the wind will have a more obvious effect on the transmission tower and the anti-fall device. In addition, the transmission tower anti-fall device contains flexible materials such as safety belts, which will swing violently under the action of wind, posing a potential threat to the life safety of high-altitude power workers. Therefore, evaluating the wind load of the transmission tower anti-fall device is of great safety significance for evaluating the rationality of the selection of the installation point of the anti-fall device.

[0123] Transmission towers are a type of lattice tower structure. Due to the characteristics of light weight, high flexibility and low damping, lattice towers will produce violent oscillations under strong winds. The mass of lattice towers is lighter than that of general high-rise building structures, so wind loads have a greater impact on lattice towers and are the main lateral loads of lattice high-rise structures. The response analysis data of the transmission tower dynamic response under strong force and the anti-fall device dynamic response under strong force are used as parameter indicators for wind load evaluation. The specific analysis is as follows:

[0124] Analysis of dynamic response of transmission towers under force: The intensity of the pulsating wind in natural wind varies with time and space. It is a zero-mean random process. The characteristics of the pulsating wind field can be described by the pulsating wind power spectrum density. In order to simulate the dynamic response of transmission towers under strong force, it is first necessary to model the pulsating wind such as strong typhoons. According to the wind load calculation requirements stipulated in my country's "Building Structure Load Code", the Davenport wind speed power spectrum is used. This wind spectrum is obtained by Davenport based on strong wind records measured in more than 90 different locations, different heights, and different environments, and then calculated based on statistics. It is currently the most widely used wind speed spectrum. Therefore, this article selects the Davenport spectrum widely used in the wind engineering industry to simulate the actual wind speed spectrum at the location of the transmission tower. Its power spectrum expression is:

[0125]

[0126]

[0127] Among them, n represents frequency in Hz; v10 represents the average wind speed at a height of 10m in m / s; K represents the ground resistance coefficient.

[0128] At present, the main methods for simulating pulsating wind fields include linear filtering, harmonic superposition, inverse Fourier transform, etc. The linear autoregressive filtering method takes into account the temporal and spatial correlations, and has the advantages of small calculation amount and fast calculation speed, so the linear autoregressive filtering method is used to simulate the wind field.

[0129] The principle of the autoregressive model is that the fluctuating wind speed history at time t is a linear combination of the wind speed history values ​​at the past time points, and then combined with the process at time t. It can be expressed by the following equation:

[0130]

[0131] Where Δ(t) represents the time step; N(t) represents a normally distributed random number with a mean of 0 and a variance of 1; represents the autoregressive parameter; p represents the order of the autoregressive model, and p is 4.

[0132] According to the above formula, the power spectrum density curves of different wind speeds in each part of the tower body are calculated and compared with the Davenport spectrum. According to the comparison curve of the pulsating wind power spectrum of the two, it can be clearly seen that the smooth one is the Davenport spectrum, and the ups and downs are the simulation spectrum. The overall trend of the two is consistent, and the fitting degree is very high, which verifies the effectiveness of the simulated wind field. Finally, the wind speed spectrum at wind speeds of 30m / s, 40m / s, and 50m / s is generated. After applying the wind load under strong force to the finite element model, the damage law of the tower head and tower neck under different wind and rain conditions is calculated.

[0133] Dynamic response analysis of fall protection device under stress: Under strong stress conditions of transmission lines, both transmission towers and transmission lines will be subjected to external forces, and there will also be interactions between the two. In order to capture this interaction, it is necessary to conduct a dynamic response analysis of the transmission tower line system.

[0134] First, based on the construction of the mechanical finite model of the transmission tower and the transmission line, the initial configuration of the transmission line is determined based on the catenary control equation, and the displacement response and tension response of the line under strong force are analyzed. The formula is as follows:

[0135]

[0136]

[0137] Among them, L 0 is the length of the catenary of the safety belt of the fall protection device with equal height suspension point; l is the horizontal length of the safety belt of the fall protection device; h is the vertical height difference distance of the safety belt of the fall protection device; γ is the load per unit length of the safety belt; σ 0 is the axial stress at the lowest point of the sag; x is the horizontal distance from the safety belt of the fall protection device to the lowest point of the sag.

[0138] On this basis, the boundary conditions of the wind field are set on the computational domain using the one-way fluid-solid coupling method, and the boundary conditions on the surface of the fall protection device safety belt model are set as non-slip walls. The Octree algorithm is first used to preliminarily divide the computational domain into a mixed unstructured grid of hexahedrons and tetrahedrons, and then the generated grid is optimized using the Delaunay algorithm. At the same time, a prismatic unit expansion layer grid with a thickness of 1.0 cm is set on the surface of the fall protection device safety belt; and a spherical area is established at the center of the fall protection device safety belt, and the grid is encrypted in this area to structure the surface as accurately as possible, thereby generating a dynamic response analysis model of the fall protection device safety belt coupling system.

[0139] 3. Weather safety index

[0140] The safety of high-altitude power operations is greatly affected by weather factors. Sudden changes in weather conditions such as strong winds, thunderstorms, and precipitation will reduce the safety protection of transmission tower anti-fall devices and increase the risk of injuries or accidents to operators during high-altitude operations. In response to the above safety hazards, this project combines weather factors that may affect high-altitude power operations into a weather safety index as a selection indicator.

[0141] The Weather Safety Index is a comprehensive quantitative tool designed to assess the impact of weather conditions at a specific time and location on the safety and feasibility of installing fall protection devices on transmission towers. The index takes into account a variety of key meteorological factors, such as temperature, humidity, wind speed, wind direction, precipitation, and thunderstorm activity. Through real-time monitoring of these factors and historical data analysis, it predicts and assesses the impact and potential meteorological risks that may have on aerial work.

[0142] By simplifying complex meteorological information into an intuitive numerical value or level, the Weather Safety Index provides clear risk assessment and decision-making support for engineering and technical personnel. This index is not only based on historical weather data, but also combines real-time observations to ensure the accuracy and timeliness of the assessment. The Weather Safety Index has a wide range of applications. It not only helps to prevent and mitigate the impact of severe weather on operational activities, but also provides decision makers with a basis for formulating preventive measures to ensure the safety of operators and equipment. In the maintenance of transmission towers, the Weather Safety Index can play an important role in guiding power workers to avoid potential meteorological risks.

[0143] In addition, the weather safety index also shows its value in optimizing resource allocation and utilization. Through accurate assessment of weather conditions, power workers can plan and dispatch resources more efficiently and avoid resource waste and economic losses caused by weather conditions. This index is particularly important during the installation of transmission tower fall protection devices, as it is directly related to the safety and efficiency of the operation and is one of the key factors to ensure the smooth progress of the project.

[0144] In the actual installation of transmission tower fall protection devices, weather conditions are crucial to the safety and feasibility of the operation. UAV field operations also need to pay special attention to the weather. The operation and performance of drones are also affected by weather factors, so it is necessary to measure relevant weather factors to calculate the weather safety index.

[0145] Furthermore, the convenience evaluation indicators of the tower top installation point of the fall protection device include: work point selection distance and working activity range.

[0146] 1. Work point distance

[0147] The working point selection distance refers to the spatial distance between the selected installation point of the anti-fall device and the predetermined position where the workers will work during the installation of the anti-fall device on the transmission tower. This distance is directly related to the effectiveness and reliability of the anti-fall device when the workers fall, and is crucial to ensure the safety of workers when working at height.

[0148] According to the different shapes and structures of transmission towers, selecting reasonable installation points can reduce the risks of workers when moving at high altitudes and improve work efficiency. At the same time, the stress conditions of different installation points are also different. Choosing the right distance helps to ensure that the anti-fall device is balanced and avoid equipment damage or failure due to uneven stress. Therefore, in actual operation, accurate measurement and reasonable selection of the working point distance are crucial.

[0149] In the monitoring of the working environment of the transmission tower, the following factors and data need to be considered when measuring the distance of the work point: Predetermined working position: determine the specific working position movement range of the staff on the transmission tower. Anti-fall device installation point: select the most suitable anti-fall device installation point according to the structure of the transmission tower and the working requirements. Distance measurement: use the obtained point cloud three-dimensional coordinates to measure the straight-line distance from the anti-fall device installation point to the working position; force direction analysis: analyze the force conditions of the anti-fall device in different directions to ensure the stability and safety of the device under standard load.

[0150] By comprehensively considering the above factors and data, power workers can choose fall protection device installation points with higher convenience indexes, ensuring that the work point selection distance meets safety requirements and improves work efficiency.

[0151] 2. Scope of operation activities

[0152] The steel frame of the transmission tower covers the main structure in a grid shape, supporting the important power conductor mounting arm. The distribution of the components is crisscrossed, and various components are woven into a complex mesh structure. When users work at height, their movements will be restricted to a certain extent, affecting the convenience of the work activities. In order to improve the convenience of the work and more effectively implement the safety of the anti-fall device, the scope of the work activities is included in the evaluation index system as an important evaluation indicator of convenience.

[0153] Provides calculation of the scope of work activities, and guarantees the working space of the user's work point with specific calculation data indicators. The anti-fall device is located in the area above the work point, and will specify the best and effectively guaranteed working range below, providing users with prompts for safe working areas, and facilitating users to select the installation point of the anti-fall device, so that when the work point moves within a small range, the anti-fall device is always in a safe working state. The scope of work activities calculates the distribution of components within the scope of the user's work point, and can provide users with highlighted display. Through the information of three-dimensional spatial distribution, it calculates the component size of the work point and the maximum activity range where the user's activities are restricted, further providing users with safety and stability guarantees for high-altitude work activities.

[0154] Furthermore, in step S30, the step of using the hierarchical analysis method to divide the evaluation index levels includes:

[0155] S301: Determine the relative importance of each factor in each level to the factors in the previous level, and construct a judgment matrix.

[0156] Specifically, the hierarchical analysis method determines the relative importance of each factor in each level to the factors in the previous level, and expresses this judgment with an appropriate scale to form a judgment matrix. Taking n elements as an example, the pairwise judgment matrix c = (c i j ) n×n . Among them: 1) c ij >0; 2)c ij =1 / c ji (i≠j); 3)c ii =1(i,j=1,2,…,n),c ij The value of is based on the comparison of the importance of i and j, ranging from 1 for equal importance to 1 / 9 for extremely unimportant, where slightly, obviously, strongly and extremely important correspond to values ​​of 3, 5, 7, and 9 respectively, while slightly, obviously, strongly and extremely unimportant correspond to values ​​of 1 / 3, 1 / 5, 1 / 7, and 1 / 9 respectively.

[0157] S302: Perform hierarchical single sorting and consistency check on the indicators to check whether the judgment matrix meets the consistency requirements. If not, modify the original judgment matrix to finally obtain a satisfactory judgment matrix.

[0158] Specifically, the main task of performing hierarchical single sorting operations is to obtain the maximum eigenvalue (λmax) and eigenvector of the judgment matrix. Based on the determined judgment matrix, the characteristic roots are obtained and consistency checks are performed.

[0159] The consistency test generally uses the consistency index CI. The smaller the CI, the better the consistency; the larger the CI, the worse the consistency. Considering the influence of randomness, the consistency ratio CR should also be considered.

[0160]

[0161]

[0162] Among them, the RI value is related to the judgment matrix order n:

[0163] n={1,2,3,4,5,6,7,8,9}, RI={0,0,0.58,0.9,1.12,1.24,1.32,1.41,1.45}.

[0164] When CR≤0.1, it indicates that the consistency of the judgment matrix meets the requirements; when CR>0.1, the original judgment matrix needs to be modified and then tested to finally obtain a satisfactory judgment matrix.

[0165] Furthermore, in step S30, the step of using a comprehensive judgment method to determine the weight of the evaluation index includes:

[0166] S303: Establish an evaluation factor set, and determine a primary factor set and a secondary factor set under the primary factor set.

[0167] In the specific implementation, the evaluation factor set constructed is as follows:

[0168] 1) First-level factor set: U = {u 1 ,u 2}={safety index, convenience index}.

[0169] 2) Secondary factor set:

[0170] u 1 = {u 11 ,u 12 ,u 13}={level of important components of transmission tower, wind load assessment, weather safety index};

[0171] u 2 = {u 21 ,u 22 ,u 23}={work point selection distance, work activity range}.

[0172] S304: Establish an evaluation set, divide the evaluation level into four levels: excellent, qualified, unqualified, and dangerous according to the analysis of the transmission tower foundation safety evaluation index and expert opinions, and assign values ​​according to the transmission tower foundation safety evaluation level assessment standard.

[0173] S305: construct a judgment matrix of various indicators of the transmission line tower foundation according to the hierarchical analysis method, and calculate and obtain the weight of the first-level indicator.

[0174] S306: Determine whether the weights at each level pass the consistency test. If they pass the test, they are determined as indicator weights.

[0175] Figure 7 is a schematic diagram of evaluating candidate installation points using an inverse distance weighting method according to one optional embodiment of the present invention. Specifically, Figure 7 As shown, in step S40, the step of extracting candidate point evaluation features based on the inverse distance weighted method includes:

[0176] S401: using the environmental detection parameters (such as temperature, wind force, humidity, etc.) collected by the drone near the measurement tower as input, combined with the drone's own positioning information, to obtain three-dimensional known parameter points;

[0177] S402: importing the candidate points obtained by random sampling, taking the positions of the candidate points as the sphere center, selecting the known points in the three-dimensional buffer within a certain range for calculation, and removing the remaining points as weakly influential points;

[0178] S403: Calculate the straight-line distance between the candidate point and the known parameter point after screening, and use the inverse distance weighted formula to obtain the influence weight of each known point on a candidate point;

[0179] Specifically, the inverse distance weighting method is used to calculate the candidate point evaluation index value. The inverse distance weighting method is a spatial weighted average algorithm. The idea of ​​this method is that things that are closer to each other are more similar than things that are farther away from each other. When predicting an unknown point with missing parameters, the inverse distance weighting method uses the known parameter values ​​around the point. Compared with the measured values ​​farther away from the predicted position, the unknown point will be closer to the known values ​​closer to its position. The inverse distance weighting method assumes that each known point has a local influence, and this influence decreases with the increase of distance. The influence of distance is quantified by weight. The basic formula is:

[0180]

[0181] Furthermore, by assigning weights to known points, we can get the estimated values ​​of unknown points:

[0182]

[0183] In the formula, x is the target point, f i is the value corresponding to the target point, w i (x) is the weight between the target point and point i, p is the distance attenuation coefficient, usually 2, d i is the Euclidean distance from the known point to the target point.

[0184] S404: Perform weighted averaging on known parameters to obtain estimated values ​​of evaluation parameters (such as temperature, wind speed, humidity, etc.) of the candidate point.

[0185] Figure 8 is a schematic diagram of an evaluation process of a candidate installation point according to one optional embodiment of the present invention. Specifically, Figure 8 As shown, in step S40, the steps of intelligently evaluating the installation point based on the tower top candidate point evaluation system of the anti-fall device include:

[0186] S405: A batch of candidate installation points are obtained by random sampling of the point cloud, and scores of the candidate points are calculated using the collected data and their corresponding weights according to the established candidate point evaluation system.

[0187] S406: Select the candidate point with the highest score. If the score of the candidate point with the highest score is still lower than the threshold, consider re-sampling the candidate points and iteratively calculate them until a suitable installation point is obtained.

[0188] Figure 5 is a schematic diagram of an evaluation system for installation points of a fall protection device according to one optional embodiment of the present invention. The evaluation system can be used to implement specific steps in the above method embodiment, specifically, Figure 5 As shown, the evaluation system includes a candidate point extraction module 10, an evaluation index selection module 20, an index system construction module 30 and a candidate point evaluation and determination module 40. The functions of each module are described as follows:

[0189] A candidate point extraction module 10 is used to extract candidate points for installing the anti-fall device on the top of the tower from the point cloud data of the transmission tower;

[0190] Evaluation index selection module 20 is used to screen out key factors that affect the selection of installation points for fall protection devices. Key indicators include the location of important components of transmission towers, the degree of wind influence, weather conditions, distance to operation points, and scope of operation activities;

[0191] The indicator system construction module 30 is used to divide the selected evaluation indicators into levels by using the hierarchical analysis method, and clarify the logical relationship and importance level between the indicators. At the same time, a comprehensive judgment method is combined to give each indicator a reasonable weight, so as to construct a comprehensive, objective and operational evaluation indicator system for the tower top installation point of the fall protection device;

[0192] The candidate point evaluation and determination module 40 is used to comprehensively score the candidate points by using the established evaluation index system and the inverse distance weighting method, and then select the installation point that meets the requirements and has the best comprehensive evaluation.

[0193] An embodiment of the present invention further provides a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for determining the installation point of the anti-fall device.

[0194] Optionally, in this embodiment, when the computer program is executed by a processor, the following steps are implemented:

[0195] Step S1, obtaining point cloud data of candidate installation points of the anti-fall device;

[0196] Step S2, based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, wherein the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range;

[0197] Step S3, comprehensively evaluating the evaluation results of multiple indicators to obtain a comprehensive evaluation result of the candidate installation points;

[0198] Step S4: when the comprehensive evaluation result meets the preset evaluation conditions, determine the candidate installation point as the installation point of the anti-fall device.

[0199] An embodiment of the present invention further provides a computer program product, including a computer program, which implements the steps of the above-mentioned method for determining the installation point of the fall prevention device when executed by a processor.

[0200] Optionally, in this embodiment, the computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0201] Step S1, obtaining point cloud data of candidate installation points of the anti-fall device;

[0202] Step S2, based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, wherein the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range;

[0203] Step S3, comprehensively evaluating the evaluation results of multiple indicators to obtain a comprehensive evaluation result of the candidate installation points;

[0204] Step S4: when the comprehensive evaluation result meets the preset evaluation conditions, determine the candidate installation point as the installation point of the anti-fall device.

[0205] An embodiment of the present invention further provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the computer-readable storage medium is controlled and the device where it is located executes the above-mentioned method for determining the installation point of the anti-fall device.

[0206] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0207] Step S1, obtaining point cloud data of candidate installation points of the anti-fall device;

[0208] Step S2, based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, wherein the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range;

[0209] Step S3, comprehensively evaluating the evaluation results of multiple indicators to obtain a comprehensive evaluation result of the candidate installation points;

[0210] Step S4: when the comprehensive evaluation result meets the preset evaluation conditions, determine the candidate installation point as the installation point of the anti-fall device.

[0211] 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 computer programs.

[0212] An embodiment of the present invention further provides a processor, which is configured to run a computer program to execute the steps in any of the above method embodiments.

[0213] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0214] Step S1, obtaining point cloud data of candidate installation points of the anti-fall device;

[0215] Step S2, based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, wherein the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range;

[0216] Step S3, comprehensively evaluating the evaluation results of multiple indicators to obtain a comprehensive evaluation result of the candidate installation points;

[0217] Step S4: when the comprehensive evaluation result meets the preset evaluation conditions, determine the candidate installation point as the installation point of the anti-fall device.

[0218] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0219] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, 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 units or modules, which can be electrical or other forms.

[0220] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0221] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0222] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0223] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining the installation point of a fall prevention device, characterized in that: The method comprises the following steps: Acquire point cloud data of candidate installation points of the fall prevention device; Based on the point cloud data, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, wherein the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range; Comprehensively evaluating the multiple indicator evaluation results to obtain a comprehensive evaluation result of the installation candidate point; When the comprehensive evaluation result meets the preset evaluation conditions, the candidate installation point is determined as the installation point of the anti-fall device.

2. The method according to claim 1, characterized in that Comprehensively evaluating the multiple indicator evaluation results to obtain the comprehensive evaluation results of the installation candidate points includes the following steps: Acquire multiple evaluation weights, wherein the evaluation weights are set in one-to-one correspondence with the evaluation indicators; Based on the evaluation weight and the index evaluation result, a comprehensive evaluation result of the candidate installation point is obtained.

3. The method according to claim 2, characterized in that Before obtaining the multiple evaluation weights, the method further includes the following steps: Using the analytic hierarchy process, the relative weights of the plurality of evaluation indicators are obtained; The relative weights of the plurality of evaluation indicators are converted into the evaluation weights by using a comprehensive judgment method.

4. The method according to claim 1, characterized in that: Evaluating multiple evaluation indicators of the candidate installation points to obtain multiple indicator evaluation results of the candidate installation points also includes the following steps: The multiple evaluation indicators of the candidate installation points are evaluated by using an inverse distance weighting method to obtain multiple indicator evaluation results of the candidate installation points.

5. The method according to claim 4, characterized in that Using the inverse distance weighted method, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points, including the following steps: Acquire environmental parameters and spatial coordinate information of the transmission tower, and generate an environmental parameter point cloud based on the environmental parameters and the spatial coordinate information, wherein the environmental parameter point cloud includes a plurality of known parameter points, and the environmental parameters include at least a temperature parameter, a wind force parameter, and a humidity parameter; Constructing a buffer zone centered on the candidate installation point, and filtering out the known parameter points in the buffer zone; Calculating the distance between the candidate installation point and the known parameter point in each buffer zone, and determining the influence weight of each known parameter point in each buffer zone on the candidate installation point by using the inverse distance weighting method; Determining an estimated value of the environmental condition of the candidate installation point based on the influence weight and the environmental parameter attribute value of the known parameter point; Based on the estimated value of the environmental condition, multiple evaluation indicators of the candidate installation points are evaluated to obtain multiple indicator evaluation results of the candidate installation points.

6. The method according to claim 1, characterized in that Before obtaining the point cloud data of the candidate installation points of the anti-fall device, the method further includes the following steps: Collect point cloud data of transmission towers; Performing voxel grid processing on the point cloud data of the transmission tower to obtain a plurality of voxels, each of which contains a plurality of points; Processing each voxel using a voxel interior point data processing method to obtain a representative point of each voxel; Some of the representative points are selected to form candidate installation points for the anti-fall device.

7. A device for determining the installation point of a fall prevention device, characterized in that: include: An acquisition module, the acquisition module is used to acquire point cloud data of candidate installation points of the anti-fall device; An evaluation module, wherein the evaluation module is used to evaluate multiple evaluation indicators of the candidate installation points based on the point cloud data to obtain multiple indicator evaluation results of the candidate installation points, wherein the multiple evaluation indicators include at least one of the following: important component level, wind load, weather safety index, work point selection distance, and work activity range; A comprehensive evaluation module, wherein the comprehensive evaluation module is used to comprehensively evaluate the multiple indicator evaluation results to obtain a comprehensive evaluation result of the installation candidate point; A determination module is used to determine that the candidate installation point is the installation point of the anti-fall device when the comprehensive evaluation result meets the preset evaluation conditions.

8. A computer program, characterized in that When the computer program is executed by a processor, the steps of the method for determining the installation point of the fall protection device according to any one of claims 1 to 6 are implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for determining the installation point of the fall protection device according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the computer-readable storage medium is controlled, and the device in which the program is located executes the method for determining the installation point of the anti-fall device according to any one of claims 1 to 6.

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