Tower attitude detection method and device, computer equipment, storage medium and product

Abstract

The invention relates to a tower attitude detection method and device, computer equipment, a storage medium and a product, and relates to the technical field of electric power. The method comprises the following steps: in response to a posture detection instruction for a to-be-detected tower, obtaining respective running states of multiple pieces of posture detection equipment mounted on the to-be-detected tower; when it is determined that offline equipment exists in the multiple pieces of attitude detection equipment based on the operation states, first equipment coordinates of online equipment in the multiple pieces of attitude detection equipment and the position relation between the online equipment and the offline equipment before the equipment is offline are obtained; determining a second device coordinate of the offline device based on the first device coordinate and the position relationship between the devices; and according to the first equipment coordinate and the second equipment coordinate, carrying out attitude detection on the to-be-detected tower to obtain an attitude detection result of the to-be-detected tower. By adopting the method, the tower attitude detection accuracy can be ensured.

Description

Technical Field

[0001] This application relates to the field of power technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for detecting the attitude of power poles. Background Technology

[0002] Transmission towers are rigid structural facilities used to support overhead transmission line conductors and lightning protection wires. Currently, in order to ensure the safety of transmission towers, attitude detection of transmission towers is one of the necessary means.

[0003] In traditional technology, tower attitude detection is usually performed manually. However, this method, which relies on human subjective awareness, is prone to detection errors, thus failing to guarantee the accuracy of tower attitude detection. Summary of the Invention

[0004] Therefore, it is necessary to provide a tower attitude detection method, device, computer equipment, computer-readable storage medium, and computer program product that can ensure the accuracy of tower attitude detection, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for detecting the attitude of a tower, including:

[0006] In response to the attitude detection command for the tower to be tested, the operating status of each of the multiple attitude detection devices installed on the tower to be tested is obtained;

[0007] When it is determined that there is an offline device among multiple attitude detection devices based on each operating state, the first device coordinates of the online device among the multiple attitude detection devices, as well as the device positional relationship between the online device and the offline device before the device went offline are obtained.

[0008] Based on the first device coordinates and the positional relationship between devices, determine the second device coordinates of the offline device;

[0009] Based on the coordinates of the first and second devices, the attitude of the tower to be tested is detected, and the attitude detection result of the tower to be tested is obtained.

[0010] In one embodiment, the attitude detection result includes the settlement detection result of the tower to be detected; based on the first equipment coordinates and the second equipment coordinates, the attitude of the tower to be detected is detected to obtain the attitude detection result of the tower to be detected, including:

[0011] Detect the average value of the device coordinates between the coordinates of the first device and the coordinates of the second device;

[0012] Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device;

[0013] Detect the average value of the initial coordinates between the first and second initial coordinates;

[0014] Based on the difference between the average value of the equipment coordinates and the average value of the initial coordinates, the settlement of the tower to be tested is detected, and the settlement test results of the tower to be tested are obtained.

[0015] In one embodiment, the attitude detection result includes the tilt angle detection result of the tower to be detected; based on the first device coordinates and the second device coordinates, the attitude of the tower to be detected is detected to obtain the attitude detection result of the tower to be detected, including:

[0016] Based on the first device coordinate vector corresponding to the first device coordinate and the second device coordinate vector corresponding to the second device coordinate, determine the target normal vector perpendicular to the tower to be inspected.

[0017] Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device;

[0018] Based on the first initial coordinate vector corresponding to the first initial coordinate and the second initial coordinate vector corresponding to the second initial coordinate, determine the initial normal vector perpendicular to the tower to be detected;

[0019] Based on the angle between the initial normal vector and the target normal vector, the tilt angle of the tower to be tested is detected, and the tilt angle detection result of the tower to be tested is obtained.

[0020] In one embodiment, the attitude detection result includes the spacing detection result corresponding to the tower to be detected; based on the first device coordinates and the second device coordinates, the attitude of the tower to be detected is detected to obtain the attitude detection result of the tower to be detected, including:

[0021] Based on the coordinates of the first and second equipment, determine the first center coordinates of the tower to be inspected;

[0022] Obtain the second center coordinates of the adjacent towers of the tower to be detected;

[0023] Based on the first and second center coordinates, the distance between the tower to be tested and its adjacent towers is detected, and the distance detection result corresponding to the tower to be tested is obtained.

[0024] In one embodiment, the tower attitude detection method further includes:

[0025] Obtain the pre-offline coordinate vector between online and offline devices, where the pre-offline coordinate vector represents the positional relationship between online and offline devices before the devices go offline;

[0026] Based on the first device coordinates and the positional relationship between devices, the second device coordinates of the offline device are detected, including:

[0027] Add the first device coordinate vector corresponding to the first device coordinate to the coordinate vector before offline to obtain the second device coordinate of the offline device.

[0028] In one embodiment, the online device includes multiple sub-online devices, the first device coordinates include the sub-device coordinates corresponding to each sub-online device, and the first device coordinate vector includes the sub-device coordinate vector corresponding to each sub-device coordinate.

[0029] The first device coordinate vector corresponding to the first device coordinate is added to the coordinate vector before offline operation to obtain the second device coordinate of the offline device, including:

[0030] Add the sub-device coordinate vector corresponding to each sub-device coordinate to the coordinate vector before offline operation to obtain multiple summed coordinate vectors;

[0031] The second device coordinates of the offline device are determined based on multiple summed coordinate vectors.

[0032] Secondly, this application also provides a tower attitude detection device, comprising:

[0033] The device status acquisition module is used to respond to the attitude detection command for the tower to be tested and acquire the operating status of each of the multiple attitude detection devices installed on the tower to be tested.

[0034] The online device coordinate acquisition module is used to acquire the first device coordinates of the online device among the multiple attitude detection devices, as well as the positional relationship between the online device and the offline device before the device went offline, when it is determined from the various operating states that there is an offline device among the multiple attitude detection devices.

[0035] The offline device coordinate determination module is used to determine the second device coordinates of the offline device based on the first device coordinates and the positional relationship between devices;

[0036] The tower attitude detection module is used to perform attitude detection on the tower to be detected based on the first device coordinates and the second device coordinates, and obtain the attitude detection result of the tower to be detected.

[0037] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0038] In response to the attitude detection command for the tower to be tested, the operating status of each of the multiple attitude detection devices installed on the tower to be tested is obtained;

[0039] When it is determined that there is an offline device among multiple attitude detection devices based on each operating state, the first device coordinates of the online device among the multiple attitude detection devices, as well as the device positional relationship between the online device and the offline device before the device went offline are obtained.

[0040] Based on the first device coordinates and the positional relationship between devices, determine the second device coordinates of the offline device;

[0041] Based on the coordinates of the first and second devices, the attitude of the tower to be tested is detected, and the attitude detection result of the tower to be tested is obtained.

[0042] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0043] In response to the attitude detection command for the tower to be tested, the operating status of each of the multiple attitude detection devices installed on the tower to be tested is obtained;

[0044] When it is determined that there is an offline device among multiple attitude detection devices based on each operating state, the first device coordinates of the online device among the multiple attitude detection devices, as well as the device positional relationship between the online device and the offline device before the device went offline are obtained.

[0045] Based on the first device coordinates and the positional relationship between devices, determine the second device coordinates of the offline device;

[0046] Based on the coordinates of the first and second devices, the attitude of the tower to be tested is detected, and the attitude detection result of the tower to be tested is obtained.

[0047] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0048] In response to the attitude detection command for the tower to be tested, the operating status of each of the multiple attitude detection devices installed on the tower to be tested is obtained;

[0049] When it is determined that there is an offline device among multiple attitude detection devices based on each operating state, the first device coordinates of the online device among the multiple attitude detection devices, as well as the device positional relationship between the online device and the offline device before the device went offline are obtained.

[0050] Based on the first device coordinates and the positional relationship between devices, determine the second device coordinates of the offline device;

[0051] Based on the coordinates of the first and second devices, the attitude of the tower to be tested is detected, and the attitude detection result of the tower to be tested is obtained.

[0052] The aforementioned pole attitude detection method, apparatus, computer equipment, computer-readable storage medium, and computer program product, in response to an attitude detection command for a pole to be detected, first acquire the operating status of multiple attitude detection devices installed on the pole. When it is determined based on the operating status that there are offline devices among the multiple attitude detection devices, the first device coordinates of the online devices and the positional relationship between the online and offline devices before they went offline are acquired. Next, based on the first device coordinates and the positional relationship between the devices, the second device coordinates of the offline devices are determined. Finally, based on the first and second device coordinates, the attitude of the pole to be detected is performed to obtain the attitude detection result of the pole. Thus, this solution, on the one hand, uses multiple attitude detection devices installed on the tower to be tested to replace manual inspection, overcoming the detection errors caused by human subjectivity, thereby effectively improving the efficiency and accuracy of tower attitude detection. On the other hand, this solution also considers offline scenarios for attitude detection devices. In this scenario, this solution uses the coordinates of the online device and the relative positional relationship between the online and offline devices before the devices go offline to deduce the coordinates of the offline device. Combining the coordinates of the online and offline devices, the attitude of the tower is detected, further ensuring the accuracy of tower attitude detection in different scenarios. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is an application environment diagram of the tower attitude detection method in one embodiment;

[0055] Figure 2 This is a flowchart illustrating a tower attitude detection method in one embodiment;

[0056] Figure 3 This is a schematic diagram of the tower settlement detection process in one embodiment;

[0057] Figure 4 This is a schematic diagram of the tower tilt angle detection process in one embodiment;

[0058] Figure 5 This is a schematic diagram of the tower spacing detection process in one embodiment;

[0059] Figure 6 This is a schematic diagram of a pole in a specific embodiment;

[0060] Figure 7 This is a schematic diagram of the framework for tower attitude detection in a specific embodiment;

[0061] Figure 8 This is a structural block diagram of a tower attitude detection device in one embodiment;

[0062] Figure 9 This is an internal structural diagram of a computer device in one embodiment;

[0063] Figure 10 This is a diagram of the internal structure of a computer device in another embodiment. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0065] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0066] The tower attitude detection method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located on the cloud or other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart TVs, smart in-vehicle devices, projection devices, etc., and portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0067] In one exemplary embodiment, such as Figure 2 As shown, a tower attitude detection method is provided. This embodiment applies this method to... Figure 1 Taking server 104 as an example, it can be understood that this method can also be applied to... Figure 1 The terminal 102 in the example can also be applied to a system including terminal 102 and server 104, and is implemented through the interaction between terminal 102 and server 104. In this embodiment, the method includes the following steps:

[0068] Step S202: In response to the attitude detection command for the tower to be tested, the operating status of each of the multiple attitude detection devices installed on the tower to be tested is obtained.

[0069] In this context, "tower under test" refers to the tower that requires attitude detection; there can be one or more towers under test. The attitude detection command is used to instruct the tower under test to perform attitude detection. This command can be automatically triggered by a timer, such as triggering it at regular intervals, or it can be manually triggered by clicking on the front-end interface. The specific command triggering method can be set according to the actual situation, and this embodiment does not impose any restrictions on it. The attitude detection device is used to perform tower attitude detection. For each tower, attitude detection devices can be pre-installed at different locations. The operating status refers to the communication status of the attitude detection device, mainly including online and offline status. Online status means the device is powered normally and maintains communication with the server, while offline status means the device cannot maintain communication with the server due to faults, power outages, or signal problems.

[0070] Preferably, the attitude detection device is a BeiDou GNSS (Global Navigation Satellite System) monitoring device. Through specific data processing technologies such as differential positioning, the BeiDou GNSS monitoring device can continuously measure and output the three-dimensional coordinates of its own location with high accuracy. Multiple BeiDou GNSS monitoring devices together form a monitoring network. By analyzing the changes in the coordinates of each device in the network, the server can infer the attitude changes of the tower.

[0071] For example, after receiving an attitude detection command for the tower to be tested, the server can send a status query command to multiple attitude detection devices pre-installed on the tower via a wireless network, and mark the devices that respond within a specified time, such as 1 second or 2 seconds, as online devices, while marking the devices that do not respond within the time limit as offline devices.

[0072] In some embodiments, the attitude detection command may carry specific parameters, such as at least one of the following: the tower number of the tower to be detected, the tower attitude detection requirement, the detection time, and the detection efficiency. The tower attitude detection requirement may include at least one of tower settlement detection, tower tilt angle detection, and tower spacing detection. Of course, other detection requirements can be configured according to actual conditions, and this embodiment does not impose any limitations on this. After receiving the attitude detection command, the server can first extract the tower attitude detection requirement and determine whether the requirement needs to rely on multiple attitude detection devices on the tower to be detected. If so, the server queries the device operating status; if not, it executes the corresponding independent processing flow.

[0073] Step S204: When it is determined that there is an offline device among the multiple attitude detection devices based on each operating state, the first device coordinates of the online device among the multiple attitude detection devices, and the device positional relationship between the online device and the offline device before the device went offline are obtained.

[0074] In this context, "offline device" refers to an attitude detection device operating in an offline state, while "online device" refers to an attitude detection device operating in an online state. In this embodiment, there can be multiple offline and online devices. The first device coordinates are the position coordinates of the online device, that is, the three-dimensional spatial coordinates of the online device obtained by the BeiDou GNSS system at the current moment. The inter-device positional relationship refers to the relative positional relationship between the online and offline devices before the devices went offline. In this embodiment, the inter-device positional relationship is essentially a three-dimensional spatial vector, which reflects the fixed orientation and distance of the offline device relative to the online device in space.

[0075] For example, when each operating state indicates the presence of at least one offline device, the server first obtains the device identifier of the offline device. Since the server continuously calculates and pre-stores three-dimensional spatial vectors reflecting the relative positional relationships between devices, it can query the three-dimensional spatial vectors of the offline device and any online device that were pre-stored before the device went offline, based on the device identifier. Simultaneously, it obtains the real-time device coordinates of the online devices. It is understandable that the attitude detection devices are fixedly installed on the same tower. Because the tower is a rigid structure, the relative positions between the devices are fixed, ensuring that the vector relationships calculated before going offline remain valid for coordinate deduction at the current moment.

[0076] In some embodiments, the server may periodically update the relative positional relationships between devices to eliminate minor errors caused by long-term, slow structural deformation.

[0077] Step S206: Determine the second device coordinates of the offline device based on the first device coordinates and the positional relationship between devices.

[0078] The second device coordinates are the location coordinates of the offline device.

[0079] For example, after the server obtains the positional relationship between online and offline devices before the device goes offline, it can add the coordinate vectors based on the three-dimensional spatial vector corresponding to the positional relationship between the devices and the coordinates of the first device to obtain the coordinates of the offline device, i.e., the coordinates of the second device.

[0080] In some embodiments, the server can also reconstruct a local coordinate system based on the first device coordinates of the online devices, transform the pre-stored coordinates of the offline devices in the local coordinate system to the global coordinate system, thereby determining the second device coordinates of the offline devices. Specifically, taking the first device coordinates of any online device as the origin, the horizontal projection direction from the origin to another online device as the X-axis, and the normal direction of the tower base plane as the Z-axis, a Y-axis perpendicular to both the X-axis and Z-axis is determined, thus establishing a local three-dimensional coordinate system. The server records the coordinates of the offline devices in this local coordinate system before they go offline. When a device goes offline, based on the current global coordinates of the online devices (which serve as the origin) and the current global coordinates of the online devices used to define the X-axis, the rotation and translation parameters of this local coordinate system relative to the global coordinate system can be deduced. Finally, by applying these transformation parameters to the coordinates of the offline devices in the local coordinate system, their current coordinates in the global coordinate system, i.e., the second device coordinates, can be obtained.

[0081] In some embodiments, data fusion algorithms such as Kalman filters can also be introduced, which are suitable for scenarios where offline devices intermittently come back online and send back brief real coordinates. In this scenario, the coordinates of the offline devices calculated based on the positional relationship between devices can be used as predicted values, and the BeiDou coordinates sent back when the offline devices come back online can be used as observed values. By weighting and fusing the two through Kalman gain, a smoother optimal estimated coordinate can be obtained.

[0082] Step S208: Based on the first device coordinates and the second device coordinates, perform attitude detection on the tower to be tested to obtain the attitude detection result of the tower to be tested.

[0083] The attitude detection results refer to the relevant results generated by the tower under test during the attitude detection process, which may include, but are not limited to, at least one of the following: settlement detection results, tilt angle detection results, spacing detection results, detection time, and detection efficiency.

[0084] For example, after retrieving the coordinates of the offline devices, the server now knows the coordinates of all attitude detection devices. Based on these coordinates, it can perform attitude detection on the tower to be inspected, such as settlement detection, tilt angle detection, or spacing detection, and obtain the corresponding attitude detection results. The final attitude detection results can be further summarized into a tower attitude detection report for management personnel to analyze and make decisions.

[0085] In some embodiments, the attitude detection results obtained in this embodiment can be fused with data from tiltmeters, stress sensors, and other sources on the tower. By mutually verifying and supplementing the data from multiple sources, a more comprehensive and accurate assessment of the tower's attitude can be formed.

[0086] In this embodiment, in response to an attitude detection command for the tower to be tested, the operating status of multiple attitude detection devices installed on the tower is first acquired. When it is determined based on the operating status that there are offline devices among the multiple attitude detection devices, the first device coordinates of the online devices and the positional relationship between the online and offline devices before they went offline are acquired. Next, based on the first device coordinates and the positional relationship between the devices, the second device coordinates of the offline devices are determined. Finally, based on the first and second device coordinates, the attitude of the tower to be tested is detected, and the attitude detection result of the tower is obtained. Thus, this solution, on the one hand, uses multiple attitude detection devices installed on the tower to replace manual detection, overcoming the detection error caused by human subjectivity, thereby effectively improving the efficiency and accuracy of tower attitude detection. On the other hand, this embodiment also considers offline scenarios for the attitude detection devices. In this scenario, this embodiment uses the online device coordinates and the relative positional relationship between the online and offline devices before they went offline to deduce the offline device coordinates, and combines the online and offline device coordinates to achieve tower attitude detection, further ensuring the accuracy of tower attitude detection in different scenarios.

[0087] In one exemplary embodiment, such as Figure 3 As shown, the attitude detection of the tower to be tested is performed based on the first and second device coordinates to obtain the attitude detection result of the tower. This includes the following steps:

[0088] Step S302: Detect the average value of the device coordinates between the first device coordinates and the second device coordinates.

[0089] The average device coordinate refers to the average coordinate between the first device coordinate and the second device coordinate at the current moment. In this embodiment, the attitude detection device on which the settlement detection depends is a device installed on the base surface of the tower to be detected. Therefore, the first device coordinate in this embodiment actually refers to the current coordinate of the online device located on the base surface of the tower to be detected, and the second device coordinate is the current coordinate of the offline device located on the base surface of the tower to be detected.

[0090] For example, suppose four attitude detection devices are installed on the base surface of the tower to be tested, located at the four ends of the base surface. The current BeiDou coordinates of attitude detection device 1 are (x1, y1, z1), those of attitude detection device 2 are (x2, y2, z2), those of attitude detection device 3 are (x3, y3, z3), and those of attitude detection device 4 are (x4, y4, z4). The average of at least three of these coordinates is calculated. , , , This is the average value of the X-axis coordinate. This is the average value of the Y-axis coordinate. This is the average value of the Z-axis coordinate. It should be noted that the base of the tower is a plane defined by at least three points. Therefore, at least any three BeiDou coordinates can be used to calculate the average value. The calculated average value of the coordinates corresponds to the center point of the base plane, and the displacement of this center point is more representative of the overall settlement of the tower.

[0091] Step S304: Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device.

[0092] Here, the first initial coordinates refer to the three-dimensional spatial coordinates of the online device at the time of device initialization or at a selected reference time, while the second initial coordinates refer to the three-dimensional spatial coordinates of the offline device at the time of device initialization or at a selected reference time. Similarly, the first initial coordinates are actually the initial coordinates of the online device located on the base surface of the tower to be tested, and the second initial coordinates are the initial coordinates of the offline device located on the base surface of the tower to be tested. The first device coordinates and the first initial coordinates correspond to the coordinates of the same online device at the current time and the initial time, respectively, while the second device coordinates and the second initial coordinates correspond to the coordinates of the same offline device obtained through calculation at the current time and the initial time, respectively.

[0093] For example, the server retrieves the three-dimensional spatial coordinates of all online and offline devices located on the base surface of the tower to be tested, at the time of device initialization or a selected reference moment, from a historical database or device configuration file. It can be understood that the goal of obtaining the first and second initial coordinates is to establish a benchmark for settlement comparison. Settlement is a relative change and requires a stable initial state as a reference.

[0094] In some embodiments, the server can periodically update the current real-time coordinates of each attitude detection device on the tower to new initial coordinates, provided that the tower is stable, in order to eliminate the impact of long-term small deformation accumulation on settlement detection and ensure that it always reflects the relative settlement changes in the recent period.

[0095] Step S306: Detect the average value of the initial coordinates between the first initial coordinates and the second initial coordinates.

[0096] The initial coordinate average value refers to the average value of the coordinates between the first initial coordinate and the second initial coordinate. The calculation process of the initial coordinate average value is similar to that of the equipment coordinate average value, and will not be repeated here.

[0097] Step S308: Based on the difference between the average value of the equipment coordinates and the average value of the initial coordinates, perform settlement detection on the tower to be tested to obtain the settlement detection result of the tower to be tested.

[0098] The difference refers to the three-dimensional coordinate value obtained by subtracting the initial average coordinate value from the average coordinate value of the equipment. In settlement detection, the main focus is on the difference in the elevation direction, i.e., the Z-axis coordinate. Settlement detection results refer to the relevant results generated during the tower settlement detection process, which may include, but are not limited to, at least one of the following: tower settlement amount, settlement detection time, settlement detection efficiency, etc. Tower settlement amount is usually expressed in millimeters; a negative value indicates settlement, and a positive value indicates uplift.

[0099] In some embodiments, in a settlement detection scenario, if there are offline devices on the tower base surface, in addition to performing settlement detection according to the above steps, offline devices can also be excluded. That is, only the initial average coordinate of all online devices on the tower base surface and the current average coordinate of all online devices are calculated, so that the tower settlement is detected based on the difference between the initial average coordinate of all online devices and the current average coordinate of all online devices.

[0100] In this embodiment, the average coordinates of all attitude monitoring devices (including online and offline devices) on the base surface of the tower are calculated at the initial and current times. The tower settlement is then detected by comparing the changes in the average coordinates at different times. This effectively eliminates the interference of local deformation or data jumps at a single monitoring point on the overall judgment, thereby significantly improving the accuracy and reliability of the settlement detection results.

[0101] In one exemplary embodiment, such as Figure 4 As shown, the attitude detection of the tower to be tested is performed based on the first device coordinates and the second device coordinates to obtain the attitude detection result of the tower to be tested. The process also includes the following steps:

[0102] Step S402: Determine the target normal vector perpendicular to the tower to be detected based on the first device coordinate vector corresponding to the first device coordinate and the second device coordinate vector corresponding to the second device coordinate.

[0103] Similar to the settlement detection scenario, the tilt detection in this embodiment also relies on attitude detection equipment on the base surface of the tower to be detected. Therefore, the first device coordinates in this embodiment refer to the current coordinates of the online device located on the base surface of the tower to be detected, and the second device coordinates refer to the current coordinates of the offline device located on the base surface of the tower to be detected. The first device coordinate vector is the vector between the origin coordinates and the first device coordinates, and the second device coordinate vector is the vector between the origin coordinates and the second device coordinates. The origin coordinates can be the coordinates of attitude detection devices on the tower base plane that are horizontally adjacent to both the online and offline devices. The target normal vector is the normal vector perpendicular to the base plane of the tower to be detected at the current moment.

[0104] For example, suppose attitude detection device 2 is an online device with coordinates (x2, y2, z2), and attitude detection device 3 is an offline device with derived coordinates (x3, y3, z3). Attitude detection device 1 is horizontally adjacent to attitude detection devices 2 and 3 respectively. Therefore, we take the coordinates (x1, y1, z1) of attitude detection device 1 as the origin coordinates, and the coordinate vector of the first device is then... The coordinate vector of the second device is then... Finally, by performing a cross product of the two vectors, we can obtain the target normal vector, i.e. Initial normal vector Perpendicular to the base plane of the tower to be tested.

[0105] For example, when performing tower tilt angle detection, the server first calculates the coordinate vector between the first device coordinate and the origin coordinate, and calculates the coordinate vector between the second device coordinate and the origin coordinate. The cross product of the two coordinate vectors can obtain the normal vector perpendicular to the base plane of the tower to be detected at the current moment, which is the target normal vector.

[0106] Step S404: Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device.

[0107] Wherein, the first initial coordinates refer to the three-dimensional spatial coordinates of the online device at the time of device initialization or at a selected reference time, and the second initial coordinates refer to the three-dimensional spatial coordinates of the offline device at the time of device initialization or at a selected reference time. Similarly, in this embodiment, the first initial coordinates refer to the initial coordinates of the online device located on the base surface of the tower to be tested, and the second initial coordinates refer to the initial coordinates of the offline device located on the base surface of the tower to be tested.

[0108] For example, the server retrieves the three-dimensional spatial coordinates of all online and offline devices located on the base surface of the tower to be tested, at the time of device initialization or a selected reference moment, from a historical database or device configuration file. It can be understood that the goal of obtaining the first and second initial coordinates is to determine the normal vector of the base plane at the initialization or reference moment, and the tower tilt angle is characterized by the change in the direction of the base plane normal vector at different times.

[0109] Step S406: Determine the initial normal vector perpendicular to the tower to be detected based on the first initial coordinate vector corresponding to the first initial coordinate and the second initial coordinate vector corresponding to the second initial coordinate.

[0110] The initial normal vector refers to the normal vector perpendicular to the base plane of the tower to be tested at the time of equipment initialization or at the selected reference time. The calculation process of the initial normal vector is similar to that of the target normal vector, and will not be repeated here.

[0111] Step S408: Based on the vector angle between the initial normal vector and the target normal vector, the tilt angle of the tower to be tested is detected to obtain the tilt angle detection result of the tower to be tested.

[0112] The vector angle refers to the angle formed in space between the initial normal vector and the target normal vector. The tilt detection result refers to the relevant results generated during the tower tilt detection process, which may include, but is not limited to, at least one of the following: tower tilt change value, tilt detection time, tilt detection efficiency, etc. The tower tilt change value is usually expressed in degrees or radians.

[0113] For example, after calculating the initial normal vector and the target normal vector, the server can use the vector dot product formula to calculate the angle between them. It can be understood that the tower's tilt directly reflects the change in the direction of the normal vector to the tower's base plane; therefore, the angle between the normal vectors is the actual change in the tower's tilt angle. In one example, the expression for the vector dot product formula is as follows:

[0114]

[0115] in, Represents the angle between vectors. Represents the target normal vector. This represents the initial normal vector.

[0116] In some embodiments, the server can also continuously calculate the tower tilt angle change value to calculate the tower tilt rate. When the tilt angle change value or tilt rate is greater than or equal to the safety threshold, an early warning can be issued immediately.

[0117] In this embodiment, by calculating the normal vector of the tower base plane at the initial moment and the current moment respectively, and accurately comparing the spatial angle between the two, the tower tilts in any direction in three-dimensional space, thereby achieving high-precision measurement of the tower tilt angle change and ensuring the accuracy and reliability of the tilt angle detection results.

[0118] In one exemplary embodiment, such as Figure 5 As shown, the attitude detection of the tower to be tested is performed based on the first device coordinates and the second device coordinates to obtain the attitude detection result of the tower to be tested. The process also includes the following steps:

[0119] Step S502: Determine the first center coordinates of the tower to be tested based on the first equipment coordinates and the second equipment coordinates.

[0120] The first center coordinate refers to the center coordinate of the tower to be tested. This coordinate can represent the position of the tower body. It can be calculated based on the first equipment coordinate and the second equipment coordinate, or the equipment coordinate of the attitude detection device located at the top of the tower can be used as the center coordinate.

[0121] For example, in the scenario of pole spacing detection, the server can first determine the center coordinates that can represent the position of the pole body to be detected. These coordinates can be the average of the current coordinates of all devices, or the device coordinates of the attitude detection device located at the top of the tower. The specific choice can be made according to the actual situation.

[0122] Step S504: Obtain the second center coordinates of the adjacent towers of the tower to be detected.

[0123] In this context, "adjacent tower" refers to another tower adjacent to the tower under test, which shares a transmission line with it. The second center coordinate refers to the center coordinate of the adjacent tower. This coordinate can represent the position of the tower body and can be calculated based on the coordinates of the attitude detection devices installed on the adjacent tower. Alternatively, the coordinates of the attitude detection device located at the top of the adjacent tower can be used as the center coordinate.

[0124] For example, the server can first determine another tower adjacent to the tower to be detected and sharing a transmission line. This can be done, for instance, by using images taken on-site, or by directly querying the data center for adjacent towers based on the tower's identification mark. The specific method for determining adjacent towers can be set according to actual circumstances, and this embodiment does not impose any limitations on this. After determining the adjacent towers, the server can query and retrieve the center coordinates of the adjacent towers from the data center.

[0125] In some embodiments, if adjacent towers also have offline devices, the server can also use the method of inferring the offline device coordinates from the online device coordinates to calculate the second center coordinates of the adjacent towers.

[0126] Step S506: Based on the first center coordinate and the second center coordinate, perform distance detection between the tower to be detected and the adjacent towers to obtain the distance detection result corresponding to the tower to be detected.

[0127] Among them, the spacing detection result refers to the relevant results generated during the tower spacing detection process, which may include, but are not limited to, at least one of the following: the straight-line distance between the tower to be detected and the adjacent towers, the spacing detection time, and the spacing detection efficiency.

[0128] For example, after obtaining the first and second center coordinates, the server can substitute them into the spacing calculation formula to calculate the tower spacing. In one example, the expression of the spacing calculation formula is as follows:

[0129]

[0130] Where L represents the straight-line distance between the tower to be tested and its adjacent towers, (x, y, z) are the first center coordinates, and (x', y', z') are the second center coordinates.

[0131] In this embodiment, the tower spacing is calculated by calculating the center coordinates of the tower to be tested and its adjacent towers, thus ensuring the accuracy and reliability of the tower spacing detection results.

[0132] In an exemplary embodiment, the tower attitude detection method further includes: obtaining the pre-offline coordinate vector between the online device and the offline device, wherein the pre-offline coordinate vector represents the positional relationship between the online device and the offline device before the device goes offline.

[0133] The pre-offline coordinate vector refers to the coordinate vectors of the online and offline devices before the device goes offline, describing the direction and distance from the online device to the offline device.

[0134] For example, when an offline device is determined to exist, the server can select any device from all online devices that is structurally directly associated with the offline device, and the coordinates of this device will be the first device coordinates. Further, based on the device identifier of this device and the device identifier of the offline device, the server retrieves a pre-stored coordinate vector from a dedicated relational database or configuration table, representing the positional relationship between the online and offline devices before the devices went offline; this is the pre-offline coordinate vector.

[0135] For example, assuming attitude detection device #4 is offline, and attitude detection device #3 is directly structurally associated with it online, the coordinate vectors of both devices before they went offline can be retrieved. This vector represents the coordinate vector before the device went offline. If attitude detection device #3 also goes offline, other online devices that are structurally directly related to attitude detection device #4, such as attitude detection device #2, can be selected, and the coordinate vectors of attitude detection devices #2 and #4 before they went offline can be retrieved. .

[0136] In some embodiments, detecting the second device coordinates of an offline device based on the first device coordinates and the positional relationship between devices includes: adding the first device coordinate vector corresponding to the first device coordinates to the coordinate vector before offline to obtain the second device coordinates of the offline device.

[0137] For example, after obtaining the pre-offline coordinate vector between the online device and the offline device, the server can obtain the coordinate vector between the first device coordinate and the origin, where the origin can be the location of any attitude detection device on the tower base plane, and add it to the pre-offline coordinate vector to obtain the device coordinates corresponding to the offline device.

[0138] Using the example of attitude detection device #4 being offline and attitude detection device #3 being online, the device coordinates of attitude detection device #3 are as follows: It can be known that Therefore, and Substituting into this expression, we can calculate... That is, the device coordinates of attitude detection device No. 4.

[0139] In this embodiment, by calling the pre-stored offline coordinate vector and adding it to the real-time coordinates of the online device, the current coordinates can be intelligently calculated without the need for the offline device to report data, thus ensuring the continuity and reliability of tower attitude monitoring in the event of device failure or signal interruption.

[0140] In an exemplary embodiment, the online device includes multiple sub-online devices. The first device coordinates include the sub-device coordinates corresponding to each sub-online device, and the first device coordinate vector includes the sub-device coordinate vector corresponding to each sub-device coordinate. Adding the first device coordinate vector corresponding to the first device coordinates to the pre-offline coordinate vector yields the second device coordinates of the offline device. This includes: adding the sub-device coordinate vector corresponding to each sub-device coordinate to the pre-offline coordinate vector to obtain multiple summed coordinate vectors; and determining the second device coordinates of the offline device based on the multiple summed coordinate vectors.

[0141] Here, "sub-online device" refers to the attitude detection device that is currently online; "sub-device coordinates" are the current device coordinates of the sub-online device; and "sub-device coordinate vector" is the coordinate vector between the sub-device coordinates and the origin. The summed coordinate vector is the vector obtained by adding the sub-device coordinate vector to the coordinate vector before offline operation.

[0142] For example, when there are multiple sub-online devices in the online device set, the server can obtain the current device coordinates and corresponding device coordinate vectors of each sub-online device. Then, each sub-device coordinate vector is added to its pre-offline coordinate vector to obtain multiple summed coordinate vectors. The server can calculate the average of these summed coordinate vectors, which can then be used as the second device coordinates of the offline device. Alternatively, the server can select any sub-online device, add its sub-device vector to its pre-offline coordinate vector to obtain a summed coordinate vector A, and simultaneously select a specified number of other sub-online devices, adding their sub-device vectors to their pre-offline coordinate vectors to obtain multiple summed coordinate vectors B. If the error between coordinate vector A and each coordinate vector B is within an error threshold, then the summed coordinate vector A can be used as the second device coordinates of the offline device. If the error between coordinate vector A and any coordinate vector B exceeds the error threshold, then coordinate vector A can be discarded, and the average of the set of coordinate vectors B can be used as the final result. The specific method chosen can be determined according to the actual situation; this embodiment does not impose any restrictions on this.

[0143] In this embodiment, by utilizing the coordinate data of multiple sub-online devices and performing parallel calculations with the pre-stored offline coordinate vectors, multiple summed coordinate vectors are generated. The final offline device coordinates are then determined through vector calculations, significantly improving the accuracy of the offline device coordinate back-calculation results and thus enhancing the accuracy of tower attitude detection.

[0144] In one specific embodiment, Figure 6A schematic diagram of the tower is shown. Four BeiDou GNSS detection devices are pre-arranged on the tower A to be tested, namely device 1, device 2, device 3 and device 4. Device 1, device 2 and device 3 are respectively set at the three ends of the base plane of the tower, while device 4 is set at the top of the tower.

[0145] Figure 7 The diagram shows a framework for tower attitude detection, which mainly includes a tower settlement detection module, a tower tilt angle detection module, and a tower spacing detection module.

[0146] In the tower settlement detection module, the server responds to an attitude detection command for tower A to be detected. This command carries the settlement detection requirement. First, it acquires the operating status of the devices installed on the base plane of tower A (i.e., device 1, device 2, and device 3). When it is determined that there are offline devices, assuming device 3 is offline, it acquires the first device coordinates of any online device, i.e., the device coordinates of device 1 or device 2, and the positional relationship between device 1 or device 2 and device 3 before they went offline, i.e., the pre-offline coordinate vector between device 1 and device 3. Or the offline pre-coordinate vector between device 2 and device 3 Next, the device coordinates of device 1 are compared with the coordinate vector before offline operation. Add them together, or combine the device coordinates of device 2 with the coordinate vector before offline operation. By adding the coordinates, we can obtain the current coordinates of device 3. Calculate the average coordinates of devices 1, 2, and 3 at the current moment, and simultaneously calculate the average coordinates of devices 1, 2, and 3 at the initial moment. Finally, calculate the difference between the two average coordinate values, which is the settlement of the tower A to be tested.

[0147] In the tower tilt detection module, the server responds to an attitude detection command for tower A to be detected. This command carries the tilt detection requirement. First, it obtains the operating status of the devices (i.e., device 1, device 2, and device 3) installed on the base plane of tower A. When it is determined that there are offline devices, assuming device 3 is offline, it obtains the first device coordinates of the online devices, i.e., the device coordinates of device 1 or device 2, and obtains the positional relationship between device 1 or device 2 and device 3 before they went offline, i.e., the pre-offline coordinate vector between device 1 and device 3. Or the offline pre-coordinate vector between device 2 and device 3 Next, the device coordinates of device 1 are compared with the coordinate vector before offline operation. Add them together, or combine the device coordinates of device 2 with the coordinate vector before offline operation. By adding the coordinates, we can obtain the current coordinates of device 3. Then, using device 1 as the origin, we calculate the device coordinate vector between device 1 and device 2. And the device coordinate vector between device 1 and device 3 , device coordinate vector With device coordinate vector The target normal vector can be obtained by performing a cross product. Simultaneously, the initial normal vector of the tower A to be tested is obtained from the historical database or device configuration file. Then calculate the initial normal vector. With the target normal vector The angle between the vectors Angle between vectors This is the actual change in tilt angle of tower A.

[0148] In the tower spacing detection module, the server responds to an attitude detection command for tower A to be detected. This command carries the spacing detection requirement. First, it obtains the operating status of the devices installed on tower A (i.e., device 1, device 2, device 3, and device 4). When it is determined that there are offline devices, assuming device 4 is offline, it obtains the first device coordinates of any online device, i.e., the individual device coordinates of device 1, device 2, or device 3, and the positional relationship between device 1, device 2, or device 3 and device 4 before the devices went offline, i.e., the pre-offline coordinate vector between device 1 and device 4. Or the offline pre-coordinate vector between device 2 and device 4 Or the offline pre-coordinate vector between device 3 and device 4 Next, the device coordinates of device 1 are compared with the coordinate vector before offline operation. Add them together, or combine the device coordinates of device 2 with the coordinate vector before offline operation. Add them together, or combine the device coordinates of device 3 with the coordinate vector before offline operation. By adding the coordinates, we can obtain the current coordinates of device 4. Using the coordinates of device 4 as the center coordinates of the tower A to be inspected, we also obtain the center coordinates of the adjacent tower B, which are the coordinates of the attitude detection device located at the top of the adjacent tower B. Finally, substituting the two center coordinates into the distance calculation formula, we can calculate the straight-line distance between the tower A to be inspected and the adjacent tower B.

[0149] In this embodiment, on the one hand, multiple attitude detection devices installed on the tower to be detected are used to replace manual detection, overcoming the detection errors caused by human subjective consciousness, thereby effectively improving the efficiency and accuracy of tower attitude detection. On the other hand, offline scenarios of attitude detection devices are also considered. In this scenario, this embodiment uses the coordinates of online devices and the relative positional relationship between online and offline devices before the devices go offline to deduce the coordinates of offline devices. Combined with the coordinates of online and offline devices, the attitude of the tower is detected, further ensuring the accuracy of tower attitude detection in different scenarios.

[0150] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0151] Based on the same inventive concept, this application also provides a tower attitude detection device for implementing the tower attitude detection method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more tower attitude detection device embodiments provided below can be found in the limitations of the tower attitude detection method described above, and will not be repeated here.

[0152] In one exemplary embodiment, such as Figure 8 As shown, a tower attitude detection device is provided, comprising:

[0153] The device status acquisition module 802 is used to acquire the operating status of each of the multiple attitude detection devices installed on the tower to be tested in response to the attitude detection command for the tower to be tested.

[0154] The online device coordinate acquisition module 804 is used to acquire the first device coordinates of the online device among the multiple attitude detection devices, as well as the device positional relationship between the online device and the offline device before the device went offline, when it is determined that there is an offline device among the multiple attitude detection devices based on each operating state.

[0155] The offline device coordinate determination module 806 is used to determine the second device coordinates of the offline device based on the first device coordinates and the positional relationship between devices;

[0156] The tower attitude detection module 808 is used to perform attitude detection on the tower to be detected based on the first device coordinates and the second device coordinates, and obtain the attitude detection result of the tower to be detected.

[0157] In one embodiment, the attitude detection result includes the settlement detection result of the tower to be detected; the tower attitude detection module 808 is also used for:

[0158] Detect the average value of the device coordinates between the coordinates of the first device and the coordinates of the second device;

[0159] Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device;

[0160] Detect the average value of the initial coordinates between the first and second initial coordinates;

[0161] Based on the difference between the average value of the equipment coordinates and the average value of the initial coordinates, the settlement of the tower to be tested is detected, and the settlement test results of the tower to be tested are obtained.

[0162] In one embodiment, the attitude detection result includes the tilt angle detection result of the tower to be detected; the tower attitude detection module 808 is also used for:

[0163] Based on the first device coordinate vector corresponding to the first device coordinate and the second device coordinate vector corresponding to the second device coordinate, determine the target normal vector perpendicular to the tower to be inspected.

[0164] Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device;

[0165] Based on the first initial coordinate vector corresponding to the first initial coordinate and the second initial coordinate vector corresponding to the second initial coordinate, determine the initial normal vector perpendicular to the tower to be detected;

[0166] Based on the angle between the initial normal vector and the target normal vector, the tilt angle of the tower to be tested is detected, and the tilt angle detection result of the tower to be tested is obtained.

[0167] In one embodiment, the attitude detection result includes the spacing detection result corresponding to the tower to be detected; the tower attitude detection module 808 is further used for:

[0168] Based on the coordinates of the first and second equipment, determine the first center coordinates of the tower to be inspected;

[0169] Obtain the second center coordinates of the adjacent towers of the tower to be detected;

[0170] Based on the first and second center coordinates, the distance between the tower to be tested and its adjacent towers is detected, and the distance detection result corresponding to the tower to be tested is obtained.

[0171] In one embodiment, the tower attitude detection device further includes: a pre-offline vector acquisition module, used to acquire the pre-offline coordinate vector between the online device and the offline device, wherein the pre-offline coordinate vector represents the positional relationship between the online device and the offline device before the device goes offline. The offline device coordinate determination module 806 further includes: a vector addition unit, used to add the first device coordinate vector corresponding to the first device coordinate to the pre-offline coordinate vector to obtain the second device coordinate of the offline device.

[0172] In one embodiment, the online device includes multiple sub-online devices, the first device coordinates include the sub-device coordinates corresponding to each sub-online device, and the first device coordinate vector includes the sub-device coordinate vector corresponding to each sub-device coordinate; the vector addition unit is further configured to:

[0173] Add the sub-device coordinate vector corresponding to each sub-device coordinate to the coordinate vector before offline operation to obtain multiple summed coordinate vectors;

[0174] The second device coordinates of the offline device are determined based on multiple summed coordinate vectors.

[0175] Each module in the aforementioned tower attitude detection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0176] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 9 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores tower attitude detection data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network. When the computer program is executed by the processor, it implements a tower attitude detection method.

[0177] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a tower attitude detection method.

[0178] Those skilled in the art will understand that Figure 9 or Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0179] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0180] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0181] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0182] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0183] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0184] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0185] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for detecting the attitude of a tower, characterized in that, The method includes: In response to an attitude detection command for the tower to be tested, the operating status of each of the multiple attitude detection devices installed on the tower to be tested is obtained; When it is determined that there is an offline device among the plurality of attitude detection devices based on the respective operating states, the first device coordinates of the online device among the plurality of attitude detection devices, and the device positional relationship between the online device and the offline device before the device went offline are obtained. Based on the first device coordinates and the positional relationship between the devices, the second device coordinates of the offline device are determined; Based on the first device coordinates and the second device coordinates, the attitude of the tower to be tested is detected to obtain the attitude detection result of the tower to be tested.

2. The method according to claim 1, characterized in that, The attitude detection result includes the settlement detection result of the tower to be tested; the step of performing attitude detection on the tower to be tested based on the first equipment coordinates and the second equipment coordinates to obtain the attitude detection result of the tower to be tested includes: Detect the average value of the device coordinates between the first device coordinates and the second device coordinates; Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device; Detect the average value of the initial coordinates between the first initial coordinates and the second initial coordinates; Based on the difference between the average value of the equipment coordinates and the average value of the initial coordinates, the settlement of the tower to be tested is detected, and the settlement detection result of the tower to be tested is obtained.

3. The method according to claim 1, characterized in that, The attitude detection result includes the tilt angle detection result of the tower to be tested; the step of performing attitude detection on the tower to be tested based on the first device coordinates and the second device coordinates to obtain the attitude detection result of the tower to be tested includes: Based on the first device coordinate vector corresponding to the first device coordinate and the second device coordinate vector corresponding to the second device coordinate, determine the target normal vector perpendicular to the tower to be detected; Obtain the first initial coordinates of the online device and the second initial coordinates of the offline device; Based on the first initial coordinate vector corresponding to the first initial coordinate and the second initial coordinate vector corresponding to the second initial coordinate, determine the initial normal vector perpendicular to the tower to be detected; Based on the vector angle between the initial normal vector and the target normal vector, the tilt angle of the tower to be tested is detected, and the tilt angle detection result of the tower to be tested is obtained.

4. The method according to claim 1, characterized in that, The attitude detection result includes the spacing detection result corresponding to the tower to be detected; the step of performing attitude detection on the tower to be detected based on the first device coordinates and the second device coordinates to obtain the attitude detection result of the tower to be detected includes: Based on the coordinates of the first device and the coordinates of the second device, determine the first center coordinates of the tower to be tested; Obtain the second center coordinates of the adjacent towers of the tower to be detected; Based on the first center coordinates and the second center coordinates, the distance between the tower to be tested and the adjacent towers is detected to obtain the distance detection result corresponding to the tower to be tested.

5. The method according to claim 1, characterized in that, The method further includes: Obtain the pre-offline coordinate vector between the online device and the offline device, wherein the pre-offline coordinate vector represents the positional relationship between the online device and the offline device before the device goes offline; Based on the first device coordinates and the positional relationship between devices, the second device coordinates of the offline device are detected, including: The first device coordinate vector corresponding to the first device coordinate is added to the offline coordinate vector to obtain the second device coordinate of the offline device.

6. The method according to claim 5, characterized in that, The online device includes multiple sub-online devices, the first device coordinates include the sub-device coordinates corresponding to each of the sub-online devices, and the first device coordinate vector includes the sub-device coordinate vector corresponding to each of the sub-device coordinates. The step of adding the first device coordinate vector corresponding to the first device coordinate to the offline coordinate vector to obtain the second device coordinate of the offline device includes: The sub-device coordinate vector corresponding to each of the sub-device coordinates is added to the pre-offline coordinate vector to obtain multiple summed coordinate vectors; The second device coordinates of the offline device are determined based on the summed coordinate vectors.

7. A tower attitude detection device, characterized in that, The device includes: The device status acquisition module is used to acquire the operating status of multiple attitude detection devices installed on the tower to be tested in response to the attitude detection command for the tower to be tested. The online device coordinate acquisition module is used to acquire the first device coordinates of the online device among the multiple attitude detection devices, and the device positional relationship between the online device and the offline device before the device went offline, when it is determined from the operating states that there is an offline device among the multiple attitude detection devices. An offline device coordinate determination module is used to determine the second device coordinates of the offline device based on the first device coordinates and the positional relationship between the devices; The tower attitude detection module is used to perform attitude detection on the tower to be detected based on the first device coordinates and the second device coordinates, and obtain the attitude detection result of the tower to be detected.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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

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