A method, device, system, electronic equipment and storage medium for intelligent inspection of tower cranes.

Abstract

This invention discloses a method, device, system, electronic device, and storage medium for intelligent tower crane inspection. The method includes: acquiring first data information, wherein the first data information includes first image information and first location information, and the first image information includes the tower crane number or tower crane model to be inspected; determining tower crane parameter data to be inspected based on the first data information, wherein the tower crane parameter data includes the tower crane number or tower crane model to be inspected, and also includes the tower crane location to be inspected; determining an inspection path template and tower crane data corresponding to the tower crane to be inspected based on the tower crane parameter data and a tower crane database; and optimizing the inspection path template based on the tower crane data to be inspected to form an inspection path for the tower crane to be inspected. This invention avoids the impact of model modeling accuracy issues that occur when constructing inspection maps using models, and also avoids the problem of remodeling due to tower crane section additions during construction.

Description

Technical Field

[0001] This invention relates to the field of intelligent inspection technology for construction equipment, and in particular to an intelligent inspection method, device, system, electronic equipment and storage medium for tower cranes. Background Technology

[0002] Currently, in traditional construction sites, tower cranes, as large pieces of equipment, require special attention to prevent safety hazards. Their inspection currently relies primarily on manual methods, which suffer from limitations such as difficulty reaching heights, low inspection frequency, and untimely monitoring, hindering comprehensive monitoring and resulting in low accuracy. In recent years, with the development of robotics and drone technology, unmanned inspection technologies have emerged, utilizing robots or drones to inspect tower cranes. This technology effectively avoids the safety hazards associated with manual inspections and can better reach areas inaccessible to humans.

[0003] In these technologies, robots and drones rely on the accuracy of inspection maps when conducting intelligent inspections. These inspection maps... Figure 1 Generally, the tower crane model is used for generation. This method is highly dependent on the accuracy of the tower crane model when generating the inspection map. In addition, as the tower crane is continuously lifted and added sections during the actual construction process, a new tower crane model needs to be generated, which further amplifies the impact of the model's accuracy. Summary of the Invention

[0004] This invention provides a method, device, system, electronic device, and storage medium for intelligent inspection of tower cranes, in order to solve the problems of difficulty in generating inspection maps and insufficient accuracy in the prior art.

[0005] According to a first aspect of the present invention, a method for intelligent inspection of tower cranes is provided, comprising:

[0006] Acquire first data information, wherein the first data information includes first image information and first location information, and the first image information includes the tower crane number or tower crane model to be inspected.

[0007] The tower crane parameter data to be inspected is determined based on the first data information. The tower crane parameter data to be inspected includes the tower crane number or tower crane model to be inspected, and also includes the location of the tower crane to be inspected.

[0008] Based on the tower crane parameter data and tower crane database, determine the inspection path template and tower crane data corresponding to the tower crane to be inspected;

[0009] The inspection path template is optimized based on the data of the tower crane to be inspected to form the inspection path for the tower crane to be inspected.

[0010] The intelligent tower crane inspection method of the present invention pre-forms inspection path templates corresponding to various tower cranes with different numbers, and then further calibrates and optimizes the inspection path templates based on the current time information of the tower crane to be inspected to form an inspection path for the tower crane to be inspected. This avoids the impact caused by the modeling accuracy when constructing an inspection map through a model, and also avoids the problem of remodeling due to the addition of tower crane sections during construction.

[0011] In some implementations, the first data information is acquired by a drone.

[0012] Therefore, this setup allows for the use of drones to pre-detect the current status of tower cranes, obtaining the number and location data of the tower crane to be inspected. Because drones offer higher positioning accuracy and can fly detached from the tower crane itself, they can be controlled to fly to the top of the tower crane for precise location.

[0013] In some implementations, determining the inspection path template and tower crane data corresponding to the tower crane to be inspected based on the tower crane parameter data and the tower crane database includes:

[0014] The tower crane with the closest installation location in the tower crane database is determined based on the location of the tower crane to be inspected;

[0015] Determine whether the tower crane number or model to be inspected matches the tower crane number or model in the tower crane database whose installation location is closest to that of the tower crane to be inspected.

[0016] When consistency is confirmed, the inspection path template and tower crane data of the tower crane whose installation location is closest to the tower crane to be inspected in the tower crane database shall be used as the corresponding inspection path template and tower crane data of the tower crane to be inspected.

[0017] If an inconsistency is detected, the first data information is retrieved again and subsequent steps are executed.

[0018] Therefore, this setting can avoid false detections of tower cranes and ensure that the data obtained in subsequent steps corresponds to the tower crane to be inspected.

[0019] In some implementations, the step of optimizing the inspection path template based on the tower crane data to form the inspection path for the tower crane to be inspected includes:

[0020] The inspection path template is verified and adjusted based on the tower crane data and tower crane parameter data to be inspected.

[0021] The inspection path template, after calibration and adjustment, is optimized to form the inspection path for the tower crane to be inspected.

[0022] Therefore, by setting it up in this way, the inspection path template can be optimized, thereby forming an inspection path for the tower crane to be inspected that matches the current state of the tower crane to be inspected.

[0023] In some implementations, the data of the tower crane to be inspected includes the height of the foundation section, the height of the standard section, the center of the installation position, and the current height of the tower crane.

[0024] The process of verifying and adjusting the inspection path template based on the tower crane data and tower crane parameter data to be inspected includes:

[0025] Calculate the current number of standard sections based on the current tower crane height and the standard section height.

[0026] Adjust the number of standard section nodes in the inspection path template according to the current number of standard sections;

[0027] The installation position center is calibrated based on the location of the tower crane to be inspected.

[0028] The position of each inspection node in the inspection path template is calibrated according to the calibrated installation location center.

[0029] Therefore, by setting it up in this way, the corresponding position information of the inspection path template can be optimized and calibrated to ensure the accuracy of the inspection path of the tower crane to be inspected and improve the inspection effect.

[0030] In some implementations, it also includes:

[0031] The inspection path of the tower crane to be inspected is uploaded to the drone inspection platform to drive the drone to complete the intelligent inspection of the tower crane.

[0032] According to a second aspect of the present invention, a tower crane intelligent inspection device is provided, comprising:

[0033] The first data information acquisition module is used to acquire first data information, wherein the first data information includes first image information and first location information, and the first image information includes the tower crane number or tower crane model to be inspected.

[0034] The tower crane parameter determination module is used to determine the tower crane parameter data to be inspected based on the first data information. The tower crane parameter data to be inspected includes the tower crane number or tower crane model to be inspected, and also includes the tower crane location to be inspected.

[0035] The tower crane data determination module is used to determine the inspection path template and tower crane data corresponding to the tower crane to be inspected based on the tower crane parameter data and the tower crane database.

[0036] The inspection path optimization module is used to optimize the inspection path template based on the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

[0037] The intelligent tower crane inspection device of the present invention pre-forms inspection path templates corresponding to various tower cranes with different numbers, and then further calibrates and optimizes the inspection path templates based on the current time information of the tower crane to be inspected, thereby forming the inspection path of the tower crane to be inspected. This avoids the impact caused by the modeling accuracy when constructing inspection maps through models, and also avoids the problem of remodeling due to the addition of tower crane sections during construction.

[0038] According to a third aspect of the present invention, a tower crane intelligent inspection system is provided, comprising:

[0039] The tower crane intelligent inspection device is used to perform the tower crane intelligent inspection method described in the first aspect above, or it is the tower crane intelligent inspection device described in the second aspect above.

[0040] The construction machinery safety management platform is equipped with a tower crane database and is connected to the tower crane intelligent inspection device.

[0041] The drone inspection platform is equipped with drones for tower crane inspection and is connected to the intelligent tower crane inspection device.

[0042] The intelligent tower crane inspection system of this invention links the intelligent tower crane inspection device with the construction machinery safety management platform, thereby enabling real-time determination of the current data status of each tower crane to be inspected, ensuring the accuracy of the generated inspection path for the tower crane to be inspected. Simultaneously, it also links with a drone inspection platform, allowing the generated inspection path for the tower crane to be inspected to be uploaded to the drone inspection platform, thus achieving intelligent inspection of the tower crane to be inspected.

[0043] According to a fourth aspect of the present invention, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the method described in the first aspect above.

[0044] According to a fifth aspect of the present invention, a storage medium is provided having a computer program stored thereon, characterized in that the program, when executed by a processor, implements the steps of the method described in the first aspect above. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is an overall flowchart of a tower crane intelligent inspection method according to an embodiment of the present invention;

[0047] Figure 2 This is a flowchart of step S13 in the intelligent inspection method for tower cranes according to an embodiment of the present invention.

[0048] Figure 3 This is a flowchart of step S14 in the intelligent inspection method for tower cranes according to an embodiment of the present invention.

[0049] Figure 4 This is a flowchart of step S31 in the intelligent inspection method for tower cranes according to an embodiment of the present invention.

[0050] Figure 5 This is a flowchart of step S44 in the intelligent inspection method for tower cranes according to an embodiment of the present invention.

[0051] Figure 6 This is an overall flowchart of another embodiment of the intelligent inspection method for tower cranes according to the present invention;

[0052] Figure 7 This is an overall flowchart of the tower crane inspection path optimization in another embodiment of the intelligent tower crane inspection method of the present invention.

[0053] Figure 8 This is a schematic block diagram of a tower crane intelligent inspection device according to an embodiment of the present invention;

[0054] Figure 9 The structural composition of a tower crane intelligent inspection system according to one embodiment of the present invention;

[0055] Figure 10 This is a schematic diagram of the structure of an embodiment of the electronic device of the present invention. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0058] This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, elements, data structures, etc., that perform a specific task or implement a specific abstract data type. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0059] In this invention, terms such as "module," "device," and "system" refer to relevant entities applied to a computer, such as hardware, combinations of hardware and software, software, or software in execution. More specifically, for example, an element can be, but is not limited to, a process running on a processor, a processor, an object, an executable element, an execution thread, a program, and / or a computer. Furthermore, an application program or script running on a server, and the server itself, can also be an element. One or more elements may be in an execution process and / or thread, and elements may be localized on a single computer and / or distributed across two or more computers, and may be run on various computer-readable media. Elements can also communicate via local and / or remote processes based on signals having one or more data packets, for example, signals from data interacting with another element in a local system, a distributed system, and / or interacting with other systems via signals over a network of the Internet.

[0060] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising" or "including" include not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0061] The intelligent tower crane inspection method in this invention can be applied to intelligent tower crane inspection devices, enabling users to quickly and in real-time generate inspection paths for the tower cranes to be inspected, and to conduct intelligent inspections by drones. These intelligent tower crane inspection devices include, but are not limited to, smartphones, tablets, personal PCs, computers, and cloud servers. Furthermore, the intelligent tower crane inspection method of this invention can also be used in construction machinery safety management platforms or drone inspection platforms, etc., and this invention does not limit its application to these applications.

[0062] The present invention will now be described in further detail with reference to the accompanying drawings.

[0063] Figure 1 The overall process of the intelligent tower crane inspection method according to an embodiment of the present invention is illustrated schematically. (Refer to...) Figure 1 As shown, the intelligent tower crane inspection method of the present invention includes the following steps:

[0064] Step S11: Obtain first data information, wherein the first data information includes first image information and first location information, and the first image information contains the tower crane number or tower crane model to be inspected.

[0065] Step S12: Determine the tower crane parameter data to be inspected based on the first data information. The tower crane parameter data to be inspected includes the tower crane number or tower crane model to be inspected, and also includes the location of the tower crane to be inspected.

[0066] Step S13: Determine the inspection path template and tower crane data corresponding to the tower crane to be inspected based on the tower crane parameter data and tower crane database;

[0067] Step S14: Optimize the inspection path template based on the tower crane data to be inspected to form the inspection path for the tower crane to be inspected.

[0068] In step S11, firstly, first data information is acquired. This first data information includes first image information and first location information. The first image information contains the tower crane number or model number to be inspected. Specifically, this first data information can be acquired by a drone or by manual measurement and photography. Taking drone acquisition as an example, the drone can be manually controlled to fly to the location on the tower crane to be inspected that contains the tower crane number or model number (such as the tower crane nameplate) to take a picture as the first image information. Then, it flies to the center directly above the tower crane to be inspected and acquires the current location information of the drone as the first location information. It is understood that the above-mentioned manual control of the drone's movement can also be fully automated through AI or program control to improve overall accuracy and reduce human intervention.

[0069] After acquiring the first data information, step S12 is executed to determine the tower crane parameter data to be inspected based on the first data information. The tower crane parameter data package contains the tower crane number or model number and the tower crane location. The tower crane number is a unique number for each tower crane to distinguish between different tower cranes, and the tower crane model number is a number corresponding to the specific model of each tower crane to distinguish between different tower crane models. After acquiring the first image information, the first image information can be identified by an image recognition module to extract the tower crane number or model number from the first image information. Since the current location information of the UAV is obtained by flying directly above the center of the tower crane to be inspected in step S11, in this embodiment, the first location information obtained is the location of the tower crane to be inspected. In other possible implementations, the first position information can be obtained by acquiring the position of one leg of the tower crane to be inspected. In this case, the first position information needs to be calculated to determine the position of the tower crane to be inspected. For example, to determine the position of the tower crane to be inspected based on the first position information, the first position information collected by the drone can be combined with a visual recognition or positioning module to determine the geometric center point of the tower crane to be inspected within the drone's camera module (denoted as...). ), that is, the latitude and longitude coordinates of the location of the tower crane's rotation center ( , The obtained tower crane number or model number to be inspected can be recorded as the number parameter or model parameter corresponding to the tower crane number or model number to be inspected, while the location of the tower crane to be inspected can be recorded as latitude and longitude coordinates.

[0070] Next, step S13 is executed. In step S13, the inspection path template and tower crane data corresponding to the tower crane to be inspected are determined based on the tower crane parameter data and tower crane database determined in step S12. The tower crane database may contain the tower crane number of each tower crane and the actual situation data of the tower crane corresponding to each tower crane number at the current moment. Therefore, the tower crane data corresponding to the tower crane to be inspected can be determined from the tower crane database based on the tower crane number. This tower crane data may include the foundation section height, standard section height, installation position center, and current tower crane height. Furthermore, since the tower crane parameter data also includes the location of the tower crane to be inspected, the data of the tower crane closest to the current location of the tower crane to be inspected can be matched from the tower crane database based on the location of the tower crane to be inspected, and used as the tower crane parameter data for the tower crane to be inspected.

[0071] The tower crane database is a pre-built database that is updated in real time according to the actual situation of each tower crane. It can be a construction machinery safety management platform (an information platform for the safety management of construction machinery), or other system platforms used to organize and sort information about various tower cranes; this embodiment does not impose any restrictions. Inspection path templates can be set up independently for each different tower crane, or independently for each different model and type of tower crane. These inspection path templates contain data such as the node locations to be inspected for different tower cranes, thus eliminating the need for additional modeling of the tower cranes to be inspected and effectively avoiding accuracy issues in inspection results caused by modeling accuracy problems. Inspection path templates can be stored together with other tower crane data in the tower crane database, or a separate database can be built to store the inspection path templates for easy retrieval.

[0072] In some implementations, since the first image information in the first data information is acquired by a drone or robot, the acquired first image information may be blurry due to environmental factors such as lighting, leading to recognition errors when performing image recognition on the first image information. Therefore, when performing step S13, it can be determined whether the tower crane number or model to be inspected is registered in the tower crane database based on the tower crane parameter data to be inspected obtained in step S12 and the tower crane database. Figure 2 The flowchart of step S13 in the intelligent tower crane inspection method according to an embodiment of the present invention is illustrated schematically. (Refer to...) Figure 2 As shown, in this embodiment, step S13 can be implemented by including the following steps:

[0073] Step S21: Based on the location of the tower crane to be inspected, determine the tower crane with the closest installation location in the tower crane database;

[0074] Step S22: Determine whether the tower crane number or tower crane model to be inspected matches the tower crane number or tower crane model in the tower crane database whose installation location is closest to the tower crane to be inspected.

[0075] Step S23: When consistency is confirmed, the inspection path template and tower crane data of the tower crane whose installation location is closest to the tower crane to be inspected in the tower crane database are used as the corresponding inspection path template and tower crane data of the tower crane to be inspected.

[0076] Step S24: When an inconsistency is determined, reacquire the first data information and execute subsequent steps.

[0077] First, step S21 determines which tower crane in the tower crane database corresponds to the tower crane to be inspected. Specifically, this is done by comparing the location of the tower crane to be inspected with the installation locations of each tower crane in the tower crane database to determine the tower crane in the database whose installation location is closest to the location of the tower crane to be inspected.

[0078] Then, step S22 is executed to compare the tower crane number or tower crane model to be inspected with the tower crane number or tower crane model stored in the tower crane database that is closest to the tower crane to be inspected, so as to determine whether the tower crane number or tower crane model to be inspected is registered in the tower crane database.

[0079] When it is determined in step S22 that the two are consistent, the inspection path template and tower crane data of the tower crane whose installation location is closest to the tower crane to be inspected in the tower crane database can be used as the tower crane data and inspection path template to be inspected.

[0080] If a discrepancy is found in step S22, it indicates that the tower crane number or model to be inspected determined based on the first image information is inconsistent with the actual tower crane number to be inspected, or the tower crane to be inspected is not a tower crane stored in the tower crane database, etc. In this case, the current execution flow is immediately exited, and execution restarts from step S11 to begin a new process.

[0081] After determining the inspection path template and tower crane data for the tower crane to be inspected, step S14 can be executed to optimize the inspection path template based on the tower crane data, thereby forming the inspection path for the tower crane to be inspected. Because the tower crane will continuously lift and add sections during actual construction, the inspection map and inspection path template used during intelligent inspection will inevitably differ. Figure 3 The flowchart of step S14 in the intelligent tower crane inspection method according to an embodiment of the present invention is illustrated schematically. (Refer to...) Figure 3 As shown, in this embodiment, step S14 can be implemented by including the following steps:

[0082] Step S31: Verify and adjust the inspection path template based on the tower crane data and tower crane parameter data to be inspected;

[0083] Step S32: Optimize the calibrated and adjusted inspection path template to form the inspection path for the tower crane to be inspected.

[0084] Step S31 involves adjusting the inspection path template based on the tower crane data and tower crane parameter data to be inspected. Specifically, the tower crane data includes the more accurate location of the tower crane obtained from measurements by drones or robots, and the tower crane parameter data contains the actual situation data of the tower crane at the current moment. Therefore, the overall current state of the tower crane to be inspected can be determined based on the tower crane data and tower crane parameter data, thereby effectively verifying and adjusting the inspection path template. Figure 4 The flowchart of step S31 in the intelligent tower crane inspection method according to an embodiment of the present invention is illustrated schematically. (Refer to...) Figure 4 As shown, in this embodiment, step S31 can be implemented by including the following steps:

[0085] Step S41: Calculate the current number of standard sections based on the current tower crane height and the standard section height;

[0086] Step S42: Adjust the number of standard section nodes in the inspection path template according to the current number of standard sections;

[0087] Step S43: Calibrate the installation position center according to the location of the tower crane to be inspected;

[0088] Step S44: Calibrate the position of each inspection node in the inspection path template according to the calibrated installation position center.

[0089] In step S41, the current number of standard sections is calculated. Since the tower crane parameter data to be inspected includes the current tower crane height and standard section height, the current number of standard sections of the tower crane to be inspected can be obtained through simple calculation.

[0090] Once the current number of standard sections of the tower crane to be inspected is determined, step S42 can be executed. Based on this, the number of standard section nodes in the inspection path template is compared to see if they are equal. If the number of standard section nodes is inconsistent, the corresponding adjustment operation is automatically executed, such as adding or deleting standard section inspection nodes, to ensure complete path coverage.

[0091] In step S43, since the data of the tower crane to be inspected includes the location of the tower crane to be inspected, which is more accurate and measured by drones or robots, the parameter of the installation location center can be calibrated by the location of the tower crane to be inspected.

[0092] After calibrating the installation center of the tower crane to be inspected, step S44 can be executed to calibrate the relative positions of each key part in the inspection path template, thereby calibrating the latitude and longitude coordinates of each node in the inspection path map, and accurately correcting the height coordinates of the inspection points by combining the number of standard sections and the height information of each part.

[0093] Figure 5 The flowchart of step S44 in the intelligent tower crane inspection method according to an embodiment of the present invention is illustrated schematically. (Refer to...) Figure 5 As shown, in this embodiment, step S44 can specifically be implemented by including the following steps:

[0094] Step S51: Extract the coordinates of the tower crane's center point:

[0095] Using the initial location information collected by the drone, combined with visual recognition or positioning modules, the geometric center point (denoted as ) of the tower crane to be inspected is determined. ), that is, the latitude and longitude coordinates of the location of the tower crane's rotation center ( , ).

[0096] Step S52: Load the relative position parameters of each inspection node in the inspection path template:

[0097] In the inspection path template, the spatial position information (such as horizontal offset, vertical height, and azimuth) of each inspection node relative to the tower crane center point is preset, as shown below:

[0098]

[0099] in Indicates the horizontal distance from the center point; Indicates the azimuth angle deviating from the main orientation; This indicates the height of the node (relative to the bottom of the tower crane, calculated based on the current number of standard sections and the heights of standard sections and foundation sections in the database).

[0100] Step S53: Convert the relative position parameters of each inspection node into a relative displacement vector:

[0101] The polar coordinate information of each node is converted into a relative displacement vector with the tower crane center as the origin (ENU local coordinate system):

[0102]

[0103] Step S54: Calculate the actual latitude and longitude coordinates of each inspection node:

[0104] Based on the latitude and longitude of the tower crane center ( , ) and relative displacement ( , The actual latitude and longitude of each inspection node are calculated using a small-area geodetic coordinate approximation method (such as the Vincenty formula or a simple spherical model). .

[0105] Step S55: Perform height calibration and matching of each inspection node with the standard section:

[0106] Based on the current total height of the tower crane Combined with standard section height Height of the base section The actual number of standard sections can be calculated: Based on this, redundant standard section nodes are retained or deleted; the height of each node is matched with its vertical coordinate.

[0107] Step S56: Output the 3D path node list of each inspection node after calibration.

[0108] The final inspection path for the tower crane to be inspected should include the three-dimensional coordinate information of each inspection node. ;in This represents the vertical height of the node relative to the ground.

[0109] After calibrating the inspection path template in steps S41 to S44, an inspection path for the tower crane to be inspected is formed. This inspection path is based on the inspection path template corresponding to the tower crane's number or model, and has been optimized and calibrated for the current status of the tower crane, thus improving the accuracy of the inspection path. It also effectively avoids the impact of modeling accuracy issues that occur when building inspection maps from models, and avoids the problem of remodeling due to tower crane section additions during construction.

[0110] In some possible implementations, after completing step S14, the formed inspection path for the tower crane to be inspected can be uploaded to a drone inspection platform for controlling the drone's operation, thereby driving the drone to complete the intelligent inspection of the tower crane. This drone inspection platform is specifically developed for inspection using drones. For example, this platform could be DJI's "Sikong 2" platform; specific operations can be controlled according to its publicly available information, which will not be elaborated upon in this embodiment.

[0111] Figure 6 A schematic flowchart illustrating the overall process of an intelligent tower crane inspection method according to an embodiment of the present invention is shown below. (Refer to...) Figure 6As shown, firstly, a drone can be manually or programmatically controlled to take photos of the target tower crane (i.e., the tower crane to be inspected) to obtain initial image information. Then, the tower crane model is identified through image recognition and used as the tower crane model for the tower crane parameter data. Next, the drone flies directly above the tower crane and outputs the identified tower crane model. The Sikong2 platform also outputs the drone's current initial position information as the tower crane location for the tower crane parameter data. Since the tower crane location has been obtained, the closest tower crane in the construction machinery safety management platform's tower crane database can be determined based on that location, and its information can be provided. Then, the tower crane model is compared with the tower crane model to be inspected. If the comparison result is inconsistent, the process fails, and the image acquisition and recognition process is repeated. If the comparison result is consistent, the process succeeds, and the tower crane information is used as the tower crane data for the tower crane to be inspected. Simultaneously, the inspection path template for the corresponding tower crane signal is obtained. Finally, the inspection path template is optimized based on the tower crane data and parameter data to be inspected. After optimization, the inspection path of the tower crane to be inspected is generated and output to the Sikong 2 platform to control the drone to start intelligent inspection of the tower crane to be inspected.

[0112] Figure 7 This diagram schematically illustrates the overall flowchart of the tower crane inspection path optimization process in a tower crane intelligent inspection method according to an embodiment of the present invention. (Refer to...) Figure 7 As shown, the process first obtains the tower crane model information, tower crane location information, and current height from the tower crane data to be inspected. Then, based on the current tower crane height and the standard section height in the tower crane model information, the number of standard sections of the current tower crane is calculated. The number of standard sections is compared with the number of standard section inspection nodes in the inspection path template. If the current number of standard sections is less than the number of standard section inspection nodes in the inspection path template, the number of standard section inspection nodes in the inspection path template is reduced; if the current number of standard sections is greater than the number of standard section inspection nodes in the inspection path template, a new number of standard section inspection nodes is added to the inspection path template, until the current number of standard sections equals the number of standard section inspection nodes in the inspection path template. Finally, the location information in the inspection path template is calibrated based on the location of the tower crane to be inspected, forming the inspection path for the tower crane to be inspected.

[0113] The intelligent tower crane inspection method of the present invention pre-forms inspection path templates corresponding to various tower cranes with different numbers, and then further calibrates and optimizes the inspection path templates based on the current time information of the tower crane to be inspected to form an inspection path for the tower crane to be inspected. This avoids the impact caused by the modeling accuracy when constructing an inspection map through a model, and also avoids the problem of remodeling due to the addition of tower crane sections during construction.

[0114] Figure 8The structural composition of a tower crane intelligent inspection device according to an embodiment of the present invention is illustrated schematically. (Refer to...) Figure 8 As shown, the intelligent tower crane inspection device of the present invention includes the following parts:

[0115] The first data information acquisition module 1 is used to acquire first data information, wherein the first data information includes first image information and first location information, and the first image information includes the tower crane number or tower crane model to be inspected.

[0116] The tower crane parameter determination module 2 is used to determine the tower crane parameter data to be inspected based on the first data information. The tower crane parameter data to be inspected includes the tower crane number or tower crane model to be inspected, and also includes the tower crane location to be inspected.

[0117] The tower crane data determination module 3 is used to determine the inspection path template and tower crane data corresponding to the tower crane to be inspected based on the tower crane parameter data and tower crane database.

[0118] The inspection path optimization module 4 is used to optimize the inspection path template based on the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

[0119] It should be noted that the implementation process and principle of the intelligent tower crane inspection device in this embodiment of the invention can be specifically referred to in the corresponding descriptions of the above method embodiments, such as the descriptions of the acquisition of first data information, the acquisition of data of the tower crane to be inspected, and the optimization of the inspection path template in the method embodiments. Therefore, they will not be repeated here. Exemplarily, the intelligent tower crane inspection device in this embodiment of the invention can be any intelligent device with a processor, including but not limited to computers, smartphones, personal computers, robots, cloud servers, etc.

[0120] Figure 9 The composition of a tower crane intelligent inspection system according to an embodiment of the present invention is illustrated schematically. (Refer to...) Figure 9 As shown, the intelligent tower crane inspection system of the present invention includes the following components:

[0121] Tower crane intelligent inspection device 5 is used to perform the above-mentioned tower crane intelligent inspection method, or is the above-mentioned tower crane intelligent inspection device.

[0122] The construction machinery safety management platform 6 is equipped with a tower crane database and is connected to the tower crane intelligent inspection device.

[0123] The drone inspection platform 7 is equipped with drones for tower crane inspection and is connected to the intelligent tower crane inspection device.

[0124] The intelligent tower crane inspection system of this invention links the intelligent tower crane inspection device with the construction machinery safety management platform, thereby enabling real-time determination of the current data status of each tower crane to be inspected, ensuring the accuracy of the generated inspection path for the tower crane to be inspected. Simultaneously, it also links with a drone inspection platform, allowing the generated inspection path for the tower crane to be inspected to be uploaded to the drone inspection platform, thus achieving intelligent inspection of the tower crane to be inspected.

[0125] In some embodiments, the present invention provides a non-volatile computer-readable storage medium storing one or more programs including execution instructions, which can be read and executed by electronic devices (including but not limited to computers, servers, or network devices) to perform the tower crane intelligent inspection method of any of the above embodiments of the present invention.

[0126] In some embodiments, the present invention also provides a computer program product, the computer program product including a computer program stored on a non-volatile computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the tower crane intelligent inspection method of any of the above embodiments.

[0127] In some embodiments, the present invention also provides an electronic device comprising: at least one processor and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to execute the tower crane intelligent inspection method of any of the above embodiments.

[0128] In some embodiments, the present invention also provides a storage medium storing a computer program, characterized in that the program, when executed by a processor, implements the tower crane intelligent inspection method of any of the above embodiments.

[0129] Figure 10 This is a schematic diagram of the hardware structure of an electronic device for implementing an intelligent tower crane inspection method according to another embodiment of this application, as shown below. Figure 10 As shown, the device includes:

[0130] One or more processors 910 and memory 920, Figure 10 Take the 910 processor as an example.

[0131] The equipment for implementing the intelligent inspection method for tower cranes may also include: an input device 930 and an output device 940.

[0132] The processor 910, memory 920, input device 930, and output device 940 can be connected via a bus or other means. Figure 10Taking the example of a connection between China and Israel via a bus.

[0133] The memory 920, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the intelligent tower crane inspection method in the embodiments of this application. The processor 910 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 920, thereby implementing the intelligent tower crane inspection method of the above-described method embodiments.

[0134] The memory 920 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the tower crane intelligent inspection method, etc. Furthermore, the memory 920 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 920 may optionally include memory remotely located relative to the processor 910, and these remote memories can be connected to electronic devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0135] Input device 930 can receive input digital or character information and generate signals related to user settings and function control of the image processing device. Output device 940 may include display devices such as a display screen.

[0136] The one or more modules are stored in the memory 920, and when executed by the one or more processors 910, they execute the tower crane intelligent inspection method in any of the above method embodiments.

[0137] The above-described product can perform the methods provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for performing the methods. Technical details not described in detail in this embodiment can be found in the methods provided in the embodiments of this application.

[0138] The electronic devices in this application embodiments exist in various forms, including but not limited to:

[0139] (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and primarily aim to provide voice and data communication. These terminals include: smartphones (e.g., iPhones), multimedia phones, feature phones, and low-end phones, etc.

[0140] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, possessing computing and processing capabilities, and generally also have mobile internet access features. These terminals include PDAs, MIDs, and UMPCs, such as the iPad.

[0141] (3) Portable entertainment devices: These devices can display and play multimedia content. This category includes audio and video players (such as iPods), handheld game consoles, e-book readers, as well as smart toys and portable car navigation devices.

[0142] (4) Server: A device that provides computing services. The components of a server include a processor, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but because they need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0143] (5) Other electronic devices with data interaction functions.

[0144] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0145] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for intelligent inspection of tower cranes, characterized in that, include: Acquire first data information, wherein the first data information includes first image information and first location information, and the first image information includes the tower crane number or tower crane model to be inspected. The tower crane parameter data to be inspected is determined based on the first data information. The tower crane parameter data to be inspected includes the tower crane number or tower crane model to be inspected, and also includes the location of the tower crane to be inspected. The tower crane with the closest installation location in the tower crane database is determined based on the location of the tower crane to be inspected; Determine whether the tower crane number or model to be inspected matches the tower crane number or model in the tower crane database whose installation location is closest to that of the tower crane to be inspected. When consistency is confirmed, the inspection path template and tower crane data of the tower crane whose installation location is closest to the tower crane to be inspected in the tower crane database shall be used as the corresponding inspection path template and tower crane data of the tower crane to be inspected. If an inconsistency is determined, the first data information is retrieved again and subsequent steps are executed. The inspection path template is optimized based on the data of the tower crane to be inspected to form the inspection path for the tower crane to be inspected.

2. The intelligent inspection method for tower cranes according to claim 1, characterized in that, The first data information was acquired by the drone.

3. The intelligent inspection method for tower cranes according to claim 1, characterized in that, The process of optimizing the inspection path template based on the data of the tower crane to be inspected to form the inspection path for the tower crane to be inspected includes: The inspection path template is verified and adjusted based on the tower crane data and tower crane parameter data to be inspected. The inspection path template, after calibration and adjustment, is optimized to form the inspection path for the tower crane to be inspected.

4. The intelligent inspection method for tower cranes according to claim 3, characterized in that, The data of the tower crane to be inspected includes the height of the foundation section, the height of the standard section, the center of the installation position, and the current height of the tower crane. The process of verifying and adjusting the inspection path template based on the tower crane data and tower crane parameter data to be inspected includes: Calculate the current number of standard sections based on the current tower crane height and the standard section height. Adjust the number of standard section nodes in the inspection path template according to the current number of standard sections; The installation position center is calibrated based on the location of the tower crane to be inspected. The position of each inspection node in the inspection path template is calibrated according to the calibrated installation location center.

5. The intelligent inspection method for tower cranes according to claim 1, characterized in that, Also includes: The inspection path of the tower crane to be inspected is uploaded to the drone inspection platform to drive the drone to complete the intelligent inspection of the tower crane to be inspected.

6. A tower crane intelligent inspection device, characterized in that, include The first data information acquisition module is used to acquire first data information, wherein the first data information includes first image information and first location information, and the first image information includes the tower crane number or tower crane model to be inspected. The tower crane parameter determination module is used to determine the tower crane parameter data to be inspected based on the first data information. The tower crane parameter data to be inspected includes the tower crane number or tower crane model to be inspected, and also includes the tower crane location. The tower crane data determination module is used to determine the tower crane with the closest installation location in the tower crane database based on the location of the tower crane to be inspected. It determines whether the tower crane number or model to be inspected matches the tower crane number or model with the tower crane with the closest installation location in the tower crane database. If they match, the inspection path template and tower crane data of the tower crane with the closest installation location in the tower crane database are used as the corresponding inspection path template and tower crane data for the tower crane to be inspected. If they do not match, the first data information is re-acquired and subsequent steps are executed. The inspection path optimization module is used to optimize the inspection path template based on the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

7. A tower crane intelligent inspection system, characterized in that, include The tower crane intelligent inspection device is used to perform the tower crane intelligent inspection method according to any one of claims 1 to 5, or is the tower crane intelligent inspection device according to claim 6. The construction machinery safety management platform is equipped with a tower crane database and is connected to the tower crane intelligent inspection device. The drone inspection platform is equipped with drones for tower crane inspection and is connected to the intelligent tower crane inspection device.

8. An electronic device, comprising: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps of the method according to any one of claims 1 to 5.

9. A storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1 to 5.

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