Intelligent inspection method, device and system for tower crane, electronic equipment and storage medium

Abstract

The invention discloses a tower crane intelligent inspection method, device and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining first data information, the first data information comprises first image information and first position information, and the first image information comprises the number of a to-be-inspected tower crane or the type content of the to-be-inspected tower crane; determining parameter data of a to-be-inspected tower crane according to the first data information, wherein the parameter data of the to-be-inspected tower crane comprises the number of the to-be-inspected tower crane or the model of the to-be-inspected tower crane and the position of the to-be-inspected tower crane; determining an inspection path template corresponding to the to-be-inspected tower crane and data of the to-be-inspected tower crane according to the parameter data of the to-be-inspected tower crane and a tower crane database; and optimizing the inspection path template according to the data of the to-be-inspected tower crane to form an inspection path of the to-be-inspected tower crane. According to the method, the influence caused by the modeling precision of the model when the inspection map is constructed through the model is avoided, and meanwhile, the problem of re-modeling caused by section adding of the tower crane in the construction process can be avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent detection of construction equipment, and in particular to an intelligent inspection method, device, system, electronic equipment and storage medium for tower cranes. Background Art

[0002] At traditional construction sites, tower cranes, as part of the larger equipment, require special attention to prevent potential safety hazards. Currently, inspections rely primarily on manual labor, which can be challenging due to difficulties reaching high altitudes, low inspection frequency, and untimely monitoring. Comprehensive monitoring of tower cranes is difficult, and the accuracy of inspection results is low. In recent years, advances in robotics and drone technology have led to the emergence of unmanned inspection techniques that use robots or drones to inspect tower cranes. This technology effectively avoids the safety hazards associated with manual inspections while also enabling better access to locations difficult to reach.

[0003] Among these technologies, robots and drones rely on the accuracy of inspection maps when conducting intelligent inspections. Figure 1 It is generally generated based on the tower crane model. This method is very dependent on the accuracy of the tower crane model when generating the inspection map. At the same time, during the actual construction process, the tower crane will be continuously jacked up and added, and a new tower crane model needs to be regenerated at this time, which further amplifies the impact of the model accuracy. Summary of the Invention

[0004] The embodiments of the present invention provide a tower crane intelligent inspection method, device, system, electronic equipment and storage medium to solve the problem in the prior art that inspection maps are difficult to generate and have insufficient accuracy.

[0005] According to a first aspect of the present invention, there is provided a tower crane intelligent inspection method, comprising: Acquire first data information, wherein the first data information includes first image information and first location information, and the first image information includes the number of the tower crane to be inspected or the model of the tower crane to be inspected; Determine the parameter data of the tower crane to be inspected according to the first data information, wherein the parameter data of the tower crane to be inspected includes the number of the tower crane to be inspected or the model of the tower crane to be inspected and the position of the tower crane to be inspected; 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; The inspection path template is optimized according to the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

[0006] The intelligent inspection method for tower cranes 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 an inspection path for the tower crane to be inspected. This avoids the influence caused by the modeling accuracy when constructing the inspection map through the model, and can also avoid the problem of re-modeling due to the addition of tower crane sections during the construction process.

[0007] In some embodiments, the first data information is acquired by a drone.

[0008] This setup allows the use of drones to pre-check the current crane's condition and obtain the crane's number and location data. Because drones offer higher positioning accuracy and can fly independently of the crane, they can be controlled to fly to the top of the crane to precisely locate it.

[0009] In some embodiments, 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: According to the location of the tower crane to be inspected, determine the tower crane with the closest installation location in the tower crane database; Determine whether the number or model of the tower crane to be inspected is consistent with the number or model of the tower crane in the tower crane database that is installed closest to the location of the tower crane to be inspected; When the consistency is determined, the inspection path template and tower crane data of the tower crane installed in the tower crane database closest to the position of the tower crane to be inspected are used as the inspection path template and tower crane data corresponding to the tower crane to be inspected; When it is determined that there is inconsistency, the first data information is reacquired and subsequent steps are performed.

[0010] Therefore, by such an arrangement, it is possible to avoid the occurrence of misdetection of the tower crane, and it is also possible to ensure that the data acquired in the subsequent steps corresponds to the tower crane to be inspected.

[0011] In some embodiments, the step of optimizing the inspection path template according to the tower crane data to be inspected to form the inspection path of the tower crane to be inspected includes: Verify and adjust the inspection path template according to the data and parameter data of the tower crane to be inspected; The inspection path template that has been calibrated and adjusted is optimized to form the inspection path of the tower crane to be inspected.

[0012] Therefore, by such an arrangement, it is possible to optimize the inspection path template, thereby forming an inspection path for the tower crane to be inspected that matches the current state of the tower crane to be inspected.

[0013] In some embodiments, the tower crane data to be inspected includes the base section height, standard section height, installation position center and current tower crane height. The checking and adjusting of the inspection path template according to the tower crane data to be inspected and the tower crane parameter data to be inspected includes: Calculate the current number of standard sections based on the current tower crane height and standard section height; Adjust the number of standard nodes in the inspection path template according to the current number of standard nodes; Calibrate the installation position center according to the position 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 position center.

[0014] Therefore, through such an arrangement, it is possible to optimize and calibrate the corresponding position information of the inspection path template, ensure the accuracy of the inspection path of the tower crane to be inspected, and improve the inspection effect.

[0015] In some embodiments, further comprising: The inspection route 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.

[0016] According to a second aspect of the present invention, there is provided an intelligent inspection device for a tower crane, comprising: A first data information acquisition module is configured to acquire first data information, wherein the first data information includes first image information and first position information, and the first image information includes the number of the tower crane to be inspected or the model of the tower crane to be inspected; A tower crane parameter determination module for determining the tower crane to be inspected according to the first data information, wherein the tower crane parameter data to be inspected includes the number of the tower crane to be inspected or the model of the tower crane to be inspected and the position of the tower crane to be inspected; 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; The inspection path optimization module is used to optimize the inspection path template according to the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

[0017] The intelligent inspection device for tower cranes 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 an inspection path for the tower crane to be inspected. This avoids the influence caused by the modeling accuracy when constructing the inspection map through the model, and can also avoid the problem of re-modeling due to the addition of tower crane sections during the construction process.

[0018] According to a third aspect of the present invention, there is provided a tower crane intelligent inspection system, comprising: An intelligent inspection device for a tower crane, configured to execute the intelligent inspection method for a tower crane described in the first aspect, or the intelligent inspection device for a tower crane described in the second aspect; The crane 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 a drone for tower crane inspection and is connected to the tower crane intelligent inspection device.

[0019] The tower crane intelligent inspection system of the present invention links the tower crane intelligent inspection device with the construction machinery safety management platform, enabling real-time determination of the current data status of each tower crane to be inspected, ensuring the accuracy of the inspection path generated for the tower crane to be inspected. It also links with the drone inspection platform, enabling the generated inspection path of the tower crane to be inspected to be uploaded to the drone inspection platform, enabling intelligent inspection of the tower crane to be inspected.

[0020] 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, and the instructions are 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.

[0021] According to a fifth aspect of the present invention, there is provided a storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the method described in the first aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 This is an overall flow chart of a tower crane intelligent inspection method according to one embodiment of the present invention; Figure 2 Flowchart of step S13 in the tower crane intelligent inspection method according to one embodiment of the present invention; Figure 3 Flowchart of step S14 in the tower crane intelligent inspection method according to one embodiment of the present invention; Figure 4 Flow chart of step S31 in the tower crane intelligent inspection method according to one embodiment of the present invention; Figure 5 Flowchart of step S44 in the tower crane intelligent inspection method according to one embodiment of the present invention; Figure 6 This is an overall flow chart of a tower crane intelligent inspection method according to another embodiment of the present invention; Figure 7 This is an overall flow chart for optimizing a tower crane inspection path in an intelligent tower crane inspection method according to another embodiment of the present invention; Figure 8 This is a principle block diagram of an intelligent inspection device for a tower crane according to one embodiment of the present invention; Figure 9 The present invention provides a structural composition of an intelligent inspection system for tower cranes according to an embodiment of the present invention; Figure 10 FIG. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0025] It should be noted that, unless there is any conflict, the embodiments and features in the embodiments of this application can be combined with each other.

[0026] The present invention may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including storage devices.

[0027] In the present invention, "module," "device," "system," and the like refer to related entities applied to a computer, such as hardware, a combination of hardware and software, software, or software in execution. Specifically, for example, a component may 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 or script running on a server, or a server, may also be a component. One or more components may be in an execution process and / or thread, and components may be localized on a single computer and / or distributed between two or more computers, and may be run by various computer-readable media. Components may also communicate via local and / or remote processes based on signals having one or more data packets, such as signals from a data packet interacting with another component in a local system, a distributed system, and / or data interacting with other systems via signals over a network on the Internet.

[0028] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include" and "comprise" include not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article or device. In the absence of further limitations, the elements defined by the phrase "include..." do not exclude the presence of other identical elements in the process, method, article or device that includes the elements.

[0029] The tower crane intelligent inspection method of the present invention can be applied to an intelligent inspection device for a tower crane, enabling users to quickly generate inspection routes for the tower crane in real time using the device to conduct intelligent inspections using drones. These intelligent inspection devices include, but are not limited to, smartphones, tablets, personal computers, computers, and cloud servers. Furthermore, the tower crane intelligent inspection method of the present invention can also be used on construction machinery safety management platforms or drone inspection platforms, without limitation to these platforms.

[0030] The present invention will be further described in detail below with reference to the accompanying drawings.

[0031] Figure 1 The overall process of the tower crane intelligent inspection method according to one embodiment of the present invention is schematically shown. Figure 1 As shown, the tower crane intelligent inspection method of the present invention includes the following steps: Step S11: Acquire first data information, wherein the first data information includes first image information and first position information, and the first image information includes the number of the tower crane to be inspected or the model of the tower crane to be inspected; Step S12: determining parameter data of the tower crane to be inspected based on the first data information, wherein the parameter data of the tower crane to be inspected includes the number of the tower crane to be inspected or the model of the tower crane to be inspected and the position of the tower crane to be inspected; Step S13: 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 the tower crane database; Step S14: Optimizing the inspection path template according to the data of the tower crane to be inspected to form an inspection path for the tower crane to be inspected.

[0032] In step S11, first data information is first obtained, wherein the obtained first data information includes first image information and first position information, and the first image information is information containing the number of the tower crane to be inspected or the model of the tower crane to be inspected. Specifically, the first data information can be obtained by a drone, or by manual measurement and photography. Taking drone acquisition as an example, the drone can be manually controlled to fly to a position on the tower crane to be inspected with the tower crane number or tower crane model content (such as the tower crane nameplate) to take a picture as the first image information, and then fly to just above the center of the tower crane to be inspected, and obtain the current position information of the drone as the first position information. It can be understood that the above-mentioned movement of the drone controlled by manual operation can also be fully automated through AI or program control to improve overall accuracy and reduce manual participation.

[0033] After obtaining the first data information, step S12 is executed to determine the parameter data of the tower crane to be inspected of the tower crane to be inspected based on the first data information. The parameter data of the tower crane to be inspected contains the number of the tower crane to be inspected or the model of the tower crane to be inspected, and the position of the tower crane to be inspected. The number of the tower crane to be inspected is an independent number for each tower crane, so that different tower cranes can be distinguished, and the model of the tower crane to be inspected is a number corresponding to the model of each tower crane, so that different tower cranes can be distinguished. After obtaining the first image information, the first image information can be identified by the image recognition module, thereby extracting the number of the tower crane to be inspected or the model of the tower crane to be inspected in the first image information. Since in step S11, the current position information of the drone is obtained by flying directly above the center of the tower crane to be inspected, in this embodiment, the first position information obtained is the position of the tower crane to be inspected. In other possible implementations, the first position information can be obtained by obtaining the position of a single foot of the tower crane to be inspected, etc. In this case, the first position information needs to be calculated to form the position of the tower crane to be inspected. For example, the position of the tower crane to be inspected can be determined 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 (denoted as ) of the tower crane to be inspected in the camera module of the drone. ), that is, the longitude and latitude coordinates of the tower crane's rotation center ( , The obtained number of the tower crane to be inspected or the model of the tower crane to be inspected can be recorded as a number parameter or a model parameter corresponding to the number or model of the tower crane to be inspected, and the position of the tower crane to be inspected can be recorded as longitude and latitude coordinate information.

[0034] Then, step S13 is executed. In step S13, the inspection path template and tower crane data corresponding to the tower crane to be inspected need to be determined based on the parameter data of the tower crane to be inspected determined in step S12 and the tower crane database. Among them, the tower crane database may contain the tower crane number of each tower crane and the actual situation data information of the tower crane corresponding to each tower crane number at the current moment, and then 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 to be inspected. These tower crane data to be inspected can include the base section height, standard section height, installation position center and current tower crane height, etc. In addition, since the parameter data of the tower crane to be inspected also includes the position of the tower crane to be inspected, the data of the tower crane closest to the current position of the tower crane to be inspected can be matched from the tower crane database based on the position of the tower crane to be inspected to serve as the parameter data of the tower crane to be inspected.

[0035] The tower crane database is a database that is pre-built and 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 construction machinery safety management), or other system platforms for collating and sorting out the information of each tower crane, etc. This embodiment does not limit this. The inspection path template can be set as an independent inspection path template for each different tower crane, or it can be set as an independent inspection path template for each different model type of tower crane. These inspection path templates contain data such as the node locations that need to be inspected for different tower cranes, so that there is no need to additionally model the tower cranes to be inspected, and it can also effectively avoid the situation where the inspection result accuracy problems caused by modeling accuracy problems. The inspection path template can be stored in the tower crane database together with other tower crane data to be inspected, or a separate database for storing the inspection path template can be constructed and stored in the database for easy search and retrieval.

[0036] In some embodiments, because the first image information in the first data information is captured by a drone or robot, the acquired first image information may be blurred due to environmental factors, lighting, etc., resulting in recognition errors when performing image recognition on the first image information. Therefore, when executing step S13, it is possible to first determine whether the number or model of the tower crane to be inspected is registered in the tower crane database based on the parameter data of the tower crane to be inspected obtained in step S12 and the tower crane database. Figure 2The present invention schematically shows the steps of step S13 in the tower crane intelligent inspection method according to one embodiment of the present invention. Figure 2 As shown, in this embodiment, step S13 can be implemented as including the following steps: Step S21: determining the tower crane with the closest installation position in the tower crane database according to the position of the tower crane to be inspected; Step S22: determining whether the number or model of the tower crane to be inspected is consistent with the number or model of the tower crane in the tower crane database that is installed closest to the location of the tower crane to be inspected; Step S23: When the results are consistent, the inspection path template and tower crane data of the tower crane installed closest to the tower crane to be inspected in the tower crane database are used as the inspection path template and tower crane data corresponding to the tower crane to be inspected; Step S24: When it is determined that there is inconsistency, the first data information is reacquired and subsequent steps are executed.

[0037] First, in step S21, it is determined which tower crane in the tower crane database corresponds to the tower crane to be inspected. Specifically, the position of the tower crane to be inspected can be compared with the installation positions of each tower crane in the tower crane database to determine the tower crane in the tower crane database whose installation position is closest to the position of the tower crane to be inspected.

[0038] Then, step S22 is executed to compare the determined tower crane number or tower crane model to be inspected with the tower crane number or tower crane model of the tower crane closest to the tower crane to be inspected stored in the tower crane database to see whether they are consistent, thereby determining whether the tower crane number or tower crane model to be inspected is registered in the tower crane database.

[0039] When it is determined in step S22 that the two are consistent, the inspection path template and tower crane data of the tower crane installed closest to the position of the tower crane to be inspected in the tower crane database can be used as the tower crane data and inspection path template of the tower crane to be inspected.

[0040] If the two are determined to be inconsistent in step S22, it means that the number or model of the tower crane to be inspected determined based on the first image information is inconsistent with the number of the actual tower crane 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 process is immediately exited and execution is restarted from step S11 to restart the new process step.

[0041] After determining the inspection path template and the data of the tower crane to be inspected, step S14 can be executed to optimize the inspection path template based on the data of the tower crane to be inspected, thereby forming an inspection path for the tower crane to be inspected. Since the tower crane to be inspected is constantly being lifted and sectioned during actual construction, the inspection map and inspection path template used during the intelligent inspection of the tower crane to be inspected will inevitably differ. Figure 3 The following schematically illustrates the process flow of step S14 in the tower crane intelligent inspection method according to one embodiment of the present invention. Figure 3 As shown, in this embodiment, step S14 can be implemented as including the following steps: Step S31: verifying and adjusting the inspection path template according to the tower crane data to be inspected and the tower crane parameter data to be inspected; Step S32: Optimizing the inspection path template after calibration and adjustment to form an inspection path for the tower crane to be inspected.

[0042] Step S31 is a step for adjusting the inspection path template based on the data and parameter data of the tower crane to be inspected. Specifically, the data of the tower crane to be inspected includes the more accurate position of the tower crane to be inspected, measured by drones or robots, and because the parameter data of the tower crane to be inspected includes data on the actual condition of the tower crane at the current moment, the current overall status of the tower crane to be inspected can be determined based on the data and parameter data, thereby effectively verifying and adjusting the inspection path template. Figure 4 The schematic diagram shows the process flow of step S31 in the tower crane intelligent inspection method according to one embodiment of the present invention, referring to Figure 4 As shown, in this embodiment, step S31 can be implemented as including the following steps: Step S41: Calculating the current number of standard sections based on the current tower crane height and the standard section height; Step S42: adjusting the number of standard nodes in the inspection path template according to the current number of standard nodes; Step S43: calibrating the installation position center according to the position of the tower crane to be inspected; Step S44: calibrating the position of each inspection node in the inspection path template according to the calibrated installation position center.

[0043] In step S41, the number of current standard sections is calculated. Since the parameter data of the tower crane to be inspected includes the current tower crane height and the standard section height, the number of current standard sections of the tower crane to be inspected can be obtained through simple calculation.

[0044] After determining the current number of standard sections of the tower crane to be inspected, step S42 can be executed to compare whether the number of standard section nodes in the inspection path template is equal, and automatically perform corresponding adjustment operations when the number of standard section nodes is inconsistent, such as adding or deleting standard section inspection nodes, to ensure complete path coverage.

[0045] In step S43, since the data of the tower crane to be inspected includes the position of the tower crane to be inspected with higher accuracy measured by a drone or a robot, the parameter of the installation position center can be calibrated based on the position of the tower crane to be inspected.

[0046] After calibrating the installation position center of the tower crane to be inspected, step S44 can be executed to calibrate the relative positions of the key parts in the inspection path template, so as to calibrate the longitude and latitude coordinates of each node in the inspection path map, and combine the number of standard sections and the height information of each part to accurately correct the height coordinates of the inspection point.

[0047] Figure 5 The following schematically illustrates the process flow of step S44 in the tower crane intelligent inspection method according to one embodiment of the present invention. Figure 5 As shown, in this embodiment, step S44 can be specifically implemented as including the following steps: Step S51: Extracting the coordinate information of the tower crane center point: Using the first position information collected by the drone, combined with the visual recognition or positioning module, the geometric center point of the tower crane to be inspected (denoted as ), that is, the longitude and latitude coordinates of the tower crane's rotation center ( , ).

[0048] Step S52: Load the relative position parameters of each inspection node in the inspection path template: In the inspection path template, the spatial position information (such as horizontal offset, vertical height, and azimuth) of each inspection node relative to the center point of the tower crane is preset and expressed as:

[0049] in Indicates the horizontal distance from the center point; Indicates the azimuth angle from the main heading; Indicates the height of the node (relative to the bottom height of the tower crane, calculated based on the current number of standard sections and the standard section height and foundation section height in the database).

[0050] Step S53: Convert the relative position parameters of each inspection node into a relative displacement vector: Convert the polar coordinate information of each node into a relative displacement vector (ENU local coordinate system) with the center of the tower crane as the origin:

[0051] Step S54: Calculate the actual latitude and longitude coordinates of each inspection node: Based on the longitude and latitude of the tower crane center ( , ) and relative displacement ( , ) Use a small area geodetic coordinate approximation method (such as the Vincenty formula or a simple spherical model) to calculate the actual latitude and longitude of each inspection node .

[0052] Step S55: Perform height calibration on each inspection node and match it with the standard node: According to the current total height of the tower crane , combined with the standard section height Height to foundation section , the actual number of standard sections can be calculated: , and retain or delete redundant standard node accordingly; match the vertical coordinates of each node's height.

[0053] Step S56: Output the calibrated three-dimensional path node list of each inspection node.

[0054] The final inspection route of the tower crane to be inspected should include the three-dimensional coordinate information of each inspection node. ;in is the vertical height of the node relative to the ground.

[0055] After calibrating the inspection path template through steps S41 through S44, a specific inspection path for the tower crane currently being inspected is formed. This inspection path is based on the inspection path template corresponding to the crane's number or model, optimized and calibrated for the current crane's status, resulting in higher accuracy. This also effectively avoids the impact of modeling accuracy that can occur when constructing inspection maps using a model, as well as the need for remodeling due to crane section additions during construction.

[0056] In some possible implementations, after completing step S14, the generated inspection path for the tower crane to be inspected can be uploaded to a drone inspection platform for controlling drone operations, so that the drone can be driven to complete the intelligent inspection of the tower crane to be inspected. The drone inspection platform is a platform developed specifically for conducting inspections using drones. For example, the drone inspection platform can be the "Skong 2" platform developed by DJI. Specific operations and other content can be controlled based on its publicly available information, and this embodiment will not be further elaborated on.

[0057] Figure 6 The overall flow chart of the tower crane intelligent inspection method according to one embodiment of the present invention is schematically shown. Figure 6 As shown, a drone can first be controlled manually or programmatically to capture a photo of the target crane (i.e., the crane to be inspected) to obtain first image information. Image recognition is then used to identify the crane model, which serves as the target crane's parameter data. The drone then flies directly above the crane and outputs the identified crane model. The Sikong 2 platform then outputs the drone's current first position information, which serves as the target crane's position for the parameter data. Since the target crane's position has been determined, the closest target crane in the crane database of the construction machinery safety management platform can be identified based on the target crane's position and provided with its information. The target crane's model is then compared with the target crane's model. If the comparison results are inconsistent, the process fails. The image acquisition and recognition process is then repeated. If the comparison results are consistent, the process passes. The target crane's information is then used as the target crane's data, and an inspection path template for the corresponding crane signal is obtained. Finally, the inspection path template is optimized according to the data of the tower crane to be inspected and the parameter data of the tower crane to be inspected. After the optimization, the inspection path of the tower crane to be inspected is formed and output to the Sikong 2 platform to control the drone to start intelligent inspection of the tower crane to be inspected.

[0058] Figure 7 The overall flow chart of optimizing the inspection path of a tower crane in the intelligent inspection method of a tower crane according to one embodiment of the present invention is schematically shown. Figure 7As shown, first obtain the tower crane model information, tower crane position information, and current tower crane height from the tower crane data to be inspected. Then, calculate the standard section number of the current tower crane based on the current tower crane height and the standard section height in the tower crane model information. Compare the standard section number with the number of standard section inspection nodes in the inspection path template. If the current standard section number is less than the number of standard section inspection nodes in the inspection path template, reduce the standard section inspection nodes in the inspection path template. If the current standard section number is greater than the number of standard section inspection nodes in the inspection path template, add the standard section inspection nodes in the inspection path template until the current standard section number equals the number of standard section inspection nodes in the inspection path template. Finally, calibrate the position information in the inspection path template based on the position of the tower crane to form the inspection path for the tower crane to be inspected.

[0059] The intelligent inspection method for tower cranes 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 an inspection path for the tower crane to be inspected. This avoids the influence caused by the modeling accuracy when constructing the inspection map through the model, and can also avoid the problem of re-modeling due to the addition of tower crane sections during the construction process.

[0060] Figure 8 The structure of the intelligent inspection device for tower crane according to one embodiment of the present invention is schematically shown. Figure 8 As shown, the tower crane intelligent inspection device of the present invention includes the following parts: A first data information acquisition module 1 is configured to acquire first data information, wherein the first data information includes first image information and first position information, and the first image information includes the number of the tower crane to be inspected or the model of the tower crane to be inspected; A tower crane parameter determination module 2 is configured to determine parameter data of the tower crane to be inspected based on the first data information, wherein the parameter data of the tower crane to be inspected includes the number of the tower crane to be inspected or the model of the tower crane to be inspected and the position of the tower crane to be inspected; 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 the tower crane database; The inspection path optimization module 4 is used to optimize the inspection path template according to the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

[0061] It should be noted that the implementation process and principles of the intelligent inspection device for tower cranes according to the embodiments of the present invention can be specifically described in the corresponding description of the above-mentioned method embodiment, such as the corresponding description of the method embodiment regarding the acquisition of the first data information, the acquisition of the tower crane data to be inspected, and the optimization of the inspection path template, so they are not repeated here. For example, the intelligent inspection device for tower cranes according to the embodiments of the present invention can be any intelligent device with a processor, including but not limited to computers, smart phones, personal computers, robots, cloud servers, etc.

[0062] Figure 9 The composition of the tower crane intelligent inspection system according to one embodiment of the present invention is schematically shown. Figure 9 As shown, the tower crane intelligent inspection system of the present invention includes the following parts: A tower crane intelligent inspection device 5, configured to execute the above-mentioned tower crane intelligent inspection method, or the above-mentioned tower crane intelligent inspection device; The construction and safety management platform 6 is equipped with a tower crane database and is connected to the tower crane intelligent inspection device; The drone inspection platform 7 is equipped with a drone for tower crane inspection and is communicatively connected to the tower crane intelligent inspection device.

[0063] The tower crane intelligent inspection system of the present invention links the tower crane intelligent inspection device with the construction machinery safety management platform, enabling real-time determination of the current data status of each tower crane to be inspected, ensuring the accuracy of the inspection path generated for the tower crane to be inspected. It also links with the drone inspection platform, enabling the generated inspection path of the tower crane to be inspected to be uploaded to the drone inspection platform, enabling intelligent inspection of the tower crane to be inspected.

[0064] In some embodiments, an embodiment of the present invention provides a non-volatile computer-readable storage medium, in which one or more programs including execution instructions are stored. The execution instructions can be read and executed by electronic devices (including but not limited to computers, servers, or network devices, etc.) to execute the tower crane intelligent inspection method of any of the above embodiments of the present invention.

[0065] In some embodiments, an embodiment of the present invention further provides a computer program product, which includes a computer program stored on a non-volatile computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the tower crane intelligent inspection method of any one of the above embodiments.

[0066] In some embodiments, an embodiment of 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, and the instructions are executed by the at least one processor so that the at least one processor can execute the tower crane intelligent inspection method of any of the above embodiments.

[0067] In some embodiments, an embodiment of the present invention further provides a storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the tower crane intelligent inspection method of any of the above embodiments.

[0068] Figure 10 This is a hardware structure diagram of an electronic device for executing a tower crane intelligent inspection method provided by another embodiment of the present application, such as Figure 10 As shown, the device includes: One or more processors 910 and memory 920, Figure 10 A processor 910 is taken as an example.

[0069] The device for executing the tower crane intelligent inspection method may further include: an input device 930 and an output device 940 .

[0070] The processor 910, the memory 920, the input device 930 and the output device 940 may be connected via a bus or other means. Figure 10 The bus connection is taken as an example.

[0071] 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 tower crane intelligent inspection method in the embodiments of this application. Processor 910 executes the non-volatile software programs, instructions, and modules stored in memory 920 to execute various server functional applications and data processing, thereby implementing the tower crane intelligent inspection method in the aforementioned method embodiment.

[0072] The memory 920 may include a program storage area and a data storage area. The program storage area may store an operating system and application programs 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 a memory remotely located relative to the processor 910, and such remote memory may be connected to the electronic device via a network. Examples of the aforementioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0073] The input device 930 may receive input digital or character information and generate signals related to user settings and function control of the image processing device. The output device 940 may include a display device such as a display screen.

[0074] The one or more modules are stored in the memory 920 , and when executed by the one or more processors 910 , perform the tower crane intelligent inspection method in any of the above method embodiments.

[0075] The above-mentioned product can execute the method provided in the embodiment of this application, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided in the embodiment of this application.

[0076] The electronic devices of the embodiments of the present application exist in various forms, including but not limited to: (1) Mobile communication devices: These devices are characterized by their mobile communication capabilities and are primarily designed to provide voice and data communications. These terminals include smartphones (e.g., iPhones), multimedia phones, feature phones, and low-end phones.

[0077] (2) Ultra-mobile personal computer devices: These devices fall under the category of personal computers, have computing and processing capabilities, and generally also have mobile Internet access. These terminals include PDAs, MIDs, and UMPCs, such as the iPad.

[0078] (3) Portable entertainment devices: These devices can display and play multimedia content. These devices include audio and video players (such as iPods), handheld game consoles, e-books, smart toys, and portable car navigation devices.

[0079] (4) Server: A device that provides computing services. The server consists of a processor, hard disk, memory, system bus, etc. The server is similar to a general computer architecture, but because it needs to provide highly reliable services, it has higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0080] (5) Other electronic devices with data interaction functions.

[0081] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0082] Through the description of the above embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a general hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the relevant 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, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A tower crane intelligent inspection method, 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 number of the tower crane to be inspected or the model of the tower crane to be inspected; Determine the parameter data of the tower crane to be inspected according to the first data information, wherein the parameter data of the tower crane to be inspected includes the number of the tower crane to be inspected or the model of the tower crane to be inspected and the position of the tower crane to be inspected; 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; The inspection path template is optimized according to the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

2. The tower crane intelligent inspection method according to claim 1, characterized in that: The first data information is obtained by a drone.

3. The tower crane intelligent inspection method according to claim 1, characterized in that: The step of determining the inspection path template and the tower crane data corresponding to the tower crane to be inspected based on the tower crane parameter data and the tower crane database includes: According to the location of the tower crane to be inspected, determine the tower crane with the closest installation location in the tower crane database; Determine whether the number or model of the tower crane to be inspected is consistent with the number or model of the tower crane in the tower crane database that is installed closest to the location of the tower crane to be inspected; When the consistency is determined, the inspection path template and tower crane data of the tower crane installed in the tower crane database closest to the position of the tower crane to be inspected are used as the inspection path template and tower crane data corresponding to the tower crane to be inspected; When it is determined that there is inconsistency, the first data information is reacquired and subsequent steps are performed.

4. The tower crane intelligent inspection method according to claim 1, characterized in that: The step of optimizing the inspection path template according to the tower crane data to be inspected to form the inspection path of the tower crane to be inspected includes: Verify and adjust the inspection path template according to the data and parameter data of the tower crane to be inspected; The inspection path template that has been calibrated and adjusted is optimized to form the inspection path of the tower crane to be inspected.

5. The tower crane intelligent inspection method according to claim 4, characterized in that: The tower crane data to be inspected include the base section height, standard section height, installation position center and current tower crane height. The checking and adjusting of the inspection path template according to the tower crane data to be inspected and the tower crane parameter data to be inspected includes: Calculate the current number of standard sections based on the current tower crane height and standard section height; Adjust the number of standard nodes in the inspection path template according to the current number of standard nodes; Calibrate the installation position center according to the position 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 position center.

6. The tower crane intelligent inspection method according to claim 1, characterized in that: Also includes: The inspection route 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.

7. An intelligent inspection device for tower crane, characterized in that: include: A first data information acquisition module is configured to acquire first data information, wherein the first data information includes first image information and first position information, and the first image information includes the number of the tower crane to be inspected or the model of the tower crane to be inspected; a tower crane parameter determination module for determining the tower crane to be inspected based on the first data information, wherein the tower crane parameter data includes the number of the tower crane to be inspected or the model of the tower crane to be inspected and the position of the tower crane to be inspected; 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; The inspection path optimization module is used to optimize the inspection path template according to the data of the tower crane to be inspected to form the inspection path of the tower crane to be inspected.

8. An intelligent inspection system for tower cranes, characterized in that: include: An intelligent inspection device for a tower crane, configured to execute the intelligent inspection method for a tower crane according to any one of claims 1 to 6, or the intelligent inspection device for a tower crane according to claim 7; The crane 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 a drone for tower crane inspection and is connected to the tower crane intelligent inspection device.

9. An electronic device, characterized in that: include: 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, and the instructions are executed 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 6.

10. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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