CN116477492B - Standard knot installation method, system, device and medium - Google Patents

Standard knot installation method, system, device and medium Download PDF

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Publication number
CN116477492B
CN116477492B CN202310419851.9A CN202310419851A CN116477492B CN 116477492 B CN116477492 B CN 116477492B CN 202310419851 A CN202310419851 A CN 202310419851A CN 116477492 B CN116477492 B CN 116477492B
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China
Prior art keywords
preset point
standard section
standard
installation
monitoring
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CN202310419851.9A
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Chinese (zh)
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CN116477492A (en
Inventor
金晓春
王魏
陆彩虹
董国
黄亚南
黄春勇
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Jiangsu Jiuhe Machinery Co ltd
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Jiangsu Jiuhe Machinery Co ltd
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Priority to CN202311749510.4A priority Critical patent/CN117923339A/en
Priority to CN202310419851.9A priority patent/CN116477492B/en
Publication of CN116477492A publication Critical patent/CN116477492A/en
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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
    • B66C23/18—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes specially adapted for use in particular purposes
    • B66C23/26—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes specially adapted for use in particular purposes for use on building sites; constructed, e.g. with separable parts, to facilitate rapid assembly or dismantling, for operation at successively higher levels, for transport by road or rail
    • B66C23/28—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes specially adapted for use in particular purposes for use on building sites; constructed, e.g. with separable parts, to facilitate rapid assembly or dismantling, for operation at successively higher levels, for transport by road or rail constructed to operate at successively higher levels
    • B66C23/283—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes specially adapted for use in particular purposes for use on building sites; constructed, e.g. with separable parts, to facilitate rapid assembly or dismantling, for operation at successively higher levels, for transport by road or rail constructed to operate at successively higher levels with frameworks composed of assembled elements
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/16—Applications of indicating, registering, or weighing devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/18—Control systems or devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/18—Control systems or devices
    • B66C13/48—Automatic control of crane drives for producing a single or repeated working cycle; Programme control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C23/00—Cranes comprising essentially a beam, boom, or triangular structure acting as a cantilever and mounted for translatory of swinging movements in vertical or horizontal planes or a combination of such movements, e.g. jib-cranes, derricks, tower cranes
    • B66C23/62—Constructional features or details
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The embodiment of the specification provides a standard knot installation method, a standard knot installation system, a standard knot installation device and a standard knot installation medium, wherein the standard knot installation method comprises the steps of pre-detecting at least one mechanism in a top structure through a pre-detecting device; receiving an installation starting instruction from a control console when a first detection result of the pre-detection is qualified, executing an installation task of at least one standard section to be installed, and executing a corresponding sub-installation task for any standard section to be installed, wherein the method comprises the following steps: the control amplitude variation mechanism lifts and moves the standard section to be installed according to the lifting speed and the translation speed respectively and is placed on the introducing mechanism; the jacking mechanism is controlled to jack the sleeve frame according to the jacking parameters; the introduction mechanism is controlled to place the standard section to be installed above the target standard section according to the introduction speed and is controlled to connect the standard section to be installed with the target standard section; post-detecting the joint of the standard joint to be installed and the target standard joint; and sending prompt information to the control console based on the second detection result of the post detection.

Description

Standard knot installation method, system, device and medium
Technical Field
The specification relates to the field of tower cranes, and in particular relates to a standard knot installation method, a standard knot installation system, a standard knot installation device and a standard knot installation medium.
Background
The tower crane is a common hoisting device in construction engineering operation, and the main body part of the tower crane is formed by superposing a plurality of standard sections. However, if the main standard section is deformed or damaged during the installation process of the tower crane, serious operation accidents are easily caused.
In order to install a tower crane, CN115818458A discloses a standard knot assembling and disassembling system and an operation method, in the prior art, after an upper sleeve frame, a lower sleeve frame and a introducing system are assembled on the ground, a preset standard knot is connected with the introducing standard knot by a pin penetrating device through a preset position in the introducing standard knot to the lower sleeve frame of the introducing system. However, there are various risks in the standard joint assembly process, for example, the higher the tower crane is installed, the more difficult it is to find defects such as deformation and cracks in the standard joint. For another example, the higher the tower crane is installed, the higher the tower crane may be inclined due to various factors such as environment, and safety accidents are caused. This prior art does not take into account the risk situation during the assembly of standard knots.
Therefore, the standard knot installation method, system, device and medium are beneficial to monitoring various risks in real time and early warning in time in the standard knot installation process.
Disclosure of Invention
One of the embodiments of the present specification provides a standard knot installation method, which is executed by a processor and includes: pre-detecting at least one mechanism in the top structure through a pre-detection device, wherein the at least one mechanism at least comprises at least one of a jacking mechanism, an amplitude changing mechanism and an introduction mechanism; and executing the installation task of at least one standard section to be installed in response to the first detection result detected in advance being qualified and receiving an installation starting instruction from the console, wherein for any standard section to be installed in the at least one standard section to be installed, executing the corresponding sub-installation task comprises the following steps: responding to a first instruction obtained from a control console, controlling an amplitude variation mechanism to lift and move the standard section to be installed according to the lifting speed and the translational speed respectively, and placing the standard section to be installed on an introduction mechanism; in response to a second instruction obtained from the control console, controlling the jacking mechanism to jack the sleeve frame according to the jacking parameters, wherein the sleeve frame is configured in the top structure; responding to a third instruction obtained from a control console, controlling an introduction mechanism to place a standard section to be installed above a target standard section according to the introduction speed, and controlling the introduction mechanism to connect the standard section to be installed with the target standard section; post-detecting the joint of the standard joint to be installed and the target standard joint; and based on a second detection result of the post detection, sending prompt information to the control console.
One of the embodiments of the present specification provides a standard knot mounting system, the system comprising: the pre-detection module is used for pre-detecting at least one mechanism in the top structure through a pre-detection device, and at least one mechanism at least comprises a jacking mechanism, an amplitude changing mechanism and an introduction mechanism; the installation module is used for responding to the first detection result of the pre-detection being qualified and receiving an installation starting instruction from the control console to execute the installation task of at least one standard section to be installed, wherein for each standard section to be installed in the at least one standard section to be installed, the corresponding sub-installation task is executed, and the installation module comprises: responding to a first instruction obtained from the control console, controlling an amplitude variation mechanism to lift and move the standard section to be installed according to the lifting speed and the translation speed respectively, and placing the standard section on the introducing mechanism; in response to a second instruction obtained from the control console, controlling a jacking mechanism to jack the sleeve frame according to jacking parameters, wherein the sleeve frame is configured in the top structure; responding to a third instruction obtained from the control console, controlling the introduction mechanism to place the standard section to be installed above the target standard section according to the introduction speed, and controlling the introduction mechanism to connect the standard section to be installed with the target standard section; and performing post-detection on the joint of the standard section to be installed and the target standard section, and sending prompt information to the control console based on a second detection result of the post-detection.
One of the embodiments of the present specification provides a standard knot installation apparatus comprising at least one processor and at least one memory; the at least one memory is configured to store computer instructions; the at least one processor is configured to execute at least some of the computer instructions to implement the standard joint installation method as described above.
One of the embodiments of the present specification provides a computer-readable storage medium storing computer instructions that, when read by a computer in the storage medium, the computer performs any one of the standard knot installation methods described above.
Drawings
The present specification will be further elucidated by way of example embodiments, which will be described in detail by means of the accompanying drawings. The embodiments are not limiting, in which like numerals represent like structures, wherein:
FIG. 1 is an exemplary flow chart of a standard knot installation method shown in accordance with some embodiments of the present description;
FIG. 2 is an exemplary flow chart of performing a job based on risk of anomaly according to some embodiments of the present description.
FIG. 3 is an exemplary diagram illustrating model-based determination of risk of anomalies according to some embodiments of the present description;
FIG. 4 is an exemplary flow chart of balance determination shown in accordance with some embodiments of the present description.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present specification, and it is possible for those of ordinary skill in the art to apply the present specification to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.
It will be appreciated that "system," "apparatus," "unit" and/or "module" as used herein is one method for distinguishing between different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.
As used in this specification and the claims, the terms "a," "an," "the," and/or "the" are not specific to a singular, but may include a plurality, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.
A flowchart is used in this specification to describe the operations performed by the system according to embodiments of the present specification. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.
FIG. 1 is an exemplary flow chart of a standard knot installation method shown in accordance with some embodiments of the present description. As shown in fig. 1, the process 100 includes the following steps. In some embodiments, the process 100 may be performed by a standard knot installation system.
At 110, pre-inspecting at least one mechanism in the top structure by a pre-inspecting device.
The pre-detection means may be used to identify the operation of the device before performing the installation task. The pre-detection means may comprise image acquisition means, various sensors (e.g. ultrasonic sensors), etc. The pre-detection means may comprise various forms.
The top structure is the top component part of the tower crane and at least comprises a sleeve frame, a slewing mechanism, a jacking mechanism, a cab, a balance arm mechanism, a crane arm, an amplitude variation mechanism, a tower top and the like from bottom to top. The sleeve frame is a structure composed of a steel plate and a steel pipe, and an operation platform, a platform railing, a jacking cylinder and the like are arranged on the sleeve frame. The roof structure may be preassembled on the floor.
In some embodiments, the at least one mechanism includes at least one of a jacking mechanism, a luffing mechanism, and an introduction mechanism.
The jacking mechanism is a device consisting of a jacking cross beam and a hydraulic system. The jacking cross beam can be used for fixing the whole jacking mechanism. The hydraulic system may be used to jack the roof structure up to create a space into which standard knots may be placed. In some embodiments, a jacking mechanism may be used to jack the shelves configured in the roof structure.
The amplitude changing mechanism is a device which consists of an amplitude changing trolley on a crane arm, a lifting hook and the like. The horn may be used to hoist objects into the air.
The introduction mechanism refers to a platform/trolley suspended on a roof structure. The introduction mechanism may be used to introduce standard knots to be installed.
After jacking, the lower end of the sleeve frame is provided with a space for placing the standard joint, the standard joint can be added into the space through the introduction mechanism, and the standard joint is fixedly connected with a structure below the standard joint (for example, the standard joint installed at the previous time, etc.). For example, an installer may be on the lead-in mechanism to drag the standard joint to be installed over the installed standard joint to fit over and tighten the bolts and nuts.
In some embodiments, the introduction mechanism may also include a robotic arm or conveyor belt structure. The introduction mechanism may send the standard knot to be installed to the upper side of the target standard knot in response to the control instruction, and automatically complete the fastening operation. For more explanation of the standard section to be installed, the target standard section, see below.
Through jacking the sleeve frame for a plurality of times, the standard section to be installed is introduced for a plurality of times and the fixed connection is completed, so that the tower body can be heightened.
Pre-detection refers to the detection of the operation of the relevant device before performing the installation task. The pre-detection device may pre-detect at least one mechanism in the top structure prior to installation of the tower crane in a variety of ways.
In some embodiments, the pre-detection module may perform appearance structure detection, hydraulic system dry running detection, vacuum detection, safety air pressure correction detection, etc. on the climbing mechanism through the pre-detection device. In some embodiments, the pre-detection module can perform appearance structure detection, stress detection and the like on the introduction mechanism through the pre-detection device, so that the introduction mechanism can bear the weight of people and standard knots. In some embodiments, the pre-detection module may perform appearance structure detection, tension detection, pulley clearance detection, pulley lubrication detection, etc. on the horn by the pre-detection device.
And step 120, executing the installation task of at least one standard section to be installed in response to the first detection result of the pre-detection being qualified and receiving an installation starting instruction from the console.
The first detection result refers to a result obtained by performing the pre-detection. For example, after at least one mechanism in the top structure is pre-detected by the pre-detection device, a qualified or unqualified detection result is obtained.
A control console is a device used to control and operate the tower crane installation process. In some embodiments, the console may include an input module and a display module. The input module may be used to receive user input and the display module may be used to display information to a user. In some embodiments, the console may be a remote console. In some embodiments, the control console may be built into the tower interior.
The installation starting instruction is an instruction sent by a user operation console after the ground foundation and the top structure are installed, and is used for carrying out a tower crane installation task.
The install initiation instructions include first instructions, second instructions, and third instructions, see step 130, step 140, and step 150 and their associated descriptions for further description of the first instructions, second instructions, and third instructions.
The ground foundation is one of the supporting structures of the tower crane and comprises a cement foundation, a foundation section and one or more reinforcing sections from bottom to top. The cement foundation is the bottommost layer of the ground foundation and is used for bearing the whole weight of the tower crane; the foundation section is connected with the cement foundation through foundation bolts and is used for supporting the tower body; one or more reinforcing joints are connected with the foundation joint through high-strength bolts and used for enhancing the stability and bearing capacity of the ground foundation and ensuring the safe and stable operation of the tower crane.
In some embodiments, the luffing mechanism, the jacking mechanism and the introduction mechanism can respond to the first detection result and the installation starting instruction to execute the installation task of the standard knot to be installed.
The standard section to be installed refers to a standard section which is already pulled up by the luffing mechanism and is not connected with the target standard section in the installation task of the tower crane.
The installation task refers to a work task of assembling at least one standard section to be installed. The installation task may include a plurality of sub-installation tasks, each corresponding to a standard section to be installed.
In some embodiments, for any of the at least one standard section to be installed, the installation module may perform a corresponding sub-installation task. See steps 130-170 for a flow of performing sub-installation tasks.
And 130, controlling the amplitude variation mechanism to lift and move the standard section to be installed according to the lifting speed and the translation speed respectively in response to a first instruction acquired from the control console, and placing the standard section on the introducing mechanism.
The first instruction is an instruction for operating the horn.
The pulling speed refers to the speed of the horn as it moves in the vertical direction. The translational velocity refers to the velocity of the horn as it moves in the horizontal direction. The pulling speed and the translational speed can be obtained by means of a preset or user input.
In some embodiments, when the standard knot to be installed is placed in the introduction mechanism, the luffing mechanism may be controlled to lift the next standard knot to be installed and move it to a designated position in the balance arm. The designated position may be preset in advance based on factors such as the weight of the standard joint to be installed, the length of the balance arm, and the like.
And 140, controlling the jacking mechanism to jack the sleeve frame according to the jacking parameters in response to a second instruction acquired from the control console.
The second instruction refers to an instruction for operating the jack mechanism. The second instruction may be issued after the standard knot to be installed is placed on the introduction mechanism and the next standard knot to be installed is lifted and moved to a designated position in the balance arm.
The jacking parameters refer to motion parameters involved in the working process of the tower crane jacking mechanism. The jacking parameters at least comprise jacking speed and jacking height. The jacking parameters can be obtained through a preset mode or a user input mode and the like.
And step 150, in response to a third instruction acquired from the control console, controlling the introducing mechanism to place the standard section to be installed above the target standard section according to the introducing speed, and controlling the introducing mechanism to connect the standard section to be installed with the target standard section.
The third instruction refers to an instruction for operating the introduction mechanism. The third instruction may be issued after the jacking of the holster.
The introduction speed refers to the speed at which the introduction mechanism moves in the column direction. The introduction speed can be obtained by means of presetting or user input.
The target standard knot is the installed standard knot at the top. The installed standard section refers to a standard section that has been installed in the tower crane. The manner in which the standard section to be installed is connected to the target standard section may include, but is not limited to, bolting, etc.
Step 160, post-detection is performed on the connection part of the standard knot to be installed and the target standard knot.
The post detection refers to detecting the joint of the standard joint to be installed and the target standard joint. For example, in checking the joint, whether the connecting bolt is fastened or not is checked by a technique such as photographing and recognition, whether the connecting bolt is correctly mounted on the connecting point, and it is ensured that the bolt joint is free from problems such as looseness or deformation.
Step 170, based on the second detection result of the post detection, sending prompt information to the console.
The second detection result refers to the result obtained by performing post-detection. For example, the connection part of the standard joint to be installed and the target standard joint is detected to obtain a qualified or unqualified detection result.
The prompt information is information sent to the control console according to the second detection result. The processor may determine the hint information in a variety of ways. For example, based on the second detection result of the post detection, if the potential safety hazard exists at the connection position, the tower crane can send prompt information to the control console, such as "the connection position is loose and please deal with in time", so that an operator can take measures in time to repair the problem, and safe operation of the tower crane is ensured. The prompt information is usually presented in the form of words, sounds, lights, etc.
According to the embodiments of the specification, through pre-detection and post-detection, the quality and the safety of the tower crane installation standard section can be improved, prompt information can be timely sent to a control console, and the safe operation of the tower crane can be guaranteed; the control console commands control the tower crane to install the standard section, so that automatic installation of the tower crane is realized, and the installation efficiency is improved.
In some embodiments, the processor may detect and pre-warn during execution of the sub-mount task. See fig. 2 for more description.
FIG. 2 is an exemplary flow chart of a standard knot installation method shown in accordance with some embodiments of the present description. As shown in fig. 2, the process 200 includes the following steps. In some embodiments, the process 200 may be performed by a risk determination module.
Step 210, monitoring the installation process based on the distributed monitoring device to obtain monitoring data.
The distributed monitoring device can monitor each key part in the tower crane installation process.
In some embodiments, the distributed monitoring device comprises at least a monitoring data acquisition unit deployed at one or more preset points.
The preset point location is a point location where abnormality monitoring is required. Abnormal conditions may include, but are not limited to, cracks, breaks, deformations, and dislocates, among others. In some embodiments, the preset points may include preset points (hereinafter referred to as first preset points) for performing anomaly monitoring on the main structure of the installed standard knot. For example, the site may monitor the main limb, abdominal limb, welds, etc. In some embodiments, the preset points may include preset points (hereinafter referred to as second preset points) for abnormality monitoring of bolts, nuts, etc. between installed standard knots. In some embodiments, the preset point positions may further include preset point positions (hereinafter referred to as third preset point positions) for performing abnormal monitoring on the fitting condition of the jacking beam and the standard joint step in the jacking process.
In some embodiments, the processor may further increase at least one newly added preset point location in response to meeting a point location update condition, and install the monitoring data acquisition unit on the at least one newly added preset point location.
The point location update condition refers to a trigger condition that requires updating of a point location. For example, the point location update condition may be that the installation of one standard section is completed.
In some embodiments, specific locations (e.g., primary chords, bolted joints, primary welds, etc.) on the newly installed standard knot may be considered as new preset points.
In some embodiments, the monitoring data acquisition unit may be grasped from the ground by the horn mechanism, sent to the introduction mechanism, and deployed to a newly added preset point by the mechanical arm of the introduction mechanism.
According to some embodiments of the present disclosure, by dynamically increasing the newly increased preset point positions, and installing the monitoring data acquisition unit on the newly increased preset point positions, more monitoring areas can be covered, occurrence of monitoring blind areas is reduced, and monitoring accuracy is improved.
The monitoring data acquisition unit is a basic unit for monitoring the state of a monitored target, and can acquire and record various data information of preset points.
In some embodiments, the monitoring data acquisition unit comprises at least an image monitoring unit, and the monitoring data comprises at least image data, respectively. In some embodiments, the monitoring data acquisition unit further comprises an ultrasound monitoring unit, and the monitoring data further comprises ultrasound data, respectively.
According to some embodiments of the present disclosure, an ultrasonic monitoring unit is used to ultrasonically monitor a key portion in a tower crane installation process, obtain ultrasonic data, and transmit the ultrasonic data to a processor for analysis and processing, so that monitoring accuracy and safety are improved.
In some embodiments, the distributed monitoring device may further comprise a drone monitoring unit. The unmanned aerial vehicle monitoring unit can be used for gathering the data information at preset point location.
In some embodiments, the drone monitoring unit may be comprised of at least one drone. The number of unmanned aerial vehicles can be determined according to the number based on preset points. For example, the number of unmanned aerial vehicles may be determined based on the number of preset points and a preset scaling factor.
In some embodiments, an image monitoring component and an ultrasound monitoring component are deployed in the unmanned aerial vehicle, wherein the image monitoring component is used for acquiring image data of a preset point location, and the ultrasound monitoring component is used for acquiring ultrasound data of the preset point location.
In some embodiments, the monitoring data includes data collected by at least one drone at a set cruising route. The cruising route is a route planning of cruising through preset discrete points in sequence when the unmanned aerial vehicle executes tasks. The unmanned aerial vehicle can reach each point to perform operations such as image shooting or ultrasonic data acquisition. The cruising route may consist of a plurality of points.
The cruising route may be determined in a number of ways. For example, the cruising route may be set by user input.
In some embodiments, the processor may determine at least one high risk outlier; determining a candidate cruising route of each unmanned aerial vehicle in the at least one unmanned aerial vehicle based on the at least one high risk abnormal point to form a candidate cruising route combination; repeating the steps for a plurality of times to obtain a plurality of candidate cruising route combinations; evaluating a preference value for each candidate cruising route combination; and determining a target cruising route combination based on the plurality of preferred values to obtain a target cruising route of each unmanned aerial vehicle.
High risk outliers are points on the standard knots where the probability of outliers is greater. In some embodiments, the high risk anomaly points may be determined based on a priori knowledge, e.g., the main chord of the main stress, the bolted connection, the main weld, the abutment of the lifting beam with the standard pitch mark, etc., may be determined as the high risk anomaly points. In some embodiments, high risk anomaly points may be determined based on historical data, e.g., cell structures that fail (e.g., deform, fracture, etc.) multiple times (e.g., greater than a preset number of times) in the history may be determined to be high risk anomaly points.
The candidate cruising route combination refers to a combination of candidate cruising routes of each of the at least one unmanned aerial vehicle.
The processor may determine the candidate cruise route combination in a number of ways. In some embodiments, for each drone, a cruising route is generated that traverses all high risk outliers in a random manner, thereby determining a candidate cruising route combination. Repeating the above steps a plurality of times, a plurality of candidate cruising route combinations can be obtained.
The preferred value is a value according to the merits of the monitoring efficiency of the evaluation candidate cruising route combination.
The processor may evaluate the preference value in a number of ways. In some embodiments, the processor may determine the preferred value for a candidate cruising route combination based on the average monitored frequency and route redundancy for each high risk outlier contained in the candidate cruising route combination. For example, the preferred value can be calculated by equation (1):
wherein C represents a preferred value; p is p i Is the average monitored frequency, k, of the ith high risk outlier i Is its coefficient; r is the line redundancy, k r Is its coefficient. Since the security is more influenced by the preferred value than the resource waste, k i Can be as large as possible greater than k r 。
The average monitored frequency of high risk outliers may refer to the average number of times each high risk outlier is monitored multiple times by the drone over a period of time. In some embodiments, the average monitored frequency of high risk outliers may be obtained through simulation by simulation software after determining the cruising route combination.
Route redundancy may refer to the number of times that the cruising routes of different drones cover the same outlier at the same time. In some embodiments, route redundancy may be obtained through simulation by simulation software after the cruising route combination is determined.
The processor may determine the target cruise route combination in a number of ways. In some embodiments, the processor may compare the magnitude of the preferred value for each candidate cruise route combination, and determine the candidate cruise route combination with the greatest preferred value as the target cruise route combination.
In some embodiments, the cruise route further includes at least one conventional point, and the preference value may also be positively correlated to the conventional point coverage.
The conventional point is a point which is positioned in the tower crane structure and has low abnormal risk. For example, the conventional points may be some common structural points.
Conventional point coverage refers to the duty cycle of a conventional point that reaches a preset monitored frequency. The preset monitored frequency refers to the preset times of monitoring the conventional point by the unmanned aerial vehicle in a period of time. In some embodiments, conventional point coverage may be obtained through simulation by simulation software after the cruise route combinations are determined.
In some embodiments, the processor may determine the preferred value for a candidate cruising route combination based on the monitored frequency and route redundancy of each high risk outlier contained by the candidate cruising route combination, the regular point coverage of the contained regular points. For example, the preferred value can be calculated by equation (2):
wherein C represents a preferred value; p is p i Is the average monitored frequency, k, of the ith high risk outlier i Is its coefficient; r is the line redundancy, k r Is its coefficient; m is the normal point coverage, k m Is its coefficient.
According to the embodiments of the present disclosure, by monitoring the high risk abnormal points and determining the preferred route, accuracy and comprehensiveness of the monitored data can be ensured to the maximum extent, and monitoring efficiency and effect can be improved. By taking the conventional points as key nodes in the cruising route, the accuracy and the comprehensiveness of monitoring data can be ensured, and the cruising equipment can be helped to realize more accurate and efficient cruising monitoring. Through regard as distributed monitoring device's important component with unmanned aerial vehicle monitoring unit, compare in traditional fixed monitoring device can greatly improve monitoring coverage area and monitoring efficiency, can adjust monitoring parameter according to the monitoring demand simultaneously, can improve the efficiency of monitoring.
Step 220, evaluating the risk of abnormality based on the monitored data.
The abnormal risk refers to the probability of occurrence of an abnormal situation. The greater the risk of abnormality, the greater the probability of occurrence of an abnormal situation.
The processor may evaluate the risk of abnormality in a number of ways. In some embodiments, the processor may construct a monitor data vector based on the monitor data and perform vector matching in a vector database based on the monitor data vector, determining the risk of abnormality. Vector databases refer to databases used to store, index and query vectors. Through the vector database, similarity queries and other vector management can be quickly performed against a large number of vectors.
In some embodiments, a plurality of reference monitor data vectors and their corresponding reference anomaly risks may be included in the vector database. In some embodiments, the reference monitor data vector may be constructed based on historical monitor data. The reference abnormal risk corresponding to the reference monitoring data vector can be obtained according to the historical abnormal risk. In some embodiments, a vector database may be constructed based on multiple reference monitor data vectors and their corresponding anomaly risk.
In some embodiments, the processor may determine an associated monitor data vector in the vector database that meets a preset condition based on the monitor data vector. The preset condition may refer to a judgment condition for determining the associated feature vector. In some embodiments, the preset conditions may include that the vector distance is less than a distance threshold, that the vector distance is minimal, etc.
In some embodiments, the processor may determine the final anomaly risk based on the determined reference anomaly risk for which the associated monitoring data vector corresponds.
In some embodiments, the processor may determine the abnormal risk by an abnormal risk assessment model. For more description of this embodiment, see fig. 3 and its associated description.
At step 230, at least one of the pull-up speed, the translation speed, the lift-up speed, and the introduction speed is adjusted based on the risk of anomaly.
The processor may adjust at least one of the pull rate, the translation rate, the lift rate, and the introduction rate in a variety of ways. In some embodiments, the processor may evaluate the impact of the risk of abnormality on the operating process, and adjust at least one of the pull-up speed, the translation speed, the lift-up speed, and the introduction speed based on the evaluation.
In some embodiments, the processor may determine an adjustment value for adjusting at least one of the pull rate, the translation rate, the lift rate, and the introduction rate based on the adjustment magnitude of the anomaly risk and/or balance adjustment parameter and the confidence thereof. The adjustment value may be in the form of a vector.
An exemplary determination rule may be: the greater the risk of abnormality, the greater the magnitude of adjustment of the balance adjustment parameter, and the lower the confidence, the greater the adjustment values (e.g., decrease values) at the pull-up speed, translation speed, lift-up speed, and pull-in speed are adjusted (e.g., decreased).
The balance adjustment parameters are parameters which need to be adjusted in order to keep the balance of the tower crane. For more description of the balance adjustment parameters, see fig. 4 and its associated description.
In some embodiments, the magnitude of the adjustment of the balance adjustment parameter may be related to the distance of movement of the horn on the tower crane boom and the added counterweight. For example, the greater the distance of movement of the luffing mechanism on the crane boom, the more counterweights are added, the greater the amplitude of its adjustment.
The confidence of the balance adjustment parameter refers to the degree of confidence of the balance adjustment parameter. The greater the confidence level, the higher the confidence level that the balance adjustment parameters are represented. In some embodiments, the confidence level may be related to the input data dimension of the parameter determination model, the accuracy of the parameter determination model's own predictions, and so on. For example, the more input data dimensions, the higher the model's own prediction accuracy, the greater the confidence. For more description of the parametric determination model, see fig. 4 and its associated description.
According to the embodiments of the present disclosure, by considering the abnormal risk and the adjustment amplitude of the balance adjustment parameter and the confidence coefficient thereof, the adjustment values of the pulling speed, the translation speed, the lifting speed and the introduction speed can be more finely adjusted, so that the system is more stable and efficient, and the loss caused by the abnormal risk is avoided.
And 240, responding to the abnormal risk meeting the preset warning condition, sending out a safety precaution and stopping operation.
The preset warning condition refers to a condition which needs to be met when a safety precaution is sent out. The preset alert condition may be preset by a user.
In some embodiments, the preset alert condition may include the abnormal risk value being greater than a preset threshold.
The safety precaution refers to precaution against safety risk. In some embodiments, the processor may issue security pre-warnings through the console, in the form of, but not limited to, sounds and images, etc.
In some embodiments, the processor may issue a safety warning and stop the job through the console in response to a condition that the risk of abnormality is greater than a preset threshold.
Some embodiments of the present disclosure facilitate real-time monitoring of the installation process and assessment of anomaly risk during installation of standard knots through the use of distributed monitoring devices. The operation parameters are adjusted based on abnormal risks, so that potential safety hazards can be found in time, the potential safety hazards are reduced, and the operation safety is improved.
FIG. 3 is an exemplary schematic diagram illustrating model-based determination of risk of anomalies according to some embodiments of the present description.
In some embodiments, the processor may determine the abnormal risk by an abnormal risk assessment model based on the monitoring data.
The abnormal risk assessment model may be a machine learning model. For example, a deep neural network (Deep Neural Networks, DNN) model, a convolutional neural network (Convolutional Neural Networks, CNN) model, or the like, or any combination thereof.
In some embodiments, the input of the abnormal risk assessment model may include monitoring data and the output may include abnormal risk.
In some embodiments, the anomaly risk assessment model may include a first image recognition layer 321, a second image recognition layer 322, a third image recognition layer 323, and an anomaly determination layer 324. In some embodiments, the first, second, and third image recognition layers 321, 322, and 323 may be CNNs; the anomaly determination layer 324 may be DNN.
In some embodiments, the input of the first image recognition layer 321 may be the image data 311 of the first preset point location, and the output may include the surface anomaly characteristic 331 of the first preset point location. The surface anomalies 331 of the first predetermined point location may include cracks, breaks, deformations of the main structure (e.g., main limb, abdominal limb, weld) to which the standard joint has been installed. The input of the first image recognition layer 321 may include image data acquired at one or more first preset points.
In some embodiments, the input of the second image recognition layer 322 may be the image data 312 of the second preset point location, and the output may include the component missing feature 341 of the second preset point location. The component missing feature 341 of the second preset point location may include deformation of a bolt, a nut, whether missing, or the like. Wherein the input of the second image recognition layer 322 may include image data acquired at one or more second preset points.
In some embodiments, the input of the third image recognition layer 323 may be the image data 313 of the third preset point location, and the output may include the fit abnormality feature 351 of the third preset point location. The third preset point location of the fit anomaly feature 351 may include a jacking beam and standard joint step fit condition. The input of the third image recognition layer 323 may include image data acquired at one or more third preset points.
In some embodiments, the inputs to the anomaly determination layer 324 may include a surface anomaly characteristic 331 of a first preset point location, a component missing characteristic 341 of a second preset point location, a fit anomaly characteristic 351 of a third preset point location, and ultrasonic data 314 of at least one preset point location, the output may be an anomaly risk 360. The at least one preset point location may include one or more first preset point locations, one or more second preset point locations, and one or more second preset point locations. In some embodiments, the at least one preset point location may also include other preset point locations than those described above.
See fig. 2 for further description of the first preset point location, the second preset point location and the third preset point location.
In some embodiments, the inputs to the anomaly determination layer further include the location of the at least one preset point location, the number of installed standard knots 315, and the scene characteristics 316.
The position of the preset point location refers to the position of the preset point location in each installed standard section. For example, the position of the preset point may be the number of standard nodes from bottom to top where a certain preset point is located.
In some embodiments, the location of the at least one preset point location may be determined by the first image recognition layer 321, the second image recognition layer 322, and the third image recognition layer 323. In some embodiments, the output of the first image recognition layer 321 may further include a standard node 332 where the first preset point is located, the output of the second image recognition layer 322 may further include a standard node 342 where the second preset point is located, and the output of the third image recognition layer 323 may further include a standard node 352 where the third preset point is located.
The scene features refer to features related to the tower crane and its environment. In some embodiments, the scene features may include tower crane features and environmental features. Scene features may be obtained by way of user input, etc.
Tower crane features may include features of ground foundations, roof structures, and individual standard sections. For example, the characteristics of a single standard knot may include the specification and weight of the single standard knot, etc. Environmental characteristics may refer to information related to the surrounding environment of the tower crane. Environmental characteristics may include wind level, whether it is raining, etc.
It should be noted that, the image data of the preset point location not only includes the image data collected by the image monitoring unit fixed on the preset point location, but also includes the image data collected by the image monitoring component of the unmanned aerial vehicle.
According to the embodiment of the specification, the accuracy and the reliability of abnormal risk prediction can be improved by considering the information such as the position of the preset point, the scene characteristics, the number of installed standard knots and the like, and more reliable support is provided for subsequent data analysis and processing.
In some embodiments, the outputs of the first, second, and third image recognition layers may be inputs to an anomaly determination layer, which may be trained jointly.
In some embodiments, the first training sample of the joint training comprises sample monitoring data, and the first label is a sample anomaly risk. The sample monitoring data may include sample image data of a first preset point of the sample, sample image data of a second preset point of the sample, sample image data of a third preset point of the sample, and sample ultrasound data of at least one preset point of the sample.
An exemplary joint training process includes: inputting sample image data of a first preset point position of a sample into a first image recognition layer to obtain surface abnormal characteristics of the first preset point position output by the first image recognition layer; inputting sample image data of a second preset point position of the sample into a second image recognition layer to obtain a part missing feature of the second preset point position output by the second image recognition layer; and inputting sample image data of a third preset point position of the sample into the third image recognition layer to obtain abnormal lamination characteristics of the third preset point position output by the third image recognition layer. And inputting the surface abnormal characteristics of the first preset point position, the part missing characteristics of the second preset point position and the laminating abnormal characteristics of the third preset point position serving as training sample data and the sample ultrasonic data of at least one sample preset point position into an abnormality determination layer to obtain an abnormality risk output by the abnormality determination layer. And constructing a loss function based on the abnormal risk output by the first label and the abnormal determination layer, and synchronously updating parameters of the first image recognition layer, the second image recognition layer, the third image recognition layer and the abnormal determination layer. And obtaining a trained first image recognition layer, a trained second image recognition layer, a trained third image recognition layer and a trained anomaly determination layer through parameter updating.
According to the method and the device for determining the abnormal risk, the monitoring data are processed through the abnormal risk assessment model, rules can be found out from a large number of tower crane operation data by utilizing the self-learning capability of the machine learning model, the association relation between the abnormal risk and the monitoring data is obtained, and the accuracy and the efficiency of determining the abnormal risk are improved.
FIG. 4 is an exemplary flow chart of balance determination shown in accordance with some embodiments of the present description. As shown in fig. 4, the process 400 includes the following steps. In some embodiments, the process 400 may be performed by an installation module.
Step 410, balance determination information in the installation process is acquired.
The balance determination information is information capable of indicating the balance of the roof structure. For example, the balance determination information may include information on whether the roof structure is balanced or not.
In some embodiments, the balance determination information may include at least laser data collected by the laser transceiver component. The laser transceiver component can comprise a laser emitting device, a laser receiving device and the like and is used for collecting laser data. The laser data may include whether to shift, the direction of shift, the angle of shift, etc.
In some embodiments, the balance determination information may include image data acquired by the image monitoring unit and/or an image monitoring component of the drone. The image data may be image data collected by an image monitoring unit configured at a part of the preset points, and/or image data collected by an image monitoring component of the unmanned aerial vehicle at a part of the preset points. For example, the partial preset point positions may be preset point positions capable of reflecting the current verticality of the top structure, preset point positions capable of reflecting the current levelness of the top structure, and the like. The details of the image monitoring unit and the image monitoring component of the drone may be seen in fig. 2 and its related content.
In some embodiments of the present disclosure, balance determination information is determined based on collected image data, so that a balance state in a tower crane installation process can be effectively determined, and operation risks are reduced. The balance judgment information obtained through part of preset point positions enables information to be collected more efficiently, and the operation efficiency and accuracy of the device are improved.
The balance determination information may be determined in a variety of ways. In some embodiments, the balance determination information may be continuously collected and stored by the relevant equipment during installation of the tower crane. For example, the balance determination information may be recorded every predetermined time. In some embodiments, the balance determination information may be determined and entered by a user.
Step 420, based on the balance determination information, determines the balance adjustment parameters in real time.
Balance adjustment parameters refer to parameters that need to be changed when adjusting the top structure to balance.
In some embodiments, the balance adjustment parameters may include a counterweight and a rest position of the horn. The rest position may refer to the position in which the horn should be when the top mechanism is adjusted to be balanced. The rest position may include a position of the horn on the lift arm.
The balance adjustment parameters may be determined in a number of ways. In some embodiments, the installation module may determine the balance adjustment parameters based on historical adjustment data. The history adjustment data comprises history balance judgment information and corresponding history balance adjustment parameters. For example, the current balance determination information may be compared with the history balance determination information in the history adjustment data, and the similarity between the current balance determination information and each history balance determination information may be determined, and the history balance adjustment parameter corresponding to the history balance determination information having the similarity greater than the threshold value may be used as the current balance adjustment parameter.
In some embodiments, the installation module may determine the balance adjustment parameters through a parameter determination model.
The parameter determination model may be a machine learning model, such as a convolutional neural network model, or the like.
In some embodiments, the inputs to the parameter determination model may include tower crane characteristics and balance determination information, and the outputs may be balance adjustment parameters. See fig. 3 for a more description of tower crane characteristics. In some embodiments, the input to the parameter determination model further includes environmental characteristics. See fig. 3 for a more description of environmental features.
In some embodiments, the model may be determined based on a plurality of second training samples with second labels. In some embodiments, the second training sample may be sample tower crane characteristics, sample balance determination information. In some embodiments, the second training sample may also include sample environmental features. In some embodiments, the second training sample may be read from a storage device storing a plurality of tower crane characteristics, balance determination information, and environmental characteristic data. In some embodiments, the second training sample may be obtained by active entry by the user. In some embodiments, the second tag may be the actual balance adjustment parameter. In some embodiments, the manner in which the identification is obtained may be based on historical data, based on manual annotations, and so forth.
In some embodiments of the present description, the balance adjustment parameters may be determined by a parameter determination model. The determination is performed based on a machine learning technology, so that the obtained balance adjustment parameters have higher accuracy based on more and richer characteristics, and the accuracy and the safety of the device are improved. By inputting the environmental characteristics into the model, the balance adjustment parameters are determined, the influence of uncontrollable factors such as the environment on the operation of the device can be fully considered, the result of the model is more accurate, and the working efficiency, accuracy and safety of the device are improved.
Step 430, controlling the luffing mechanism based on the balance adjustment parameter.
In some embodiments, the mounting module may control the configuration of the horn via the console and move it to the rest position based on the balance adjustment parameters.
In the jacking process, the balance of the tower crane is affected to a certain extent because the weight of the transported objects is added to the internal structure of the tower crane and the top of the tower crane is in motion. In some embodiments provided by the specification, the balance adjustment parameters are determined in real time by acquiring the balance judgment information in the installation process and based on the balance judgment information, and then the luffing mechanism is controlled based on the balance adjustment parameters, so that not only can the real-time monitoring of the operation process of the tower crane be realized, but also the real-time adjustment can be realized, the continuous and stable operation of the device is ensured, the stability and the safety of the device are improved, and the risk of safety accidents is reduced.
Some embodiments of the present description provide a standard knot mounting system, the system comprising: the pre-detection module is used for pre-detecting at least one mechanism in the top structure through a pre-detection device, and at least one mechanism at least comprises a jacking mechanism, an amplitude changing mechanism and an introduction mechanism; the installation module is used for responding to the first detection result of the pre-detection being qualified and receiving an installation starting instruction from the control console to execute the installation task of at least one standard section to be installed, wherein for each standard section to be installed in the at least one standard section to be installed, the corresponding sub-installation task is executed, and the installation module comprises: responding to a first instruction obtained from the control console, controlling an amplitude variation mechanism to lift and move the standard section to be installed according to the lifting speed and the translation speed respectively, and placing the standard section on the introducing mechanism; in response to a second instruction obtained from the control console, controlling a jacking mechanism to jack the sleeve frame according to jacking parameters, wherein the sleeve frame is configured in the top structure; responding to a third instruction obtained from the control console, controlling the introduction mechanism to place the standard section to be installed above the target standard section according to the introduction speed, and controlling the introduction mechanism to connect the standard section to be installed with the target standard section; and performing post-detection on the joint of the standard section to be installed and the target standard section, and sending prompt information to the control console based on a second detection result of the post-detection.
Some embodiments of the present specification provide a standard knot installation apparatus comprising at least one memory and at least one processor, the at least one memory for storing computer instructions; at least one processor is configured to execute computer instructions to implement the standard knot installation method of any of the embodiments of the present specification.
Some embodiments of the present description provide a computer-readable storage medium storing computer instructions that, when executed by a computer, implement the standard knot installation method of any one of the embodiments of the present description.
While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting. Although not explicitly described herein, various modifications, improvements, and adaptations to the present disclosure may occur to one skilled in the art. Such modifications, improvements, and modifications are intended to be within the scope of the present disclosure.
Meanwhile, the specification uses specific words to describe the embodiments of the specification. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the present description. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the present description may be combined as suitable.
Furthermore, the order in which the elements and sequences are processed, the use of numerical letters, or other designations in the description are not intended to limit the order in which the processes and methods of the description are performed unless explicitly recited in the claims. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of various examples, it is to be understood that such details are merely illustrative and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements included within the spirit and scope of the embodiments of the present disclosure. For example, while the system components described above may be implemented by hardware devices, they may also be implemented solely by software solutions, such as installing the described system on an existing server or mobile device.
Likewise, it should be noted that in order to simplify the presentation disclosed in this specification and thereby aid in understanding one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure, however, is not intended to imply that more features than are presented in the claims are required for the present description. Indeed, less than all of the features of a single embodiment disclosed above.
It is noted that, if the description, definition, and/or use of a term in an attached material in this specification does not conform to or conflict with what is described in this specification, the description, definition, and/or use of the term in this specification controls.
Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments of this specification. Other variations are possible within the scope of this description. Thus, by way of example, and not limitation, alternative configurations of embodiments of the present specification may be considered as consistent with the teachings of the present specification. Accordingly, the embodiments of the present specification are not limited to only the embodiments explicitly described and depicted in the present specification.

Claims (10)

1. A method of standard knot installation, the method performed by a processor, comprising:
pre-detecting at least one mechanism in the top structure through a pre-detection device, wherein the at least one mechanism at least comprises at least one of a jacking mechanism, an amplitude changing mechanism and an introduction mechanism;
and executing the installation task of at least one standard section to be installed in response to the first detection result of the pre-detection being qualified and receiving an installation starting instruction from a console, wherein for any standard section to be installed in the at least one standard section to be installed, executing a corresponding sub-installation task comprises the following steps:
Responding to a first instruction obtained from the control console, controlling the amplitude variation mechanism to hoist and move the standard section to be installed according to the lifting speed and the translational speed respectively, and placing the standard section to be installed on the introducing mechanism;
in response to a second instruction obtained from the control console, controlling the jacking mechanism to jack up a sleeve frame according to jacking parameters, wherein the sleeve frame is configured in the top structure;
responding to a third instruction acquired from the control console, controlling the introduction mechanism to place the standard section to be installed above a target standard section according to the introduction speed, and controlling the introduction mechanism to connect the standard section to be installed with the target standard section;
post-detecting the joint of the standard section to be installed and the target standard section;
based on the second detection result of the post detection, sending prompt information to the console;
and, during execution of the sub-installation task,
monitoring an installation process based on a distributed monitoring device to obtain monitoring data, wherein the distributed monitoring device at least comprises a monitoring data acquisition unit deployed at one or more preset points, the monitoring data acquisition unit comprises an image monitoring unit and an ultrasonic monitoring unit, the monitoring data comprises image data and ultrasonic data, at least one newly added preset point is added in response to the point updating condition being met, and the monitoring data acquisition unit is installed on the at least one newly added preset point;
Based on the monitoring data, assessing an abnormal risk by an abnormal risk assessment model, the abnormal risk assessment model being a machine learning model, the abnormal risk assessment model comprising a first image recognition layer, a second image recognition layer, a third image recognition layer and an abnormality determination layer,
the input of the first image recognition layer comprises image data of a first preset point position, the output comprises surface abnormal characteristics of the first preset point position,
the input of the second image recognition layer comprises image data of a second preset point location, the output comprises part missing features of the second preset point location,
the input of the third image recognition layer comprises image data of a third preset point position, the output comprises abnormal laminating characteristics of the third preset point position,
the input of the anomaly determination layer comprises surface anomaly characteristics of the first preset point, component missing characteristics of the second preset point, laminating anomaly characteristics of the third preset point, ultrasonic data of at least one preset point, positions of the at least one preset point, the number of installed standard nodes and scene characteristics, and the output comprises anomaly risks;
adjusting at least one of the pull-up speed, the translation speed, the jack-up speed, and the introduction speed based on the abnormal risk; and
And responding to the abnormal risk meeting a preset warning condition, sending out a safety early warning and stopping operation.
2. The method of claim 1, wherein the jacking parameters include at least a jacking speed, a jacking height.
3. The method of claim 2, wherein the distributed monitoring device comprises at least an unmanned aerial vehicle monitoring unit, the unmanned aerial vehicle monitoring unit being comprised of at least one unmanned aerial vehicle, the monitoring data comprising at least data collected by the at least one unmanned aerial vehicle at a set cruising route.
4. The method of claim 1, wherein the method further comprises: during the execution of the sub-installation task,
acquiring balance judgment information in the installation process;
determining balance adjustment parameters in real time based on the balance judgment information, wherein the balance judgment information at least comprises laser data collected by a laser receiving and transmitting component, and the balance adjustment parameters comprise a counterweight and a rest position of the amplitude variation mechanism;
and controlling the amplitude variation mechanism based on the balance adjustment parameter.
5. A modular segment mounting system, the system comprising:
the pre-detection module is used for pre-detecting at least one mechanism in the top structure through a pre-detection device, and the at least one mechanism at least comprises a jacking mechanism, an amplitude changing mechanism and an introduction mechanism;
The installation module is configured to execute an installation task of at least one standard section to be installed in response to the first detection result of the pre-detection being qualified and an installation start instruction being received from a console, where for each standard section to be installed in the at least one standard section to be installed, execute a corresponding sub-installation task, including:
responding to a first instruction obtained from the control console, controlling the amplitude variation mechanism to hoist and move the standard section to be installed according to the lifting speed and the translational speed respectively, and placing the standard section to be installed on the introducing mechanism;
in response to a second instruction obtained from the control console, controlling the jacking mechanism to jack up a sleeve frame according to jacking parameters, wherein the sleeve frame is configured in the top structure;
responding to a third instruction acquired from the control console, controlling the introduction mechanism to place the standard section to be installed above a target standard section according to the introduction speed, and controlling the introduction mechanism to connect the standard section to be installed with the target standard section;
post-detecting the joint of the standard section to be installed and the target standard section, and sending prompt information to the control console based on a second detection result of the post-detection;
And, during execution of the sub-installation task,
monitoring an installation process based on a distributed monitoring device to obtain monitoring data, wherein the distributed monitoring device at least comprises a monitoring data acquisition unit deployed at one or more preset points, the monitoring data acquisition unit comprises an image monitoring unit and an ultrasonic monitoring unit, the monitoring data comprises image data and ultrasonic data, at least one newly added preset point is added in response to the point updating condition being met, and the monitoring data acquisition unit is installed on the at least one newly added preset point;
based on the monitoring data, assessing an abnormal risk by an abnormal risk assessment model, the abnormal risk assessment model being a machine learning model, the abnormal risk assessment model comprising a first image recognition layer, a second image recognition layer, a third image recognition layer and an abnormality determination layer,
the input of the first image recognition layer comprises image data of a first preset point position, the output comprises surface abnormal characteristics of the first preset point position,
the input of the second image recognition layer comprises image data of a second preset point location, the output comprises part missing features of the second preset point location,
The input of the third image recognition layer comprises image data of a third preset point position, the output comprises abnormal laminating characteristics of the third preset point position,
the input of the anomaly determination layer comprises surface anomaly characteristics of the first preset point, component missing characteristics of the second preset point, laminating anomaly characteristics of the third preset point, ultrasonic data of at least one preset point, positions of the at least one preset point, the number of installed standard nodes and scene characteristics, and the output comprises anomaly risks;
adjusting at least one of the pull-up speed, the translation speed, the jack-up speed, and the introduction speed based on the abnormal risk; and
and responding to the abnormal risk meeting a preset warning condition, sending out a safety early warning and stopping operation.
6. The system of claim 5, wherein the jacking parameters include at least a jacking speed, a jacking height.
7. The system of claim 6, wherein the distributed monitoring device comprises at least an unmanned aerial vehicle monitoring unit, the unmanned aerial vehicle monitoring unit being comprised of at least one unmanned aerial vehicle, the monitoring data comprising at least data collected by the at least one unmanned aerial vehicle at a set cruising route.
8. The system of claim 5, wherein the mounting module is further to: during the execution of each sub-case task,
acquiring balance judgment information in the installation process;
determining balance adjustment parameters in real time based on the balance judgment information, wherein the balance judgment information at least comprises laser data collected by a laser receiving and transmitting component, and the balance adjustment parameters comprise a counterweight and a rest position of the amplitude variation mechanism;
and controlling the amplitude variation mechanism based on the balance adjustment parameter.
9. A standard knot mounting device, the device comprising at least one processor and at least one memory;
the at least one memory is configured to store computer instructions;
the at least one processor is configured to execute at least some of the computer instructions to implement the standard knot installation method of any one of claims 1-4.
10. A computer-readable storage medium storing computer instructions that, when read by a computer in the storage medium, the computer performs the standard knot installation method of any one of claims 1-4.
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CN205772976U (en) * 2016-05-24 2016-12-07 江西飞达电气设备有限公司 A kind of tower crane lifting guide support adding fall joint pre-alarming device
CN113734995A (en) * 2021-06-28 2021-12-03 廊坊中建机械有限公司 Full-automatic jacking and joint adding tower crane
CN115010014A (en) * 2022-05-12 2022-09-06 北京建筑大学 Tower crane intelligent jacking monitoring control method and system based on ROS platform

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN205772976U (en) * 2016-05-24 2016-12-07 江西飞达电气设备有限公司 A kind of tower crane lifting guide support adding fall joint pre-alarming device
CN113734995A (en) * 2021-06-28 2021-12-03 廊坊中建机械有限公司 Full-automatic jacking and joint adding tower crane
CN115010014A (en) * 2022-05-12 2022-09-06 北京建筑大学 Tower crane intelligent jacking monitoring control method and system based on ROS platform

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