CN115072598A - Tower crane monitoring method and device based on artificial intelligence - Google Patents
Tower crane monitoring method and device based on artificial intelligence Download PDFInfo
- Publication number
- CN115072598A CN115072598A CN202211003108.7A CN202211003108A CN115072598A CN 115072598 A CN115072598 A CN 115072598A CN 202211003108 A CN202211003108 A CN 202211003108A CN 115072598 A CN115072598 A CN 115072598A
- Authority
- CN
- China
- Prior art keywords
- tower crane
- monitored
- early warning
- data
- monitoring
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
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
- B66C23/88—Safety gear
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- 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 utility model provides a tower crane monitoring method and device based on artificial intelligence, and relates to the technical field of tower crane safety monitoring. The specific scheme is as follows: in response to the obtained attribute information of the tower crane to be monitored, configuring a safety interval distance between the tower crane to be monitored and each current adjacent tower crane based on the attribute information; monitoring the tower crane to be monitored in response to the completion of the configuration of the safety spacing distance so as to obtain tower crane data of the tower crane to be monitored in real time; generating early warning events corresponding to the tower crane to be monitored at any moment according to tower crane data of the tower crane to be monitored at any moment and preset early warning indexes; and sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a proctoring person for displaying. Therefore, the tower crane safety major hazard source can be monitored in real time, various data overall process records during tower crane operation are recorded and danger early warning is provided, real remote operation monitoring and early warning at different places are achieved, and the effect of simple screen monitoring is surpassed.
Description
Technical Field
The disclosure relates to the technical field of tower crane safety monitoring, in particular to a tower crane monitoring method and device based on artificial intelligence.
Background
Along with the development of the society, the building industry has leaped forward in recent years, all high-rise buildings can use the tower crane, along with the increasing engineering quantity of buildings, the working time of the tower crane is gradually prolonged, and if the potential safety hazards of some tower cranes cannot be found in time, the potential safety hazards can be brought to the construction site.
Therefore, how to monitor and early warn the tower crane in real time is a problem which needs to be solved currently.
Disclosure of Invention
The disclosure provides a tower crane monitoring method and device based on artificial intelligence.
According to a first aspect of the disclosure, a tower crane monitoring method based on artificial intelligence is provided, which includes:
responding to the obtained attribute information of the tower crane to be monitored, and configuring the safety interval distance between the tower crane to be monitored and each current adjacent tower crane based on the attribute information;
responding to the completion of the configuration of the safety spacing distance, monitoring the tower crane to be monitored so as to obtain the tower crane data of the tower crane to be monitored in real time;
generating an early warning event corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored at any moment and preset early warning indexes;
and sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person for display in an associated manner.
According to the second aspect of the present disclosure, a tower crane monitoring device based on artificial intelligence is provided, including:
the configuration module is used for responding to the acquired attribute information of the tower crane to be monitored and configuring the safety spacing distance between the tower crane to be monitored and each current adjacent tower crane based on the attribute information;
the monitoring module is used for responding to the completion of the configuration of the safety spacing distance, monitoring the tower crane to be monitored, and acquiring the tower crane data of the tower crane to be monitored in real time;
the generating module is used for generating an early warning event corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored at any moment and preset early warning indexes;
and the early warning module is used for sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person in an associated manner for displaying.
According to a third aspect of the present disclosure, there is provided an electronic device comprising:
memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the method of any of the first aspect are implemented when the program is executed by the processor.
In a fourth aspect, the present application provides a computer program product comprising a computer program and/or instructions, wherein the computer program and/or instructions, when executed by a processor, implement the steps of the method of any of the first aspects.
The following beneficial effects can be achieved through the present disclosure:
in the embodiment of the disclosure, firstly, in response to acquiring the attribute information of the tower crane to be monitored, based on the attribute information, configuring the safety interval distance between the tower crane to be monitored and each adjacent current tower crane, then, in response to the completion of the configuration of the safety interval distance, monitoring the tower crane to be monitored so as to acquire the tower crane data of the tower crane to be monitored in real time, and then, according to any moment, generating any moment according to the tower crane data of the tower crane to be monitored and each preset early warning index, generating any moment according to the early warning event corresponding to the tower crane to be monitored, and then, sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person for display. From this, can all carry out real time monitoring to tower crane safety great danger source, various data overall process record during to the tower crane operation to provide dangerous early warning, and will the early warning incident arbitrary moment and the attribute information correlation of the tower crane of waiting to monitor is sent and is shown in presetting the terminal display screen of supervision personnel, thereby can reach real long-range strange land operation control and early warning, surpass simple screen monitoring effect, advance the emergence of diagnosis prevention incident, provide the technological basis for the maintenance, the transformation, the supervision of tower crane relevant part, guarantee the safe operation of tower crane.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a flow chart of a tower crane monitoring method based on artificial intelligence provided by an embodiment of the disclosure;
FIG. 2 is a flow chart of a tower crane monitoring method based on artificial intelligence provided according to yet another embodiment of the present disclosure;
FIG. 3 is a structural block diagram of a tower crane monitoring device based on artificial intelligence provided in an embodiment of the present disclosure;
fig. 4 is a block diagram of an electronic device for implementing an artificial intelligence-based tower crane monitoring method according to an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of embodiments of the present disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The tower crane monitoring method and device based on artificial intelligence according to the embodiments of the present disclosure are described below with reference to the accompanying drawings.
The tower crane monitoring method based on artificial intelligence can be executed by the tower crane monitoring device based on artificial intelligence, and the device can be realized by software and/or hardware and can also be executed by the electronic equipment provided by the disclosure. The tower crane monitoring method based on artificial intelligence provided by the present disclosure is executed by the tower crane monitoring device based on artificial intelligence provided by the present disclosure, and is not limited by the present disclosure, and is hereinafter referred to as "device" for short.
Fig. 1 is a schematic flow diagram of a tower crane monitoring method based on artificial intelligence according to an embodiment of the disclosure.
As shown in FIG. 1, the application provides a tower crane monitoring method based on artificial intelligence, wherein the method comprises the following steps:
The attribute information at least comprises the equipment number, the equipment model, the qualification information, the driver information, the inspection record, the arm length, the lifting capacity, the tower height and the like of the tower crane to be monitored, and is not limited herein. The tower crane monitoring device has the advantages that the tower crane driver information and the association of a tower crane to be monitored can be bound, so that the information such as a certificate photo of the tower crane driver corresponding to the equipment number can be inquired and obtained in the device through the equipment number of the tower crane to be monitored, and the tower crane to be monitored can be effectively supervised from personnel conveniently.
It should be noted that the tower crane to be monitored may be a hoisting device used in a construction site, also called a "tower crane", and is extended (high) section by section (referred to as a "standard section") to hoist construction raw materials such as reinforcing steel bars, wooden ridges, concrete, steel pipes and the like for construction.
Wherein, adjacent tower crane can be for waiting to monitor the tower crane near the current position of tower crane, for example can be for should waiting to monitor each tower crane in near certain extent of tower crane.
Wherein, safe interval distance can be for waiting to monitor the safe distance between tower crane and the adjacent tower crane.
It should be noted that, if the spacing distance between the tower crane to be monitored and at least one of the adjacent tower cranes does not satisfy the safety spacing distance, the danger of collision between the tower crane to be monitored and each of the adjacent tower cranes occurs, which is very unsafe. And because different tower crane attribute information is usually different, for example the arm length is different, and the height is different, etc. therefore can be according to the attribute information of waiting to monitor the tower crane, confirm the equipment model of waiting to monitor the tower crane to can be for waiting to monitor the safety interval distance of configuration between tower crane and the adjacent tower crane.
And step 102, responding to the completion of the configuration of the safety spacing distance, monitoring the tower crane to be monitored so as to acquire the tower crane data of the tower crane to be monitored in real time.
Specifically, after the safety interval distance between the tower crane to be monitored and the adjacent tower crane is configured, the device can monitor the tower crane to be monitored based on a plurality of measuring points on the tower crane to be monitored, so that tower crane data of each position area of the tower crane to be monitored can be acquired, and the monitoring of the tower crane to be monitored is very comprehensive and fine.
The tower crane data at least comprises information such as rotation, amplitude, height of a lifting hook, lifting weight, torque percentage, inclination angle, wind speed and online state, and is not limited herein.
For example, a bracket can be arranged between an upper cross beam and a lower cross beam of two adjacent standard knots of the tower crane to be monitored; the bracket and the lower cross beam are relatively fixed, and a first gap is kept between the bracket and the bottom of the upper cross beam; and fixing a measuring point at the bottom of the support or the outer extending area of the bottom of the support so as to acquire tower crane data through the measuring point. It will be appreciated that there are a large number of components on the tower crane, each of which contains a number of parts, such as bolts, shock mounts, runners, brackets, protective fairings, and the like. Therefore, measuring points can be arranged at each position of the tower crane to be monitored in advance to acquire tower crane data of the tower crane to be monitored.
Wherein, tower crane data can be that the sensor directly measures, perhaps, also can be the image of gathering by image acquisition unit, later, then can carry out analysis and discernment to the image to the steel construction of waiting to monitor the tower crane that contains in the image or the state of other spare parts carry out analysis and judgement.
Specifically, the device can include cameras arranged at each measuring point, the camera unit is arranged at the tail end of the working arm of the tower crane and used for carrying out video recording on the working condition of the working arm and sensing the sensor, and for example, the device can comprise a radio frequency wireless corner sensor, a radio frequency wireless height sensor, a radio frequency wireless wind speed sensor, a radio frequency wireless amplitude sensor, a radio frequency wireless inclination angle sensor and a radio frequency wireless weight sensor. In addition, the device can also comprise a wireless network, the wireless network comprises a field base station and a coordinator, the field base station is arranged in the tower crane area, and the coordinator is arranged in the transmitting range of the field base station, collects the tower crane operation scene information and transmits the information through the wireless network.
From this, can acquire in real time and treat that monitoring tower crane is clear, comprehensive, reliable tower crane data, for the operating mode and the early warning of the monitoring tower crane of later control treat that the guarantee and the support on the data are provided, the supervision personnel of also being convenient for treat that monitoring tower crane carries out better supervision to timely acquisition treats the operation scene information of monitoring tower crane scene, and the real-time is stronger, and the position is more.
As a possible implementation manner, the device can also perform data desensitization on tower crane data of a tower crane to be monitored, then upload the tower crane data subjected to data desensitization to a tower crane data analysis module, and then perform fault identification analysis on the tower crane data subjected to data desensitization based on the tower crane data analysis module to obtain tower crane fault characteristics, wherein the tower crane data analysis module comprises a tower crane data analysis model generated by historical reference tower crane data training, and then perform maintenance and management on the tower crane to be monitored based on the tower crane fault characteristics.
Specifically, data desensitization is carried out on tower crane data and then the data desensitization is carried out, wherein the data desensitization refers to deformation of real data of certain wind power sensitive information through desensitization rules, reliable protection of tower crane sensitive private data is achieved, and data transmission safety is guaranteed. And transmitting the data to a tower crane data analysis module for analysis, wherein the tower crane data analysis module is a basic module for analyzing the acquired data so as to realize identification control of the tower crane fault information.
Specifically, the device can be based on tower crane data analysis module and carry out fault identification analysis to each type of data in the tower crane data. The method comprises the steps of firstly classifying tower crane data information through a tower crane characteristic decision tree, constructing the tower crane characteristic decision tree through tower crane characteristic information, and obtaining tower crane classification characteristic information, wherein the tower crane classification characteristic information is a tower crane characteristic classification result and comprises size specification characteristics, material characteristics, scene characteristics and the like of each component. The different types of tower cranes have different fault identification modes, so that the tower crane calibration coefficients are determined according to the classification characteristic information of the tower cranes, and the tower crane calibration coefficients are used for selecting the identification model when the fault calibration is carried out on the tower cranes.
And then, based on tower crane calibration coefficients, calling a tower crane fault identification support vector machine from a tower crane fault identification model library, wherein the tower crane identification support vector machine is a fault identification model suitable for the tower crane. And inputting the tower crane data information into a tower crane fault identification support vector machine to obtain a training output result of the model, namely the tower crane fault characteristics. Through classifying and identifying the fault data, the fault data of the tower crane can be accurately and effectively acquired, and the accuracy and effectiveness of the tower crane data processing result can be further improved.
Specifically, according to the trained tower crane data analysis model, fault analysis is performed on the tower crane to be monitored, and corresponding tower crane fault characteristics, such as whether the tower crane works safely, fault types, fault severity, fault influence range and the like, are obtained. And maintenance management, such as maintenance measures of overhauling, replacing, diagnosing, transforming and the like, is carried out on the wind turbine generator based on the fault characteristics of the tower crane.
103, generating early warning events corresponding to the tower crane to be monitored at any moment according to tower crane data of the tower crane to be monitored at any moment and preset early warning indexes.
It should be noted that the early warning index is an index that monitors key features of the tower crane to be monitored in the operation process and sends out a warning by comparing normal values, such as an arm length distance early warning index, an amplitude early warning index, a wind speed early warning index, a hoisting weight early warning index and the like, and before warning, that is, when dangers are continuously gathered, some abnormal changes occur, so that the possibility of occurrence of the danger of the tower crane to be monitored can be measured by observing the abnormal changes occurring in the early warning index.
Wherein, the early warning index comprises a corresponding early warning threshold value.
The early warning events at least comprise tower crane multi-machine anti-collision early warning, tower crane overload early warning and tower crane amplitude limit early warning.
Optionally, the device can determine each early warning index corresponding to the tower crane to be monitored according to the attribute information of the tower crane to be monitored based on the preset mapping relation.
It should be noted that, for different types of tower cranes, due to different attribute information, the rotation, amplitude, height of the lifting hook, lifting weight, torque percentage, inclination angle and arm length are different, so that the early warning indexes can be different. For example, the amplitude early warning threshold values are different, and the hoisting weight early warning threshold values are different.
In this disclosure, the device can be in advance after the tower crane data of the tower crane of waiting to monitor is obtained, for waiting to monitor the tower crane setting corresponding early warning index to and the early warning threshold value that every early warning index corresponds.
Specifically, the device can generate the early warning event corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored at any moment and each preset early warning index.
The early warning event can be an event generated when any one of wind speed, load, gyration, amplitude and height information, the distance between tower cranes and the like exceeds an early warning threshold value. Because the early warning threshold values of tower cranes to be monitored with different attributes are different, the early warning threshold values are not limited, and can be set according to actual experience.
Optionally, when any early warning event is generated, the device can automatically suspend the dangerous action of the tower crane corresponding to the early warning event, and alarm and early warn based on the acousto-optic equipment.
And step 104, correlating the early warning event, any moment and the attribute information of the tower crane to be monitored and sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person for displaying.
Optionally, the device can associate the early warning event corresponding to the tower crane to be monitored, any moment when the early warning event occurs, and the attribute information of the tower crane to be monitored through the wireless network, and send the attribute information to the terminal display screen of the preset supervision staff for displaying.
The preset supervisor may be at least one project manager determined in advance.
It should be noted that the preset supervisor may have a corresponding terminal device and a corresponding terminal display screen. In the present disclosure, the type of the terminal device and the corresponding terminal display screen is not limited, and may be, for example, a liquid crystal computer, a tablet, a mobile phone, a monitor display, and the like.
Particularly, the safety data of the operation condition of the tower crane to be monitored and the early warning information can be sent to a GIS visual monitoring platform in real time through remote high-speed wireless data transmission, and a short message can be automatically triggered to give an alarm to related personnel (preset supervision personnel) when the alarm is given, so that real-time dynamic remote monitoring, remote alarm and remote notification are realized, and the safety monitoring of the tower crane to be monitored becomes open real-time dynamic monitoring.
Optionally, the device can make safe alarm and evade dangerous measure according to the information of gathering in real time based on the controller, simultaneously give the server relevant safety information transmission, the operation condition of every tower crane in the network is looked up to the supervision department accessible client of tower crane, in time supervision to tower crane use and action has been ensured from the technical means, take precautions against conscientiously, dangerous factor and potential safety hazard in the management and control equipment operation process, take precautions against and reduced tower crane building construction occurence of failure effectively.
In the embodiment of the disclosure, firstly, in response to acquiring the attribute information of the tower crane to be monitored, based on the attribute information, configuring the safety interval distance between the tower crane to be monitored and each adjacent current tower crane, then, in response to the completion of the configuration of the safety interval distance, monitoring the tower crane to be monitored so as to acquire the tower crane data of the tower crane to be monitored in real time, and then, according to any moment, generating any moment according to the tower crane data of the tower crane to be monitored and each preset early warning index, generating any moment according to the early warning event corresponding to the tower crane to be monitored, and then, sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person for display. Therefore, the tower crane safety major hazard source can be monitored in real time, various data overall process records are carried out during tower crane operation, danger early warning is provided, and the early warning event, any moment and attribute information of the tower crane to be monitored are sent to a terminal display screen of a preset supervision person in an associated mode to be displayed, so that real remote operation monitoring and early warning can be achieved, and the monitoring effect of a simple screen is surpassed.
Fig. 2 is a schematic flow diagram of a tower crane monitoring method based on artificial intelligence according to another embodiment of the disclosure.
As shown in fig. 2, the present application provides another tower crane monitoring method based on artificial intelligence, wherein the method includes:
And 202, in response to the completion of the configuration of the safety interval distance, monitoring the tower crane to be monitored so as to acquire the tower crane data of the tower crane to be monitored in real time.
And 203, generating an early warning event corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored at any moment and each preset early warning index.
The specific implementation manners of steps 201, 202, and 203 may refer to the above embodiments, and are not limited herein.
The first time can be the total times of the early warning events of the tower crane to be monitored from the beginning of the tower crane to be monitored to the present, namely the sum of the times of the early warning events of various types.
It should be noted that there are many types of the early warning events, and therefore the device records the occurrence frequency of each type of the early warning event, so that the occurrence frequency of each type of the early warning event, that is, the second occurrence frequency, can be obtained.
For example, if 18 early warning events occur in total from the time T0 when the tower crane to be monitored starts to be monitored to the current time T1, the first time is 18, if the early warning event of the type a occurs 8 times, the early warning event of the type B occurs 9 times, and the early warning event of the type C occurs 1 time in the 18 early warning events, the second time corresponding to the early warning event of the type a is 8, the second time corresponding to the early warning event of the type B is 9, and the second time corresponding to the early warning event of the type C is 1.
The designated period may be a preset operation time period, such as 3 months, 4 months, 5 months to 8 months, etc., and is not limited herein.
Wherein the first threshold may be a threshold of the first number of times.
Wherein, first danger warning information is used for warning and predetermines the supervision personnel, treats that the tower crane that monitors is whole to have serious danger at present, breaks down very probably, need shut down the rectification, even change.
It can be understood that if the first number of early warning events occurring to the tower crane to be monitored in a specified period is greater than a first threshold value, the problem of the tower crane to be monitored is serious, the problem often occurs, the engineering quality is poor, the tower crane to be monitored needs to be shut down at the moment so as to perform all-around rectification and maintenance, and first danger warning information is sent to the terminal equipment of a preset supervision person.
And step 206, in response to that the second time is greater than a second threshold value in a specified period, stopping the tower crane to be monitored, and sending second danger warning information to terminal equipment of preset supervision personnel, wherein the second danger warning information includes the type of the early warning event.
Wherein the second threshold may be a threshold of the second number of times.
It should be noted that, since the first number is the total number of times of various types of early warning events occurring on the tower crane to be monitored, and the second number is the number of times of any type of early warning event occurring on the tower crane to be monitored, the first threshold value and the second threshold value are generally different, and the second threshold values of different types of early warning events are also generally different.
Wherein, dangerous warning information of second is used for warning predetermines the prisoner, treat that the tower crane of monitoring often produces the early warning incident of certain type easily at present, then predetermine the fault parts that the prisoner can treat the monitoring tower crane at present according to the type location of early warning incident to and the weak region of trouble, thereby predetermine the prisoner and can learn that this region has serious danger, break down very probably, need shut down the rectification, so that treat the monitoring tower crane and avoid appearing this type's risk later.
And step 207, sending the early warning event, the any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person for display in an associated manner.
It should be noted that, the specific implementation manner of step 207 may refer to the foregoing embodiments, and is not limited herein.
In the embodiment of the disclosure, firstly responding to the acquisition of attribute information of a tower crane to be monitored, configuring a safety interval distance between the tower crane to be monitored and each adjacent current tower crane based on the attribute information, then responding to the completion of the configuration of the safety interval distance, monitoring the tower crane to be monitored so as to acquire tower crane data of the tower crane to be monitored in real time, then generating an early warning event corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored and each preset early warning index at any moment, then recording a first number of times that the early warning event is triggered by the current tower crane to be monitored and a second number of times that any type of early warning event is triggered by the tower crane to be monitored, and then responding to the stop of the tower crane to be monitored when the first number is greater than a first threshold value in a specified period, and sending first danger warning information to the terminal equipment of the preset supervision personnel, then responding to the condition that the second time is greater than a second threshold value in a specified period, stopping the tower crane to be monitored, sending second danger warning information to the terminal equipment of the preset supervision personnel, wherein the second danger warning information comprises the type of the early warning event, and then sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of the preset supervision personnel in a correlated mode for displaying. From this, can trigger according to treating the monitoring tower crane the first number of times of early warning incident, and treat the second number of monitoring tower crane triggering the early warning incident of arbitrary type, treat the monitoring tower crane and carry out hierarchical early warning, can make more meticulously predetermineeing the supervisor and treat the monitoring tower crane and carry out safety precaution, guarantee construction safety improves the engineering quality to for the maintenance of tower crane relevant part, reform transform, supervise provide the technical basis, guarantee tower crane safe operation.
Fig. 3 is a schematic structural diagram of a tower crane monitoring device based on artificial intelligence according to an embodiment of the disclosure.
As shown in fig. 3, this tower crane monitoring devices 300 based on artificial intelligence includes:
the configuration module 310 is configured to, in response to obtaining attribute information of a tower crane to be monitored, configure a safety interval distance between the tower crane to be monitored and each current adjacent tower crane based on the attribute information;
the monitoring module 320 is configured to monitor the tower crane to be monitored in response to completion of configuration of the safety separation distance, so as to obtain tower crane data of the tower crane to be monitored in real time;
the generating module 330 is configured to generate an early warning event corresponding to the tower crane to be monitored at any time according to the tower crane data of the tower crane to be monitored at any time and preset early warning indexes;
and the early warning module 340 is used for sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person in an associated manner for displaying.
Preferably, the attribute information at least comprises the equipment number, the equipment model, the qualification information, the driver information, the inspection record, the arm length, the lifting capacity and the tower height of the tower crane to be monitored;
the tower crane data at least comprises rotation, amplitude, height of a lifting hook, lifting weight, torque percentage, inclination angle, wind speed and online state;
the early warning events at least comprise tower crane multi-machine anti-collision early warning, tower crane overload early warning and tower crane amplitude limiting early warning.
Preferably, the generating module is further configured to:
and determining each early warning index corresponding to the tower crane to be monitored according to the attribute information of the tower crane to be monitored based on a preset mapping relation.
Preferably, the generating module is further configured to:
recording a first number of times that the current tower crane to be monitored triggers the early warning event and a second number of times that the tower crane to be monitored triggers any type of early warning event;
in response to the fact that the first time number is larger than a first threshold value in a specified period, stopping the tower crane to be monitored, and sending first danger warning information to terminal equipment of preset supervision personnel;
and in response to the fact that the second number is larger than a second threshold value in a specified period, stopping the tower crane to be monitored, and sending second danger warning information to terminal equipment of preset supervision personnel, wherein the second danger warning information comprises the type of the early warning event.
Preferably, the monitoring module is further configured to:
carrying out data desensitization on tower crane data of the tower crane to be monitored;
uploading tower crane data subjected to data desensitization to a tower crane data analysis module;
fault identification analysis is carried out on the tower crane data after the data desensitization based on the tower crane data analysis module to obtain the fault characteristics of the tower crane,
the tower crane data analysis module comprises a tower crane data analysis model generated through historical reference tower crane data training;
and maintaining and managing the tower crane to be monitored based on the tower crane fault characteristics.
In the embodiment of the disclosure, firstly, in response to acquiring the attribute information of the tower crane to be monitored, based on the attribute information, configuring the safety interval distance between the tower crane to be monitored and each adjacent current tower crane, then, in response to the completion of the configuration of the safety interval distance, monitoring the tower crane to be monitored so as to acquire the tower crane data of the tower crane to be monitored in real time, and then, according to any moment, generating any moment according to the tower crane data of the tower crane to be monitored and each preset early warning index, generating any moment according to the early warning event corresponding to the tower crane to be monitored, and then, sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person for display. From this, can all carry out real time monitoring to tower crane safety great danger source, various data overall process record during to the tower crane operation to provide dangerous early warning, and will the early warning incident arbitrary moment and the attribute information correlation of the tower crane of waiting to monitor is sent and is shown in presetting the terminal display screen of supervision personnel, thereby can reach real long-range strange land operation control and early warning, surpass simple screen monitoring effect, advance the emergence of diagnosis prevention incident, provide the technological basis for the maintenance, the transformation, the supervision of tower crane relevant part, guarantee the safe operation of tower crane.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 4 shows a schematic block diagram of an example electronic device 400 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 4, the apparatus 400 includes a computing unit 401 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 402 or a computer program loaded from a storage unit 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the device 400 can also be stored. The calculation unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
A number of components in device 400 are connected to I/O interface 405, including: an input unit 406 such as a keyboard, a mouse, or the like; an output unit 407 such as various types of displays, speakers, and the like; a storage unit 408 such as a magnetic disk, optical disk, or the like; and a communication unit 409 such as a network card, modem, wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), the internet, and blockchain networks.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (10)
1. A tower crane monitoring method based on artificial intelligence is characterized by comprising the following steps:
responding to the obtained attribute information of the tower crane to be monitored, and configuring the safety interval distance between the tower crane to be monitored and each current adjacent tower crane based on the attribute information;
responding to the completion of the configuration of the safety spacing distance, monitoring the tower crane to be monitored so as to obtain the tower crane data of the tower crane to be monitored in real time;
generating early warning events corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored at any moment and each preset early warning index;
and sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person for display in an associated manner.
2. The method of claim 1, wherein,
the attribute information at least comprises the equipment number, the equipment model, the certificate information, the driver information, the inspection record, the arm length, the lifting capacity and the tower height of the tower crane to be monitored;
the tower crane data at least comprises rotation, amplitude, height of a lifting hook, lifting weight, torque percentage, inclination angle, wind speed and online state;
the early warning events at least comprise tower crane multi-machine anti-collision early warning, tower crane overload early warning and tower crane amplitude limit early warning.
3. The method according to claim 1 or 2, characterized by, before generating the early warning event corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored at any moment and preset early warning indexes, further comprising:
and determining each early warning index corresponding to the tower crane to be monitored according to the attribute information of the tower crane to be monitored based on a preset mapping relation.
4. The method according to claim 1, wherein after the early warning event corresponding to the tower crane to be monitored at any moment is generated, the method further comprises:
recording a first number of times that the current tower crane to be monitored triggers the early warning event and a second number of times that the tower crane to be monitored triggers any type of early warning event;
in response to the fact that the first time is larger than a first threshold value in a specified period, stopping the tower crane to be monitored, and sending first danger warning information to terminal equipment of preset supervision personnel;
and in response to the fact that the second number is larger than a second threshold value in a specified period, stopping the tower crane to be monitored, and sending second danger warning information to terminal equipment of preset supervision personnel, wherein the second danger warning information comprises the type of the early warning event.
5. The method according to claim 1, characterized in that after the monitoring of the tower crane to be monitored is performed to obtain tower crane data of the tower crane to be monitored in real time, the method further comprises:
carrying out data desensitization on tower crane data of the tower crane to be monitored;
uploading tower crane data subjected to data desensitization to a tower crane data analysis module;
fault recognition analysis is carried out on the tower crane data after the data desensitization based on the tower crane data analysis module to obtain tower crane fault characteristics, wherein the tower crane data analysis module comprises a tower crane data analysis model generated through historical reference tower crane data training;
and maintaining and managing the tower crane to be monitored based on the tower crane fault characteristics.
6. The utility model provides a tower crane monitoring devices based on artificial intelligence which characterized in that includes:
the configuration module is used for responding to the acquired attribute information of the tower crane to be monitored and configuring the safety spacing distance between the tower crane to be monitored and each current adjacent tower crane based on the attribute information;
the monitoring module is used for responding to the completion of the configuration of the safety spacing distance, monitoring the tower crane to be monitored, and acquiring the tower crane data of the tower crane to be monitored in real time;
the generating module is used for generating an early warning event corresponding to the tower crane to be monitored at any moment according to the tower crane data of the tower crane to be monitored at any moment and preset early warning indexes;
and the early warning module is used for sending the early warning event, any moment and the attribute information of the tower crane to be monitored to a terminal display screen of a preset supervision person in an associated manner for displaying.
7. The apparatus of claim 6, wherein,
the attribute information at least comprises the equipment number, the equipment model, the qualification information, the driver information, the inspection record, the arm length, the lifting capacity and the tower height of the tower crane to be monitored;
the tower crane data at least comprises rotation, amplitude, height of a lifting hook, lifting weight, torque percentage, inclination angle, wind speed and online state;
the early warning events at least comprise tower crane multi-machine anti-collision early warning, tower crane overload early warning and tower crane amplitude limit early warning.
8. The apparatus of claim 6 or 7, wherein the generating module is further configured to: and determining each early warning index corresponding to the tower crane to be monitored according to the attribute information of the tower crane to be monitored based on a preset mapping relation.
9. The apparatus of claim 6, wherein the generating module is further configured to:
recording a first number of times that the current tower crane to be monitored triggers the early warning event and a second number of times that the tower crane to be monitored triggers any type of early warning event;
in response to the fact that the first time is larger than a first threshold value in a specified period, stopping the tower crane to be monitored, and sending first danger warning information to terminal equipment of preset supervision personnel;
and in response to the fact that the second number is larger than a second threshold value in a specified period, stopping the tower crane to be monitored, and sending second danger warning information to terminal equipment of preset supervision personnel, wherein the second danger warning information comprises the type of the early warning event.
10. The apparatus of claim 6, wherein the monitoring module is further configured to:
carrying out data desensitization on tower crane data of the tower crane to be monitored;
uploading tower crane data subjected to data desensitization to a tower crane data analysis module;
fault identification analysis is carried out on the tower crane data after the data desensitization based on the tower crane data analysis module to obtain the fault characteristics of the tower crane,
the tower crane data analysis module comprises a tower crane data analysis model generated through historical reference tower crane data training;
and maintaining and managing the tower crane to be monitored based on the tower crane fault characteristics.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211003108.7A CN115072598B (en) | 2022-08-22 | 2022-08-22 | Tower crane monitoring method and device based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211003108.7A CN115072598B (en) | 2022-08-22 | 2022-08-22 | Tower crane monitoring method and device based on artificial intelligence |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115072598A true CN115072598A (en) | 2022-09-20 |
| CN115072598B CN115072598B (en) | 2022-12-20 |
Family
ID=83244745
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211003108.7A Active CN115072598B (en) | 2022-08-22 | 2022-08-22 | Tower crane monitoring method and device based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115072598B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116128166A (en) * | 2023-04-17 | 2023-05-16 | 广州云硕科技发展有限公司 | Data visualization processing method and device for intelligent traffic |
| CN116229692A (en) * | 2023-05-08 | 2023-06-06 | 陕西汇天广科信息科技有限公司 | Monitoring video safety system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5730305A (en) * | 1988-12-27 | 1998-03-24 | Kato Works Co., Ltd. | Crane safety apparatus |
| CN106957020A (en) * | 2017-05-11 | 2017-07-18 | 深圳市柘叶红实业有限公司 | Safety of tower crane management system and management method |
| CN207347027U (en) * | 2017-10-24 | 2018-05-11 | 清华大学合肥公共安全研究院 | A kind of intelligent and safe tower crane that early warning is perceived based on Internet of Things |
| CN110127526A (en) * | 2019-06-05 | 2019-08-16 | 重庆两江新区管理委员会 | A kind of wisdom early warning system for derrick crane |
| CN214087383U (en) * | 2020-10-20 | 2021-08-31 | 广东米量信息科技有限公司 | Building tower crane safety monitoring system |
| CN114455476A (en) * | 2022-02-15 | 2022-05-10 | 深圳市双盈科技有限公司 | Tower crane safety monitoring method, device and system |
| CN114604761A (en) * | 2022-01-24 | 2022-06-10 | 杭州大杰智能传动科技有限公司 | Intelligent tower crane-assisted operation and control safety warning system and method |
-
2022
- 2022-08-22 CN CN202211003108.7A patent/CN115072598B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5730305A (en) * | 1988-12-27 | 1998-03-24 | Kato Works Co., Ltd. | Crane safety apparatus |
| CN106957020A (en) * | 2017-05-11 | 2017-07-18 | 深圳市柘叶红实业有限公司 | Safety of tower crane management system and management method |
| CN207347027U (en) * | 2017-10-24 | 2018-05-11 | 清华大学合肥公共安全研究院 | A kind of intelligent and safe tower crane that early warning is perceived based on Internet of Things |
| CN110127526A (en) * | 2019-06-05 | 2019-08-16 | 重庆两江新区管理委员会 | A kind of wisdom early warning system for derrick crane |
| CN214087383U (en) * | 2020-10-20 | 2021-08-31 | 广东米量信息科技有限公司 | Building tower crane safety monitoring system |
| CN114604761A (en) * | 2022-01-24 | 2022-06-10 | 杭州大杰智能传动科技有限公司 | Intelligent tower crane-assisted operation and control safety warning system and method |
| CN114455476A (en) * | 2022-02-15 | 2022-05-10 | 深圳市双盈科技有限公司 | Tower crane safety monitoring method, device and system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116128166A (en) * | 2023-04-17 | 2023-05-16 | 广州云硕科技发展有限公司 | Data visualization processing method and device for intelligent traffic |
| CN116229692A (en) * | 2023-05-08 | 2023-06-06 | 陕西汇天广科信息科技有限公司 | Monitoring video safety system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115072598B (en) | 2022-12-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115072598B (en) | Tower crane monitoring method and device based on artificial intelligence | |
| CN115303946B (en) | Digital twinning-based tower crane operation monitoring method and system | |
| US10994970B2 (en) | Crane risk logic apparatus and system and method for use of same | |
| CN113467433A (en) | Method and device for detecting faults of mechanical equipment | |
| CN113689693A (en) | Method and device for processing abnormity of road side equipment and intelligent high-speed monitoring platform | |
| US20240112503A1 (en) | Crane Risk Logic Apparatus and System and Method for Use of Same | |
| CN108792947A (en) | A kind of garbage grab bucket bridge crane monitoring system | |
| CN114314347B (en) | Safety monitoring and management system for hoisting machinery | |
| CN109377030A (en) | Calculation method, electronic equipment and the storage medium of aircraft risk case value-at-risk | |
| CN115876252A (en) | Multi-azimuth detection method, device, equipment and medium for external broken hidden danger points | |
| CN114743332A (en) | Perception early warning method and device for intelligent fire fighting, storage medium and terminal | |
| CN114707674A (en) | Power cable damage event early warning method, device, equipment and storage medium | |
| CN112151195A (en) | Method and device for checking potential safety hazards of power distribution equipment | |
| CN116281683A (en) | Method, device, equipment and storage medium for monitoring state of steel rope in real time | |
| CN114955596A (en) | Chute protection method, device, control equipment, system and medium for loading operation | |
| CN115966073A (en) | Risk early warning method and device, electronic equipment and storage medium | |
| CN117392587B (en) | Special equipment safety monitoring system based on Internet of things | |
| CN116821604A (en) | Intelligent building site monitoring management method, system, storage medium and equipment | |
| KR102137366B1 (en) | System for managing power facility and method thereof | |
| CN115032499A (en) | Monitoring method, device and system for preventing external force damage of power transmission line | |
| CN116074656A (en) | Intelligent engineering patrol management system based on dynamic and static image monitoring | |
| CN116418951A (en) | Method, device, equipment and medium for managing and controlling operation area | |
| CN116580525A (en) | Safety early warning method, device and equipment for electric power operation and storage medium | |
| CN117475680A (en) | Unmanned aerial vehicle inspection early warning method, unmanned aerial vehicle inspection early warning device, unmanned aerial vehicle controller, unmanned aerial vehicle inspection early warning system and storage medium | |
| CN116644592A (en) | Method, device, equipment and medium for testing construction object |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |