CN113340344B - Hydraulic climbing mould intelligent monitoring control early warning system based on digital twin technology - Google Patents
Hydraulic climbing mould intelligent monitoring control early warning system based on digital twin technology Download PDFInfo
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- G—PHYSICS
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- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
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- G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
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- 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
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/0202—Child monitoring systems using a transmitter-receiver system carried by the parent and the child
- G08B21/0225—Monitoring making use of different thresholds, e.g. for different alarm levels
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- G—PHYSICS
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses a hydraulic creeping formwork intelligent monitoring and early warning system based on a digital twinning technology, which comprises a field hydraulic creeping formwork and monitoring sensor module, a data acquisition and transmission module, a twinning space analysis and prediction module and a real-time precontrol and warning module, wherein the twinning space analysis and prediction module is used for storing and analyzing data, monitoring in real time, automatically giving out precontrol measures when unsafe factors possibly occur, and realizing the adjustment and early warning of the hydraulic creeping formwork through the real-time precontrol and warning module; the invention adopts a finite element analysis method to determine the positions of the measuring points, compared with the traditional personal experience determination, the measuring point determination is more targeted, the problems that key point positions are easy to miss monitoring points and artificial influence factors are large in the traditional method measuring point arrangement are solved, and the problem that the traditional method cannot adopt pre-control measures in advance can be solved.
Description
Technical Field
The invention belongs to the technical field of creeping formwork, and particularly relates to a hydraulic creeping formwork intelligent monitoring control early warning system based on a digital twinning technology.
Background
Along with the gradual reduction of urban construction land, buildings are gradually developing to high-rise and super-high-rise buildings. The hydraulic creeping formwork technology plays an important role in the construction process of high-rise and super high-rise buildings. The attention degree of engineering construction safety in the world is increased year by year, and a hydraulic creeping formwork intelligent monitoring control early warning system is urgently needed to be developed so as to ensure the smooth proceeding of engineering construction and the life safety of field operation personnel.
At present, the hydraulic creeping formwork monitoring control in China generally adopts the means of site arrangement of measuring points, manual data acquisition and then processing and analysis. In the traditional method, monitoring point position arrangement is basically carried out by depending on personal experience, and monitoring points are possibly omitted for some parts which are stressed greatly or deformed greatly, so that monitoring information cannot be acquired, and potential safety hazards are brought to creeping formwork operation; the traditional method has low data acquisition frequency and may not be capable of early warning abnormal conditions in time; the traditional method has large labor capacity for data acquisition and processing, and has larger potential safety hazard because the monitoring work bundle is not timely under the condition that the number of field workers is limited; the traditional method can only obtain information of monitoring point positions, and cannot obtain stress deformation information of the whole creeping formwork, so that the whole safety state of the creeping formwork is not favorably evaluated, and potential safety hazards are easily caused; the traditional method has low monitoring efficiency and more man-made interference factors; the traditional method can only stay at the level of solving problems, can not predict the possible problems in advance, and then takes pre-control measures in advance.
The method has the advantages that the digital twin technology can be used for simulating virtual reality and establishing an interactive feedback relationship between the real world and the virtual world. The prediction and early warning of the technical problems in the process are realized, and then the pre-control measures are pertinently taken in advance, so that the safety of the hydraulic climbing formwork in the climbing and using processes can be guaranteed. The invention introduces a digital twinning technology into the intelligent monitoring control early warning system of the hydraulic creeping formwork, can monitor the state index of the hydraulic creeping formwork in the climbing and using processes in real time, can reasonably conjecture the stress condition and the safe and stable state of other parts of the hydraulic creeping formwork according to monitoring data, and can carry out real-time optimization adjustment of the creeping formwork according to the real-time stress condition and the safe and stable state of the creeping formwork so as to avoid larger potential safety hazard.
Disclosure of Invention
The invention aims to provide a hydraulic creeping formwork intelligent monitoring control early warning system based on a digital twinning technology.
The purpose of the invention can be realized by the following technical scheme:
the hydraulic creeping formwork intelligent monitoring control early warning system based on the digital twinning technology comprises a field hydraulic creeping formwork and monitoring sensor module, a data acquisition and transmission module, a twinning space analysis and prediction module and a real-time pre-control and warning module, wherein the twinning space analysis and prediction module is used for storing and analyzing data, monitoring in real time, automatically giving out pre-control measures when unsafe factors possibly occur, and realizing the adjustment and early warning of the hydraulic creeping formwork through the real-time pre-control and warning module;
the field hydraulic climbing formwork and monitoring sensor module comprises a hydraulic climbing formwork and a monitoring sensor arranged on the hydraulic climbing formwork, the monitoring sensor comprises a stress sensor, a horizontal sensor and an axial force sensor, the stress sensor is used for collecting stress information of key parts of a frame body, the horizontal sensor is used for collecting gradient information of the frame body and climbing formwork climbing synchronism information, and the axial force sensor is used for collecting stress information between a tail cone of the hydraulic climbing formwork frame body and a wall body;
the data acquisition and transmission module comprises a high-speed multi-channel data acquisition device and a 5G high-speed mobile transmission device, the high-speed multi-channel data acquisition device is used for acquiring monitoring data of each sensor in the field hydraulic creeping formwork and the monitoring sensor module, and the 5G high-speed mobile transmission device is used for transmitting the monitoring data to the data storage and processing device and transmitting the real-time condition and the pre-control measure of the hydraulic creeping formwork to the real-time pre-control and alarm module;
the twin space analysis and prediction module comprises a data storage and processing device, a Bayesian network inference prediction system, a finite element analysis optimization system and a potential risk and pre-control measure recommendation system; the system comprises a data storage and processing device, a Bayesian network inference prediction system and a Bayesian network inference prediction system, wherein the data storage and processing device is used for storing and processing sensor data, the Bayesian network inference prediction system infers the stress and deformation information of the whole creeping formwork to local information obtained by a field hydraulic creeping formwork and a monitoring sensor module, the finite element analysis optimization system is used for optimizing the sensor layout point position, inputting the variable value under each working condition and the calculated result corresponding to the monitoring point into the Bayesian network inference prediction system, learning of the Bayesian network inference prediction system is realized, and the potential risk and pre-control measure recommendation system obtains a creeping formwork potential risk part and gives pre-control measures according to the monitoring data collected by the field hydraulic creeping formwork and the monitoring sensor module;
the real-time pre-control and alarm module comprises a field LED display screen, a field alarm and a manager smart phone; the field LED display screen and the intelligent mobile phone of the manager can receive the whole creeping formwork stress and deformation information, the occurrence probability of potential risk positions and risks, alarm information, suggested pre-control measures and other information transmitted by the 5G high-speed mobile transmission device, and the field alarm is used for receiving the alarm information transmitted by the 5G high-speed mobile transmission device and initiating early warning on the field.
As a further scheme of the present invention, the method for optimizing the sensor layout point position by the finite element analysis optimization system comprises:
the hydraulic climbing formwork to be adopted and the load condition of the hydraulic climbing formwork are input into a finite element analysis optimization system, stress distribution, axial force distribution, displacement distribution and the like of the hydraulic climbing formwork structure are obtained through finite element analysis, a stress sensor is arranged at a position with large stress distribution, a horizontal sensor is arranged at a position with large displacement and a hydraulic operation layer of the frame body, and an axial force sensor is arranged at a position with large axial force of a caudal vertebra of the frame body, so that the optimal arrangement of monitoring point positions is realized.
As a further scheme of the present invention, the method for learning by the bayesian network inference prediction system through the finite element analysis optimization system comprises:
the method comprises the steps of taking the load size, load distribution and difference values corresponding to asynchronous climbing of each platform of the hydraulic creeping formwork structure as variables, adopting a finite element analysis system to calculate stress results, levelness results and axial force results at the positions of actual field monitoring points corresponding to the hydraulic creeping formwork structure under various working conditions, and inputting variable values and calculated results corresponding to the monitoring points under each condition into a Bayesian network inference prediction system, so that learning of the Bayesian network inference prediction system is realized.
As a further scheme of the invention, the method for sending out the early warning by the real-time pre-control and alarm module comprises the following steps:
the field monitoring data collected by the field hydraulic creeping formwork and monitoring sensor module is input into a learnt Bayesian network reasoning and predicting system in real time through a data storage and processing device, the system can give the load size, the load distribution, the difference corresponding to asynchronous climbing and the corresponding occurrence probability of each platform of the corresponding hydraulic creeping formwork, and the difference corresponding to asynchronous load size, load distribution and climbing is input into a finite element analysis and optimization system to obtain the stress and deformation distribution condition of the whole creeping formwork, so that the stress and deformation information of the whole creeping formwork can be deduced according to local monitoring information;
the Bayesian network reasoning and predicting system is also used for giving corresponding load size, load distribution and difference values corresponding to asynchronous climbing under the conditions of higher occurrence probability, so that stress and deformation distribution conditions of the whole hydraulic climbing formwork under the conditions of higher occurrence probability can be obtained;
the stress and deformation distribution conditions of the whole creeping formwork corresponding to the conditions with higher occurrence probability are respectively input into a potential risk and pre-control measure recommendation system, so that the safety evaluation of the bearing capacity and the deformation condition of the hydraulic creeping formwork can be realized, and the safety coefficient is obtained.
As a further scheme of the invention, the occurrence probability and the safety coefficient are taken according to the field requirements, the occurrence probability is less than 100%, the safety coefficient is greater than 1.0, and the lower the occurrence probability and the greater the safety coefficient, the safer the climbing state is.
As a further scheme of the invention, stress and deformation distribution conditions of the whole creeping formwork are subjected to key analysis under the condition that the occurrence probability is more than 60% and the safety coefficient is less than 1.2, risk pre-control measures are given, and an alarm instruction is given;
the stress and deformation distribution condition, the risk pre-control measure and the alarm instruction of the whole creeping formwork under the condition that the occurrence probability is more than 60 percent and the safety coefficient is less than 1.2 are transmitted to an intelligent and on-site LED display screen of a manager in real time through a 5G high-speed mobile transmission device, and the alarm instruction is transmitted to an on-site alarm through the 5G high-speed mobile transmission device so as to send out the alarm instruction;
after receiving the risk pre-control measures sent by the 5G high-speed mobile transmission device, field managers can quickly and pertinently take the pre-control measures for the hydraulic climbing formwork, and when the field alarm does not give an alarm any more, the field managers show that the adopted pre-control measures are effective, and then the treatment can be stopped.
The working method of the hydraulic creeping formwork intelligent monitoring control early warning system based on the digital twinning technology is characterized by comprising the following steps of:
s1, creep finite element modeling analysis: after the concrete specification of the hydraulic creeping formwork is determined according to engineering requirements, the creeping formwork load is determined according to actual conditions, a finite element model is established and analyzed to obtain the stress distribution, the displacement distribution, the axial force distribution and the safety coefficient of the hydraulic creeping formwork;
s2, monitoring point location optimization: the part with larger creep stress is determined as a stress sensor arrangement point position, the part with larger displacement and part of the frame body hydraulic operation layer are determined as a horizontal sensor arrangement point position, and the part with larger axial force of the frame body caudal vertebra is determined as an axial force sensor arrangement point position;
s3, mounting a creeping formwork and an instrument: and (5) mounting a creeping formwork, and mounting a sensor according to the optimized point position. Mounting a high-speed multi-channel data acquisition device, a 5G high-speed mobile transmission device, a data storage and processing device, a field LED display screen and a field alarm;
s4, learning by a Bayesian network inference prediction system: determining the load size and the load distribution condition of each platform of the hydraulic creeping formwork according to the field construction organization design, calculating the stress, displacement and axial force results at the positions of the corresponding field actual monitoring points under a plurality of working conditions by using the difference values corresponding to the load size, the load distribution and the climbing asynchronization as variables through a finite element analysis optimization system, inputting the variable values under each working condition and the calculated results corresponding to the monitoring points into a Bayesian network inference prediction system, and realizing the learning of the Bayesian network inference prediction system;
s5, system connection and debugging: debugging is carried out after the systems are connected, so that the normal operation of the systems is ensured;
s6, system operation: the hydraulic climbing formwork starts to operate, and the twin space analysis and prediction module and the real-time pre-control and alarm module also start to operate;
s7, sending out early warning: the method comprises the steps that information monitored by a sensor is collected through a high-speed multi-channel data collecting device and then is transmitted to a data storing and processing device in real time through a 5G high-speed mobile transmission device, then the information is transmitted to a learnt Bayesian network reasoning and predicting system through the data storing and processing device, the Bayesian network reasoning and predicting system obtains the load size, the load distribution and the difference corresponding to asynchronous climbing of each platform of a creeping formwork under various occurrence probabilities according to monitoring information, the difference corresponding to the load size, the load distribution and the asynchronous climbing is input into a finite element analysis and optimization system to obtain the stress and deformation distribution condition of the whole creeping formwork, the stress and deformation distribution condition of the whole creeping formwork corresponding to each occurrence probability is automatically input into a potential risk and pre-control measure recommending system in real time to obtain the safety coefficient of the creeping formwork under each occurrence probability, corresponding pre-control measures are given for the conditions that the occurrence probability is greater than 60% and the safety coefficient is less than 1.2, and the stress and deformation distribution condition of the whole creeping formwork, the pre-control measures and alarm instructions are transmitted to a pre-control measure module through the 5G high-speed mobile transmission device and an alarm module;
s8, taking measures: after the intelligent mobile phone or the field alarm or the field LED screen of the manager receives the alarm, the field manager carries out field treatment according to the received pre-control measures until the alarm information disappears, and the creeping formwork normally operates;
s9, removing the creeping formwork and the instrument: and after the structure construction is finished, dismantling the creeping formwork and each system device for subsequent projects to continue to use.
The invention has the beneficial effects that:
1. the invention adopts a finite element analysis method to determine the positions of the measuring points, compared with the traditional personal experience determination, the measuring point determination is more targeted, and the problems that key point positions are easy to miss monitoring points and artificial influence factors are large in the traditional measuring point arrangement method are solved.
2. The invention adopts the twin space analysis and prediction module to achieve the purpose of obtaining the stress and deformation information of the whole creeping formwork from the local monitoring information of the creeping formwork, and can obtain the safety coefficient, the accident occurrence probability and the pre-control measure of the creeping formwork at the same time, and the pre-control measure can be taken in advance for the condition of smaller safety coefficient and larger accident occurrence probability, thereby solving the problems that the monitoring information in the traditional method is incomplete and the stress and deformation information of the whole creeping formwork can not be obtained, and simultaneously solving the problem that the traditional method can not take the pre-control measure in advance.
3. The method provided by the invention has the advantages that other steps such as finite element modeling, equipment installation and field disposal, data acquisition, transmission, processing, analysis, early warning and the like are automatically completed, the automation degree is higher, and the real-time performance is better, so that the problems of untimely monitoring and early warning, large monitoring labor amount, low monitoring efficiency, multiple artificial interference factors, large potential safety hazard and the like in the traditional method can be solved.
4. The invention is a set of detachable and reusable device, the structure composition is simpler, and the maintenance and the use are very convenient.
Drawings
The invention is described in further detail below with reference to the figures and specific embodiments.
Fig. 1 is a schematic system structure diagram of the hydraulic creeping intelligent monitoring, controlling and early warning system based on the digital twinning technology.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
A hydraulic creeping formwork intelligent monitoring control early warning system based on a digital twinning technology is shown in figure 1 and comprises a field hydraulic creeping formwork and monitoring sensor module, a data acquisition and transmission module, a twinning space analysis and prediction module and a real-time precontrol and warning module, wherein the twinning space analysis and prediction module is used for storing and analyzing data, monitoring in real time, automatically giving out precontrol measures when unsafe factors possibly occur, and the precontrol measures realize adjustment and early warning on the hydraulic creeping formwork through the real-time precontrol and warning module;
the field hydraulic climbing formwork and monitoring sensor module comprises a hydraulic climbing formwork and a monitoring sensor arranged on the hydraulic climbing formwork, the monitoring sensor comprises a stress sensor, a horizontal sensor and an axial force sensor, the stress sensor is used for collecting stress information of key parts of a frame body, the horizontal sensor is used for collecting gradient information of the frame body and climbing formwork climbing synchronism information, and the axial force sensor is used for collecting stress information between a tail cone of the hydraulic climbing formwork frame body and a wall body;
the data acquisition and transmission module comprises a high-speed multi-channel data acquisition device and a 5G high-speed mobile transmission device, the high-speed multi-channel data acquisition device is used for acquiring monitoring data of each sensor in the field hydraulic creeping formwork and the monitoring sensor module, and the 5G high-speed mobile transmission device is used for transmitting the monitoring data to the data storage and processing device and transmitting the real-time condition and the pre-control measures of the hydraulic creeping formwork to the real-time pre-control and alarm module;
the twin space analysis and prediction module comprises a data storage and processing device, a Bayesian network inference prediction system, a finite element analysis optimization system and a potential risk and pre-control measure recommendation system; the system comprises a data storage and processing device, a Bayesian network inference prediction system and a Bayesian network inference prediction system, wherein the data storage and processing device is used for storing and processing sensor data, the Bayesian network inference prediction system infers the stress and deformation information of the whole creeping formwork to local information obtained by a field hydraulic creeping formwork and a monitoring sensor module, the finite element analysis optimization system is used for optimizing the sensor layout point position, inputting the variable value under each working condition and the calculated result corresponding to the monitoring point into the Bayesian network inference prediction system, learning of the Bayesian network inference prediction system is realized, and the potential risk and pre-control measure recommendation system obtains a creeping formwork potential risk part and gives pre-control measures according to the monitoring data collected by the field hydraulic creeping formwork and the monitoring sensor module;
the real-time pre-control and alarm module comprises a field LED display screen, a field alarm and a manager smart phone; the field LED display screen and the intelligent mobile phone of the manager can receive the whole creeping formwork stress and deformation information, the occurrence probability of potential risk positions and risks, alarm information, suggested pre-control measures and other information transmitted by the 5G high-speed mobile transmission device, and the field alarm is used for receiving the alarm information transmitted by the 5G high-speed mobile transmission device and initiating early warning on the field;
the method for optimizing the sensor layout point position by the finite element analysis optimization system comprises the following steps:
the hydraulic creeping formwork and the load condition thereof to be adopted are input into a finite element analysis optimization system, the stress distribution, the axial force distribution, the displacement distribution and the like of the hydraulic creeping formwork structure are obtained through finite element analysis, a stress sensor is arranged at the position with larger stress distribution, a horizontal sensor is arranged at the position with larger displacement and a hydraulic operation layer of the frame body, and an axial force sensor is arranged at the position with larger axial force of the caudal vertebra of the frame body, so that the optimized arrangement of monitoring point positions is realized.
The method for learning by the Bayesian network inference prediction system through the finite element analysis optimization system comprises the following steps:
the method comprises the steps that the difference values corresponding to load size, load distribution and asynchronous climbing of each platform of the hydraulic climbing formwork structure are used as variables, a finite element analysis system is adopted to calculate stress results, levelness results and axial force results at the positions of actual monitoring points on site corresponding to the platforms under various working conditions, and variable values and calculated results corresponding to the monitoring points under each condition are input into a Bayesian network inference prediction system, so that learning of the Bayesian network inference prediction system is achieved;
the method for sending out the early warning by the real-time pre-control and alarm module comprises the following steps:
the system can give the load size, the load distribution, the difference value corresponding to asynchronous climbing and the corresponding occurrence probability of each platform of the corresponding hydraulic creeping formwork, and the difference value corresponding to asynchronous climbing is input into a finite element analysis optimization system to obtain the stress and deformation distribution condition of the whole creeping formwork, so that the aim of deducing the stress and deformation information of the whole creeping formwork according to local monitoring information is fulfilled;
the Bayesian network reasoning and predicting system can give corresponding load size, load distribution and difference values of asynchronous climbing under the conditions of high occurrence probability, and further can obtain stress and deformation distribution conditions of the whole hydraulic climbing formwork under the conditions of high occurrence probability;
the stress and deformation distribution conditions of the whole creeping formwork corresponding to the conditions with higher occurrence probability are respectively input into a potential risk and pre-control measure recommendation system, so that the safety evaluation of the bearing capacity and the deformation condition of the hydraulic creeping formwork can be realized, and the safety coefficient is obtained.
Performing key analysis on the stress and deformation distribution condition of the whole creeping formwork under the condition that the occurrence probability is more than 60% and the safety coefficient is less than 1.2, giving a risk pre-control measure and giving an alarm instruction;
the stress and deformation distribution condition, the risk pre-control measure and the alarm instruction of the whole creeping formwork under the condition that the occurrence probability is more than 60 percent and the safety coefficient is less than 1.2 are transmitted to an intelligent and on-site LED display screen of a manager in real time through a 5G high-speed mobile transmission device, and the alarm instruction is transmitted to an on-site alarm through the 5G high-speed mobile transmission device so as to send out the alarm instruction;
when the field manager receives the risk pre-control measures sent by the 5G high-speed mobile transmission device, the pre-control measures can be quickly and pertinently taken for the hydraulic climbing formwork, and when the field alarm does not give an alarm any more, the adopted pre-control measures are shown to be effective, and then the treatment can be stopped;
the values of the occurrence probability and the safety coefficient can be taken according to the field requirements, but the occurrence probability is less than 100% and the safety coefficient is more than 1.0, and the lower the occurrence probability and the higher the safety coefficient are, the safer the climbing state is;
the working method of the hydraulic creeping formwork intelligent monitoring control early warning system based on the digital twinning technology comprises the following steps:
s1, creep finite element modeling analysis: after the specific specification of the hydraulic creeping formwork is determined according to engineering requirements, creeping formwork load is determined according to actual conditions, a finite element model is established and analyzed to obtain stress distribution, displacement distribution, axial force distribution and safety coefficient of the hydraulic creeping formwork;
s2, monitoring point location optimization: the part with larger creep stress is determined as a stress sensor arrangement point position, the part with larger displacement and part of the frame body hydraulic operation layer are determined as a horizontal sensor arrangement point position, and the part with larger axial force of the frame body caudal vertebra is determined as an axial force sensor arrangement point position;
s3, installing a creeping formwork and an instrument: and (5) mounting a creeping formwork, and mounting a sensor according to the optimized point position. Mounting a high-speed multi-channel data acquisition device, a 5G high-speed mobile transmission device, a data storage and processing device, a field LED display screen and a field alarm;
s4, learning by a Bayesian network inference prediction system: determining the load size and the load distribution condition of each platform of the hydraulic creeping formwork according to the field construction organization design, calculating the stress, displacement and axial force results at the positions of the corresponding field actual monitoring points under a plurality of working conditions by using the difference values corresponding to asynchronous load size, load distribution and climbing as variables through a finite element analysis optimization system, inputting the variable values under each working condition and the calculated results corresponding to the monitoring points into a Bayesian network inference prediction system, and realizing the learning of the Bayesian network inference prediction system;
s5, system connection and debugging: debugging is carried out after the systems are connected, so that the normal operation of the systems is ensured;
s6, system operation: the hydraulic climbing formwork starts to operate, and the twin space analysis and prediction module and the real-time pre-control and alarm module also start to operate;
s7, sending out early warning: the method comprises the steps that information monitored by a sensor is collected through a high-speed multi-channel data collecting device and then is transmitted to a data storing and processing device in real time through a 5G high-speed mobile transmission device, then the information is transmitted to a learnt Bayesian network reasoning and predicting system through the data storing and processing device, the Bayesian network reasoning and predicting system obtains the load size, the load distribution and the difference corresponding to asynchronous climbing of each platform of a creeping formwork under various occurrence probabilities according to monitoring information, the difference corresponding to the load size, the load distribution and the asynchronous climbing is input into a finite element analysis and optimization system to obtain the stress and deformation distribution condition of the whole creeping formwork, the stress and deformation distribution condition of the whole creeping formwork corresponding to each occurrence probability is automatically input into a potential risk and pre-control measure recommending system in real time to obtain the safety coefficient of the creeping formwork under each occurrence probability, corresponding pre-control measures are given for the conditions that the occurrence probability is greater than 60% and the safety coefficient is less than 1.2, and the stress and deformation distribution condition of the whole creeping formwork, the pre-control measures and alarm instructions are transmitted to a pre-control measure module through the 5G high-speed mobile transmission device and an alarm module;
s8, taking measures: after the intelligent mobile phone or the field alarm or the field LED screen of the manager receives the alarm, the field manager carries out field treatment according to the received pre-control measures until the alarm information disappears, and the creeping formwork normally operates;
s9, removing the creeping formwork and the instrument: and after the structure construction is finished, dismantling the creeping formwork and each system device for subsequent projects to continue to use.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. The intelligent hydraulic creeping formwork monitoring, controlling and early warning system based on the digital twin technology is characterized by comprising an on-site hydraulic creeping formwork and monitoring sensor module, a data acquisition and transmission module, a twin space analysis and prediction module and a real-time pre-control and warning module, wherein the twin space analysis and prediction module is used for storing and analyzing data, monitoring in real time, automatically giving out pre-control measures when unsafe factors possibly occur, and the pre-control measures realize the adjustment and early warning of the hydraulic creeping formwork through the real-time pre-control and warning module;
the field hydraulic climbing formwork and monitoring sensor module comprises a hydraulic climbing formwork and a monitoring sensor arranged on the hydraulic climbing formwork, the monitoring sensor comprises a stress sensor, a horizontal sensor and an axial force sensor, the stress sensor is used for collecting stress information of key parts of a frame body, the horizontal sensor is used for collecting gradient information of the frame body and climbing formwork climbing synchronism information, and the axial force sensor is used for collecting stress information between a tail cone of the hydraulic climbing formwork frame body and a wall body;
the data acquisition and transmission module comprises a high-speed multi-channel data acquisition device and a 5G high-speed mobile transmission device, the high-speed multi-channel data acquisition device is used for acquiring monitoring data of each sensor in the field hydraulic creeping formwork and the monitoring sensor module, and the 5G high-speed mobile transmission device is used for transmitting the monitoring data to the data storage and processing device and transmitting the real-time condition and the pre-control measure of the hydraulic creeping formwork to the real-time pre-control and alarm module;
the twin space analysis and prediction module comprises a data storage and processing device, a Bayesian network inference prediction system, a finite element analysis optimization system and a potential risk and pre-control measure recommendation system; the data storage and processing device is used for storing and processing sensor data, the Bayesian network inference prediction system infers the stress and deformation information of the whole creeping formwork on the local information obtained by the field hydraulic creeping formwork and the monitoring sensor module, and the finite element analysis optimization system is used for optimizing the sensor layout point position
Changing and inputting variable values under each working condition and a result corresponding to the monitoring point obtained by calculation into a Bayesian network inference prediction system to realize the learning of the Bayesian network inference prediction system, wherein the potential risk and pre-control measure recommendation system obtains a creeping potential risk part and gives pre-control measures according to monitoring data acquired by a field hydraulic creeping and monitoring sensor module;
the real-time pre-control and alarm module comprises a field LED display screen, a field alarm and a manager smart phone; the field LED display screen and the intelligent mobile phone of the manager can receive the whole creeping formwork stress and deformation information, the occurrence probability of potential risk positions and risks, alarm information, suggested pre-control measures and other information transmitted by the 5G high-speed mobile transmission device, and the field alarm is used for receiving the alarm information transmitted by the 5G high-speed mobile transmission device and initiating early warning on the field;
the method for optimizing the sensor layout point position by the finite element analysis optimization system comprises the following steps:
inputting a hydraulic creeping formwork to be adopted and a load condition thereof into a finite element analysis optimization system, obtaining stress distribution, axial force distribution, displacement distribution and the like of a hydraulic creeping formwork structure through finite element analysis, arranging a stress sensor at a position with larger stress distribution, arranging a horizontal sensor at a position with larger displacement and a hydraulic operating layer of a frame body, and arranging an axial force sensor at a position with larger axial force of a caudal vertebra of the frame body, thereby realizing the optimized arrangement of monitoring point positions;
the method for learning by the Bayesian network inference prediction system through the finite element analysis optimization system comprises the following steps:
the method comprises the steps of taking the load size, the load distribution and the difference value corresponding to asynchronous climbing of each platform of the hydraulic climbing formwork structure as variables, adopting a finite element analysis system to calculate a stress result, a levelness result and an axial force result at the position of a site actual monitoring point respectively corresponding to the platforms under a plurality of working conditions, and inputting variable values and calculated results corresponding to the monitoring point under each condition into a Bayesian network inference prediction system, so that learning of the Bayesian network inference prediction system is realized.
2. The intelligent hydraulic creeping formwork monitoring, controlling and early warning system based on the digital twinning technology as claimed in claim 1, wherein the method for sending out the early warning by the real-time pre-controlling and warning module comprises the following steps:
the field monitoring data collected by the field hydraulic creeping formwork and the monitoring sensor module is input into a learnt Bayesian network inference prediction system in real time through a data storage and processing device, the system can give the load size, the load distribution, the difference value corresponding to asynchronous climbing and the corresponding occurrence probability of each platform of the corresponding hydraulic creeping formwork, and the difference value corresponding to asynchronous load size, load distribution and asynchronous climbing is input into a finite element analysis optimization system to obtain the stress and deformation distribution condition of the whole creeping formwork, so that the stress and deformation information of the whole creeping formwork can be deduced according to local monitoring information;
the Bayesian network reasoning and predicting system is also used for giving corresponding load size, load distribution and difference values corresponding to asynchronous climbing under the conditions of higher occurrence probability, so that stress and deformation distribution conditions of the whole hydraulic climbing formwork under the conditions of higher occurrence probability can be obtained;
the stress and deformation distribution conditions of the whole creeping formwork corresponding to the conditions with higher occurrence probability are respectively input into a potential risk and pre-control measure recommendation system, so that the safety evaluation of the bearing capacity and the deformation condition of the hydraulic creeping formwork can be realized, and the safety coefficient is obtained.
3. The intelligent hydraulic creeping formwork monitoring, controlling and early warning system based on the digital twinning technology as claimed in claim 2, wherein the values of the occurrence probability and the safety coefficient are taken according to the field requirements, the occurrence probability is less than 100%, the safety coefficient is greater than 1.0, and the lower the occurrence probability and the greater the safety coefficient, the safer the creeping formwork state is.
4. The intelligent monitoring, controlling and early warning system for the hydraulic creeping formwork based on the digital twinning technology as claimed in claim 3, characterized in that stress and deformation distribution of the whole creeping formwork are mainly analyzed under the condition that the occurrence probability is more than 60% and the safety coefficient is less than 1.2, risk pre-control measures are given, and an alarm instruction is given;
the stress and deformation distribution condition, the risk pre-control measure and the alarm instruction of the whole creeping formwork under the condition that the occurrence probability is more than 60 percent and the safety coefficient is less than 1.2 are transmitted to an intelligent and on-site LED display screen of a manager in real time through a 5G high-speed mobile transmission device, and the alarm instruction is transmitted to an on-site alarm through the 5G high-speed mobile transmission device so as to send out the alarm instruction;
after receiving the risk pre-control measures sent by the 5G high-speed mobile transmission device, field managers can quickly and pertinently take the pre-control measures on the hydraulic climbing formwork, and when the field alarm does not give an alarm any more, the field alarm indicates that the taken pre-control measures play a role, and the field alarm can stop processing.
5. The intelligent hydraulic climbing monitoring, controlling and early warning system based on the digital twinning technology as claimed in claim 1, wherein the working method of the system comprises the following steps:
s1, creep finite element modeling analysis: after the specific specification of the hydraulic creeping formwork is determined according to engineering requirements, creeping formwork load is determined according to actual conditions, a finite element model is established and analyzed to obtain stress distribution, displacement distribution, axial force distribution and safety coefficient of the hydraulic creeping formwork;
s2, monitoring point location optimization: the part with larger creep stress is determined as a stress sensor arrangement point position, the part with larger displacement and part of the frame body hydraulic operation layer are determined as a horizontal sensor arrangement point position, and the part with larger axial force of the frame body caudal vertebra is determined as an axial force sensor arrangement point position;
s3, installing a creeping formwork and an instrument: mounting a creeping formwork, mounting a sensor according to the optimized point position, and mounting a high-speed multi-channel data acquisition device, a 5G high-speed mobile transmission device, a data storage and processing device, a field LED display screen and a field alarm;
s4, learning by a Bayesian network inference prediction system: determining the load size and the load distribution condition of each platform of the hydraulic creeping formwork according to the field construction organization design, calculating the stress, displacement and axial force results at the positions of the corresponding field actual monitoring points under a plurality of working conditions by using the difference values corresponding to asynchronous load size, load distribution and climbing as variables through a finite element analysis optimization system, inputting the variable values under each working condition and the calculated results corresponding to the monitoring points into a Bayesian network inference prediction system, and realizing the learning of the Bayesian network inference prediction system;
s5, system connection and debugging: debugging is carried out after the systems are connected, so that the normal operation of the systems is ensured;
s6, system operation: the hydraulic climbing formwork starts to operate, and the twin space analysis and prediction system and the real-time pre-control and alarm module also start to operate;
s7, sending out early warning: the method comprises the steps that information monitored by a sensor is collected through a high-speed multi-channel data collecting device and then is transmitted to a data storing and processing device in real time through a 5G high-speed mobile transmission device, then the information is transmitted to a learnt Bayesian network reasoning and predicting system through the data storing and processing device, the Bayesian network reasoning and predicting system obtains the load size, the load distribution and the difference corresponding to asynchronous climbing of each platform of a creeping formwork under various occurrence probabilities according to monitoring information, the difference corresponding to the load size, the load distribution and the asynchronous climbing is input into a finite element analysis and optimization system to obtain the stress and deformation distribution condition of the whole creeping formwork, the stress and deformation distribution condition of the whole creeping formwork corresponding to each occurrence probability is automatically input into a potential risk and pre-control measure recommending system in real time to obtain the safety coefficient of the creeping formwork under each occurrence probability, corresponding pre-control measures are given for the conditions that the occurrence probability is greater than 60% and the safety coefficient is less than 1.2, and the stress and deformation distribution condition of the whole creeping formwork, the pre-control measures and alarm instructions are transmitted to a pre-control measure module through the 5G high-speed mobile transmission device and an alarm module;
s8, taking measures: after the intelligent mobile phone or the field alarm or the field LED screen of the manager receives the alarm, the field manager carries out field treatment according to the received pre-control measures until the alarm information disappears, and the creeping formwork normally operates;
s9, removing the creeping formwork and the instrument: and after the structure construction is finished, dismantling the creeping formwork and each system device for subsequent projects to continue to use.
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