CN117196893B - Infrastructure foundation pit real-time monitoring and early warning management method and system - Google Patents
Infrastructure foundation pit real-time monitoring and early warning management method and system Download PDFInfo
- Publication number
- CN117196893B CN117196893B CN202311462540.7A CN202311462540A CN117196893B CN 117196893 B CN117196893 B CN 117196893B CN 202311462540 A CN202311462540 A CN 202311462540A CN 117196893 B CN117196893 B CN 117196893B
- Authority
- CN
- China
- Prior art keywords
- data
- foundation pit
- monitoring
- time
- real
- 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.)
- Active
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 246
- 238000007726 management method Methods 0.000 title claims abstract description 28
- 238000004364 calculation method Methods 0.000 claims abstract description 100
- 238000012795 verification Methods 0.000 claims abstract description 61
- 238000000034 method Methods 0.000 claims abstract description 54
- 238000005516 engineering process Methods 0.000 claims abstract description 45
- 238000010276 construction Methods 0.000 claims abstract description 35
- 238000012545 processing Methods 0.000 claims abstract description 11
- 238000005259 measurement Methods 0.000 claims description 69
- 238000011161 development Methods 0.000 claims description 60
- 230000008859 change Effects 0.000 claims description 50
- 238000001914 filtration Methods 0.000 claims description 38
- 230000009467 reduction Effects 0.000 claims description 28
- 230000008569 process Effects 0.000 claims description 18
- 239000011148 porous material Substances 0.000 claims description 13
- 239000011159 matrix material Substances 0.000 claims description 12
- 238000012937 correction Methods 0.000 claims description 10
- 238000012549 training Methods 0.000 claims description 10
- 230000005856 abnormality Effects 0.000 claims description 8
- 238000004891 communication Methods 0.000 claims description 6
- 238000012800 visualization Methods 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 abstract description 5
- 230000000007 visual effect Effects 0.000 abstract description 3
- 230000015654 memory Effects 0.000 description 5
- 230000002159 abnormal effect Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 238000009440 infrastructure construction Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000012098 association analyses Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 2
- 230000009977 dual effect Effects 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 230000007787 long-term memory Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 238000004062 sedimentation Methods 0.000 description 2
- 230000006403 short-term memory Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Abstract
The invention discloses a real-time monitoring and early warning management method and system for foundation pit of an infrastructure, and aims to ensure stability and safety of foundation pit engineering through effective data processing and analysis. First, a data table is established, and main field information of sensor data is recorded. Then, a plurality of sensor data sequences are acquired through the micro-service interface. And constructing a numerical calculation model by adopting an LSTM technology, and generating a numerical solution data set sample for foundation pit monitoring. Setting a threshold value of foundation pit monitoring data, corresponding verification scheme and generating data early warning information. And finally, building a foundation pit engineering BIM model to realize visual presentation of data early warning information. The method realizes real-time monitoring and early warning of foundation pit construction of the infrastructure, improves the safety and efficiency of engineering, and is expected to be widely applied to the field of foundation pit engineering.
Description
Technical Field
The invention relates to the technical field of infrastructure construction monitoring, in particular to a real-time monitoring and early warning management method and system for an infrastructure foundation pit.
Background
Foundation pit engineering plays a vital role in urban infrastructure construction, and covers the fields of subway stations, underground parking lots, open-cut tunnels, large buildings and the like. Stability of foundation pit, safety of supporting structure and influence on surrounding environment are all core problems needing high attention in the construction process.
However, current foundation pit monitoring methods rely mainly on manual inspection, with a series of serious problems. Firstly, the manual inspection mode is low in monitoring efficiency, is greatly interfered by natural environment factors such as weather, temperature and the like, and is unstable in monitoring period, so that a great potential safety hazard exists in foundation pit monitoring. Secondly, although the automatic monitoring equipment is applied to a certain extent, the automatic monitoring equipment is interfered by vibration and the like of mechanical equipment of a construction site, a large number of noise points exist in automatic feedback data, and the foundation pit construction process is difficult to accurately monitor.
Therefore, it is necessary to provide an innovative foundation pit real-time monitoring and early warning management method and system, so as to overcome the limitations of the traditional monitoring method, improve the monitoring efficiency, reduce the safety risk and ensure the stability and safety of foundation pit engineering. The invention aims to provide a more reliable, accurate and automatic foundation pit monitoring method by combining a sensor technology and a data analysis technology, and brings greater safety and efficiency to the field of urban infrastructure construction. By processing sensor data, constructing a numerical calculation model and establishing a data early warning mechanism, the invention is expected to meet the requirements of foundation pit engineering monitoring, and provides solid technical support for smooth construction of foundation pit engineering.
Disclosure of Invention
In order to solve at least one technical problem, the invention provides a real-time monitoring and early warning management method and system for foundation pit of an infrastructure.
The first aspect of the invention provides a real-time monitoring and early warning management method for foundation pits of an infrastructure, which comprises the following steps:
constructing a data table and setting main field information of sensor data;
the method comprises the steps of calling the name, the number, the position, the return data and the return time of a sensor data sequence through a micro-service interface to obtain sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge;
filtering and denoising the sensor data, and filling the sensor data subjected to filtering and denoising into a data table correspondingly constructed to form a real-time actual measurement monitoring data set;
constructing a numerical calculation model of an infrastructure foundation pit structure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in the foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, and predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network to obtain actually measured development trend data;
Setting a threshold value of foundation pit monitoring data, performing double verification with the set threshold value according to a sensor data sequence and actual measurement development trend data returned in real time to obtain a verification scheme, and performing data early warning according to the verification scheme to obtain data early warning information;
and constructing a foundation pit engineering BIM model, performing position matching on the actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information.
In this scheme, the main field information of the sensor data is set by constructing the data table, specifically:
constructing a foundation pit sensor monitoring platform based on the internet of things technology, and receiving foundation pit monitoring data of the foundation pit sensor monitoring platform in real time;
and constructing a data table, setting main field information of the data table, and importing the foundation pit monitoring data into the data table.
In this scheme, call the sensor data sequence of sensor name, quantity, position, passback data and passback time through the microservice interface, obtain sensor data, the sensor includes inclinometer, strainometer, pore pressure gauge, axial force meter, specifically does:
micro-service programming is carried out based on Java programming technology, a scheduling interface is formed on the data table, and a micro-service interface is obtained;
And calling the name, the number, the position, the return data and the sensor data sequence of the return time of the sensor through the micro-service interface to obtain the sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge.
In this scheme, carry out filtering noise reduction to sensor data, fill the sensor data after filtering noise reduction to the data table that corresponds the constitution, form real-time actual measurement monitoring dataset, specifically do:
initializing a state vector and a covariance matrix of sensor data to obtain initial guess data of sensor data filtering operation;
predicting the state of the next time step according to the initial guess data by using a Kalman filter to obtain a data correction state value;
updating a state vector and a covariance matrix of the sensor data according to the data correction state value, and performing data reduction according to the updated state vector and covariance matrix of the sensor data to obtain sensor data subjected to filtering noise reduction;
and comparing the sensor data subjected to the filtering and noise reduction treatment with the data in the data table, judging the accuracy of the data, and filling the sensor data subjected to the filtering and noise reduction treatment into the data table correspondingly constructed to obtain a real-time actual measurement monitoring data set.
In this scheme, based on the numerical calculation model of infrastructure foundation ditch structure is established to the LSTM technique, simulate the foundation ditch theoretical data of foundation ditch in the foundation ditch work progress along with the time change, form the numerical solution dataset sample of foundation ditch monitoring, and train the numerical calculation model, obtain the numerical calculation LSTM network after training, predict the trend of real-time actual measurement monitoring dataset according to the numerical calculation LSTM network, obtain actual measurement trend data, specifically:
constructing a numerical calculation model of the foundation pit structure of the infrastructure based on the LSTM technology, and defining an input layer, an output layer and a hidden layer of the numerical calculation model;
acquiring foundation pit theoretical data according to a foundation pit construction drawing;
the method comprises the steps of taking foundation pit theoretical data as input characteristics, importing the input characteristics into a numerical calculation model, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, and predicting a change trend of the theoretical data to obtain output layer data, wherein the output layer data comprises a numerical solution data set sample of foundation pit monitoring;
predicting the foundation pit state according to the numerical solution data set sample to obtain a theoretical foundation pit state;
analyzing the numerical solution data set sample and the theoretical foundation pit state to obtain the change trend of theoretical data and the prediction weight of the foundation pit state;
Introducing the real-time actual measurement monitoring data set into a numerical calculation model, simulating the real-time actual measurement monitoring data to obtain an actual measurement data sequence, and analyzing according to the actual measurement data sequence to obtain an actual foundation pit state;
comparing the theoretical foundation pit state with the actual foundation pit state, observing the difference between the actual data sequence and the theoretical data sequence in the time sequence, and correcting the parameter weight of the numerical calculation model according to the actual foundation pit state to obtain a trained numerical calculation LSTM network;
and importing the real-time actual measurement monitoring data set into a numerical calculation LSTM network to predict the development trend of the real-time actual measurement monitoring data set, so as to obtain actual measurement development trend data.
In this scheme, set up foundation ditch monitoring data's threshold value, according to real-time passback's sensor data sequence and actual measurement development trend data, carry out dual verification with the threshold value that sets up, obtain verification scheme, carry out the data early warning according to verification scheme, obtain data early warning information, specifically do:
determining foundation pit parameters to be monitored, and setting a monitoring threshold value for each foundation pit parameter according to engineering requirements and safety standards;
double verification is carried out with a set threshold according to the real-time returned sensor data sequence and the actually measured development trend data, and if the real-time returned sensor data sequence is larger than the monitoring threshold, abnormality is prompted but no alarm is given;
If the real-time returned sensor data sequence and the actually measured development trend data are both larger than the monitoring threshold value, early warning and alarming are carried out, and a verification scheme is formed;
and carrying out data early warning according to the verification scheme to obtain data early warning information.
In this scheme, construct foundation ditch engineering BIM model, carry out the position matching with actual measurement monitoring data dataset and foundation ditch engineering BIM model, carry out the visualization to data early warning information, specifically do:
constructing a foundation pit engineering BIM model based on a BIM technology;
performing position matching on the actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information;
and sending the visualized data early warning to communication equipment of engineering monitoring personnel.
The second aspect of the invention also provides an infrastructure foundation pit real-time monitoring and early warning management system, which comprises: the system comprises a memory and a processor, wherein the memory comprises an infrastructure foundation pit real-time monitoring and early warning management method program, and when the infrastructure foundation pit real-time monitoring and early warning management method program is executed by the processor, the following steps are realized:
constructing a data table and setting main field information of sensor data;
the method comprises the steps of calling the name, the number, the position, the return data and the return time of a sensor data sequence through a micro-service interface to obtain sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge;
Filtering and denoising the sensor data, and filling the sensor data subjected to filtering and denoising into a data table correspondingly constructed to form a real-time actual measurement monitoring data set;
constructing a numerical calculation model of an infrastructure foundation pit structure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in the foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, and predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network to obtain actually measured development trend data;
setting a threshold value of foundation pit monitoring data, performing double verification with the set threshold value according to a sensor data sequence and actual measurement development trend data returned in real time to obtain a verification scheme, and performing data early warning according to the verification scheme to obtain data early warning information;
and constructing a foundation pit engineering BIM model, performing position matching on the actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information.
In this scheme, based on the numerical calculation model of infrastructure foundation ditch structure is established to the LSTM technique, simulate the foundation ditch theoretical data of foundation ditch in the foundation ditch work progress along with the time change, form the numerical solution dataset sample of foundation ditch monitoring, and train the numerical calculation model, obtain the numerical calculation LSTM network after training, predict the trend of real-time actual measurement monitoring dataset according to the numerical calculation LSTM network, obtain actual measurement trend data, specifically:
Constructing a numerical calculation model of the foundation pit structure of the infrastructure based on the LSTM technology, and defining an input layer, an output layer and a hidden layer of the numerical calculation model;
acquiring foundation pit theoretical data according to a foundation pit construction drawing;
the method comprises the steps of taking foundation pit theoretical data as input characteristics, importing the input characteristics into a numerical calculation model, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, and predicting a change trend of the theoretical data to obtain output layer data, wherein the output layer data comprises a numerical solution data set sample of foundation pit monitoring;
predicting the foundation pit state according to the numerical solution data set sample to obtain a theoretical foundation pit state;
analyzing the numerical solution data set sample and the theoretical foundation pit state to obtain the change trend of theoretical data and the prediction weight of the foundation pit state;
introducing the real-time actual measurement monitoring data set into a numerical calculation model, simulating the real-time actual measurement monitoring data to obtain an actual measurement data sequence, and analyzing according to the actual measurement data sequence to obtain an actual foundation pit state;
comparing the theoretical foundation pit state with the actual foundation pit state, observing the difference between the actual data sequence and the theoretical data sequence in the time sequence, and correcting the parameter weight of the numerical calculation model according to the actual foundation pit state to obtain a trained numerical calculation LSTM network;
And importing the real-time actual measurement monitoring data set into a numerical calculation LSTM network to predict the development trend of the real-time actual measurement monitoring data set, so as to obtain actual measurement development trend data.
In this scheme, set up foundation ditch monitoring data's threshold value, according to real-time passback's sensor data sequence and actual measurement development trend data, carry out dual verification with the threshold value that sets up, obtain verification scheme, carry out the data early warning according to verification scheme, obtain data early warning information, specifically do:
determining foundation pit parameters to be monitored, and setting a monitoring threshold value for each foundation pit parameter according to engineering requirements and safety standards;
double verification is carried out with a set threshold according to the real-time returned sensor data sequence and the actually measured development trend data, and if the real-time returned sensor data sequence is larger than the monitoring threshold, abnormality is prompted but no alarm is given;
if the real-time returned sensor data sequence and the actually measured development trend data are both larger than the monitoring threshold value, early warning and alarming are carried out, and a verification scheme is formed;
and carrying out data early warning according to the verification scheme to obtain data early warning information.
The invention discloses a real-time monitoring and early warning management method and system for foundation pit of an infrastructure, and aims to ensure stability and safety of foundation pit engineering through effective data processing and analysis. First, a data table is established, and main field information of sensor data is recorded. Then, through the micro-service interface, various sensor data sequences are acquired. And constructing a numerical calculation model by adopting an LSTM technology, and generating a numerical solution data set sample for foundation pit monitoring. Setting a threshold value of foundation pit monitoring data, corresponding verification scheme and generating data early warning information. And finally, building a foundation pit engineering BIM model to realize visual presentation of data early warning information. The method realizes real-time monitoring and early warning of foundation pit construction of the infrastructure, improves the safety and efficiency of engineering, and is expected to be widely applied to the field of foundation pit engineering.
Drawings
FIG. 1 shows a flow chart of an infrastructure pit real-time monitoring and early warning management method of the invention;
FIG. 2 illustrates a flow chart of the present invention for forming a real-time measured monitoring dataset;
FIG. 3 shows a flow chart of the present invention for obtaining data pre-warning information;
fig. 4 shows a block diagram of an infrastructure pit real-time monitoring and early warning management system of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
Fig. 1 shows a flow chart of an infrastructure pit real-time monitoring and early warning management method of the invention.
As shown in fig. 1, the first aspect of the present invention provides a method for real-time monitoring and early warning management of an infrastructure foundation pit, including:
S102, constructing a data table and setting main field information of sensor data;
s104, calling the name, the number, the position, the return data and the sensor data sequence of the return time of the sensor through the micro-service interface to obtain sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge;
s106, carrying out filtering noise reduction treatment on the sensor data, and filling the sensor data subjected to the filtering noise reduction treatment into a data table correspondingly constructed to form a real-time actual measurement monitoring data set;
s108, constructing a numerical calculation model of the foundation pit structure of the infrastructure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in the foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, and predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network to obtain actually measured development trend data;
s110, setting a threshold value of foundation pit monitoring data, performing double verification with the set threshold value according to a sensor data sequence and actual measurement development trend data returned in real time to obtain a verification scheme, and performing data early warning according to the verification scheme to obtain data early warning information;
And S112, constructing a foundation pit engineering BIM model, performing position matching on the actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information.
According to the embodiment of the invention, the data table is constructed, and main field information of sensor data is set, specifically:
constructing a foundation pit sensor monitoring platform based on the internet of things technology, and receiving foundation pit monitoring data of the foundation pit sensor monitoring platform in real time;
and constructing a data table, setting main field information of the data table, and importing the foundation pit monitoring data into the data table.
It is to be noted that firstly, an internet of things technology is adopted to construct a foundation pit sensor monitoring platform, and the platform can receive monitoring data from foundation pit sensor monitoring equipment in real time; secondly, in order to effectively manage the foundation pit monitoring data, a data table is established for storing and organizing the foundation pit monitoring data; the data field is set to ensure accuracy and ease of analysis of the data.
According to the embodiment of the invention, the name, the number, the position, the return data and the sensor data sequence of the return time of the sensor are called through the micro-service interface to obtain the sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge, and specifically comprises:
Micro-service programming is carried out based on Java programming technology, a scheduling interface is formed on the data table, and a micro-service interface is obtained;
and calling the name, the number, the position, the return data and the sensor data sequence of the return time of the sensor through the micro-service interface to obtain the sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge.
It should be noted that, through Java programming technology, a micro-service is developed, and the micro-service forms a scheduling interface for interacting with the data table, and through the scheduling interface, key information of the foundation pit sensor can be easily obtained, so that efficient obtaining and management of sensor data are realized.
FIG. 2 illustrates a flow chart of the present invention for forming a real-time measured monitoring dataset.
According to the embodiment of the invention, the sensor data is subjected to filtering noise reduction treatment, and the sensor data after the filtering noise reduction treatment is filled into a data table correspondingly constructed to form a real-time actual measurement monitoring data set, specifically:
s202, initializing a state vector and a covariance matrix of sensor data to obtain initial guess data of sensor data filtering operation;
s204, predicting the state of the next time step according to the initial guess data by using a Kalman filter to obtain a data correction state value;
S206, updating a state vector and a covariance matrix of the sensor data according to the data correction state value, and performing data reduction according to the updated state vector and covariance matrix of the sensor data to obtain sensor data subjected to filtering noise reduction;
s208, comparing the sensor data subjected to the filtering and noise reduction processing with the data in the data table, judging the accuracy of the data, and filling the sensor data subjected to the filtering and noise reduction processing into the data table correspondingly constructed to obtain a real-time actual measurement monitoring data set.
It should be noted that, in the embodiment of the invention, the accuracy of the sensor data can be improved by performing Kalman filtering noise reduction processing on the sensor data, noise and fluctuation in the data can be removed, and the monitoring data is more reliable; the time step is a preset time period length.
According to the embodiment of the invention, a numerical calculation model of an infrastructure foundation pit structure is constructed based on an LSTM technology, foundation pit theoretical data changing along with time in the foundation pit construction process is simulated, a numerical solution data set sample of foundation pit monitoring is formed, the numerical calculation model is trained, a trained numerical calculation LSTM network is obtained, and the development trend of a real-time actually measured monitoring data set is predicted according to the numerical calculation LSTM network, so that actually measured development trend data is obtained, specifically:
Constructing a numerical calculation model of the foundation pit structure of the infrastructure based on the LSTM technology, and defining an input layer, an output layer and a hidden layer of the numerical calculation model;
acquiring foundation pit theoretical data according to a foundation pit construction drawing;
the method comprises the steps of taking foundation pit theoretical data as input characteristics, importing the input characteristics into a numerical calculation model, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, and predicting a change trend of the theoretical data to obtain output layer data, wherein the output layer data comprises a numerical solution data set sample of foundation pit monitoring;
predicting the foundation pit state according to the numerical solution data set sample to obtain a theoretical foundation pit state;
analyzing the numerical solution data set sample and the theoretical foundation pit state to obtain the change trend of theoretical data and the prediction weight of the foundation pit state;
introducing the real-time actual measurement monitoring data set into a numerical calculation model, simulating the real-time actual measurement monitoring data to obtain an actual measurement data sequence, and analyzing according to the actual measurement data sequence to obtain an actual foundation pit state;
comparing the theoretical foundation pit state with the actual foundation pit state, observing the difference between the actual data sequence and the theoretical data sequence in the time sequence, and correcting the parameter weight of the numerical calculation model according to the actual foundation pit state to obtain a trained numerical calculation LSTM network;
And importing the real-time actual measurement monitoring data set into a numerical calculation LSTM network to predict the development trend of the real-time actual measurement monitoring data set, so as to obtain actual measurement development trend data.
The method is characterized in that the theoretical state of the foundation pit is firstly predicted according to the theoretical data of the foundation pit through an LSTM technology, then the actual state of the foundation pit is predicted according to real-time actually measured monitoring data, and a numerical calculation model is subjected to parameter correction according to the theoretical state and the actual state, so that a trained numerical calculation LSTM network is obtained, and the prediction accuracy rate of the development trend of a real-time actually measured monitoring data set is improved; the LSTM technology is utilized to simulate and predict the foundation pit monitoring data, so that the accurate prediction and real-time monitoring of the foundation pit state are realized, and the powerful foundation pit real-time monitoring and early warning management capability of the infrastructure is provided; the numerical calculation LSTM network has the main function of predicting the monitoring data of the foundation pit in the future; the foundation pit theoretical data comprise displacement, deformation, sedimentation and internal force change data of the foundation pit; the LSTM is a long and short-term memory network and can accurately predict data.
Fig. 3 shows a flow chart of the present invention for obtaining data pre-warning information.
According to the embodiment of the invention, the threshold value of the foundation pit monitoring data is set, double verification is carried out with the set threshold value according to the real-time returned sensor data sequence and the actually measured development trend data to obtain a verification scheme, and data early warning is carried out according to the verification scheme to obtain data early warning information, specifically:
s302, determining foundation pit parameters to be monitored, and setting a monitoring threshold value for each foundation pit parameter according to engineering requirements and safety standards;
s304, performing double verification with a set threshold according to the real-time returned sensor data sequence and the actually measured development trend data, and prompting abnormality but not alarming if the real-time returned sensor data sequence is larger than the monitoring threshold;
s306, if the real-time returned sensor data sequence and the actually measured development trend data are both larger than the monitoring threshold value, early warning and alarming are carried out, and a verification scheme is formed;
and S308, carrying out data early warning according to the verification scheme to obtain data early warning information.
By means of a double verification mechanism, real-time sensor data and development trend data are comprehensively considered, so that accurate early warning can be conducted when foundation pit construction abnormality occurs; by setting the monitoring threshold value and generating the verification scheme, the accuracy and the reliability of foundation pit monitoring of the infrastructure are improved, and necessary measures can be taken in time to ensure the safety and the stability of engineering; the sensor data sequence returned in real time is the sensor data returned by the foundation pit sensor monitoring platform in time sequence; the data early warning information comprises data change dangerous degree, data abnormal positions and data abnormal equipment.
According to the embodiment of the invention, the foundation pit engineering BIM model is constructed, the actually measured monitoring data set is matched with the foundation pit engineering BIM model in position, and the data early warning information is visualized, specifically:
constructing a foundation pit engineering BIM model based on a BIM technology;
performing position matching on the actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information;
and sending the visualized data early warning to communication equipment of engineering monitoring personnel.
It should be noted that, a three-dimensional model of foundation pit engineering is constructed by BIM technology, the model comprises various structures and characteristic information of the foundation pit, and the actually measured monitoring data set is matched with the foundation pit engineering BIM model in position, so that the corresponding relation between the monitoring data and the engineering model is realized; the embodiment of the invention combines BIM technology and actually measured monitoring data, so that engineering monitoring personnel can intuitively observe data early warning information in a three-dimensional model and correlate the early warning information with the specific position of foundation pit engineering, a more intuitive and more information-based monitoring data presentation mode is provided, the engineering monitoring personnel can be helped to identify problems more quickly and accurately and take necessary actions, and the real-time monitoring and early warning management level of foundation pit construction is improved; in addition, based on the visualized data early warning information, the method can also send the warning information to the communication equipment of engineering monitoring personnel, so as to ensure timely response and decision; the BIM model is a building information model.
According to an embodiment of the present invention, further comprising:
acquiring the change data of each sensor of a foundation pit sensor monitoring platform in a preset time period, and drawing the change data into a graph;
carrying out association analysis on each drawn graph, sequentially extracting the graphs, acquiring the monitoring item name of the graph according to a sensor monitoring platform by using the extracted graphs, and taking the monitoring item name as a reference item;
analyzing whether the change information of the extracted graph can cause the related change of other graphs, and if the related change exists, marking the graph of the related change to obtain a marked graph;
acquiring the project name of the foundation pit of the infrastructure of the graph according to the marked graph;
obtaining a foundation pit engineering project associated change project according to the project name;
and if the data change of the basic project exceeds the foundation pit parameter set monitoring threshold, performing key monitoring on the related change project of the foundation pit engineering project to form a related change project monitoring scheme of the foundation pit engineering project.
It should be noted that, the data change of a certain project in the foundation pit engineering may cause the data change of other projects, the foundation pit project which causes the change is marked as the related change project of the foundation pit engineering project, if the reference project changes, the related change project of the foundation pit engineering project is monitored, and a monitoring scheme for forming the related change project of the foundation pit engineering project is formed, through early discovery and monitoring of potential problems, the occurrence of safety accidents can be prevented, the construction risk is reduced, the safety of constructors is protected, and meanwhile, the efficiency and quality of the engineering are improved.
Fig. 4 shows a block diagram of an infrastructure pit real-time monitoring and early warning management system of the present invention.
The second aspect of the present invention also provides an infrastructure foundation pit real-time monitoring and early warning management system 4, which comprises: the system comprises a memory 41 and a processor 42, wherein the memory comprises an infrastructure foundation pit real-time monitoring and early warning management method program, and when the infrastructure foundation pit real-time monitoring and early warning management method program is executed by the processor, the following steps are realized:
constructing a data table and setting main field information of sensor data;
the method comprises the steps of calling the name, the number, the position, the return data and the return time of a sensor data sequence through a micro-service interface to obtain sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge;
filtering and denoising the sensor data, and filling the sensor data subjected to filtering and denoising into a data table correspondingly constructed to form a real-time actual measurement monitoring data set;
constructing a numerical calculation model of an infrastructure foundation pit structure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in the foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, and predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network to obtain actually measured development trend data;
Setting a threshold value of foundation pit monitoring data, performing double verification with the set threshold value according to a sensor data sequence and actual measurement development trend data returned in real time to obtain a verification scheme, and performing data early warning according to the verification scheme to obtain data early warning information;
and constructing a foundation pit engineering BIM model, performing position matching on the actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information.
According to the embodiment of the invention, the data table is constructed, and main field information of sensor data is set, specifically:
constructing a foundation pit sensor monitoring platform based on the internet of things technology, and receiving foundation pit monitoring data of the foundation pit sensor monitoring platform in real time;
and constructing a data table, setting main field information of the data table, and importing the foundation pit monitoring data into the data table.
It is to be noted that firstly, an internet of things technology is adopted to construct a foundation pit sensor monitoring platform, and the platform can receive monitoring data from foundation pit sensor monitoring equipment in real time; secondly, in order to effectively manage the foundation pit monitoring data, a data table is established for storing and organizing the foundation pit monitoring data; the data field is set to ensure accuracy and ease of analysis of the data.
According to the embodiment of the invention, the name, the number, the position, the return data and the sensor data sequence of the return time of the sensor are called through the micro-service interface to obtain the sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge, and specifically comprises:
micro-service programming is carried out based on Java programming technology, a scheduling interface is formed on the data table, and a micro-service interface is obtained;
and calling the name, the number, the position, the return data and the sensor data sequence of the return time of the sensor through the micro-service interface to obtain the sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge.
It should be noted that, through Java programming technology, a micro-service is developed, and the micro-service forms a scheduling interface for interacting with the data table, and through the scheduling interface, key information of the foundation pit sensor can be easily obtained, so that efficient obtaining and management of sensor data are realized.
According to the embodiment of the invention, the sensor data is subjected to filtering noise reduction treatment, and the sensor data after the filtering noise reduction treatment is filled into a data table correspondingly constructed to form a real-time actual measurement monitoring data set, specifically:
Initializing a state vector and a covariance matrix of sensor data to obtain initial guess data of sensor data filtering operation;
predicting the state of the next time step according to the initial guess data by using a Kalman filter to obtain a data correction state value;
updating a state vector and a covariance matrix of the sensor data according to the data correction state value, and performing data reduction according to the updated state vector and covariance matrix of the sensor data to obtain sensor data subjected to filtering noise reduction;
and comparing the sensor data subjected to the filtering and noise reduction treatment with the data in the data table, judging the accuracy of the data, and filling the sensor data subjected to the filtering and noise reduction treatment into the data table correspondingly constructed to obtain a real-time actual measurement monitoring data set.
It should be noted that, in the embodiment of the invention, the accuracy of the sensor data can be improved by performing Kalman filtering noise reduction processing on the sensor data, noise and fluctuation in the data can be removed, and the monitoring data is more reliable; the time step is a preset time period length.
According to the embodiment of the invention, a numerical calculation model of an infrastructure foundation pit structure is constructed based on an LSTM technology, foundation pit theoretical data changing along with time in the foundation pit construction process is simulated, a numerical solution data set sample of foundation pit monitoring is formed, the numerical calculation model is trained, a trained numerical calculation LSTM network is obtained, and the development trend of a real-time actually measured monitoring data set is predicted according to the numerical calculation LSTM network, so that actually measured development trend data is obtained, specifically:
Constructing a numerical calculation model of the foundation pit structure of the infrastructure based on the LSTM technology, and defining an input layer, an output layer and a hidden layer of the numerical calculation model;
acquiring foundation pit theoretical data according to a foundation pit construction drawing;
the method comprises the steps of taking foundation pit theoretical data as input characteristics, importing the input characteristics into a numerical calculation model, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, and predicting a change trend of the theoretical data to obtain output layer data, wherein the output layer data comprises a numerical solution data set sample of foundation pit monitoring;
predicting the foundation pit state according to the numerical solution data set sample to obtain a theoretical foundation pit state;
analyzing the numerical solution data set sample and the theoretical foundation pit state to obtain the change trend of theoretical data and the prediction weight of the foundation pit state;
introducing the real-time actual measurement monitoring data set into a numerical calculation model, simulating the real-time actual measurement monitoring data to obtain an actual measurement data sequence, and analyzing according to the actual measurement data sequence to obtain an actual foundation pit state;
comparing the theoretical foundation pit state with the actual foundation pit state, observing the difference between the actual data sequence and the theoretical data sequence in the time sequence, and correcting the parameter weight of the numerical calculation model according to the actual foundation pit state to obtain a trained numerical calculation LSTM network;
And importing the real-time actual measurement monitoring data set into a numerical calculation LSTM network to predict the development trend of the real-time actual measurement monitoring data set, so as to obtain actual measurement development trend data.
The method is characterized in that the theoretical state of the foundation pit is firstly predicted according to the theoretical data of the foundation pit through an LSTM technology, then the actual state of the foundation pit is predicted according to real-time actually measured monitoring data, and a numerical calculation model is subjected to parameter correction according to the theoretical state and the actual state, so that a trained numerical calculation LSTM network is obtained, and the prediction accuracy rate of the development trend of a real-time actually measured monitoring data set is improved; the LSTM technology is utilized to simulate and predict the foundation pit monitoring data, so that the accurate prediction and real-time monitoring of the foundation pit state are realized, and the powerful foundation pit real-time monitoring and early warning management capability of the infrastructure is provided; the numerical calculation LSTM network has the main function of predicting the monitoring data of the foundation pit in the future; the foundation pit theoretical data comprise displacement, deformation, sedimentation and internal force change data of the foundation pit; the LSTM is a long and short-term memory network and can accurately predict data.
According to the embodiment of the invention, the threshold value of the foundation pit monitoring data is set, double verification is carried out with the set threshold value according to the real-time returned sensor data sequence and the actually measured development trend data to obtain a verification scheme, and data early warning is carried out according to the verification scheme to obtain data early warning information, specifically:
Determining foundation pit parameters to be monitored, and setting a monitoring threshold value for each foundation pit parameter according to engineering requirements and safety standards;
double verification is carried out with a set threshold according to the real-time returned sensor data sequence and the actually measured development trend data, and if the real-time returned sensor data sequence is larger than the monitoring threshold, abnormality is prompted but no alarm is given;
if the real-time returned sensor data sequence and the actually measured development trend data are both larger than the monitoring threshold value, early warning and alarming are carried out, and a verification scheme is formed;
and carrying out data early warning according to the verification scheme to obtain data early warning information.
By means of a double verification mechanism, real-time sensor data and development trend data are comprehensively considered, so that accurate early warning can be conducted when foundation pit construction abnormality occurs; by setting the monitoring threshold value and generating the verification scheme, the accuracy and the reliability of foundation pit monitoring of the infrastructure are improved, and necessary measures can be taken in time to ensure the safety and the stability of engineering; the sensor data sequence returned in real time is the sensor data returned by the foundation pit sensor monitoring platform in time sequence; the data early warning information comprises data change dangerous degree, data abnormal positions and data abnormal equipment.
According to the embodiment of the invention, the foundation pit engineering BIM model is constructed, the actually measured monitoring data set is matched with the foundation pit engineering BIM model in position, and the data early warning information is visualized, specifically:
constructing a foundation pit engineering BIM model based on a BIM technology;
performing position matching on the actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information;
and sending the visualized data early warning to communication equipment of engineering monitoring personnel.
It should be noted that, a three-dimensional model of foundation pit engineering is constructed by BIM technology, the model comprises various structures and characteristic information of the foundation pit, and the actually measured monitoring data set is matched with the foundation pit engineering BIM model in position, so that the corresponding relation between the monitoring data and the engineering model is realized; the embodiment of the invention combines BIM technology and actually measured monitoring data, so that engineering monitoring personnel can intuitively observe data early warning information in a three-dimensional model and correlate the early warning information with the specific position of foundation pit engineering, a more intuitive and more information-based monitoring data presentation mode is provided, the engineering monitoring personnel can be helped to identify problems more quickly and accurately and take necessary actions, and the real-time monitoring and early warning management level of foundation pit construction is improved; in addition, based on the visualized data early warning information, the method can also send the warning information to the communication equipment of engineering monitoring personnel, so as to ensure timely response and decision; the BIM model is a building information model.
According to an embodiment of the present invention, further comprising:
acquiring the change data of each sensor of a foundation pit sensor monitoring platform in a preset time period, and drawing the change data into a graph;
carrying out association analysis on each drawn graph, sequentially extracting the graphs, acquiring the monitoring item name of the graph according to a sensor monitoring platform by using the extracted graphs, and taking the monitoring item name as a reference item;
analyzing whether the change information of the extracted graph can cause the related change of other graphs, and if the related change exists, marking the graph of the related change to obtain a marked graph;
acquiring the project name of the foundation pit of the infrastructure of the graph according to the marked graph;
obtaining a foundation pit engineering project associated change project according to the project name;
and if the data change of the basic project exceeds the foundation pit parameter set monitoring threshold, performing key monitoring on the related change project of the foundation pit engineering project to form a related change project monitoring scheme of the foundation pit engineering project.
It should be noted that, the data change of a certain project in the foundation pit engineering may cause the data change of other projects, the foundation pit project which causes the change is marked as the related change project of the foundation pit engineering project, if the reference project changes, the related change project of the foundation pit engineering project is monitored, and a monitoring scheme for forming the related change project of the foundation pit engineering project is formed, through early discovery and monitoring of potential problems, the occurrence of safety accidents can be prevented, the construction risk is reduced, the safety of constructors is protected, and meanwhile, the efficiency and quality of the engineering are improved.
The invention discloses a real-time monitoring and early warning management method and system for foundation pit of an infrastructure, and aims to ensure stability and safety of foundation pit engineering through effective data processing and analysis. First, a data table is established, and main field information of sensor data is recorded. Then, through the micro-service interface, various sensor data sequences are acquired. And constructing a numerical calculation model by adopting an LSTM technology, and generating a numerical solution data set sample for foundation pit monitoring. Setting a threshold value of foundation pit monitoring data, corresponding verification scheme and generating data early warning information. And finally, building a foundation pit engineering BIM model to realize visual presentation of data early warning information. The method realizes real-time monitoring and early warning of foundation pit construction of the infrastructure, improves the safety and efficiency of engineering, and is expected to be widely applied to the field of foundation pit engineering.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. The infrastructure foundation pit real-time monitoring and early warning management method is characterized by comprising the following steps of:
constructing a data table and setting main field information of sensor data;
the method comprises the steps of calling the name, the number, the position, the return data and the return time of a sensor data sequence through a micro-service interface to obtain sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge;
filtering and denoising the sensor data, and filling the sensor data subjected to filtering and denoising into a data table correspondingly constructed to form a real-time actual measurement monitoring data set;
constructing a numerical calculation model of an infrastructure foundation pit structure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in the foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, and predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network to obtain actually measured development trend data;
setting a threshold value of foundation pit monitoring data, performing double verification with the set threshold value according to a sensor data sequence and actual measurement development trend data returned in real time to obtain a verification scheme, and performing data early warning according to the verification scheme to obtain data early warning information;
Building a foundation pit engineering BIM model, performing position matching on a real-time actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information;
the method comprises the steps of constructing a numerical calculation model of an infrastructure foundation pit structure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network, and obtaining actually measured development trend data, wherein the method comprises the following steps of:
constructing a numerical calculation model of the foundation pit structure of the infrastructure based on the LSTM technology, and defining an input layer, an output layer and a hidden layer of the numerical calculation model;
acquiring foundation pit theoretical data according to a foundation pit construction drawing;
the method comprises the steps of taking foundation pit theoretical data as input characteristics, importing the input characteristics into a numerical calculation model, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, and predicting a change trend of the theoretical data to obtain output layer data, wherein the output layer data comprises a numerical solution data set sample of foundation pit monitoring;
Predicting the foundation pit state according to the numerical solution data set sample to obtain a theoretical foundation pit state;
analyzing the numerical solution data set sample and the theoretical foundation pit state to obtain the change trend of theoretical data and the prediction weight of the foundation pit state;
introducing the real-time actual measurement monitoring data set into a numerical calculation model, simulating the real-time actual measurement monitoring data to obtain an actual measurement data sequence, and analyzing according to the actual measurement data sequence to obtain an actual foundation pit state;
comparing the theoretical foundation pit state with the actual foundation pit state, observing the difference between the actual data sequence and the theoretical data sequence in the time sequence, and correcting the parameter weight of the numerical calculation model according to the actual foundation pit state to obtain a trained numerical calculation LSTM network;
introducing the real-time actual measurement monitoring data set into a numerical calculation LSTM network to predict the development trend of the real-time actual measurement monitoring data set, so as to obtain actual measurement development trend data;
the threshold value of the foundation pit monitoring data is set, double verification is carried out with the set threshold value according to the sensor data sequence and the actually measured development trend data which are returned in real time, a verification scheme is obtained, data early warning is carried out according to the verification scheme, and data early warning information is obtained specifically as follows:
Determining foundation pit parameters to be monitored, and setting a monitoring threshold value for each foundation pit parameter according to engineering requirements and safety standards;
double verification is carried out with a set threshold according to the real-time returned sensor data sequence and the actually measured development trend data, and if the real-time returned sensor data sequence is larger than the monitoring threshold, abnormality is prompted but no alarm is given;
if the real-time returned sensor data sequence and the actually measured development trend data are both larger than the monitoring threshold value, early warning and alarming are carried out, and a verification scheme is formed;
and carrying out data early warning according to the verification scheme to obtain data early warning information.
2. The method for real-time monitoring and early warning management of foundation pit of claim 1, wherein the constructing a data table sets main field information of sensor data, specifically:
constructing a foundation pit sensor monitoring platform based on the internet of things technology, and receiving foundation pit monitoring data of the foundation pit sensor monitoring platform in real time;
and constructing a data table, setting main field information of the data table, and importing the foundation pit monitoring data into the data table.
3. The method for monitoring and early warning management of foundation pit in real time according to claim 1, wherein the name, number, position, return data and return time sensor data sequence of the sensor are called through a micro service interface to obtain sensor data, and the sensor comprises inclinometer, strain gauge, pore pressure gauge and axial force gauge, specifically:
And performing micro-service programming based on Java programming technology, and forming a scheduling interface for the data table to obtain the micro-service interface.
4. The method for real-time monitoring and early warning management of foundation pit according to claim 1, wherein the filtering and noise reduction processing is performed on the sensor data, and the sensor data after the filtering and noise reduction processing is filled into a correspondingly constructed data table to form a real-time actual measurement monitoring data set, specifically:
initializing a state vector and a covariance matrix of sensor data to obtain initial guess data of sensor data filtering operation;
predicting the state of the next time step according to the initial guess data by using a Kalman filter to obtain a data correction state value;
updating a state vector and a covariance matrix of the sensor data according to the data correction state value, and performing data reduction according to the updated state vector and covariance matrix of the sensor data to obtain sensor data subjected to filtering noise reduction;
and comparing the sensor data subjected to the filtering and noise reduction treatment with the data in the data table, judging the accuracy of the data, and filling the sensor data subjected to the filtering and noise reduction treatment into the data table correspondingly constructed to obtain a real-time actual measurement monitoring data set.
5. The method for real-time monitoring and early warning management of foundation pit according to claim 1, wherein the building of the foundation pit engineering BIM model, the position matching of the real-time actually measured monitoring dataset and the foundation pit engineering BIM model, and the visualization of the data early warning information are specifically as follows:
constructing a foundation pit engineering BIM model based on a BIM technology;
performing position matching on the real-time actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information;
and sending the visualized data early warning to communication equipment of engineering monitoring personnel.
6. The infrastructure foundation pit real-time monitoring and early warning management system is characterized by comprising a storage and a processor, wherein the storage comprises an infrastructure foundation pit real-time monitoring and early warning management method program, and when the infrastructure foundation pit real-time monitoring and early warning management method program is executed by the processor, the following steps are realized:
constructing a data table and setting main field information of sensor data;
the method comprises the steps of calling the name, the number, the position, the return data and the return time of a sensor data sequence through a micro-service interface to obtain sensor data, wherein the sensor comprises an inclinometer, a strain gauge, a pore pressure gauge and an axial force gauge;
Filtering and denoising the sensor data, and filling the sensor data subjected to filtering and denoising into a data table correspondingly constructed to form a real-time actual measurement monitoring data set;
constructing a numerical calculation model of an infrastructure foundation pit structure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in the foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, and predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network to obtain actually measured development trend data;
setting a threshold value of foundation pit monitoring data, performing double verification with the set threshold value according to a sensor data sequence and actual measurement development trend data returned in real time to obtain a verification scheme, and performing data early warning according to the verification scheme to obtain data early warning information;
building a foundation pit engineering BIM model, performing position matching on a real-time actually measured monitoring data set and the foundation pit engineering BIM model, and visualizing data early warning information;
the method comprises the steps of constructing a numerical calculation model of an infrastructure foundation pit structure based on an LSTM technology, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, forming a numerical solution data set sample of foundation pit monitoring, training the numerical calculation model to obtain a trained numerical calculation LSTM network, predicting the development trend of a real-time actually measured monitoring data set according to the numerical calculation LSTM network, and obtaining actually measured development trend data, wherein the method comprises the following steps of:
Constructing a numerical calculation model of the foundation pit structure of the infrastructure based on the LSTM technology, and defining an input layer, an output layer and a hidden layer of the numerical calculation model;
acquiring foundation pit theoretical data according to a foundation pit construction drawing;
the method comprises the steps of taking foundation pit theoretical data as input characteristics, importing the input characteristics into a numerical calculation model, simulating foundation pit theoretical data changing along with time in a foundation pit construction process, and predicting a change trend of the theoretical data to obtain output layer data, wherein the output layer data comprises a numerical solution data set sample of foundation pit monitoring;
predicting the foundation pit state according to the numerical solution data set sample to obtain a theoretical foundation pit state;
analyzing the numerical solution data set sample and the theoretical foundation pit state to obtain the change trend of theoretical data and the prediction weight of the foundation pit state;
introducing the real-time actual measurement monitoring data set into a numerical calculation model, simulating the real-time actual measurement monitoring data to obtain an actual measurement data sequence, and analyzing according to the actual measurement data sequence to obtain an actual foundation pit state;
comparing the theoretical foundation pit state with the actual foundation pit state, observing the difference between the actual data sequence and the theoretical data sequence in the time sequence, and correcting the parameter weight of the numerical calculation model according to the actual foundation pit state to obtain a trained numerical calculation LSTM network;
Introducing the real-time actual measurement monitoring data set into a numerical calculation LSTM network to predict the development trend of the real-time actual measurement monitoring data set, so as to obtain actual measurement development trend data;
the threshold value of the foundation pit monitoring data is set, double verification is carried out with the set threshold value according to the sensor data sequence and the actually measured development trend data which are returned in real time, a verification scheme is obtained, data early warning is carried out according to the verification scheme, and data early warning information is obtained specifically as follows:
determining foundation pit parameters to be monitored, and setting a monitoring threshold value for each foundation pit parameter according to engineering requirements and safety standards;
double verification is carried out with a set threshold according to the real-time returned sensor data sequence and the actually measured development trend data, and if the real-time returned sensor data sequence is larger than the monitoring threshold, abnormality is prompted but no alarm is given;
if the real-time returned sensor data sequence and the actually measured development trend data are both larger than the monitoring threshold value, early warning and alarming are carried out, and a verification scheme is formed;
and carrying out data early warning according to the verification scheme to obtain data early warning information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311462540.7A CN117196893B (en) | 2023-11-06 | 2023-11-06 | Infrastructure foundation pit real-time monitoring and early warning management method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311462540.7A CN117196893B (en) | 2023-11-06 | 2023-11-06 | Infrastructure foundation pit real-time monitoring and early warning management method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117196893A CN117196893A (en) | 2023-12-08 |
| CN117196893B true CN117196893B (en) | 2024-01-05 |
Family
ID=89005636
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311462540.7A Active CN117196893B (en) | 2023-11-06 | 2023-11-06 | Infrastructure foundation pit real-time monitoring and early warning management method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117196893B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104796483A (en) * | 2015-04-29 | 2015-07-22 | 无锡悟莘科技有限公司 | Large infrastructure monitoring and early warning system |
| CN107829452A (en) * | 2017-11-12 | 2018-03-23 | 湖南科技大学 | It is a kind of to merge multisensor and ground SAR deep foundation pit construction monitoring and warning technology |
| CN109118388A (en) * | 2018-09-13 | 2019-01-01 | 深圳市栋森工程项目管理有限公司 | A kind of infrastructure building Supervision based on BIM |
| KR102225146B1 (en) * | 2019-12-13 | 2021-03-10 | 주식회사 이에스피 | Mine Vehicle V2X System and Method for Management of Mine Safety |
| CN112528365A (en) * | 2020-11-30 | 2021-03-19 | 北京航空航天大学 | Method for predicting health evolution trend of underground infrastructure structure |
| CN113404029A (en) * | 2021-07-12 | 2021-09-17 | 苏州思萃融合基建技术研究所有限公司 | Construction site deep foundation pit intelligent monitoring and early warning system based on digital twin technology |
| CN113779835A (en) * | 2021-09-11 | 2021-12-10 | 浙江永欣联科信息科技股份有限公司 | AI and intelligent monitoring system based deep and large foundation pit safety early warning method |
| CN215114531U (en) * | 2021-04-25 | 2021-12-10 | 武汉智岩测控技术有限公司 | Foundation pit inclination angle inclinometer |
| CN114005278A (en) * | 2021-11-01 | 2022-02-01 | 河北省高速公路延崇管理中心 | Intelligent monitoring and early warning system and method for highway infrastructure group |
-
2023
- 2023-11-06 CN CN202311462540.7A patent/CN117196893B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104796483A (en) * | 2015-04-29 | 2015-07-22 | 无锡悟莘科技有限公司 | Large infrastructure monitoring and early warning system |
| CN107829452A (en) * | 2017-11-12 | 2018-03-23 | 湖南科技大学 | It is a kind of to merge multisensor and ground SAR deep foundation pit construction monitoring and warning technology |
| CN109118388A (en) * | 2018-09-13 | 2019-01-01 | 深圳市栋森工程项目管理有限公司 | A kind of infrastructure building Supervision based on BIM |
| KR102225146B1 (en) * | 2019-12-13 | 2021-03-10 | 주식회사 이에스피 | Mine Vehicle V2X System and Method for Management of Mine Safety |
| CN112528365A (en) * | 2020-11-30 | 2021-03-19 | 北京航空航天大学 | Method for predicting health evolution trend of underground infrastructure structure |
| CN215114531U (en) * | 2021-04-25 | 2021-12-10 | 武汉智岩测控技术有限公司 | Foundation pit inclination angle inclinometer |
| CN113404029A (en) * | 2021-07-12 | 2021-09-17 | 苏州思萃融合基建技术研究所有限公司 | Construction site deep foundation pit intelligent monitoring and early warning system based on digital twin technology |
| CN113779835A (en) * | 2021-09-11 | 2021-12-10 | 浙江永欣联科信息科技股份有限公司 | AI and intelligent monitoring system based deep and large foundation pit safety early warning method |
| CN114005278A (en) * | 2021-11-01 | 2022-02-01 | 河北省高速公路延崇管理中心 | Intelligent monitoring and early warning system and method for highway infrastructure group |
Non-Patent Citations (5)
| Title |
|---|
| 基于BIM技术的基坑监测应用研究;孙艳崇;;科学技术创新(第24期);193-194 * |
| 基于长短时记忆网络的深基坑变形安全风险预警;夏天 等;地球科学;第48卷(第10期);3925-3930 * |
| 某地铁站深基坑支护桩的变形分析及预测;彭涛;高玉华;;工程与建设(第06期);90-93 * |
| 深基坑施工中基坑监测技术的应用;许俊杰;科技创新与生产力;第44卷(第10期);124-129 * |
| 郑沟站拆除重建工程基坑安全监测 及预警阈值分析;史冲;江淮水利科技(第3期);25-28 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117196893A (en) | 2023-12-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109064037B (en) | Foundation pit construction risk management and control method, system and equipment | |
| CN106368247A (en) | Foundation pit intelligent monitoring and active forewarning method and system based on building information modeling (BIM) | |
| CN108615098B (en) | Bayesian survival analysis-based water supply network pipeline pipe burst risk prediction method | |
| CN110808864A (en) | Communication early warning method, device and system | |
| US9719881B2 (en) | Scalable framework for managing civil structure monitoring devices | |
| CN111583067A (en) | Urban underground large space construction safety early warning and emergency decision-making method and system | |
| CN115456331B (en) | Application of multi-dimensional multi-measuring point model on-line monitoring algorithm to monitoring analysis system platform | |
| CN114693114A (en) | Monitoring method and device for underground space structure, computer equipment and storage medium | |
| CN116523312A (en) | Smart city data management method and system | |
| CN117493815B (en) | BIM-based deep foundation pit monitoring method and system | |
| CN117196893B (en) | Infrastructure foundation pit real-time monitoring and early warning management method and system | |
| CN117526561A (en) | Digital twinning-based transformer substation equipment abnormality monitoring and early warning method and system | |
| KR100958941B1 (en) | Internet-based total excavation management system | |
| CN116579601B (en) | Mine safety production risk monitoring and early warning system and method | |
| CN115546433B (en) | Slope softening area prediction method, system and equipment and readable storage medium | |
| CN116575985A (en) | Informationized monitoring and measuring system for soft rock large deformation tunnel and construction method | |
| CN116090616A (en) | Coal mine risk disaster prediction method and device | |
| CN115116195B (en) | Foundation pit monitoring method and device based on artificial intelligence | |
| CN116378123A (en) | BIM-based foundation pit health monitoring system | |
| CN111105163A (en) | Traffic engineering potential safety hazard assessment device and method | |
| CN116310521A (en) | Abnormality detection method, abnormality detection device, abnormality detection storage medium, abnormality detection electronic device, abnormality detection system, abnormality detection program, and recording medium | |
| CN116311770A (en) | House safety early warning system, method and terminal based on Internet of things edge computing gateway | |
| CN112100796A (en) | Drilling track determination method and device for preventing casing in shale gas well from being damaged | |
| CN110705835A (en) | Coal mine safety risk early warning method based on GIS and BIM | |
| CN111663935A (en) | Method and system for evaluating shaft annulus air tightness |
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 |