CN115575007A - Soil pressure and temperature monitoring and early warning method for soil covering tank based on digital twinning technology - Google Patents
Soil pressure and temperature monitoring and early warning method for soil covering tank based on digital twinning technology Download PDFInfo
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- CN115575007A CN115575007A CN202211120196.9A CN202211120196A CN115575007A CN 115575007 A CN115575007 A CN 115575007A CN 202211120196 A CN202211120196 A CN 202211120196A CN 115575007 A CN115575007 A CN 115575007A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K1/00—Details of thermometers not specially adapted for particular types of thermometer
- G01K1/02—Means for indicating or recording specially adapted for thermometers
- G01K1/022—Means for indicating or recording specially adapted for thermometers for recording
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K13/00—Thermometers specially adapted for specific purposes
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
Abstract
The invention discloses a soil pressure and temperature monitoring and early warning method for a soil covering tank based on a digital twinning technology, which comprises the following steps: a sampling scheme generation method, a sensor arrangement method, a monitoring data-driven real-time monitoring method and a calculation data three-dimensional reconstruction and early warning method; through less sensing monitoring data, the soil pressure and the temperature of the whole arbitrary position of earthing jar are monitored to can be accurate carry out the early warning to soil pressure and the too big position of temperature, and can predict the soil pressure and the temperature variation trend of this position according to historical monitoring data, can three-dimensionally visualize the holistic soil pressure of covering jar and temperature distribution in real time simultaneously, provide the guidance for staff's maintenance work.
Description
Technical Field
The invention relates to the technical field of soil pressure and temperature monitoring and early warning of soil covering tanks, in particular to a soil pressure and temperature monitoring and early warning method of a soil covering tank based on a digital twinning technology.
Background
Today in the digital era, the intelligent manufacturing industry of China is continuously and deeply developed, the high-quality development of the manufacturing industry is promoted by taking intelligent manufacturing as a trigger, and the method is not only a main attack direction of the fusion development of the digital economy and the entity economy in China, but also a key breakthrough for realizing a double-circulation new development pattern. Therefore, the intelligent manufacturing new technology is introduced into the traditional industrial field, and the realization of innovative application has great significance. The soil covering tank is storage equipment for storing flammable and explosive liquid materials, the tank body is located below the ground, the upper portion of the tank body is covered with soil, the influence of the surrounding environment on the equipment is reduced, the harm of accidental combustion and explosion of the tank body to other surrounding tank bodies, workers, buildings and the like can be effectively reduced, and meanwhile, the land space utilization rate can be fully improved. Compared with an overground storage tank, the maintenance of the tank body after the tank body is covered with soil has some difficulties, firstly, the monitoring of the soil pressure around the tank body, the covering soil layer can be settled along with the change of time and the surrounding environment after the tank body is covered with soil, the soil pressure around the tank body is changed, the tank body can be unstable, the structure of the tank body can be damaged, even danger can be caused, the settlement degrees at different positions of the tank body are different, the soil pressure distribution is different, and the deformation of each part of the tank body can be different, so that the structure of the tank body can be damaged; secondly, how to monitor the soil pressure and the temperature of the whole arbitrary position of earthing jar comprehensively to in time make the early warning to the position of too big pressure or high temperature, so that the staff in time accurately finds the fault location.
In order to solve the above problems, a great deal of research is carried out by scholars at home and abroad, and some solutions are provided, for example, the soil pressure monitoring device for the soil covering slope of the soil covering tank with the application number of 202023202959.3 monitors the soil pressure around the soil covering tank by arranging a pressure monitoring unit around the tank body. Although this technical scheme can monitor the slope body soil pressure of level and vertical direction, in time discovers the problem and early warning, to the great covering soil jar of volume, this scheme can't accomplish to monitor and early warning the soil pressure of the whole optional position of covering soil jar. If all parts of the whole earthing tank set up the pressure monitoring unit in this technical scheme densely, can greatly increase and cover native jar equipment maintenance cost, and increased monitoring devices' fault rate, in addition, because the distribution of soil pressure around each part of earthing tank is different, the non-linear degree that some positions compressive deformation or displacement are low, the non-linear degree that some positions compressive deformation or displacement are high, so if all parts set up the pressure monitoring unit around the earthing tank evenly densely, not only cover the monitoring of native jar whole soil pressure distribution not accurate enough, still caused the wasting of resources. A temperature and leakage monitoring device for casing pot as in application No. 202023349304.9, the structure of which comprises: the optical fiber splice box comprises a tank body, a soil covering layer, a grating array sensing optical cable and an optical fiber splice box, wherein a plurality of outwards extending supporting columns are arranged on the outer wall of the tank body; the covering soil layer is arranged outside the tank body; the grating array sensing optical cable is laid for a plurality of circles from top to bottom along the outer wall of the tank body and is connected with the plurality of struts; the optical fiber splice closure is connected with the grating array sensing optical cable and is connected with the controller through the transmission optical cable. This technical scheme is to the great soil covering jar of volume, and this scheme can't monitor and the early warning to the temperature of the whole optional position of soil covering jar, and to the great soil covering jar of volume, if set up grating array sensing optical cable densely, can greatly increase and cover soil jar equipment maintenance cost, and increased monitoring devices' fault rate.
The digital twin technology is an innovative technology in the digital era, and provides an innovative solution for various problems in the traditional industry, such as design, manufacture, monitoring, operation and maintenance and the like. The digital twinning technology can fully utilize physical entity information, sensing monitoring information, historical monitoring data and the like, and can realize three-dimensional virtual mapping of the monitoring operation and maintenance process by combining a finite element method, an artificial intelligence algorithm and a three-dimensional visualization technology, so that an innovative solution is provided for solving the problems of soil pressure and temperature monitoring and early warning of the soil covering tank.
Disclosure of Invention
The invention aims to provide a soil pressure and temperature monitoring and early warning method of an earth covering tank based on a digital twinning technology, which aims to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following scheme:
a soil pressure and temperature monitoring and early warning method of a soil covering tank based on a digital twinning technology comprises a sampling scheme generation method, a sensor arrangement method, a monitoring data-driven real-time monitoring method and a calculation data three-dimensional reconstruction and early warning method; firstly, coordinates of sampling points are obtained by using the sampling scheme generation method, then the soil pressure monitoring unit and the temperature monitoring unit are arranged at all the sampling points by using the sensor arrangement method, then the soil pressure predicted value and the temperature predicted value of any position of the soil covering tank are obtained by using the real-time monitoring method driven by the monitoring data, finally the soil pressure predicted value and the temperature predicted value of any position of the soil covering tank are displayed in a three-dimensional visualization manner in real time by using the calculated data three-dimensional reconstruction and early warning method, the soil pressure and temperature change trend of any position of the soil covering tank can be predicted according to historical monitoring data, and the position of abnormal data is subjected to visualization early warning, so that a worker can find problems in time and accurately position the positions of the problems;
the sampling scheme generation method specifically comprises the following steps:
step 1.1: establishing a soil pressure calculation model of the soil covering tank, wherein the soil pressure calculation model of the soil covering tank can be obtained by a finite element method based on commercially mature finite element simulation software or can be obtained by calculation of a theoretically derived analytic mathematical model;
step 1.2: designing an initial Sampling scheme, wherein the initial Sampling scheme can adopt various methods such as a uniform Sampling method, a Latin Hypercube Sampling method (LHS), a Markov Chain Monte Carlo Method (MCMC) and the like; the initial sampling scheme comprises three variables, namely a distance r, an azimuth angle theta and a length z; the number of sampling points of the initial sampling scheme is determined by the affordable cost;
step 1.3: calculating the soil pressure of the soil covering tank at all sampling points (r, theta, z) by using the soil pressure calculation model of the soil covering tank;
step 1.4: taking coordinates (r, theta, z) of sampling points in the initial sampling scheme as input, taking soil pressure of the soil covering tank calculated at the sampling points as output, establishing a soil pressure calculation proxy model, and carrying out error evaluation on the soil pressure calculation proxy model; the soil pressure calculation agent Model can adopt a plurality of methods such as a Radial Basis Function (RBF), a Kriging Model (Kriging Model), a Polynomial Response Surface method (PRS), support Vector Regression (SVR) and the like;
step 1.5: if the error is unqualified, updating the initial sampling scheme by using a sequence sampling method to obtain a new sampling scheme, and repeating the step 1.3-1.5, wherein the sequence sampling method can adopt a plurality of methods such as a Statistical Lower Bound method (Statistical Lower Bound), a Maximum Improvement Probability (Maximum Improvement of Improvement), a Maximum Expected Improvement (Maximum Expected Improvement) and the like;
if the error is qualified, determining the sampling scheme at the moment as a final sampling scheme; and numbering and storing the sampling points in the final sampling scheme.
The sensor arrangement method comprises the soil pressure monitoring unit, the temperature monitoring unit, a data acquisition unit and an industrial personal computer; at the coordinate position of each sampling point in the final sampling scheme, fixedly mounting the soil pressure monitoring unit and the temperature monitoring unit on a soil covering tank side by side, respectively connecting the soil pressure monitoring unit and the temperature monitoring unit with the data acquisition unit through data lines, connecting the data acquisition unit with the industrial personal computer through the data lines, and transmitting the data monitored by the soil pressure monitoring unit and the temperature monitoring unit to the industrial personal computer through the data lines in real time by the data acquisition unit and storing the data according to the time sequence;
the real-time monitoring method driven by the monitoring data specifically comprises the following steps:
step 2.1: taking the coordinates (r, theta, z) of the sampling points in the final sampling scheme as input, taking the soil pressure of the soil covering tank measured by the soil pressure monitoring unit at the sampling points as output, establishing a soil pressure prediction agent model, and calculating to obtain the soil pressure of any coordinate position on the surface of the soil covering tank; the soil pressure prediction agent Model can adopt a plurality of methods such as a Radial Basis Function (RBF), a Kriging Model (Kriging Model), a Polynomial Response Surface method (PRS), support Vector Regression (SVR) and the like;
step 2.2: taking the coordinates (r, theta, z) of the sampling point in the final sampling scheme as input, taking the surface temperature of the soil covering tank measured by the temperature monitoring unit at the sampling point as output, establishing a temperature prediction proxy model, and calculating to obtain the temperature of any coordinate on the surface of the soil covering tank; the temperature prediction proxy Model can adopt a plurality of methods such as a Radial Basis Function (RBF), a Kriging Model (Kriging Model), a Polynomial Response Surface method (PRS), support Vector Regression (SVR) and the like;
step 2.3: collecting data obtained by monitoring the soil pressure monitoring unit and the temperature monitoring unit in real time, repeating the step 2.1-2.2 to obtain the real-time soil pressure and temperature at any coordinate position on the surface of the soil covering tank, and uploading the real-time soil pressure and temperature to an industrial personal computer;
the three-dimensional reconstruction and early warning method for the calculated data specifically comprises the following steps:
step 3.1: guiding the three-dimensional model of the soil covering tank into a digital twin platform, wherein the digital twin platform can adopt software such as Unity 3D and Web GL; uniformly dividing a three-dimensional model of the soil covering tank into grids in the digital twin platform, recording coordinates of each node of the grids, and numbering the nodes according to a position relationship;
step 3.2: according to the real-time monitoring method driven by the monitoring data, real-time soil pressure and temperature at each grid node on the surface of the soil covering tank are obtained, and coordinates, soil pressure and temperature of each grid node on the surface of the soil covering tank are stored according to a time sequence;
step 3.3: each node is endowed with a color in the digital twin platform, the depth of the color represents the soil pressure or temperature of the node, and the three-dimensional visualization of the soil covering tank three-dimensional model, the soil pressure and the soil temperature in the digital twin platform is realized;
step 3.4: setting a soil pressure threshold and a temperature threshold in the digital twin platform, and judging the real-time soil pressure and temperature at each grid node on the surface of the soil covering tank in real time;
if the soil pressure value of the node is smaller than the soil pressure threshold value, firstly, extracting the node and the soil pressure values monitored at the previous n-1 moments from the monitoring database, wherein the n soil pressure values are n, numbering is carried out from 1 to n according to time, and the numbering of the soil pressure predicted value at the next moment is recorded as n +1; secondly, establishing a soil pressure trend prediction agent model by taking the numbers 1, 2, \ 8230;, n as input and the soil pressure value corresponding to each number as output; then, inputting n +1 into the soil pressure trend prediction agent model to obtain a soil pressure prediction value at the next moment; finally, judging whether the predicted value of the soil pressure at the next moment is greater than the soil pressure threshold value; if not, continuing monitoring, and repeating the step 3.2-3.4; if so, highlighting and giving out early warning on the position of the node in the digital twin platform in a visual and sound effect mode so as to prompt a worker to carry out maintenance work in time; the soil pressure trend prediction agent Model can adopt a plurality of methods such as a Radial Basis Function (RBF), a Kriging Model (Kriging Model), a Polynomial Response Surface method (PRS), support Vector Regression (SVR) and the like;
if the soil pressure value of the node is larger than the soil pressure threshold value, recording the coordinates of the node where the soil pressure value is located, highlighting the position of the node in the digital twin platform in a visual and sound mode, and giving out early warning to prompt a worker to perform maintenance work in time;
if the temperature value of the node is smaller than the temperature threshold value, firstly, extracting the node and the temperature values monitored at the previous n-1 moments from the monitoring database, wherein the n temperature values are n, numbering is carried out from 1 to n according to time, and the numbering of the temperature predicted value at the next moment is recorded as n +1; secondly, establishing a temperature trend prediction agent model by taking the numbers 1, 2, \ 8230;, n as input and the temperature value corresponding to each number as output; then, inputting n +1 into the temperature prediction agent model to obtain a temperature prediction value at the next moment; finally, judging whether the predicted temperature value at the next moment is greater than the temperature threshold value; if not, continuing monitoring, and repeating the step 3.2-3.4; if so, highlighting and giving out early warning to the position of the node in the digital twin platform in a visual and sound effect mode so as to prompt a worker to carry out maintenance work in time; the temperature trend prediction agent Model can adopt a plurality of methods such as a Radial Basis Function (RBF), a Kriging Model (Kriging Model), a Polynomial Response Surface method (PRS), support Vector Regression (SVR) and the like;
if the temperature value of the node is larger than the temperature threshold value, recording the coordinates of the node where the temperature value is located, highlighting the position of the node in the digital twin platform in a visual and sound mode, and giving out early warning to prompt a worker to perform maintenance work in time.
Compared with the prior art, the invention achieves the following technical effects: the method can realize the monitoring of the soil pressure and the temperature of any position of the whole soil covering tank through less sensing monitoring data; the position with overlarge soil pressure and temperature can be highlighted and early warned timely and accurately; the soil pressure and temperature change trend of the position can be predicted according to historical monitoring data; the soil pressure and temperature distribution of the whole soil covering tank can be visually and visually displayed in real time in a three-dimensional manner; the system provides guidance for the maintenance work of workers and prevents accidents in time.
Drawings
FIG. 1 is a general flow chart of a soil pressure and temperature monitoring and early warning method of a soil covering tank based on a digital twinning technology, provided by the invention;
FIG. 2 is a schematic diagram of a soil covering tank structure and its cylindrical coordinate system provided by the present invention;
FIG. 3 is a flow chart of a sampling plan generation method provided by the present invention;
FIG. 4 is a sensor placement method provided by the present invention;
FIG. 5 is a flow chart of a monitoring data-driven real-time monitoring method provided by the present invention;
FIG. 6 is a flow chart of a method for three-dimensional reconstruction and early warning of computed data according to the present invention;
in the figure: 1-circular arch one; 2-a middle barrel; 3-circular arch II;
Detailed Description
The following further describes a specific embodiment of the present invention with reference to the drawings and technical solutions.
As shown in fig. 1: the embodiment provides a soil pressure and temperature monitoring and early warning method for a soil covering tank based on a digital twinning technology, which comprises a sampling scheme generation method, a sensor arrangement method, a monitoring data-driven real-time monitoring method and a calculation data three-dimensional reconstruction and early warning method; firstly, coordinates of sampling points are obtained by using the sampling scheme generation method, then the soil pressure monitoring unit and the temperature monitoring unit are arranged at all the sampling points by using the sensor arrangement method, then the soil pressure predicted value and the temperature predicted value of any position of the soil covering tank are obtained by using the real-time monitoring method driven by the monitoring data, finally the soil pressure predicted value and the temperature predicted value of any position of the soil covering tank are displayed in a three-dimensional visualization manner in real time by using the calculated data three-dimensional reconstruction and early warning method, the soil pressure and temperature change trend of any position of the soil covering tank can be predicted according to historical monitoring data, and the position of abnormal data is subjected to visualization early warning, so that a worker can find problems in time and accurately position the positions of the problems;
as shown in fig. 2, the soil covering tank is cylindrical and has two arched ends, the soil covering tank is divided into a first arch 1, a middle barrel 2 and a second arch 3, and a cylindrical coordinate system is established by taking the vertex of the outer surface of the first arch 1 as an origin;
as shown in fig. 3, the sampling scheme generating method specifically includes the following steps:
step 1: establishing a soil covering tank soil pressure calculation model, wherein the soil covering tank soil pressure calculation model can be obtained by a finite element method based on commercially mature finite element simulation software, and can also be obtained by calculation by an analytic mathematical model derived theoretically;
in this embodiment, a finite element method is used to establish a soil pressure calculation model of the soil covering tank, which specifically includes the following steps:
step 1.1: establishing a three-dimensional model by using ANSYS, wherein the diameter is 5.2m, the length is 18m, the thickness is 12mm, and the cell type is a shell cell SHEELL63;
step 1.2: adding boundary conditions and applying load, burying the soil covering tank underground, wherein the upper part of the soil covering tank is under the action of soil pressure, the lower part of the soil covering tank is supported by soil body, and the soil covering tank generates deformation and stress under the action of the soil pressure; supposing that the upper half part of the earthing tank is acted by soil pressure, and the lower half part of the earthing tank is elastically supported by soil; applying a resultant force sigma of the self weight of the soil body and the lateral pressure on the outer surface of the upper half part of the earthing tank, wherein the force is obtained by soil mechanics calculation, and the calculation method is shown as the formula (1);
wherein gamma is the soil mass gravity, kN/m 3 (ii) a h is the buried depth m; k 0 Taking the pressure coefficient of the soil side as 0.25; the included angle between the resultant force sigma and the vertical direction is arctanK 0 ＝16.7°；
Step 1.3: dividing grids;
step 1.4: solving a result;
and 2, step: designing an initial sampling scheme, wherein a Latin hypercube sampling method is adopted in the embodiment; the initial sampling scheme comprises three variables, namely a distance r, an azimuth angle theta and a length z; the number of sampling points of the initial sampling scheme is determined by the affordable cost;
on the first circular arch 1, the distance r ranges from 0 to 2.6, the azimuth angle theta ranges from 0 to 360 degrees, and the length z ranges from 0 to
On the intermediate barrel 2, the distance r is always 2.6 constant, the range of the azimuth angle theta is 0-360 degrees, and the range of the length z is 2.6-15.4;
on the second circular arch 2, the distance r ranges from 0 to 2.6, the azimuth angle theta ranges from 0 to 360 degrees, and the length z ranges
To 18;
the number of sample points is 50;
and step 3: calculating the soil pressure of the soil covering tank at all sampling points (r, theta, z) by using the soil pressure calculation model of the soil covering tank;
and 4, step 4: taking coordinates (r, theta, z) of a sampling point in the initial sampling scheme as input, taking soil pressure of the soil covering tank obtained by calculation at the sampling point as output, establishing a soil pressure calculation proxy model, and carrying out error evaluation on the soil pressure calculation proxy model; in this embodiment, the soil pressure calculation proxy model adopts a radial basis function based on gaussian, and the specific form is shown as the following formula;
wherein, c (i) Represents the ith basis function center; psi represents the basis function, and the present embodiment employs a Gaussian basis
I | · | | represents the euclidean distance between the prediction point and the center of the basis function; w is a i Represents a weight; x represents the input of the character string,
representing the predicted value at x;
and 5: if the error is not qualified, updating the initial sampling scheme by using a sequence sampling method to obtain a new sampling scheme, and repeating the steps 3-5, wherein in the embodiment, the sequence sampling method adopts a maximum improvement probability method, and the specific form is shown as the following formula;
I＝y min -Y(x) (3)
wherein, y min Represents the minimum of the current model prediction; y (x) represents the predicted value of the improved model; i represents the improvement amount; p [ I (x)]Represents an improved probability;
a root Mean Square Error (MSE) representing the prediction of a prediction gaussian process;
representing a predicted value;
if the error is qualified, determining the sampling scheme at the moment as a final sampling scheme; numbering and storing the sampling points in the final sampling scheme, wherein the storage format is shown in a table 1;
table 1 final sampling scheme storage format
| Sampling point serial number | Coordinate r | Coordinate theta | Coordinate z |
| 01 | r 1 | θ 1 | z 1 |
| 02 | r 2 | θ 2 | z 2 |
| … | … | … | … |
The sensor arrangement method comprises the soil pressure monitoring unit, the temperature monitoring unit, a data acquisition unit and an industrial personal computer; at the coordinate position of each sampling point in the final sampling scheme, fixedly mounting the soil pressure monitoring unit and the temperature monitoring unit on a soil covering tank side by side, respectively connecting the soil pressure monitoring unit and the temperature monitoring unit with the data acquisition unit through data lines, connecting the data acquisition unit with the industrial personal computer through the data lines, and transmitting the data monitored by the soil pressure monitoring unit and the temperature monitoring unit to the industrial personal computer through the data lines in real time by the data acquisition unit and storing the data according to the time sequence;
the storage format of the monitoring data of soil pressure and temperature is shown in table 2;
TABLE 2 soil pressure and temperature monitoring data storage Format
As shown in fig. 5, the real-time monitoring method driven by the monitoring data specifically includes the following steps:
step 1: taking the coordinates (r, theta, z) of the sampling point in the final sampling scheme as input, taking the soil pressure of the soil covering tank measured by the soil pressure monitoring unit at the sampling point as output, establishing a soil pressure prediction proxy model, and calculating to obtain the soil pressure of any coordinate on the surface of the soil covering tank; in the embodiment, the soil pressure prediction agent model adopts a radial basis function based on gauss, and the specific form is shown as formula (2);
step 2: taking the coordinates (r, theta, z) of the sampling point in the final sampling scheme as input, taking the surface temperature of the soil covering tank measured by the temperature monitoring unit at the sampling point as output, establishing a temperature prediction proxy model, and calculating to obtain the temperature of any coordinate on the surface of the soil covering tank; in the embodiment, the temperature prediction agent model adopts a radial basis function based on gauss, and the specific form is shown as formula (2);
and step 3: collecting data monitored by the soil pressure monitoring unit and the temperature monitoring unit in real time, repeating the steps 1-2 to obtain the real-time soil pressure and temperature of any coordinate position on the surface of the soil covering tank, and uploading and storing the real-time soil pressure and temperature;
as shown in fig. 6, the method for three-dimensional reconstruction and early warning of computed data specifically includes the following steps:
step 3.1: guiding the three-dimensional model of the soil covering tank into a digital twin platform, wherein the digital twin platform adopts Unity 3D software in the embodiment; uniformly dividing a three-dimensional model of the soil covering tank into grids in the digital twin platform, recording coordinates of each node of the grids, and numbering the nodes according to a position relationship;
step 3.2: according to the real-time monitoring method driven by the monitoring data, real-time soil pressure and temperature at each grid node on the surface of the covering tank are obtained, coordinates, soil pressure and temperature of each grid node on the surface of the covering tank are stored according to a time sequence, and the storage format is shown in table 3;
TABLE 3 storage Format for real-time soil pressure and temperature at grid nodes
Step 3.3: each node is endowed with color in the digital twin platform, the depth of the color represents the soil pressure or temperature of the node, and the three-dimensional visualization of the soil covering tank three-dimensional model, the soil pressure and the soil temperature in the digital twin platform is realized;
and 4, step 4: setting a soil pressure threshold and a temperature threshold in the digital twin platform, and judging the real-time soil pressure and temperature at each grid node on the surface of the soil covering tank in real time;
if the soil pressure value of the node is smaller than the soil pressure threshold value, firstly, extracting the node and soil pressure values monitored at the previous 9 moments from the monitoring database, wherein the total number of the nodes is 10, numbering is carried out from 1 to 10 according to time sequence, and the numbering of the soil pressure predicted value at the next moment is marked as 11; secondly, establishing a soil pressure trend prediction agent model by taking the numbers 1, 2, 8230and 10 as input and taking the soil pressure value corresponding to each number as output; then, inputting 11 into the soil pressure trend prediction agent model to obtain a soil pressure prediction value at the next moment; finally, judging whether the predicted value of the soil pressure at the next moment is greater than the soil pressure threshold value; if not, continuing monitoring, and repeating the steps 2-4; if so, highlighting and giving out early warning to the position of the node in the digital twin platform in a visual and sound effect mode so as to prompt a worker to carry out maintenance work in time; in this embodiment, the soil pressure trend prediction agent model adopts a radial basis function based on gaussian, and the specific form is shown in formula (2);
if the soil pressure value of the node is greater than the soil pressure threshold value, recording the coordinates of the node where the soil pressure value is located, highlighting the position of the node in the digital twin platform in a visual and sound effect mode, and giving out early warning to prompt a worker to perform maintenance work in time;
if the temperature value of the node is smaller than the temperature threshold value, firstly, 10 temperature values of the node and the temperature values monitored at the previous 9 moments are extracted from the monitoring database, numbering is carried out from 1 to 10 according to time, and the numbering of the temperature predicted value at the next moment is marked as 11; secondly, establishing a temperature trend prediction agent model by taking the numbers 1, 2, 8230and 10 as inputs and the temperature value corresponding to each number as an output; then, inputting 11 into the temperature prediction proxy model to obtain a temperature prediction value at the next moment; finally, judging whether the predicted temperature value at the next moment is greater than the temperature threshold value; if not, continuing monitoring, and repeating the steps 2-4; if so, highlighting and giving out early warning on the position of the node in the digital twin platform in a visual and sound effect mode so as to prompt a worker to carry out maintenance work in time; in this embodiment, the temperature trend prediction proxy model adopts a radial basis function based on gaussian, and the specific form is shown in formula (2);
if the temperature value of the node is greater than the temperature threshold value, recording the coordinates of the node where the temperature value is located, highlighting the position of the node in the digital twin platform in a visual and sound effect mode, and giving out early warning to prompt a worker to perform maintenance work in time;
therefore, soil pressure and temperature monitoring and early warning of the soil covering tank based on the digital twinning technology are completed.
Claims (1)
1. A soil pressure and temperature monitoring and early warning method of a soil covering tank based on a digital twinning technology is characterized by comprising a sampling scheme generation method, a sensor arrangement method, a monitoring data-driven real-time monitoring method and a calculation data three-dimensional reconstruction and early warning method; firstly, obtaining coordinates of sampling points by using the sampling scheme generation method, secondly, arranging soil pressure monitoring units and temperature monitoring units at all the sampling points by using the sensor arrangement method, then, calculating in real time by using a real-time monitoring method driven by the monitoring data to obtain a soil pressure predicted value and a temperature predicted value of any position of the soil covering tank, and finally, performing real-time three-dimensional visual display on the soil pressure predicted value and the temperature predicted value of any position of the soil covering tank by using a calculated data three-dimensional reconstruction and early warning method, predicting the soil pressure and temperature change trend of any position of the soil covering tank according to historical monitoring data, performing visual early warning on the position of abnormal data, and accurately positioning the position of a problem;
the sampling scheme generation method specifically comprises the following steps:
step 1.1: establishing a soil pressure calculation model of the soil covering tank;
step 1.2: designing an initial sampling scheme, wherein the initial sampling scheme comprises three variables, namely a distance r, an azimuth angle theta and a length z; the number of sampling points of the initial sampling scheme is determined by the affordable cost;
step 1.3: calculating the soil pressure of the soil covering tank at all sampling points (r, theta, z) by using the soil pressure calculation model of the soil covering tank;
step 1.4: taking coordinates (r, theta, z) of a sampling point in the initial sampling scheme as input, taking soil pressure of the soil covering tank obtained by calculation at the sampling point as output, establishing a soil pressure calculation proxy model, and carrying out error evaluation on the soil pressure calculation proxy model;
step 1.5: if the error is unqualified, updating the initial sampling scheme by using a sequence sampling method to obtain a new sampling scheme, and repeating the step 1.3-1.5; if the error is qualified, determining the sampling scheme at the moment as a final sampling scheme; numbering and storing sampling points in the final sampling scheme;
the sensor arrangement method comprises the soil pressure monitoring unit, the temperature monitoring unit, a data acquisition unit and an industrial personal computer; at the coordinate position of each sampling point in the final sampling scheme, fixedly mounting the soil pressure monitoring unit and the temperature monitoring unit on a soil covering tank side by side, respectively connecting the soil pressure monitoring unit and the temperature monitoring unit with the data acquisition unit through data lines, connecting the data acquisition unit with the industrial personal computer through data lines, and transmitting the data monitored by the soil pressure monitoring unit and the temperature monitoring unit to the industrial personal computer through the data lines in real time by the data acquisition unit and storing the data according to the time sequence;
the real-time monitoring method driven by the monitoring data specifically comprises the following steps:
step 2.1: taking the coordinates (r, theta, z) of the sampling point in the final sampling scheme as input, taking the soil pressure of the soil covering tank measured by the soil pressure monitoring unit at the sampling point as output, establishing a soil pressure prediction proxy model, and calculating to obtain the soil pressure of any coordinate on the surface of the soil covering tank;
step 2.2: taking the coordinates (r, theta, z) of the sampling points in the final sampling scheme as input, taking the surface temperature of the soil covering tank measured by the temperature monitoring unit at the sampling points as output, establishing a temperature prediction proxy model, and calculating to obtain the temperature of any coordinate position on the surface of the soil covering tank;
step 2.3: collecting data obtained by monitoring the soil pressure monitoring unit and the temperature monitoring unit in real time, repeating the step 2.1-2.2 to obtain the real-time soil pressure and temperature at any coordinate position on the surface of the soil covering tank, and uploading and storing the real-time soil pressure and temperature;
the three-dimensional reconstruction and early warning method for the calculated data specifically comprises the following steps:
step 3.1: guiding the three-dimensional model of the soil covering tank into a digital twin platform; uniformly dividing the three-dimensional model of the soil covering tank into grids in the digital twin platform, recording coordinates of each node of the grids, and numbering the nodes according to the position relationship;
step 3.2: according to the real-time monitoring method driven by the monitoring data, real-time soil pressure and temperature at each grid node on the surface of the soil covering tank are obtained, and coordinates, soil pressure and temperature of each grid node on the surface of the soil covering tank are stored according to a time sequence;
step 3.3: each node is endowed with a color in the digital twin platform, the depth of the color represents the soil pressure or temperature of the node, and the three-dimensional visualization of the soil covering tank three-dimensional model, the soil pressure and the soil temperature in the digital twin platform is realized;
step 3.4: setting a soil pressure threshold and a temperature threshold in the digital twin platform, and judging the real-time soil pressure and temperature at each grid node on the surface of the soil covering tank in real time;
if the soil pressure value of the node is smaller than the soil pressure threshold value, firstly, extracting the node and the soil pressure values monitored at the previous n-1 moments from the monitoring database, wherein the n soil pressure values are n, numbering is carried out from 1 to n according to time, and the numbering of the soil pressure predicted value at the next moment is recorded as n +1; secondly, establishing a soil pressure trend prediction agent model by taking the numbers 1, 2, \ 8230;, n as input and the soil pressure value corresponding to each number as output; then, inputting n +1 into the soil pressure trend prediction agent model to obtain a soil pressure prediction value at the next moment; finally, judging whether the predicted value of the soil pressure at the next moment is greater than the soil pressure threshold value; if not, continuing monitoring, and repeating the step 3.2-3.4; if so, highlighting and giving out an early warning to the position of the node in the digital twin platform in a visual and sound effect mode;
if the soil pressure value of the node is larger than the soil pressure threshold value, recording the coordinates of the node where the soil pressure value is located, highlighting the position of the node in the digital twin platform in a visual and sound effect mode, and giving out early warning;
if the temperature value of the node is smaller than the temperature threshold value, firstly, extracting the node and the temperature values monitored at the previous n-1 moments from the monitoring database, wherein the n temperature values are n, numbering is carried out from 1 to n according to time, and the numbering of the temperature predicted value at the next moment is recorded as n +1; secondly, establishing a temperature trend prediction agent model by taking the numbers 1, 2, \ 8230;, n as input and the temperature value corresponding to each number as output; then, inputting n +1 into the temperature prediction agent model to obtain a temperature prediction value at the next moment; finally, judging whether the predicted temperature value at the next moment is greater than the temperature threshold value; if not, continuing monitoring, and repeating the step 3.2-3.4; if yes, highlighting the position of the node in the digital twin platform in a visual and sound effect mode, and giving out an early warning;
if the temperature value of the node is larger than the temperature threshold value, recording the coordinates of the node where the temperature value is located, highlighting the position of the node in the digital twin platform in a visual and sound effect mode, and giving an early warning.
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| CN116186634A (en) * | 2023-04-26 | 2023-05-30 | 青岛新航农高科产业发展有限公司 | Intelligent management system for construction data of building engineering |
| CN116357899A (en) * | 2023-03-06 | 2023-06-30 | 上海市政工程设计研究总院（集团）有限公司 | Digital twin safety evaluation system and method for ultra-large caliber flexible pipeline |
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| CN116357899A (en) * | 2023-03-06 | 2023-06-30 | 上海市政工程设计研究总院（集团）有限公司 | Digital twin safety evaluation system and method for ultra-large caliber flexible pipeline |
| CN116186634A (en) * | 2023-04-26 | 2023-05-30 | 青岛新航农高科产业发展有限公司 | Intelligent management system for construction data of building engineering |
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