CN119958445B - Deep foundation pit side slope deformation monitoring method and device, storage medium and electronic equipment - Google Patents
Deep foundation pit side slope deformation monitoring method and device, storage medium and electronic equipmentInfo
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- CN119958445B CN119958445B CN202510081792.8A CN202510081792A CN119958445B CN 119958445 B CN119958445 B CN 119958445B CN 202510081792 A CN202510081792 A CN 202510081792A CN 119958445 B CN119958445 B CN 119958445B
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Abstract
The invention provides a method and a device for monitoring side slope deformation of a deep foundation pit, a storage medium and electronic equipment, and relates to the technical field of deep foundation pit monitoring. The method comprises the steps of obtaining monitoring data of a deep foundation pit slope, wherein the monitoring data comprise data uploaded by a GNSS receiver, a horizontal optical fiber, a sedimentation optical fiber and a three-dimensional scanner, constructing a three-dimensional deformation field model of the deep foundation pit slope according to the monitoring data and a time stamp, segmenting and refining the three-dimensional deformation field model to obtain time sequence deformation information of deformation units, predicting the predicted deformation quantity of each deformation unit through a prediction network model, and further obtaining the risk condition of the deep foundation pit slope. The three-dimensional deformation field model is divided and thinned, the change condition of each deformation unit is monitored, early warning can be carried out in the initial stage when various risk conditions are not or just appear, and the timeliness of the early warning is improved.
Description
Technical Field
The invention relates to the technical field of deep foundation pit monitoring, in particular to a method and a device for monitoring side slope deformation of a deep foundation pit, a storage medium and electronic equipment.
Background
Along with the increasing of high-rise buildings, the underground foundation pit excavation scale is increased, and the stability and safety of the structural elevation and the foundation pit slope become key links for engineering monitoring in the construction process of foundation pit excavation and underground engineering.
In order to find problems in time and avoid accidents, deformation monitoring is needed to be carried out on a deep foundation pit in the building construction and operation processes, and in the traditional deformation monitoring, methods such as total stations or leveling instruments are often adopted for monitoring.
The single monitoring method can only monitor the deformation condition of the side slope of the deep foundation pit in a certain dimension, so that the potential risk of the side slope of the deep foundation pit obtained by analysis is also relatively one-sided according to the data obtained by the traditional deformation monitoring method, and the deformation prediction is inaccurate and the safety early warning is not timely.
Disclosure of Invention
The invention aims to solve the problem that a single monitoring method can only monitor the deformation condition of the side slope of the deep foundation pit in a certain dimension, so that the deformation prediction is inaccurate and the safety early warning is not timely.
In order to solve the above problems, in a first aspect, the present invention provides a method for monitoring deformation of a side slope of a deep foundation pit, including:
Acquiring monitoring data of a deep foundation pit slope, wherein the monitoring data comprise slope surface data, slope internal horizontal displacement data, slope internal sedimentation data and deep foundation pit slope three-dimensional data;
Constructing a three-dimensional deformation field model of the deep foundation pit slope according to the monitoring data and the time stamp;
Dividing each three-dimensional deformation field model constructed at a plurality of time points into a plurality of deformation units to obtain time sequence deformation information of each deformation unit, wherein the deformation units are three-dimensional models obtained by dividing according to preset sizes;
inputting the time sequence deformation information of the deformation units into a trained prediction network model to obtain the predicted deformation of each deformation unit;
and obtaining the risk condition of the deep foundation pit slope according to the predicted deformation of the deformation units.
Optionally, after the monitoring data of the side slope of the deep foundation pit is obtained, the monitoring method for the side slope deformation of the deep foundation pit further includes:
preprocessing the slope internal sedimentation data in the monitoring data, wherein the slope internal sedimentation data comprises sedimentation amount, and the sedimentation amount is as follows:
Wherein D (z 1-z2) represents the soil settlement measured by the optical fiber from the z1 position to the z2 position, epsilon (z) represents the strain quantity of the optical fiber, f 0 (z) represents the initial Brillouin scattering light frequency shift quantity of the optical fiber at the z position, f (z) represents the Brillouin scattering light frequency shift quantity of the optical fiber at the z position, C s represents the proportionality coefficient of the optical fiber back Brillouin scattering light frequency shift quantity and the optical cable strain, C T represents the proportionality coefficient of the optical fiber back Brillouin scattering light frequency shift quantity and the optical cable temperature, and DeltaT (z) represents the temperature change of the optical fiber at the z position.
Optionally, the constructing the three-dimensional deformation field model of the deep foundation pit slope according to the monitoring data and the time stamp includes:
The method for aligning the time stamps is adopted, and the obtained monitoring data uploaded by different devices at different time points are aligned to a unified time axis; and aligning the acquired monitoring data uploaded by different devices into a unified coordinate system by adopting a coordinate conversion tool.
Optionally, the obtaining the risk condition of the deep foundation pit slope according to the predicted deformation amounts of the deformation units includes:
Obtaining a predicted deformation average value of the three-dimensional deformation field model in each direction according to the predicted deformation of the deformation units, wherein the predicted deformation average value comprises a transverse predicted deformation average value, a longitudinal predicted deformation average value and a vertical predicted deformation average value;
accumulating the average values of the predicted deformation obtained at a plurality of time points continuously in each direction to obtain a cumulative value of the predicted deformation;
when any one of the predicted deformation accumulation values is larger than the corresponding accumulated early warning value, judging whether the directions of the predicted deformation mean values corresponding to the predicted deformation accumulation values are consistent at a plurality of time points or not;
and generating excessive deformation early warning when the directions of the predicted deformation average values at a plurality of time points are consistent.
Optionally, the obtaining the risk condition of the deep foundation pit slope according to the predicted deformation amounts of the deformation units includes:
Determining a deformation difference value of two deformation units in the analysis direction according to the predicted deformation of two adjacent deformation units in the selected analysis direction;
When the deformation difference value is larger than a deformation difference value threshold value corresponding to the analysis direction, determining that deformation risks exist between two adjacent deformation units in the analysis direction, marking contact surfaces of the two adjacent deformation units as deformation surfaces, and marking the selected analysis direction as the deformation direction;
Optionally selecting one direction as a preset deformation direction, controlling a preset frame selection window to move in the current three-dimensional deformation field model, and counting the number of deformation surfaces with the deformation direction being the same as the preset deformation direction in the preset frame selection window to obtain the number of deformation surfaces;
When the number of the deformation surfaces is larger than a preset deformation surface threshold value, predicting that cracks can be generated in the deep foundation pit slope, and the extending direction of the cracks is perpendicular to the preset deformation direction.
Optionally, when the number of the deformation surfaces is greater than a preset deformation surface threshold, predicting that a crack will occur in the deep foundation pit slope, and taking the extending direction of the preset range as the extending direction of the crack, the deep foundation pit slope deformation monitoring method further includes:
when the preset deformation direction is transverse or longitudinal, judging whether the predicted deformation average value of one side of the crack, which is close to the center of the three-dimensional deformation field model, is larger than the predicted deformation average value of the other corresponding side in the preset deformation direction;
When the deformation is larger than the preset deformation, predicting that the deep foundation pit slope can generate extrusion and bulge deformation;
And when the deformation is smaller than the preset deformation, predicting that the deep foundation pit slope can generate fracture deformation.
Optionally, when the number of the deformation surfaces is greater than a preset deformation surface threshold, predicting that a crack will occur in the deep foundation pit slope, and taking the extending direction of the preset range as the extending direction of the crack, the deep foundation pit slope deformation monitoring method further includes:
When the preset deformation direction is vertical, judging whether the average value of the predicted deformation of the upper region of the three-dimensional deformation field model is larger than the average value of the predicted deformation of the lower region of the three-dimensional deformation field model in the preset deformation direction;
When the sliding risk is larger than the preset sliding risk, predicting that the deep foundation pit slope can generate the sliding risk;
when smaller, the deep foundation pit slope is predicted to generate a risk of extrusion uplift.
In a second aspect, the present invention further provides a deep foundation pit slope deformation monitoring device, including:
The monitoring data acquisition module is used for acquiring monitoring data of the side slope of the deep foundation pit, wherein the monitoring data comprise side slope surface data, side slope internal horizontal displacement data, side slope internal sedimentation data and three-dimensional data of the side slope of the deep foundation pit;
The deformation field construction module is used for constructing a three-dimensional deformation field model of the deep foundation pit slope according to the monitoring data and the time stamp;
the deformation field segmentation module is used for segmenting each three-dimensional deformation field model constructed at a plurality of time points into a plurality of deformation units to obtain time sequence deformation information of each deformation unit, wherein the deformation units are three-dimensional models obtained by segmentation according to preset sizes;
The deformation prediction module is used for inputting the time sequence deformation information of the deformation units into a trained prediction network model to obtain the predicted deformation of each deformation unit;
And the monitoring and early warning module is used for obtaining the risk condition of the deep foundation pit slope according to the predicted deformation of the deformation units so as to early warn the risk of the deep foundation pit slope.
In a third aspect, the present invention provides a storage medium storing a computer program for causing a computer to execute the deep foundation pit slope deformation monitoring method as described above.
In a fourth aspect, the present invention provides an electronic device, comprising:
One or more processors, memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs comprising instructions for performing the deep foundation pit slope deformation monitoring method as described above.
The invention provides a method and a device for monitoring side slope deformation of a deep foundation pit, a storage medium and electronic equipment. Compared with the prior art, the method has the following beneficial effects:
The method comprises the steps of obtaining data of multiple aspects of the deep foundation pit slope, adopting multiple data sources, monitoring the surface deformation condition of the deep foundation pit slope, monitoring the internal deformation condition of the deep foundation pit slope, combining internal and external monitoring data, guaranteeing the accuracy of a constructed three-dimensional deformation field model, guaranteeing the accuracy of subsequent prediction, segmenting and refining the three-dimensional deformation field model, predicting the deformation of each deformation unit by using a prediction network model, monitoring the change condition of each deformation unit, predicting the initial stage of deformation of the deep foundation pit slope, and carrying out early warning in the initial stage of non-occurrence or just-occurrence of various risk conditions, thereby improving the timeliness of early warning.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for monitoring deformation of a side slope of a deep foundation pit according to an embodiment of the present invention;
Fig. 2 is a schematic flow chart of early warning of deformation risk of a side slope of a deep foundation pit according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a deep foundation pit slope deformation monitoring device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application are clearly and completely described, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The embodiment of the application solves the problems of inaccurate deformation prediction and untimely safety early warning caused by the fact that a single monitoring method can only monitor the deformation condition of the side slope of the deep foundation pit in a certain dimension by providing the method, the device, the storage medium and the electronic equipment for monitoring the side slope of the deep foundation pit, realizes the omnibearing monitoring of the side slope of the deep foundation pit, and ensures the timeliness of deformation monitoring early warning.
The technical scheme in the embodiment of the application aims to solve the technical problems, and the overall thought is as follows:
in order to find problems in time and avoid accidents, deformation monitoring is needed to be carried out on the foundation pit in the building construction and operation process, the change of the shape and the space position of the foundation pit under the action of external load is focused, and the stability of the foundation pit is judged by analyzing structural deformation. Therefore, the deformation monitoring of the structural facade has important significance for preventing potential safety hazards, guaranteeing the structural integrity of the building and ensuring the smooth construction.
In the traditional deformation monitoring, methods such as total stations or leveling instruments are often adopted. However, the conventional monitoring means such as total station or level often have the problems of long operation time, low efficiency and the like, and a single monitoring method can only monitor the deformation condition of the side slope of the deep foundation pit in a certain dimension, and according to the data acquired by the conventional deformation monitoring method, the potential risk of the side slope of the deep foundation pit obtained by analysis is also relatively one-sided, so that the deformation prediction is inaccurate and the safety early warning is not timely. Therefore, the multi-source heterogeneous data acquired by various monitoring devices are fused, so that a three-dimensional deformation field is constructed, the deformation condition of the foundation pit in each direction can be monitored, the foundation pit is monitored in all directions, and the accuracy of deformation monitoring is ensured.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
As shown in fig. 1, the method for monitoring the side slope deformation of the deep foundation pit provided by the embodiment of the application comprises the following steps:
And S1, acquiring monitoring data of the deep foundation pit slope, wherein the monitoring data comprise slope surface data uploaded by a GNSS receiver (Global Navigation SATELLITE SYSTEM RECEIVER, a global navigation satellite system receiver), slope internal horizontal displacement data uploaded by a horizontal optical fiber, slope internal sedimentation data uploaded by a sedimentation optical fiber and deep foundation pit slope three-dimensional data uploaded by a three-dimensional scanner.
And S2, constructing a three-dimensional deformation field model of the deep foundation pit slope according to the monitoring data and the time stamp.
S3, dividing each three-dimensional deformation field model constructed at a plurality of time points into a plurality of deformation units to obtain time sequence deformation information of each deformation unit, wherein the deformation units are three-dimensional models obtained by dividing according to preset dimensions, and the time sequence deformation information comprises transverse deformation amount, longitudinal deformation amount and vertical deformation amount of the deformation units at the plurality of time points.
S4, inputting the time sequence deformation information of the deformation units into a trained prediction network model to obtain the predicted deformation of each deformation unit, wherein the predicted deformation comprises a transverse predicted deformation, a longitudinal predicted deformation and a vertical predicted deformation.
S5, obtaining the risk condition of the deep foundation pit slope according to the predicted deformation amounts of the deformation units.
In the embodiment, the monitoring data comprises slope surface data uploaded by a GNSS receiver, slope internal horizontal displacement data uploaded by a horizontal optical fiber, slope internal sedimentation data uploaded by a sedimentation optical fiber and deep foundation pit three-dimensional data uploaded by a three-dimensional scanner, various equipment can be used for collecting data, data of various aspects of the deep foundation pit slope can be obtained, multiple data sources are used, the surface deformation condition of the deep foundation pit slope can be monitored, the internal deformation condition of the deep foundation pit slope can be monitored, a three-dimensional deformation field model of the deep foundation pit slope can be constructed according to the monitoring data and a time stamp, the internal and external monitoring data are combined, the accuracy of the constructed three-dimensional deformation field model can be guaranteed, the accuracy of follow-up prediction is guaranteed, each three-dimensional deformation field model constructed at multiple time points is divided into multiple deformation units, time sequence deformation information of each deformation unit is obtained, the time sequence deformation information of each deformation unit is input into a prediction network model after training, the predicted deformation quantity of each deformation unit is refined, the three-dimensional deformation field is further refined, the deformation unit is predicted by utilizing the prediction network model, the deformation unit is predicted at each deformation stage, and the initial deformation condition of the deep foundation pit is predicted, and the deformation condition of the deep foundation pit is predicted according to the initial deformation condition is improved.
The respective steps are described in detail below.
Optionally, after the monitoring data of the side slope of the deep foundation pit is obtained, the monitoring method for the side slope deformation of the deep foundation pit further comprises the following steps:
Preprocessing the monitoring data.
The method comprises the steps of distributing a plurality of GNSS receivers according to monitoring requirements, configuring working modes of the GNSS receivers, setting parameters such as sampling rate, data format and the like, ensuring time synchronization of the plurality of GNSS receivers, recording accurate time stamps, starting the GNSS receivers, starting data acquisition, monitoring the state of the GNSS receivers in real time, and periodically checking data storage equipment to ensure that data storage is not lost or damaged. The method comprises the steps of importing acquired GNSS data into data processing software for preliminary preprocessing and arrangement, resolving the data by using professional GNSS data processing software (such as Trimble Business Center, LEICA INFINITY, topcon Magnet, bernese GNSS Software and the like) to obtain high-precision coordinate and displacement information, correcting errors in the GNSS data by applying differential technology, precise ephemeris, atmospheric correction and other methods, and improving data precision.
And (3) collecting the uploaded slope internal sedimentation data through the optical fiber, converting the microstrain data into deformation data, and calculating sedimentation (the slope internal sedimentation data comprises sedimentation) as follows:
Wherein D (z 1-z2) represents the soil settlement measured by the optical fiber from the z1 position to the z2 position, epsilon (z) represents the strain quantity of the optical fiber, f 0 (z) represents the initial Brillouin scattering light frequency shift quantity (MHz) of the optical fiber at the z position, f (z) represents the Brillouin scattering light frequency shift quantity (MHz) of the optical fiber at the z position, C s represents the proportionality coefficient (MHz/mu epsilon) of the optical fiber back-to-Brillouin scattering light frequency shift quantity and the optical cable strain, and can be provided by an optical cable provider or determined through an optical cable calibration test, C T represents the proportionality coefficient (MHz/DEGC) of the optical fiber back-to-Brillouin scattering light frequency shift quantity and the optical cable temperature, and DeltaT (z) represents the temperature change of the optical fiber at the z position.
In addition, the monitoring data also comprises slope internal inclination deformation data uploaded by the inclinometer, the inclinometer monitors the inclination change of rock strata in the slope, and the inclination change is equivalent to the comprehensive change result of the horizontal displacement change and the vertical settlement change in the slope, so that the data uploaded by the inclinometer can be used for verifying the data uploaded by the horizontal optical fiber and the settlement optical fiber.
And importing the acquired three-dimensional point cloud data into data processing software, and preprocessing the point cloud data by using professional data processing software (such as Cyclone, realWorks and the like) to obtain a three-dimensional boundary model of the deep foundation pit slope, wherein the three-dimensional data of the deep foundation pit slope is uploaded by the three-dimensional scanner.
Optionally, S2, constructing the three-dimensional deformation field model of the deep foundation pit slope according to the monitoring data and the time stamp comprises the following steps:
And (3) aligning the obtained monitoring data uploaded by different devices at different time points to a unified time axis by adopting a time stamp alignment method, so as to ensure the time consistency of the data. And (3) aligning the acquired monitoring data uploaded by different devices into a unified coordinate system by adopting a coordinate conversion tool, so as to ensure the spatial consistency of the data.
Specifically, the same data acquisition time point or acquisition period is set for a plurality of devices, so that the plurality of devices are ensured to acquire at the same time point, the time point of data acquisition is recorded when the data are acquired, the data acquired at the same time point are processed, and the data uploaded by the plurality of devices are converted into the same coordinate system by utilizing the relative position relationship between the devices or the position relationship between the devices and the same datum point, so that the data alignment is performed in the time dimension and the space dimension.
And S3, constructing and obtaining a three-dimensional deformation field model by utilizing the data acquired at each time point, acquiring data at a plurality of acquisition time points in the early stage to obtain a plurality of three-dimensional deformation field models, dividing each three-dimensional deformation field model, dividing only a first three-dimensional deformation field model, fixing a separation point as a part of the three-dimensional deformation field model, and moving the separation point along with the deformation of the three-dimensional deformation field model, so that deformation units can be correspondingly obtained in the three-dimensional deformation field model obtained later, and deformation amount of each deformation unit can be also obtained, and in order to monitor the three-dimensional deformation field model in a multi-dimensional manner, the deformation conditions of the deformation units in the transverse direction, the longitudinal direction and the vertical direction can be monitored seriously. For example, the specific deformation amounts of a deformation unit at a plurality of time points in the transverse direction are recorded, the transverse time series deformation information of the deformation unit is formed, and similarly, the longitudinal time series deformation information and the vertical time series deformation information of the deformation unit can also be obtained.
And for the step S4, pre-training ConvLSTM (convolution long-short-term memory network) models by utilizing the time sequence deformation information of each deformation unit obtained in the earlier stage to obtain a prediction network model. Deformation prediction network models may also be built using TensorFlow or PyTorch libraries. In addition, the actual deformation obtained continuously later can be compared with the predicted deformation, and the predicted network model is corrected, so that the predicted network model is more accurate.
Optionally, as shown in fig. 2, S5, obtaining the risk condition of the deep foundation pit slope according to the predicted deformation amounts of the deformation units includes:
S511, obtaining a predicted deformation average value of the three-dimensional deformation field model in each direction according to the predicted deformation of the deformation units, wherein the predicted deformation average value comprises a transverse predicted deformation average value, a longitudinal predicted deformation average value and a vertical predicted deformation average value.
Specifically, the deformation amounts of all deformation units in the transverse direction are added and divided by the number of the deformation units to obtain a transverse prediction deformation amount average value, and similarly, a longitudinal prediction deformation amount average value and a vertical prediction deformation amount average value can be obtained through calculation.
And S512, accumulating the average value of the predicted deformation obtained at a plurality of time points continuously in each direction to obtain an accumulated value of the predicted deformation.
Specifically, the deformation is the change value of the current three-dimensional deformation field model relative to the three-dimensional deformation field model at the previous time point, so that the predicted deformation accumulation value is the change value accumulation of a plurality of continuous time points, and the predicted deformation accumulation value can be accumulated from the first monitoring time or from a certain time point, so that the global predicted deformation accumulation value or the predicted deformation accumulation value of a certain time period in the middle can be obtained, and the three-dimensional deformation field model can be flexibly analyzed. The predicted deformation amount cumulative value includes a lateral predicted deformation amount cumulative value, a longitudinal predicted deformation amount cumulative value, and a vertical predicted deformation amount cumulative value.
And S513, judging whether the directions of the average values of the predicted deformation corresponding to the predicted deformation accumulation values are consistent at a plurality of time points or not when any one of the predicted deformation accumulation values is larger than the corresponding accumulation early-warning value.
And S514, generating excessive deformation early warning when the directions of the predicted deformation average values at a plurality of time points are consistent.
Specifically, the predicted deformation amount accumulation value in each direction corresponds to one accumulation early-warning value. When a certain predicted deformation accumulation value is larger than a corresponding accumulated early warning value, the fact that the deformation of the deep foundation pit slope is too large in the direction corresponding to the predicted deformation accumulation value is needed to be further judged, whether the directions of the predicted deformation mean values corresponding to the predicted deformation accumulation values are consistent in a plurality of time points or not is needed to be further judged, if the directions are consistent, the fact that the plurality of time points continuously change in the same direction is indicated, the probability of continuous deformation in the direction is high in the future, early warning can be carried out when the deformation is already out, if the directions are inconsistent, the fact that the deformation direction in the plurality of time points is in reverse deformation is indicated, if the inconsistent conditions are relatively large, the fact that the current deformation accumulation value is out in the opposite direction is indicated, the deformation is possible to be carried out at the next time point, the accumulated value is reduced, the phenomenon that the deformation is not exceeded is indicated, and at the moment, the early warning can be temporarily not carried out. And the direction consistency judgment is carried out, so that the early warning accuracy can be greatly improved, and the false alarm probability is reduced.
Optionally, S5, according to the predicted deformation amounts of the deformation units, obtaining the risk condition of the deep foundation pit slope includes:
S521, determining the deformation difference value of the two deformation units in the analysis direction according to the predicted deformation of the two adjacent deformation units in the selected analysis direction.
In particular, the analysis direction is an optional one of a lateral direction, a longitudinal direction and a vertical direction. And in the two adjacent deformation units, determining the deformation unit close to the edge of the three-dimensional deformation field model as a first deformation unit, determining the other deformation unit as a second deformation unit, and subtracting the predicted deformation amount of the second deformation unit from the predicted deformation amount of the first deformation unit to obtain the deformation amount difference. For example, the transverse direction is selected as the analysis direction, and the difference value of the deformation amounts of the two adjacent deformation units in the transverse direction is calculated according to the predicted deformation amounts of the two adjacent deformation units in the transverse direction. The difference of the deformation amount is positive value to indicate that the two deformation units have a mutual deviation trend in the transverse direction, and the difference of the deformation amount is negative value to indicate that the two deformation units have a mutual approaching trend in the transverse direction.
And S522, when the deformation difference value is larger than a deformation difference value threshold value corresponding to the analysis direction, determining that deformation risks exist between two adjacent deformation units in the analysis direction, marking the contact surfaces of the two adjacent deformation units as deformation surfaces, and marking the selected analysis direction as the deformation direction.
Specifically, when the deformation amount difference in the transverse direction is larger than the deformation amount difference threshold in the transverse direction, it is determined that the two deformation units have deformation risks in the transverse direction, and a contact surface perpendicular to the transverse direction is marked as a deformation surface, and the transverse direction is marked as a deformation direction.
And S523, selecting one direction as a preset deformation direction, controlling a preset frame selection window to move in the current three-dimensional deformation field model, and counting the number of deformation surfaces with the deformation direction being the same as the preset deformation direction in the preset frame selection window to obtain the number of deformation surfaces.
S524, when the number of the deformation surfaces is larger than a preset deformation surface threshold value, predicting that cracks can be generated in the deep foundation pit slope, wherein the extending direction of the cracks is perpendicular to the preset deformation direction.
Specifically, if the transverse direction is selected to be the preset deformation direction, for example, the preset frame window is a sheet-shaped cuboid with 30cm in the longitudinal direction and the vertical direction and 2cm in the transverse direction. Selecting a position, transversely moving a preset frame selection window, wherein the moving step distance can be 2cm, the two frame selection positions are not crossed, the moving step distance can be 1cm, and thus a crossed frame selection three-dimensional deformation field model can be arranged, after the preset frame selection window is moved from one side surface to the opposite other side surface of the three-dimensional deformation field model at the selected position along the transverse direction, the preset frame selection window is longitudinally or vertically moved, the moving step distance is 30cm, 20cm or 10cm, and the like, then the preset frame selection window is gradually moved along the transverse direction, and the steps are repeated until the preset frame selection window traverses the whole current three-dimensional deformation field model. After each frame selection is completed, counting the number of deformation surfaces with transverse deformation directions in a preset frame selection window, if the number of deformation surfaces is 63, and if the preset deformation surface threshold is 30, the situation that the transverse deviation occurs in all 63 contact surfaces in the preset frame selection window is indicated, transverse cracks can possibly occur in a narrow preset range, the crack extending direction is approximately perpendicular to the preset deformation direction, for example, in the distance analysis, the preset deformation direction is transverse, and transverse deformation surfaces exceeding the preset deformation surface threshold are analyzed in the preset frame selection window, so that a plurality of positions in the preset frame selection window can be subjected to larger transverse deformation, and the cracks approximately perpendicular to the transverse directions can be generated in the deformation field model. And further analyzing the risk type of the side slope of the deep foundation pit on the basis of knowing the risk of deformation. It should be noted that the crack may be irregularly shaped, and the extending direction thereof may not be a straight line, and may be curved or undulated, so that the crack is approximately perpendicular to the preset deformation direction, and may be regarded as being perpendicular to the preset deformation direction.
In an optional embodiment of the present invention, when the number of deformation surfaces is greater than a preset deformation surface threshold, a crack is predicted to be generated in the deep foundation pit slope, and after the extension direction in the preset range is taken as the extension direction of the crack, the deep foundation pit slope deformation monitoring method further includes:
And when the preset deformation direction is transverse or longitudinal, judging whether the predicted deformation average value of one side of the crack, which is close to the center of the three-dimensional deformation field model, is larger than the predicted deformation average value of the other corresponding side in the preset deformation direction.
And when the deformation is larger than the preset deformation, the deep foundation pit slope is predicted to generate extrusion and bulge deformation.
And when the deformation is smaller than the preset deformation, predicting that the deep foundation pit slope can generate fracture deformation.
Specifically, when the preset deformation direction is transverse or longitudinal, the crack extends vertically to the transverse or longitudinal direction, or the crack extends vertically to the longitudinal direction or the transverse direction, but the deformation direction is transverse or longitudinal, so that the crack of the deep foundation pit slope may be caused by fracture or internal extrusion deformation. Therefore, the average value of the predicted deformation amount at two sides of the crack needs to be analyzed, if the preset deformation direction is transverse, the average value of the transverse predicted deformation amount at two sides of the crack is compared, and if the preset deformation direction is longitudinal, the average value of the longitudinal predicted deformation amount at two sides of the crack is compared. When the predicted deformation average value of one side close to the center of the three-dimensional deformation field model is larger than the predicted deformation average value of the other corresponding side, the deformation of one side close to the center is larger, but the peripheral soil layer is blocked due to the fact that the soil layer with smaller deformation is arranged on the periphery, at the moment, only the peripheral layer can be extruded in the future, extrusion bulging deformation can occur with high probability, when the predicted deformation average value of one side close to the center of the three-dimensional deformation field model is smaller than the predicted deformation average value of the other corresponding side, the deformation of one side close to the center is smaller, the deformation of one side far away from the center is larger, at the moment, the peripheral soil layer is a peripheral soil layer area, at the moment, the peripheral soil layer deformation is not blocked, and the peripheral soil layer is separated from an inner layer, so that fracture deformation is generated. When the average value of the predicted deformation quantity near one side of the center of the three-dimensional deformation field model is equal to the average value of the predicted deformation quantity at the other corresponding side, the three-dimensional deformation field model is uniformly deformed, and cracks are not generated. After the occurrence of cracks in the deep foundation pit slope is analyzed, the occurrence source of the cracks is further positioned, the more accurate deformation type is determined, and targeted preventive measures are conveniently carried out in advance.
In an optional embodiment of the present invention, when the number of deformation surfaces is greater than a preset deformation surface threshold, a crack is predicted to be generated in the deep foundation pit slope, and after the extension direction in the preset range is taken as the extension direction of the crack, the deep foundation pit slope deformation monitoring method further includes:
When the preset deformation direction is vertical, judging whether the predicted deformation average value of the upper region of the three-dimensional deformation field model is larger than the predicted deformation average value of the lower region of the three-dimensional deformation field model in the preset deformation direction, wherein the three-dimensional deformation field model is divided into an upper part and a lower part at the height center of the three-dimensional deformation field model, the upper part is used as the upper region of the three-dimensional deformation field model, and the lower part is used as the lower region of the three-dimensional deformation field model.
When the sliding risk is larger than the preset sliding risk, predicting that the deep foundation pit slope can generate the sliding risk;
when smaller, the deep foundation pit slope is predicted to generate a risk of extrusion uplift.
Specifically, similar to the deformation analysis described above, when the preset deformation direction is vertical, the crack will extend along the transverse direction or the longitudinal direction, when the predicted deformation average value of the upper layer area is greater than the predicted deformation average value of the lower layer area, the crack will be generated between the upper layer soil layer and the lower layer soil layer, when the crack is greater, the upper layer soil layer will slide along the lower layer soil layer, especially in the deep foundation pit slope area, the slope itself has a certain slope, and when this occurs, the risk of sliding is greater, so that the deep foundation pit slope can be predicted in advance to generate the sliding risk. When the average value of the predicted deformation of the upper layer area is smaller than that of the lower layer area, the lower layer soil layer can squeeze the upper layer soil layer when the preset deformation direction is vertical upwards, and the upper layer soil layer is forced to bulge, however, when the preset deformation direction is vertical downwards, the lower layer soil layer and the upper layer soil layer are described to be settled, at the moment, the even settlement has little influence on a building on the foundation pit, and further attention is needed to avoid the larger settlement of the foundation pit.
In summary, compared with the prior art, the method has the following beneficial effects:
1. The method comprises the steps of acquiring data by adopting various devices, acquiring the data of the side slope of the deep foundation pit from various aspects, monitoring the surface deformation condition of the side slope of the deep foundation pit, monitoring the internal deformation condition, combining the internal and external monitoring data, guaranteeing the accuracy of a constructed three-dimensional deformation field model and guaranteeing the accuracy of subsequent prediction, segmenting and refining the three-dimensional deformation field model, predicting the deformation of each deformation unit by using a prediction network model, monitoring the change condition of each deformation unit, predicting the initial stage of the side slope deformation of the deep foundation pit, and carrying out early warning at the initial stage of the non-occurrence or just-occurrence of various risk conditions, thereby improving the timeliness of early warning.
2. When a certain predicted deformation accumulation value is larger than a corresponding accumulated early warning value, the fact that the deformation of the deep foundation pit slope is too large in the direction corresponding to the predicted deformation accumulation value is needed to be further judged, whether the directions of the average values of the predicted deformation corresponding to the predicted deformation accumulation value are consistent in a plurality of time points or not is needed to be further judged, if the directions are consistent, the fact that the directions of the plurality of time points continuously change in the same direction is needed to be judged, the probability that the deep foundation pit slope continuously deforms in the future is large, and early warning can be carried out under the condition that the deformation is out in excess. And the direction consistency judgment is carried out, so that the early warning accuracy can be greatly improved, and the false alarm probability is reduced.
3. After the occurrence of cracks in the deep foundation pit slope is analyzed, the occurrence source of the cracks is further positioned, the more accurate deformation type is determined, and targeted preventive measures are conveniently carried out in advance.
As shown in fig. 3, a deep foundation pit side slope deformation monitoring device provided by an embodiment of the present application includes:
The monitoring data acquisition module 100 is configured to acquire monitoring data of a side slope of the deep foundation pit, where the monitoring data includes side slope surface data, side slope internal horizontal displacement data, side slope internal sedimentation data, and three-dimensional data of the side slope of the deep foundation pit.
And the deformation field construction module 200 is used for constructing a three-dimensional deformation field model of the deep foundation pit slope according to the monitoring data and the time stamp.
The deformation field segmentation module 300 is configured to segment each three-dimensional deformation field model constructed at a plurality of time points into a plurality of deformation units, and obtain time sequence deformation information of each deformation unit, where the deformation units are three-dimensional models obtained by segmentation according to a preset size, and the time sequence deformation information includes transverse deformation amounts, longitudinal deformation amounts and vertical deformation amounts of the deformation units at a plurality of time points.
The deformation prediction module 400 is configured to input the time-series deformation information of the deformation units into a trained prediction network model, and obtain a predicted deformation of each deformation unit, where the predicted deformation includes a lateral predicted deformation, a longitudinal predicted deformation, and a vertical predicted deformation.
And the monitoring and early warning module 500 is configured to obtain a risk condition of the deep foundation pit slope according to the predicted deformation amounts of the deformation units, so as to early warn the risk of the deep foundation pit slope.
An alternative embodiment of the present application provides a storage medium storing a computer program that causes a computer to execute the deep foundation pit slope deformation monitoring method as described above.
An electronic device provided in an alternative embodiment of the present application includes:
One or more processors, memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs comprising instructions for performing the deep foundation pit slope deformation monitoring method as described above.
The beneficial effects of the deep foundation pit slope deformation monitoring device, the storage medium and the electronic equipment in this embodiment are the same as those of the deep foundation pit slope deformation monitoring method, and are not described in detail herein.
An electronic device that can be a server or a client of the present application will now be described, which is an example of a hardware device that can be applied to aspects of the present application. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and/or claimed herein.
The electronic device includes a computing unit that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) or a computer program loaded from a storage unit into a Random Access Memory (RAM). In the RAM, various programs and data required for the operation of the device may also be stored. The computing unit, ROM and RAM are connected to each other by a bus. An input/output (I/O) interface is also connected to the bus.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random-access Memory (Random Access Memory, RAM), or the like. In the present application, the units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present application. In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The foregoing embodiments are merely for illustrating the technical solution of the present application, but not for limiting the same, and although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that modifications may be made to the technical solution described in the foregoing embodiments or equivalents may be substituted for parts of the technical features thereof, and that such modifications or substitutions do not depart from the spirit and scope of the technical solution of the embodiments of the present application in essence.
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