CN117589120A - BIM-based foundation pit deformation automatic monitoring and early warning method, system and electronic equipment - Google Patents
BIM-based foundation pit deformation automatic monitoring and early warning method, system and electronic equipment Download PDFInfo
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- 238000012360 testing method Methods 0.000 claims description 29
- 238000012549 training Methods 0.000 claims description 28
- 238000011156 evaluation Methods 0.000 claims description 22
- 238000012216 screening Methods 0.000 claims description 15
- 239000011159 matrix material Substances 0.000 claims description 10
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/32—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring the deformation in a solid
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- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02D—FOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
- E02D33/00—Testing foundations or foundation structures
Abstract
The application provides a foundation pit deformation automatic monitoring and early warning method, a system and electronic equipment based on BIM. The reliability of the result is greatly improved, so that the stability of the current state of the target foundation pit and the foundation pit deformation predicted value of the target foundation pit are obtained more accurately, and monitoring and early warning can be provided for subsequent construction of the foundation pit, so that the construction scheme can be changed in time.
Description
Technical Field
The application relates to the technical field of foundation pit monitoring, in particular to a foundation pit deformation automatic monitoring and early warning method, system and electronic equipment based on BIM.
Background
In large-scale infrastructure construction and high-rise building foundation pit construction, monitoring and early warning of foundation pit deformation are extremely important work. The traditional monitoring method mainly depends on manual measurement and regular inspection, and the method is low in efficiency and difficult to ensure the real-time performance and accuracy of monitoring.
BIM technique combines together with automatic monitoring early warning system, can realize the real-time, the accurate control to foundation ditch deformation, through arranging a series of high accuracy sensors around the foundation ditch for the deformation condition of monitoring the foundation ditch, and the actual monitoring data of foundation ditch only can reflect the foundation ditch deformation condition at present, can't predict in advance, can not provide technical support for the optimization of construction scheme.
Disclosure of Invention
The embodiment of the application aims to provide a foundation pit deformation automatic monitoring and early warning method, system and electronic equipment based on BIM, which aim to monitor foundation pit deformation in real time and predict deformation trend of a foundation pit based on current monitoring data so as to optimize a foundation pit construction scheme.
In order to achieve the above object, embodiments of the present application are realized by:
in a first aspect, an embodiment of the present application provides a foundation pit deformation automatic monitoring and early warning method based on BIM, including: determining the position of a monitoring point according to the data information of the target foundation pit, and establishing a target foundation pit monitoring BIM; screening past foundation pit cases based on the similarity of the foundation pit construction scheme, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity; collecting monitoring point position monitoring data, and determining the stability of the current state of the target foundation pit according to the monitoring data; carrying out normalization processing on the monitoring data of past foundation pit cases with the front similarity to form a training set and a testing set, respectively carrying out training and testing by utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm; and integrating the stability of the current state of the target foundation pit and the foundation pit deformation predicted value into the predicted foundation pit deformation value for early warning.
In the embodiment of the application, a target foundation pit monitoring BIM model is established by determining the positions of monitoring points according to the data information of the target foundation pit; screening past foundation pit cases based on the similarity of the foundation pit construction scheme, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity; collecting monitoring point position monitoring data, and determining the stability of the current state of the target foundation pit according to the monitoring data; carrying out normalization processing on the monitoring data of past foundation pit cases with the front similarity to form a training set and a testing set, respectively carrying out training and testing by utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm; and integrating the stability of the current state of the target foundation pit and the foundation pit deformation predicted value into the predicted foundation pit deformation value for early warning. The method can fully utilize the existing foundation pit case data by utilizing the similarity of the construction scheme, respectively adopts different foundation pit deformation prediction algorithms, determines the weight of each foundation pit deformation prediction algorithm, and carries out overall prediction. The reliability of the result is greatly improved, so that the stability of the current state of the target foundation pit and the foundation pit deformation predicted value of the target foundation pit are obtained more accurately, and monitoring and early warning can be provided for subsequent construction of the foundation pit, so that the construction scheme can be changed in time. With reference to the first aspect, in a first possible implementation manner of the first aspect, screening past foundation pit cases based on a similarity of a foundation pit construction scheme, determining a foundation pit case with a high similarity to a current foundation pit construction scheme, and obtaining monitoring data of the foundation pit case, including: establishing construction scheme evaluation indexes based on a past foundation pit case construction scheme and a target foundation pit construction scheme; expert evaluation is introduced based on the construction scheme evaluation index, an expert evaluation matrix and an average weight matrix are determined, and the similarity of the construction scheme is determined; and sequencing based on the similarity to determine a past foundation pit case construction scheme with the front similarity to the target foundation pit construction scheme, and acquiring monitoring data of the past foundation pit case with the front similarity.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the construction plan evaluation index includes an excavation depth, a foundation pit shape, a hydrogeological environment, and a foundation pit enclosure construction structure type.
With reference to the first aspect, in a third possible implementation manner of the first aspect, monitoring point position monitoring data is collected, and stability of a current state of the target foundation pit is determined according to the monitoring data;
preprocessing and decomposing monitoring point position monitoring data, wherein trend term components are as follows:
wherein: />For trend component +.>For monitoring the position of the monitoring point, the +.>As a random component of the light,
based on the point mutation theory, constructing an evaluation model of the stability of the current state of the target foundation pit, wherein the expression is as follows:
wherein: q and p are mutation characteristic parameters; t is a time variable;
determining mutation characteristic parameters q and p based on trend components of monitoring point position monitoring data, and determining mutation characteristic values based on the mutation characteristic parameters q and p：
And determining the stability of the current state of the foundation pit based on the mutation characteristic value.
With reference to the third possible implementation manner of the first aspect, in a fourth possible implementation manner of the first aspect, performing normalization processing on the monitored data of the past foundation pit cases with the previous similarity to form a training set and a testing set, respectively performing training and testing by using a first preset algorithm, a second preset algorithm and a third preset algorithm, determining a foundation pit deformation predicted value result of each algorithm, determining a weight coefficient of each algorithm according to a variance corresponding to the foundation pit deformation predicted value result, and determining a foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm, wherein the method specifically comprises the following steps:,
wherein:Spredicting the integrated value for foundation pit deformation>Foundation pit deformation predicted value of first prediction algorithm, < ->Foundation pit deformation predicted value of second prediction algorithm, < ->Foundation pit deformation predicted value of third prediction algorithm, < ->For predicting the variance of the sample correspondence +.>Is->The algorithm is at->Error between the monitored value and the predicted value in the individual samples,/->Is error average value +.>Taking 1,2 and 3.
In a second aspect, an embodiment of the present application provides a foundation pit deformation automatic monitoring and early warning system based on BIM, including: the modeling unit is used for determining the position of the monitoring point according to the data information of the target foundation pit and establishing a target foundation pit monitoring BIM; the screening unit is used for screening past foundation pit cases based on the similarity of the foundation pit construction scheme, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity; the current state determining unit is used for collecting monitoring point position monitoring data and determining the stability of the current state of the target foundation pit according to the monitoring data; the prediction unit is used for carrying out normalization processing on the monitoring data of the past foundation pit cases with the front similarity to form a training set and a testing set, respectively utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm to carry out training and testing, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm; and the early warning unit is used for integrating the stability of the current state of the target foundation pit and the predicted value of the deformation of the foundation pit into the predicted value of the deformation of the foundation pit for early warning.
With reference to the second aspect, in a first possible implementation manner of the second aspect, screening past foundation pit cases based on a similarity of a foundation pit construction scheme, determining a foundation pit case with a high similarity to the current foundation pit construction scheme, and obtaining monitoring data of the foundation pit case, including:
establishing construction scheme evaluation indexes based on a past foundation pit case construction scheme and a target foundation pit construction scheme;
expert evaluation is introduced based on the construction scheme evaluation index, an expert evaluation matrix and an average weight matrix are determined, and the similarity of the construction scheme is determined; and sequencing based on the similarity to determine a past foundation pit case construction scheme with the front similarity to the target foundation pit construction scheme, and acquiring monitoring data of the past foundation pit case with the front similarity.
With reference to the second aspect, in a first possible implementation manner of the first aspect, monitoring point position monitoring data is collected, and stability of a current state of the target foundation pit is determined according to the monitoring data;
preprocessing and decomposing monitoring point position monitoring data, wherein trend term components are as follows:
wherein: />For trend component +.>For monitoring point position monitoring data, < >>As a random component of the light,
based on the point mutation theory, constructing an evaluation model of the stability of the current state of the target foundation pit, wherein the expression is as follows:
wherein: q and p are mutation characteristic parameters, t is a time variable, the mutation characteristic parameters q and p are determined based on trend components of monitoring point position monitoring data, and mutation characteristic values are determined based on the mutation characteristic parameters q and p> ：And determining the stability of the current state of the foundation pit based on the mutation characteristic value.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the monitoring data of the past foundation pit cases with a front similarity are normalized to form a training set and a testing set, training and testing are performed by using a first preset algorithm, a second preset algorithm and a third preset algorithm respectively, a foundation pit deformation predicted value result of each algorithm is determined, a weight coefficient of each algorithm is determined according to a variance corresponding to the foundation pit deformation predicted value result, and a foundation pit deformation predicted value of a target foundation pit is determined according to the weight coefficient of each algorithm, wherein the method specifically comprises the following steps:,
wherein:Spredicting the integrated value for foundation pit deformation>Foundation pit deformation predicted value of first prediction algorithm, < ->Foundation pit deformation predicted value of second prediction algorithm, < ->Foundation pit deformation predicted value of third prediction algorithm, < ->For predicting the variance of the sample correspondence +.>Is->The algorithm is at->Error between the monitored value and the predicted value in the individual samples,/->Is error average value +.>Taking 1,2 and 3.
In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor, where the memory is configured to store information including program instructions, and the processor is configured to control execution of the program instructions, where the program instructions when loaded and executed by the processor implement the BIM-based foundation pit deformation automatic monitoring and early warning method according to any one of the first aspect or the possible implementation manners of the first aspect.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a foundation pit deformation automatic monitoring and early warning method based on BIM according to the embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1, fig. 1 is a flowchart of a foundation pit deformation automatic monitoring and early warning method based on BIM according to the embodiment of the present application. In this embodiment, the automatic monitoring and early warning method for foundation pit deformation based on BIM may be executed by an electronic device, which may be a server (e.g. cloud server, server cluster, etc.) or a terminal (e.g. personal computer, notebook computer, etc.), and is not limited herein.
In this embodiment, the automatic monitoring and early warning method for foundation pit deformation based on BIM may include step S10, step S20, step S30, step S40 and step S50.
The visual management of foundation pit deformation monitoring by using BIM technology means that the BIM model is combined with real-time foundation pit deformation monitoring data to be presented to managers and constructors in an intuitive and visual mode. The visual management mode can greatly improve decision-making efficiency and response speed so as to cope with construction risks possibly occurring. The electronic device may perform step S10.
Step S10: and determining the positions of the monitoring points according to the data information of the target foundation pit, and establishing a target foundation pit monitoring BIM model.
In foundation pit engineering, the location and arrangement of the sensors for deformation monitoring will vary depending on the specific engineering requirements and construction conditions, but generally includes the following aspects:
foundation pit support structure: deformation monitoring can be carried out aiming at a foundation pit support structure, and comprises monitoring of horizontal displacement and vertical displacement of a top of a retaining wall (pile), monitoring of horizontal displacement of the retaining wall (pile) or a soil body deep layer, and monitoring of supporting axial force, upright post settlement and the like. The monitoring can reflect the deformation condition of the supporting structure and provide basis for taking corresponding measures.
Surrounding environment: foundation pit excavation and construction may have an impact on the surrounding environment, and thus deformation monitoring of surrounding buildings, roads, underground facilities, etc. is required to evaluate whether damage is likely. Such monitoring may include monitoring in terms of displacement, tilt, sedimentation, stress, cracking, and the like.
Groundwater level and soil layer pore water pressure: the monitoring can reflect the hydrologic conditions inside and outside the foundation pit, and is very important for preventing the influence of underground water on the foundation pit.
When arranging the sensor, the sensor needs to be selected and arranged according to the actual construction situation and the monitoring requirement. Common sensor types include strain gauges, inclinometers, water level gauges, and the like. The strain gauge can be used for monitoring deformation of an object, and can be used for monitoring deformation conditions of a supporting structure and soil in foundation pit engineering; the inclinometer can be used for measuring the inclination condition of a structure, and can be used for monitoring the inclination condition of a foundation pit supporting body in foundation pit engineering; the water level gauge can be used for measuring the water level, and can be used for monitoring the underground water level condition in the foundation pit in foundation pit engineering.
And determining the positions of the monitoring points according to the data information of the target foundation pit, and after establishing a target foundation pit monitoring BIM model, the electronic equipment can execute step S20.
Step S20: and screening past foundation pit cases based on the foundation pit construction scheme similarity, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity.
Determining the similarity of foundation pit construction schemes needs to be considered from the following aspects:
construction environment: including hydrogeologic conditions, climatic conditions, and the like.
The construction requirements are as follows: the construction requirements of different engineering projects on the foundation pit are different, such as the requirements of depth, safety, construction progress and the like. These requirements have an impact on the design and implementation of the construction scheme and therefore need to be considered in determining the similarity.
The construction method comprises the following steps: there are many methods for foundation pit construction, including slope excavation, support excavation, reinforcement excavation, and the like. Different methods have different application ranges and advantages and disadvantages, so that proper construction methods are required to be selected according to specific situations, and the similarity is determined and considered.
Engineering materials: different materials, such as cement, sand, stones, etc., have different effects on the properties of the concrete, and therefore it is necessary to consider the effects of engineering materials in determining the similarity.
The structural form is as follows: the structural form of the foundation pit also affects the similarity of the construction scheme. Different structural forms have different stress characteristics and construction difficulties, so that the influence of the structural forms needs to be considered when determining the similarity.
And (3) construction organization design: construction organization design is one of the important factors in determining a construction scheme, including construction sequence, construction machinery, labor arrangement, and the like. Different construction organization designs have an impact on the implementation of the construction scheme, and therefore the impact of the construction organization design needs to be considered in determining the similarity.
In summary, determining the similarity of foundation pit construction schemes requires consideration of a plurality of factors, including construction environment, construction requirements, construction method, engineering materials, structural form, construction organization design, and the like.
Here, step S20 may specifically include: establishing construction scheme evaluation indexes based on a past foundation pit case construction scheme and a target foundation pit construction scheme; expert evaluation is introduced based on the construction scheme evaluation index, an expert evaluation matrix and an average weight matrix are determined, and the similarity of the construction scheme is determined;
and sequencing based on the similarity to determine a past foundation pit case construction scheme with the front similarity to the target foundation pit construction scheme, and acquiring monitoring data of the past foundation pit case with the front similarity.
The past foundation pit cases are screened based on the foundation pit construction scheme similarity, the foundation pit cases with high similarity with the current foundation pit construction scheme are determined, monitoring data of the past foundation pit cases with the front similarity are obtained, and the electronic equipment can execute step S30.
Step S30: and collecting monitoring point position monitoring data, and determining the stability of the current state of the target foundation pit according to the monitoring data.
The method specifically comprises the following steps:
preprocessing and decomposing monitoring point position monitoring data, wherein trend term components are as follows:
wherein: />For trend component +.>For monitoring point position monitoring data, < >>As a random component of the light,
based on the point mutation theory, constructing an evaluation model of the stability of the current state of the target foundation pit, wherein the expression is as follows:
wherein: q and p are mutation characteristic parameters; t is a time variable;
determining mutation characteristic parameters q and p based on trend components of monitoring point position monitoring data, and determining mutation characteristic values based on the mutation characteristic parameters q and p ：
And determining the stability of the current state of the foundation pit based on the mutation characteristic value.
And collecting monitoring point position monitoring data, determining the stability of the current state of the target foundation pit according to the monitoring data, and executing step S40 by the electronic equipment.
Step S40: and carrying out normalization processing on the monitoring data of the past foundation pit cases with the front similarity to form a training set and a testing set, respectively carrying out training and testing by utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm.
In this embodiment, the electronic device may normalize the monitored data of the past foundation pit cases with the previous similarity to form a training set and a testing set, respectively perform training and testing by using a first preset algorithm, a second preset algorithm and a third preset algorithm, determine the result of the foundation pit deformation predicted value of each algorithm, determine the weight coefficient of each algorithm according to the variance corresponding to the result of the foundation pit deformation predicted value, and determine the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm, specifically:
,
wherein:Spredicting the integrated value for foundation pit deformation>Foundation pit deformation predicted value of first prediction algorithm, < ->Foundation pit deformation predicted value of second prediction algorithm, < ->Foundation pit deformation predicted value of third prediction algorithm, < ->For predicting sample correspondenceVariance (L)/(L)>Is->The algorithm is at->Error between the monitored value and the predicted value in the individual samples,/->Is error average value +.>Taking 1,2 and 3.
And carrying out normalization processing on the monitoring data of the past foundation pit cases with the front similarity to form a training set and a testing set, respectively carrying out training and testing by utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm, wherein the electronic equipment can execute step S50.
Step S50: and integrating the stability of the current state of the target foundation pit and the foundation pit deformation predicted value into the predicted foundation pit deformation value for early warning.
The embodiment of the application provides a schematic diagram of a foundation pit deformation automatic monitoring and early warning system based on BIM.
In this embodiment, the foundation pit deformation automatic monitoring and early warning system based on the BIM may include: the modeling unit is used for determining the position of the monitoring point according to the data information of the target foundation pit and establishing a target foundation pit monitoring BIM;
the screening unit is used for screening past foundation pit cases based on the similarity of the foundation pit construction scheme, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity;
the current state determining unit is used for collecting monitoring point position monitoring data and determining the stability of the current state of the target foundation pit according to the monitoring data;
the prediction unit is used for carrying out normalization processing on the monitoring data of the past foundation pit cases with the front similarity to form a training set and a testing set, respectively utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm to carry out training and testing, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm;
and the early warning unit is used for integrating the stability of the current state of the target foundation pit and the predicted value of the deformation of the foundation pit into the predicted value of the deformation of the foundation pit for early warning.
The embodiment of the application provides a schematic diagram of an electronic device.
In this embodiment, the electronic device may be a terminal, such as a tablet computer, a personal computer, or the like; the electronic device may also be a server, such as a cloud server, a server cluster, etc., which is not limited herein.
By way of example, the electronic device may include: a communication module connected to the outside world through a network, one or more processors for executing program instructions, a bus, and various forms of memory, such as a disk, ROM, or RAM, or any combination thereof. The memory, the communication module and the processor can be connected through a bus.
Illustratively, the memory has a program stored therein. The processor can call and run the programs from the memory, so that the BIM-based foundation pit deformation automatic monitoring and early warning method can be realized by running the programs.
In summary, the embodiment of the application provides a foundation pit deformation automatic monitoring and early warning system and equipment based on BIM, which establishes a target foundation pit monitoring BIM model by determining the position of a monitoring point according to the data information of the target foundation pit; screening past foundation pit cases based on the similarity of the foundation pit construction scheme, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity; collecting monitoring point position monitoring data, and determining the stability of the current state of the target foundation pit according to the monitoring data; carrying out normalization processing on the monitoring data of past foundation pit cases with the front similarity to form a training set and a testing set, respectively carrying out training and testing by utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm; and integrating the stability of the current state of the target foundation pit and the foundation pit deformation predicted value into the predicted foundation pit deformation value for early warning. The method can fully utilize the existing foundation pit case data by utilizing the similarity of the construction scheme, respectively adopts different foundation pit deformation prediction algorithms, determines the weight of each foundation pit deformation prediction algorithm, and carries out overall prediction. The reliability of the result is greatly improved, so that the stability of the current state of the target foundation pit and the foundation pit deformation predicted value of the target foundation pit are obtained more accurately, and monitoring and early warning can be provided for subsequent construction of the foundation pit, so that the construction scheme can be changed in time.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
Further, 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 over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In this document, relational terms such as first and second, and the like may be 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.
The foregoing is merely exemplary embodiments of the present application and is not intended to limit the scope of the present application, and various modifications and variations may be suggested to one skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (10)
1. BIM-based foundation pit deformation automatic monitoring and early warning method is characterized by comprising the following steps:
determining the position of a monitoring point according to the data information of the target foundation pit, and establishing a target foundation pit monitoring BIM;
screening past foundation pit cases based on the similarity of the foundation pit construction scheme, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity;
collecting monitoring point position monitoring data, and determining the stability of the current state of the target foundation pit according to the monitoring data;
carrying out normalization processing on the monitoring data of past foundation pit cases with the front similarity to form a training set and a testing set, respectively carrying out training and testing by utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm;
and integrating the stability of the current state of the target foundation pit and the foundation pit deformation predicted value into the predicted foundation pit deformation value for early warning.
2. The automatic monitoring and early warning method for foundation pit deformation based on BIM according to claim 1, wherein screening past foundation pit cases based on the similarity of foundation pit construction schemes, determining a foundation pit case having a high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the foundation pit case, comprises:
establishing construction scheme evaluation indexes based on a past foundation pit case construction scheme and a target foundation pit construction scheme;
expert evaluation is introduced based on the construction scheme evaluation index, an expert evaluation matrix and an average weight matrix are determined, and the similarity of the construction scheme is determined;
and sequencing based on the similarity to determine a past foundation pit case construction scheme with the front similarity to the target foundation pit construction scheme, and acquiring monitoring data of the past foundation pit case with the front similarity.
3. The automatic monitoring and early warning method for foundation pit deformation based on BIM according to claim 2, wherein the construction scheme evaluation indexes comprise excavation depth, foundation pit shape, hydrogeological environment and foundation pit support construction structure type.
4. The automatic monitoring and early warning method for foundation pit deformation based on BIM according to claim 1, wherein monitoring point position monitoring data are collected, and the stability of the current state of the target foundation pit is determined according to the monitoring data;
preprocessing and decomposing monitoring point position monitoring data, wherein trend term components are as follows:
wherein: />For trend component +.>For monitoring point position monitoring data, < >>As a random component of the light,
based on the point mutation theory, constructing an evaluation model of the stability of the current state of the target foundation pit, wherein the expression is as follows:
wherein: q and p are mutation characteristic parameters; />Is a time variable;
determining mutation characteristic parameters q and p based on trend components of monitoring point position monitoring data, and determining mutation characteristic values based on the mutation characteristic parameters q and p ：
And determining the stability of the current state of the foundation pit based on the mutation characteristic value.
5. The automatic monitoring and early warning method for foundation pit deformation based on BIM according to claim 4, wherein the monitoring data of past foundation pit cases with the front similarity are normalized to form a training set and a testing set, training and testing are respectively carried out by using a first preset algorithm, a second preset algorithm and a third preset algorithm, the foundation pit deformation predicted value result of each algorithm is determined, the weight coefficient of each algorithm is determined according to the variance corresponding to the foundation pit deformation predicted value result, and the foundation pit deformation predicted value of the target foundation pit is determined according to the weight coefficient of each algorithm, specifically:
,
wherein:Sis a foundation pit changeShape prediction integrated value->Foundation pit deformation predicted value of first prediction algorithm, < ->Foundation pit deformation predicted value of second prediction algorithm, < ->Foundation pit deformation predicted value of third prediction algorithm, < ->For predicting the variance of the sample correspondence +.>Is->The algorithm is at->Error between the monitored value and the predicted value in the individual samples,/->Is error average value +.>Taking 1,2 and 3.
6. BIM-based foundation pit deformation automatic monitoring and early warning system is characterized by comprising:
the modeling unit is used for determining the position of the monitoring point according to the data information of the target foundation pit and establishing a target foundation pit monitoring BIM;
the screening unit is used for screening past foundation pit cases based on the similarity of the foundation pit construction scheme, determining foundation pit cases with high similarity with the current foundation pit construction scheme, and acquiring monitoring data of the past foundation pit cases with the front similarity;
the current state determining unit is used for collecting monitoring point position monitoring data and determining the stability of the current state of the target foundation pit according to the monitoring data;
the prediction unit is used for carrying out normalization processing on the monitoring data of the past foundation pit cases with the front similarity to form a training set and a testing set, respectively utilizing a first preset algorithm, a second preset algorithm and a third preset algorithm to carry out training and testing, determining the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm;
and the early warning unit is used for integrating the stability of the current state of the target foundation pit and the predicted value of the deformation of the foundation pit into the predicted value of the deformation of the foundation pit for early warning.
7. The automated BIM-based pit deformation monitoring and early warning system of claim 6, wherein screening past pit cases based on pit construction scheme similarity, determining pit cases having a high similarity to a current pit construction scheme, and obtaining monitoring data for the pit cases, comprises:
establishing construction scheme evaluation indexes based on a past foundation pit case construction scheme and a target foundation pit construction scheme;
expert evaluation is introduced based on the construction scheme evaluation index, an expert evaluation matrix and an average weight matrix are determined, and the similarity of the construction scheme is determined;
and sequencing based on the similarity to determine a past foundation pit case construction scheme with the front similarity to the target foundation pit construction scheme, and acquiring monitoring data of the past foundation pit case with the front similarity.
8. The automatic monitoring and early warning system for foundation pit deformation based on BIM according to claim 6, wherein monitoring point position monitoring data are collected, and the stability of the current state of the target foundation pit is determined according to the monitoring data;
preprocessing and decomposing monitoring point position monitoring data, wherein trend term components are as follows:
wherein: />For trend component +.>For monitoring point position monitoring data, < >>As a random component of the light,
based on the point mutation theory, constructing an evaluation model of the stability of the current state of the target foundation pit, wherein the expression is as follows:
wherein: q and p are mutation characteristic parameters; />Is a time variable;
determining mutation characteristic parameters q and p based on trend components of monitoring point position monitoring data, and determining mutation characteristic values based on the mutation characteristic parameters q and p ：
And determining the stability of the current state of the foundation pit based on the mutation characteristic value.
9. The automatic monitoring and early warning system for foundation pit deformation based on BIM according to claim 8, wherein the monitoring data of past foundation pit cases with a previous similarity are normalized to form a training set and a testing set, and the training set and the testing set are respectively calculated by using a first preset algorithmTraining and testing the method, a second preset algorithm and a third preset algorithm to determine the foundation pit deformation predicted value result of each algorithm, determining the weight coefficient of each algorithm according to the variance corresponding to the foundation pit deformation predicted value result, and determining the foundation pit deformation predicted value of the target foundation pit according to the weight coefficient of each algorithm, wherein the method specifically comprises the following steps:,wherein:Spredicting the integrated value for foundation pit deformation>Foundation pit deformation predicted value of first prediction algorithm, < ->Foundation pit deformation predicted value of second prediction algorithm, < ->Foundation pit deformation predicted value of third prediction algorithm, < ->For predicting the variance of the sample correspondence +.>Is->The algorithm is at->Error between the monitored value and the predicted value in the individual samples,/->Is error average value +.>Taking 1,2 and 3.
10. An electronic device comprising a memory for storing information including program instructions and a processor for controlling execution of the program instructions, the program instructions when loaded and executed by the processor implementing the BIM-based pit deformation automatic monitoring and early warning method of any one of claims 1 to 5.
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