Road construction project supervision construction real-time monitoring method based on big data

Abstract

The invention provides a road construction project supervision construction real-time monitoring method based on big data, and relates to the technical field of construction monitoring. The method comprises the following steps: collecting roadbed settlement local monitoring data of a plurality of monitoring sites in a target construction road section, generating a settlement monitoring time sequence matrix of each monitoring site, and constructing dynamic characteristic fields corresponding to a plurality of settlement monitoring indexes respectively; extracting a settlement feature vector of each monitoring site, performing regional division on the target construction road section to generate a plurality of local monitoring regions, and calculating a settlement risk value of each local monitoring region in an initial state; determining the settlement risk propagation coefficient of each local monitoring area, and updating the settlement risk value of each local monitoring area; and respectively calculating the settlement comprehensive risk values of the plurality of local monitoring areas, and optimizing the construction scheme of the target construction road section based on the settlement comprehensive risk values. According to the invention, the recognition precision of the roadbed settlement high-risk area is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of construction monitoring, and particularly to a real-time monitoring method for highway construction project supervision and construction based on big data. Background Art

[0002] In the supervision and construction of highway construction projects, the real-time monitoring of subgrade settlement is an important means to ensure construction quality and project safety. Some monitoring schemes rely on sensors to collect data such as pressure and displacement, and analyze and process the monitoring data through preset thresholds. This static monitoring method is prone to ignoring the significant differences in risk sensitivity and settlement response characteristics between soft soil areas and hard soil areas, resulting in inaccurate risk prediction. Specifically, during the highway construction process, subgrade settlement exhibits strong dynamic characteristics, including the real-time changes of pressure and displacement and their conduction laws between regions. If precise modeling and analysis cannot be carried out in combination with the dynamic changes and propagation differences of regional soil characteristics, it is easy to affect the identification of high-risk areas and the control effect of risk diffusion. Summary of the Invention

[0003] To solve the above technical problems, the present invention proposes a real-time monitoring method for highway construction project supervision and construction based on big data. Starting from the differences in soil characteristics of different construction section areas, the monitoring data related to subgrade settlement collected is analyzed and processed to capture the dynamic changes of multiple monitoring indicators in the monitoring data, and precise data analysis is carried out based on the dynamic changes and propagation differences of regional soil characteristics to improve the identification accuracy of high-risk areas.

[0004] The real-time monitoring method for highway construction project supervision and construction based on big data provided by the present invention includes: Collect the local monitoring data of subgrade settlement at multiple monitoring points in the target construction section. The local monitoring data of subgrade settlement includes the time series data corresponding to multiple settlement monitoring indicators; Generate a settlement monitoring time series matrix for each monitoring point according to the local monitoring data of subgrade settlement, and perform three-dimensional space mapping on multiple settlement monitoring time series matrices based on the physical positions of the monitoring points to construct dynamic characteristic fields corresponding to multiple settlement monitoring indicators; Extract the differential features and gradient features of each settlement monitoring indicator in the dynamic characteristic field, and construct a settlement feature vector for each monitoring point regarding multiple settlement monitoring indicators according to the differential features and gradient features; Divide the target construction section into multiple local monitoring areas according to the settlement feature vectors, and calculate the settlement risk value of each local monitoring area in the initial state according to the local monitoring data of subgrade settlement; Determine the settlement risk propagation coefficient for each local monitoring area, and update the settlement risk value of each local monitoring area based on the settlement risk propagation coefficient and the real-time settlement monitoring data of multiple monitoring points in the target construction section; After each update of the settlement risk value of the local monitoring area, calculate the comprehensive settlement risk values of multiple local monitoring areas respectively, and optimize the construction plan of the target construction section based on the comprehensive settlement risk values.

[0005] Preferably, calculate the settlement risk value of each local monitoring area in the initial state according to the local monitoring data of subgrade settlement, including: Calculate the cumulative pressure parameter and cumulative settlement parameter of each monitoring point according to the local monitoring data of subgrade settlement, and determine the regional characteristic weight of each local monitoring area according to the cumulative pressure parameter and cumulative settlement parameter; Calculate the settlement risk value of each local monitoring area in the initial state according to the regional characteristic function, where:

[0006] In the formula, represents the settlement risk value of the local monitoring area in the initial state, is the regional characteristic function, represents the cumulative pressure parameter of the monitoring point in the local monitoring area, represents the cumulative settlement parameter of the monitoring point in the local monitoring area, represents the regional characteristic weight of the local monitoring area.

[0007] Preferably, for the settlement risk value of the local monitoring area in the initial state, it also includes: For the regional characteristic function , if the soil property of the local monitoring area belongs to hard soil, the regional characteristic function is:

[0008] If the soil property of the local monitoring area belongs to soft soil, the regional characteristic function is:

[0009] For the regional characteristic weight of the local monitoring area, it is calculated by the following formula:

[0010] In the formula, represents the regional characteristic weight of the local monitoring area, , respectively represent the average pressure value and the average settlement value of multiple monitoring sites in the local monitoring area, 、 respectively represent the average pressure gradient and the average settlement gradient of multiple monitoring sites in the local monitoring area.

[0011] Preferably, based on the settlement risk propagation coefficient and the real-time settlement monitoring data of multiple monitoring sites in the target construction section, the settlement risk value of each local monitoring area is updated, including: The settlement risk value of the local monitoring area is updated using the following formula:

[0012] In the formula, 、 are respectively time and time, the settlement risk values of the local monitoring area, represents at time, the settlement risk value of the monitoring site in the set of adjacent points of the local monitoring area, represents the settlement risk propagation coefficient of the monitoring site in the set of adjacent points of the local monitoring area, represents the set of adjacent points of the local monitoring area; For the settlement risk propagation coefficient , it is determined according to the set of adjacent points of the local monitoring area, where:

[0013] In the formula, represents the set of monitoring sites in the local monitoring area, represents the first propagation coefficient, represents the second propagation coefficient, where if the soil properties corresponding to the monitoring site in the set of adjacent points are the same as the soil properties of the local monitoring area, the second propagation coefficient takes the value of the first propagation coefficient. If the soil properties corresponding to the monitoring site in the set of adjacent points are different from the soil properties of the local monitoring area, the second propagation coefficient is determined according to the monitoring site in the set of adjacent points and the soil properties of the local monitoring area.

[0014] Preferably, the second propagation coefficient is determined according to the monitoring site in the set of adjacent points and the soil properties of the local monitoring area, including: Denote the current local monitoring area as the first area, and denote the monitoring site The local monitoring area to which it belongs is the second area. If the soil property of the first area belongs to hard soil and the soil property of the second area belongs to soft soil, the value of the second propagation coefficient is the ratio of the settlement risk value of the second area to the settlement risk value of the first area. If the soil property of the first area belongs to soft soil and the soil property of the second area belongs to hard soil, the value of the second propagation coefficient is the ratio of the settlement risk value of the first area to the settlement risk value of the second area.

[0015] Preferably, calculate the comprehensive settlement risk values of multiple local monitoring areas respectively, and optimize the construction plan of the target construction section based on the comprehensive settlement risk values, including: Calculate the comprehensive settlement risk value of the local monitoring area according to the following formula:

[0016] In the formula, represents the comprehensive settlement risk value of the local monitoring area, represents the coverage area parameter of the monitoring site in the local monitoring area; After calculating the comprehensive settlement risk value of each local monitoring area in the above manner, determine multiple construction abnormal areas according to the preset risk threshold, determine multiple risk sites in the construction abnormal areas according to the settlement risk value of each monitoring site, and optimize and adjust the construction plan of the construction abnormal areas according to the multiple risk sites.

[0017] Preferably, calculate the cumulative pressure parameter and the cumulative settlement parameter of each monitoring site according to the local subgrade settlement monitoring data, including: Determine the time interval between any two adjacent time steps in the local subgrade settlement monitoring data of the monitoring site. After multiplying the instantaneous pressure values at each time step based on the time interval, accumulate the multiple instantaneous pressure values at each time step to obtain the cumulative pressure parameter of the monitoring site; Calculate the absolute value of the difference between the instantaneous displacement values corresponding to any two adjacent time steps in the local subgrade settlement monitoring data, and accumulate multiple absolute values to obtain the cumulative settlement parameter of the monitoring site.

[0018] The present invention has the following beneficial effects: 1. Based on multiple groups of local subgrade settlement monitoring data collected from the target construction section, the present invention constructs dynamic characteristic fields of different settlement monitoring indicators to extract differential features and gradient features, analyzes the spatio-temporal distribution of the dynamic features to reflect the dynamic changes and spatial distribution laws of subgrade settlement, divides multiple local monitoring areas according to the similarity of settlement characteristics, calculates the cumulative pressure parameter and cumulative settlement parameter of each local monitoring area, calculates the settlement risk values of different areas by combining the soil sensitivity and construction response of different areas, and models the propagation law of settlement risk between areas with different soil characteristics by introducing a propagation coefficient and combining the soil characteristics and risk value ratios between monitoring points, and updates the risk values of different areas in real time, which can reflect the risk changes in local areas during the construction process in real time and provide more accurate settlement risk analysis results for construction optimization.

[0019] 2. The present invention combines the risk values of monitoring points, the regional characteristic weights and the coverage area parameters to calculate the comprehensive risk value of the area, globally quantifies the overall risk level of the area, and combines the risk update and comprehensive evaluation of real-time data. This precise data analysis method based on the dynamic changes and propagation differences of regional soil characteristics improves the identification accuracy of high-risk areas, facilitates the construction team to dynamically adjust the construction plan based on the risk values, and provides guarantee for the quality and safety of the construction process. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic flow chart of the real-time monitoring method for highway construction project supervision and construction based on big data provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0022] Please refer to Figure 1 , the real-time monitoring method for highway construction project supervision and construction based on big data provided by an embodiment of the present invention specifically includes the following steps: Step S1: Collect local subgrade settlement monitoring data of multiple monitoring sites in the target construction section, and the local subgrade settlement monitoring data includes time series data corresponding to multiple settlement monitoring indicators.

[0023] Specifically, through a distributed sensor network, sensors can be arranged at multiple monitoring points on the target construction section to form a multi-point and multi-dimensional data acquisition environment, so as to collect multi-dimensional monitoring data related to subgrade settlement in real time, such as pressure, displacement, vibration intensity, etc. For example, settlement monitoring indicators such as pressure, displacement, and construction vibration intensity are collected through pressure sensors, displacement sensors, vibration sensors, etc. Each monitoring sensor collects multi-dimensional time-series data at specific time intervals, so as to obtain local subgrade settlement monitoring data for each monitoring site. The collected data can be preliminarily processed, including denoising, outlier detection, interpolation and complementation, etc., to ensure the integrity and reliability of the monitoring data, so as to obtain a multi-source, dynamic and rich-feature information construction monitoring data set and store it, providing relevant data support for subsequent subgrade settlement monitoring analysis.

[0024] Step S2: Generate a settlement monitoring time-series matrix for each monitoring site based on the local subgrade settlement monitoring data, and perform three-dimensional space mapping on multiple settlement monitoring time-series matrices based on the physical positions of the monitoring sites to construct dynamic feature fields corresponding to multiple settlement monitoring indicators.

[0025] Specifically, the time-series data collected at each monitoring site is constructed to obtain the corresponding settlement monitoring time-series matrix, which is used to indicate the changes of multiple settlement monitoring indicators at the monitoring site over time. According to the physical position of each monitoring site, such as specific coordinate information, the time-series matrix is mapped into a three-dimensional space, including three dimensions: space, time, and data. Among them, the space dimension contains the physical coordinates of the monitoring site, the time dimension contains the time axis of the time-series matrix, and the data dimension contains multiple monitoring indicators such as pressure and displacement, forming a dynamic feature field corresponding to each settlement monitoring indicator, such as pressure and displacement corresponding to the pressure feature field, settlement feature field, etc.

[0026] Step S3: Extract the differential features and gradient features of each settlement monitoring indicator in the dynamic feature field, and construct a settlement feature vector for each monitoring site regarding multiple settlement monitoring indicators according to the differential features and gradient features.

[0027] Specifically, for each dynamic feature field, calculate the differential features of the corresponding settlement monitoring indicator in the time dimension, that is, the difference between the corresponding eigenvalue at adjacent time steps, to reflect the dynamic change trend of the data. Calculate the gradient features of each monitoring indicator in the space dimension to reflect the change law of the monitoring data in space. According to the extracted differential features and gradient features regarding each settlement monitoring indicator, construct a settlement feature vector for each monitoring site regarding multiple settlement monitoring indicators. The settlement feature vector contains multi-dimensional dynamic feature information and can be used for regional division of the construction section.

[0028] Step S4: Divide the target construction section into multiple local monitoring areas according to the settlement feature vectors, and calculate the settlement risk values of each local monitoring area under the initial state based on the local subgrade settlement monitoring data.

[0029] Specifically, based on the settlement feature vectors of the monitoring points, the target construction section is divided into areas through clustering algorithms such as the K-means clustering algorithm, DBSCAN algorithm, etc. The monitoring points with similar settlement feature variation rules are divided into one local monitoring area, thus generating multiple local areas. The process of data clustering based on feature vectors is a well-known technical means to those skilled in the art, and it is not specifically limited in this embodiment.

[0030] After dividing the target construction section into multiple local monitoring areas, each local monitoring area contains multiple monitoring points. According to the local subgrade settlement monitoring data of each monitoring point, the subgrade settlement state within the area corresponding to each monitoring point is analyzed, and the settlement risk value of each local monitoring area under the initial state is calculated.

[0031] Step S5: Determine the settlement risk propagation coefficient of each local monitoring area, and update the settlement risk value of each local monitoring area based on the settlement risk propagation coefficient and the real-time settlement monitoring data of multiple monitoring points in the target construction section.

[0032] Specifically, according to the collected local subgrade settlement monitoring data and the data related to the soil properties within the area corresponding to the monitoring points, the settlement risk propagation coefficient of each local monitoring area is comprehensively determined to characterize the propagation and variation law of the settlement within the area. Based on the determined settlement risk propagation coefficient, the real-time settlement monitoring data of the monitoring points is analyzed to update the settlement risk value of the local monitoring area and obtain the new settlement risk value corresponding to the real-time data.

[0033] Step S6: After each update of the settlement risk value of the local monitoring area, calculate the comprehensive settlement risk values of multiple local monitoring areas respectively, and optimize the construction plan of the target construction section based on the comprehensive settlement risk values.

[0034] Specifically, after each risk value update, calculate the comprehensive risk value of each local monitoring area and use it as an important indicator to measure the overall risk level of the area. Based on the results of the comprehensive risk value, appropriate construction optimization strategies can be adopted for different areas. For example, for high-risk areas, the vibration frequency of construction equipment can be reduced and the load can be lowered. For low-risk areas, construction efficiency can be increased and resource allocation can be optimized, etc. The calculation of the comprehensive risk value makes construction optimization more targeted and enables the formulation of personalized construction strategies for different areas. This risk update combined with real-time data realizes the dynamic adjustment of the construction plan, which can better improve construction safety and efficiency. The hierarchical management of high- and low-risk areas can optimize resource scheduling and avoid unnecessary waste.

[0035] As one of the implementation processes, in step S4, in order to quantify the settlement risk of each local monitoring area of the target construction section in the initial state, it is necessary to calculate the risk value based on the monitoring data. Specifically, calculate the settlement risk value of each local monitoring area in the initial state according to the local monitoring data of subgrade settlement, and adopt the following method: Calculate the cumulative pressure parameter and the cumulative settlement parameter of each monitoring point according to the local monitoring data of subgrade settlement, and determine the regional characteristic weight of each local monitoring area according to the cumulative pressure parameter and the cumulative settlement parameter.

[0036] Specifically, the cumulative pressure parameter is used to represent the magnitude of the pressure accumulated by the monitoring point due to the application of external loads and can reflect the stress state of the soil. The cumulative settlement parameter is used to represent the cumulative settlement amount of the monitoring point during the construction process and can reflect the compression degree of the subgrade.

[0037] Among them, for the cumulative pressure parameter, determine the time interval between any two adjacent time steps in the local monitoring data of subgrade settlement of the monitoring point. After multiplying the instantaneous pressure values at each time step based on the time interval, accumulate the multiple instantaneous pressure values at each time step to obtain the cumulative pressure parameter of the monitoring point, which reflects the pressure accumulation amount during the entire monitoring period. For the cumulative settlement parameter, calculate the absolute value of the difference between the instantaneous displacement values corresponding to any two adjacent time steps in the local monitoring data of subgrade settlement to prevent the error influence of the settlement change direction (such as rising or falling) on the cumulative settlement amount. After accumulating multiple absolute values, obtain the cumulative settlement parameter of the monitoring point, which reflects the subgrade settlement accumulation during the entire monitoring period. By cumulatively calculating the cumulative pressure parameter and the cumulative settlement parameter based on the data of the monitoring point at different time points, it is ensured that the comprehensive settlement response characteristics of each monitoring point can be characterized.

[0038] Meanwhile, based on the actually monitored data, the soil properties of the local monitoring area are characterized, and the regional property weights of the local monitoring area are calculated to describe the risk sensitivity of soil properties in different regions. For the regional property weights of the local monitoring area, they are calculated using the following formula:

[0039] In the formula, represents the regional property weight of the local monitoring area, and respectively represent the average pressure value and the average settlement value of multiple monitoring sites in the local monitoring area, and respectively represent the average pressure gradient and the average settlement gradient of multiple monitoring sites in the local monitoring area. Specifically, when the cumulative pressure and settlement in the area are large while the gradient distribution is small, which means a uniform distribution, the weight value is high, indicating that this area is more sensitive to construction loads. When the gradient is large, which means a non-uniform distribution, the weight value will be lower, indicating that this area is relatively stable.

[0040] After calculating the above-mentioned multiple parameters, the settlement risk value of each local monitoring area in the initial state is calculated according to the regional property function. Specifically:

[0041] In the formula, represents the settlement risk value of the local monitoring area in the initial state, is the regional property function, represents the cumulative pressure parameter of the monitoring site in the local monitoring area, represents the cumulative settlement parameter of the monitoring site in the local monitoring area, represents the regional property weight of the local monitoring area.

[0042] In this process, the role of the regional property function is to combine the previously obtained regional property weights and monitoring data of different regions to ensure that the calculation of the settlement risk value can reflect the soil sensitivity and construction response within the region. In this process, combined with the soil properties of the local monitoring area, different methods are used to jointly analyze and calculate the regional property weights and monitoring data to obtain the corresponding settlement risk.

[0043] Specifically, if the soil property of the local monitoring area belongs to hard soil, then the regional property function is:

[0044] If the soil property of the local monitoring area belongs to soft soil, then the regional property function is:

[0045] It should be noted that for the soil characteristics in different regions, the physical parameters of the soil can be obtained through on-site experimental tests and regional geological surveys, and then the soil characteristics can be divided based on the physical parameters combined with professional knowledge. For example, the compression modulus of the soil is measured to reflect the deformation resistance of the soil, the void ratio is measured to represent the proportion of voids in the soil, the liquidity index is used to measure the consolidation state of the soil, and the soil characteristics are divided based on multiple physical parameters. For example, soils with a small compression modulus, a large void ratio and a large liquidity index can be classified as soft soils, while soils with a large compression modulus, a small void ratio and a small liquidity index can be classified as hard soils. In this case, the characteristics of hard soil are slow settlement but limited local bearing capacity, and cumulative settlement is likely to cause stress concentration. The regional risk mainly depends on the combined effect of pressure and settlement. The higher the pressure, the greater the settlement, and the higher the risk. Therefore, the regional characteristic function emphasizes the contribution of cumulative pressure to risk and reflects the risk level of the hard soil area through the ratio of pressure to settlement. The characteristics of soft soil are sensitive to pressure changes and have relatively fast cumulative settlement. The regional risk mainly depends on the contribution of cumulative pressure to displacement. The smaller the pressure value required for unit settlement, the higher the risk. Therefore, the regional characteristic function emphasizes the combined action of cumulative pressure and cumulative settlement. The soft soil area is highly sensitive to both. In the soft soil area, the risk increases significantly with the increase of pressure and settlement.

[0046] By distinguishing the regional characteristic functions of soft soil and hard soil in soil characteristics, the settlement risk value can be calculated for different soil property regions, ensuring more accurate risk assessment. The introduction of regional characteristic weights enables the risk value to directly reflect the soil sensitivity and pressure distribution characteristics of the region, enhancing the adaptability of the model. This way of comprehensively considering cumulative pressure, settlement and gradient characteristics to quantify the risk value can better conform to the dynamic response in the actual construction environment and achieve more refined construction safety management.

[0047] As one of the implementation processes, in step S5, in order to reflect the dynamic settlement risk propagation law within the local monitoring area and between adjacent areas, it is necessary to update the settlement risk value of each local monitoring area according to the real-time monitoring data and the settlement risk propagation coefficient. Specifically, based on the settlement risk propagation coefficient and the real-time settlement monitoring data of multiple monitoring points in the target construction section, the settlement risk value of each local monitoring area is updated, specifically including: The settlement risk value of the local monitoring area is updated using the following formula:

[0048] In the formula, and are respectively At a moment and the settlement risk value of the local monitoring area at the moment, denotes the settlement risk value of the monitoring site in the set of adjacent points of the local monitoring area at the moment ; denotes the settlement risk propagation coefficient of the monitoring site in the set of adjacent points of the local monitoring area, reflecting the influence of the risk of adjacent points on the risk of this point, and denotes the set of adjacent points of the local monitoring area.

[0049] Among them, for the set of adjacent points of the local monitoring area , it is reasonably divided according to the setting of the monitoring site during the actual subgrade settlement monitoring process. For example, when the monitoring sites are in a discrete state, they can be divided based on the center point of the local monitoring area and a preset neighborhood radius, and the monitoring sites within a certain range with the center of the local monitoring area as the reference are divided into the set of adjacent points.

[0050] The risk difference between the adjacent point and the current point in the formula is used to determine the direction and intensity of risk propagation. When the risk value of the adjacent point is higher than that of the current point, it means that the risk will spread to the current point, otherwise it means that the risk value of the current point will decrease, and the weight of the risk value spreading from the adjacent point to the current point is specifically described by the settlement risk propagation coefficient.

[0051] For the settlement risk propagation coefficient , it is determined according to the set of adjacent points of the local monitoring area , where:

[0052] In the formula, denotes the set of monitoring sites of the local monitoring area, denotes the first propagation coefficient, denotes the second propagation coefficient, where if the soil property corresponding to the monitoring site in the set of adjacent points is the same as the soil property of the local monitoring area, the second propagation coefficient takes the value of the first propagation coefficient; if the soil property corresponding to the monitoring site in the set of adjacent points is different from the soil property of the local monitoring area, the second propagation coefficient is determined according to the soil property of the monitoring site in the set of adjacent points and the soil property of the local monitoring area.

[0053] Specifically, for any local monitoring area, when the monitoring site in the set of adjacent points of this local monitoring area belongs to this local monitoring area, the first propagation coefficient The value is the regional characteristic weight of the local monitoring area. When the monitoring site in the middle of the set of adjacent points for this local monitoring area does not belong to this local monitoring area, further analyze the monitoring site to determine the difference between the soil characteristics corresponding to it and the soil characteristics of this local monitoring area, so as to determine the second propagation coefficient.

[0054] In this process, denote the current local monitoring area as the first area, and denote the local monitoring area to which the monitoring site in the middle of the set of adjacent points belongs as the second area. If the soil characteristics of the first area belong to hard soil and the soil characteristics of the second area belong to soft soil, then the second propagation coefficient takes the value of the ratio of the settlement risk value of the second area to the settlement risk value of the first area, that is, the risk propagation coefficient takes the value of the ratio of the risk value of the soft soil area to the risk value of the hard soil area, reflecting the high sensitivity of soft soil to risk. If the soil characteristics of the first area belong to soft soil and the soil characteristics of the second area belong to hard soil, then the second propagation coefficient takes the value of the ratio of the settlement risk value of the first area to the settlement risk value of the second area, that is, the risk propagation coefficient takes the value of the ratio of the risk value of the hard soil area to the risk value of the soft soil area, reflecting the buffering effect of hard soil on risk.

[0055] Through the above method, by combining soil characteristics, regional attributes and risk value distribution, the propagation coefficient can dynamically adapt to the risk diffusion law in complex construction scenarios. At the junction of hard and soft soils, the dynamic adjustment of the risk propagation coefficient effectively simulates the actual impact of different soil characteristics on risk diffusion, dynamically combines the regional risk value ratio to adjust the propagation coefficient, enhances the adaptability of the model to cross-regional risk propagation, and improves the accuracy of risk propagation prediction.

[0056] As one of the implementation processes, in step S6, in order to optimize the construction plan of the target construction section, it is necessary to calculate and analyze based on the comprehensive settlement risk value of the local monitoring area, and identify the construction abnormal area in combination with the risk threshold, and then adjust the construction strategy. Specifically, calculate the comprehensive settlement risk values of multiple local monitoring areas respectively, and optimize the construction plan of the target construction section based on the comprehensive settlement risk value, including: Calculate the comprehensive settlement risk value of the local monitoring area according to the following formula:

[0057] In the formula, represents the comprehensive settlement risk value of the local monitoring area, which is used to quantify the overall risk level of the area, represents the monitoring site in the local monitoring area The coverage area parameter is used to weigh the contributions of different monitoring points to the overall regional risk. After dynamically updating the settlement risk value of the local monitoring area each time, the global quantification of the overall risk level of the local area is performed, and the comprehensive settlement risk value representing the comprehensive settlement risk situation within the area is calculated, which can be directly used to identify high-risk areas and construction abnormal areas.

[0058] After calculating the comprehensive settlement risk value of each local monitoring area in the above manner, multiple construction abnormal areas are determined according to the preset risk threshold. Specifically, if the comprehensive settlement risk value is less than the preset risk threshold, it can be identified as normal settlement status, while for the case where the comprehensive settlement risk value is greater than or equal to the preset risk threshold, it can be marked as a construction abnormal area. For these areas with relatively high settlement risks, multiple risk sites in the construction abnormal areas can be determined according to the settlement risk values of each monitoring site, and then the construction plan for the construction abnormal areas can be optimized and adjusted accordingly. For example, in the area where soft and hard soils meet, the layout of construction equipment can be reasonably adjusted to avoid additional risks caused by excessive concentration of equipment on the soft soil area. According to the dynamic changes of the comprehensive risk value, the construction progress and sequence can be flexibly adjusted. For example, the construction tasks in low-risk areas can be completed first, and the construction in high-risk areas can be postponed, etc.

[0059] Based on multiple groups of local subgrade settlement monitoring data collected from the target construction section, the present invention constructs a dynamic feature field of different settlement monitoring indicators to extract differential features and gradient features, analyzes the spatio-temporal distribution of the dynamic features to reflect the dynamic changes and spatial distribution laws of subgrade settlement, divides multiple local monitoring areas according to the similarity of settlement characteristics, calculates the cumulative pressure parameter and cumulative settlement parameter of each local monitoring area, combines the soil sensitivity and construction response of different areas to calculate the settlement risk values of different areas, introduces a propagation coefficient, combines the soil characteristics and risk value ratio between monitoring points to model the propagation law of settlement risk between areas with different soil characteristics, and updates the risk values of different areas in real time, which can reflect the risk changes in local areas during the construction process in real time, provides a more accurate settlement risk analysis result for construction optimization, combines the monitoring point risk value, regional characteristic weight and coverage area parameter, calculates the comprehensive risk value of the area, globally quantifies the overall risk level of the area, and combines the risk update and comprehensive evaluation of real-time data. This way of precise data analysis based on the dynamic changes and propagation differences of regional soil characteristics improves the identification accuracy of high-risk areas, can dynamically adjust the construction plan based on the risk value, and provides guarantee for the quality and safety of the construction process.

[0060] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The parts not described in detail in this specification belong to the prior art well known to those skilled in the art.

Claims

1. A real-time monitoring method for highway construction project supervision based on big data, characterized in that: include: Collect local monitoring data of roadbed settlement at multiple monitoring points in the target construction section, where the local monitoring data of roadbed settlement includes time series data corresponding to multiple settlement monitoring indicators; Generate a settlement monitoring time series matrix for each monitoring site based on the local monitoring data of roadbed settlement, map multiple settlement monitoring time series matrices into three-dimensional space based on the physical location of the monitoring site, and construct dynamic characteristic fields corresponding to multiple settlement monitoring indicators; The differential features and gradient features of each subsidence monitoring index in the dynamic feature field are extracted, and the subsidence feature vectors of each monitoring site for multiple subsidence monitoring indexes are constructed based on the differential features and gradient features; The target construction section is divided into multiple local monitoring areas according to the settlement characteristic vector, and the settlement risk value of each local monitoring area in the initial state is calculated according to the local monitoring data of the roadbed settlement; Determine the settlement risk propagation coefficient for each local monitoring area, and update the settlement risk value for each local monitoring area based on the settlement risk propagation coefficient and the real-time settlement monitoring data of multiple monitoring points in the target construction section; After the settlement risk value of the local monitoring area is updated each time, the comprehensive settlement risk values ​​of multiple local monitoring areas are calculated respectively, and the construction plan of the target construction section is optimized based on the comprehensive settlement risk values.

2. The real-time monitoring method for highway construction project supervision based on big data according to claim 1 is characterized in that: The settlement risk value of each local monitoring area in the initial state is calculated based on the local monitoring data of roadbed settlement, including: Calculate the cumulative pressure parameter and cumulative settlement parameter of each monitoring site according to the local monitoring data of roadbed settlement, and determine the regional characteristic weight of each local monitoring area according to the cumulative pressure parameter and cumulative settlement parameter; The settlement risk value of each local monitoring area in the initial state is calculated according to the regional characteristic function, where: In the formula, Indicates the settlement risk value of the local monitoring area in the initial state, is the regional characteristic function, Indicates monitoring points in the local monitoring area The cumulative pressure parameter, Indicates monitoring points in the local monitoring area The cumulative sedimentation parameters, Represents the regional characteristic weight of the local monitoring area.

3. The real-time monitoring method for highway construction project supervision based on big data according to claim 2 is characterized in that: For the settlement risk value of the local monitoring area in the initial state, it also includes: For the regional characteristic function , if the soil characteristics of the local monitoring area belong to hard soil, then the regional characteristic function for: If the soil characteristics of the local monitoring area belong to soft soil, the regional characteristic function for: The regional characteristic weight of the local monitoring area is calculated using the following formula: In the formula, represents the regional characteristic weight of the local monitoring area, , They represent the average pressure and average settlement values ​​of multiple monitoring sites in the local monitoring area, respectively. , They respectively represent the mean pressure gradient and the mean sedimentation gradient of multiple monitoring sites in the local monitoring area.

4. The real-time monitoring method for highway construction project supervision based on big data according to claim 3 is characterized in that: Based on the settlement risk propagation coefficient and the real-time settlement monitoring data of multiple monitoring sites in the target construction section, the settlement risk value of each local monitoring area is updated, including: The following formula is used to update the settlement risk value of the local monitoring area: In the formula, , They are Moment and The settlement risk value of the local monitoring area at the moment, express The monitoring point in the neighboring point set of the local monitoring area at the time The subsidence risk value, Represents the monitoring point in the set of neighboring points in the local monitoring area The sedimentation risk propagation coefficient is A set of neighboring points representing a local monitoring area; For the sedimentation risk propagation coefficient , based on the neighboring point set of the local monitoring area Determine, where: In the formula, represents the set of monitoring sites in the local monitoring area, represents the first propagation coefficient, represents the second propagation coefficient, where if the monitoring point in the neighboring point set The corresponding soil characteristics are the same as those of the local monitoring area, then the second propagation coefficient is taken as the first propagation coefficient. If the monitoring point in the neighboring point set is The corresponding soil characteristics are different from those of the local monitoring area. and soil characteristics of the local monitoring area to determine the second propagation coefficient.

5. The real-time monitoring method for highway construction project supervision based on big data according to claim 4 is characterized in that: According to the monitoring point in the neighboring point set and soil characteristics of the local monitoring area to determine the second propagation coefficient, including: The current local monitoring area is recorded as the first area, and the middle monitoring point of the neighboring point set is recorded as The local monitoring area is the second area. If the soil characteristics of the first area are hard soil and the soil characteristics of the second area are soft soil, then the second propagation coefficient is the ratio of the settlement risk value of the second area to the settlement risk value of the first area. If the soil characteristics of the first area are soft soil and the soil characteristics of the second area are hard soil, then the second propagation coefficient is the ratio of the settlement risk value of the first area to the settlement risk value of the second area.

6. The real-time monitoring method for highway construction project supervision based on big data according to claim 5 is characterized in that: Calculate the comprehensive settlement risk values ​​of multiple local monitoring areas respectively, and optimize the construction plan of the target construction section based on the comprehensive settlement risk values, including: The comprehensive settlement risk value of the local monitoring area is calculated according to the following formula: In the formula, Represents the comprehensive risk value of subsidence in the local monitoring area, Indicates monitoring points in the local monitoring area The coverage area parameter; After calculating the comprehensive settlement risk value of each local monitoring area in the above manner, multiple construction abnormality areas are determined according to the preset risk threshold, and multiple risk points in the construction abnormality area are determined according to the settlement risk value of each monitoring point. The construction plan of the construction abnormality area is optimized and adjusted according to the multiple risk points.

7. The real-time monitoring method for highway construction project supervision based on big data according to claim 6 is characterized in that: The cumulative pressure parameters and cumulative settlement parameters of each monitoring site are calculated based on the local monitoring data of roadbed settlement, including: Determine the time interval between any two adjacent time steps in the local monitoring data of the roadbed settlement at the monitoring site, multiply the instantaneous pressure value at each time step based on the time interval, and then accumulate multiple instantaneous pressure values ​​at each time step to obtain the cumulative pressure parameter of the monitoring site; The instantaneous displacement values ​​corresponding to any two adjacent time steps in the local monitoring data of roadbed settlement are calculated, and the absolute value is taken after the difference is obtained. After accumulating multiple absolute values, the cumulative settlement parameters of the monitoring site are obtained.

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