Highway construction engineering supervision construction real-time monitoring method based on big data

Abstract

The application provides a highway construction engineering 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 subgrade settlement local monitoring data of multiple monitoring points in a target construction section, generating a settlement monitoring time sequence matrix of each monitoring point and constructing a dynamic characteristic field corresponding to multiple settlement monitoring indexes respectively; extracting a settlement feature vector of each monitoring point and generating multiple local monitoring areas by regionally dividing the target construction section to calculate a settlement risk value of each local monitoring area in an initial state; determining a settlement risk propagation coefficient of each local monitoring area to update the settlement risk value of each local monitoring area; respectively calculating settlement comprehensive risk values of the multiple local monitoring areas, and optimizing a construction scheme of the target construction section based on the settlement comprehensive risk values.The application realizes the improvement of the identification accuracy of high-risk areas of subgrade settlement.

Description

Technical Field

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

[0002] During highway construction project supervision and construction, real-time monitoring of roadbed settlement is an important means of ensuring construction quality and project safety. Some monitoring solutions rely on sensors to collect data such as pressure and displacement, and analyze and process the monitoring data using pre-set thresholds. This static monitoring method tends to overlook the significant differences in risk sensitivity and settlement response characteristics between soft and hard soil areas, resulting in inaccurate risk predictions. Specifically, during highway construction, roadbed settlement exhibits strong dynamic characteristics, including real-time changes in pressure and displacement and their transmission patterns between regions. If accurate modeling and analysis cannot be conducted in combination with the dynamic changes and propagation differences in regional soil characteristics, the identification of high-risk areas and the control of risk diffusion will be easily affected. 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 based on big data. Starting from the differences in soil properties in different construction sections, the collected roadbed settlement-related monitoring data are analyzed and processed, and the dynamic changes of multiple monitoring indicators in the monitoring data are captured. Accurate data analysis is performed based on the dynamic changes and propagation differences of regional soil properties, thereby improving the identification accuracy of high-risk areas.

[0004] The present invention provides a real-time monitoring method for highway construction project supervision based on big data, including:

[0005] Collect local monitoring data of roadbed settlement at multiple monitoring points in the target construction section. The local monitoring data of roadbed settlement includes time series data corresponding to multiple settlement monitoring indicators.

[0006] 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 to construct dynamic characteristic fields corresponding to multiple settlement monitoring indicators.

[0007] The differential features and gradient features of each settlement monitoring indicator in the dynamic feature field are extracted, and the settlement feature vector of each monitoring site with respect to multiple settlement monitoring indicators is constructed based on the differential features and gradient features;

[0008] The target construction section is divided into multiple local monitoring areas based on the settlement characteristic vector, and the settlement risk value of each local monitoring area under the initial state is calculated based on the local monitoring data of the roadbed settlement;

[0009] 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 real-time settlement monitoring data from multiple monitoring sites in the target construction section;

[0010] After the settlement risk value of a 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.

[0011] Preferably, the settlement risk value of each local monitoring area in the initial state is calculated based on the local monitoring data of the roadbed settlement, including:

[0012] Calculate the cumulative pressure parameter and cumulative settlement parameter of each monitoring site based on the local monitoring data of roadbed settlement, and determine the regional characteristic weight of each local monitoring area based on the cumulative pressure parameter and cumulative settlement parameter;

[0013] The settlement risk value of each local monitoring area in the initial state is calculated based on the regional characteristic function, where:

[0014]

[0015] Where, Indicates the settlement risk value of the local monitoring area in the initial state, is the regional characteristic function, Indicates monitoring sites in the local monitoring area The cumulative pressure parameter, Indicates monitoring sites in the local monitoring area The cumulative sedimentation parameters, Represents the regional characteristic weight of the local monitoring area.

[0016] Preferably, the settlement risk value of the local monitoring area in the initial state further includes:

[0017] For the regional characteristic function If the soil characteristics of the local monitoring area belong to hard soil, then the regional characteristic function for:

[0018]

[0019] If the soil characteristics of the local monitoring area belong to soft soil, the regional characteristic function for:

[0020]

[0021] The regional characteristic weight of the local monitoring area is calculated using the following formula:

[0022]

[0023] Where, represents the regional characteristic weight of the local monitoring area, 、 Respectively represent the average pressure value and average settlement value of multiple monitoring sites in the local monitoring area, 、 They represent the mean pressure gradient and mean sedimentation gradient of multiple monitoring sites in the local monitoring area respectively.

[0024] 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:

[0025] The following formula is used to update the settlement risk value of the local monitoring area:

[0026]

[0027] Where, 、 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 moment The settlement risk value, Represents the monitoring site in the set of neighboring points in the local monitoring area The settlement risk propagation coefficient, represents a set of neighboring points in a local monitoring area;

[0028] For the sedimentation risk propagation coefficient , based on the neighboring point set of the local monitoring area Determine, where:

[0029]

[0030] Where, 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 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.

[0031] Preferably, the monitoring site in the neighboring point set is and the soil characteristics of the local monitoring area to determine the second propagation coefficient, including:

[0032] 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, 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, 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.

[0033] Preferably, 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, including:

[0034] The comprehensive settlement risk value of the local monitoring area is calculated according to the following formula:

[0035]

[0036] Where, Indicates the comprehensive settlement risk value of the local monitoring area, Indicates monitoring sites in the local monitoring area Coverage area parameters;

[0037] After calculating the comprehensive settlement risk value of each local monitoring area using the above method, 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.

[0038] Preferably, the cumulative pressure parameter and the cumulative settlement parameter of each monitoring site are calculated based on the local monitoring data of the roadbed settlement, including:

[0039] 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 accumulate multiple instantaneous pressure values ​​at each time step to obtain the cumulative pressure parameter of the monitoring site;

[0040] 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. The cumulative settlement parameters of the monitoring site are obtained by accumulating multiple absolute values.

[0041] The present invention has the following beneficial effects:

[0042] 1. Based on multiple groups of local monitoring data of roadbed settlement collected from target construction sections, the present invention constructs dynamic characteristic fields of different settlement monitoring indicators to extract differential characteristics and gradient characteristics, and conducts spatiotemporal distribution analysis on the dynamic characteristics to reflect the dynamic changes and spatial distribution laws of roadbed settlement. A plurality of local monitoring areas are obtained according to the similarity of settlement characteristics, and the cumulative pressure parameters and cumulative settlement parameters of each local monitoring area are calculated. The settlement risk values ​​of different areas are calculated in combination with the soil sensitivity and construction response of different areas. By introducing a propagation coefficient and combining the soil characteristics and risk value ratios between monitoring points, a model is constructed to model the propagation law of settlement risk between areas with different soil characteristics. The risk values ​​of different areas are updated in real time, which can reflect the risk changes of local areas during construction in real time, and provide more accurate settlement risk analysis results for construction optimization.

[0043] 2. The present invention combines the risk value of the monitoring point, the regional characteristic weight and the coverage area parameter to calculate the comprehensive risk value of the region, and globally quantifies the overall risk level of the region. Combined with the risk update and comprehensive assessment of real-time data, this method of accurate data analysis based on the dynamic changes and propagation differences of regional soil characteristics improves the accuracy of identifying high-risk areas, facilitates the construction team to dynamically adjust the construction plan based on the risk value, and provides protection for the quality and safety of the construction process. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A flowchart of a method for real-time monitoring of highway construction project supervision based on big data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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 intended to limit the present invention.

[0046] See Figure 1 The embodiment of the present invention provides a real-time monitoring method for highway construction project supervision based on big data, which specifically includes the following steps:

[0047] Step S1: collecting local monitoring data of roadbed settlement at multiple monitoring points in a target construction section. The local monitoring data of roadbed settlement includes time series data corresponding to multiple settlement monitoring indicators.

[0048] Specifically, a distributed sensor network can be used to deploy sensors at multiple monitoring points along the target construction section, creating a multi-point, multi-dimensional data collection environment. This allows for real-time collection of multi-dimensional monitoring data related to subgrade settlement, including pressure, displacement, and vibration intensity. For example, pressure sensors, displacement sensors, and vibration sensors can be used to collect settlement monitoring indicators such as pressure, displacement, and construction vibration intensity. Each monitoring sensor collects multi-dimensional time series data within a specific time interval, thereby obtaining local monitoring data for subgrade settlement at each monitoring location. The collected data can be preliminarily processed, including denoising, outlier detection, and interpolation, to ensure its integrity and reliability. This allows for the generation and storage of a multi-source, dynamic, and feature-rich construction monitoring dataset, providing relevant data support for subsequent subgrade settlement monitoring and analysis.

[0049] Step S2: Generate a settlement monitoring time series matrix for each monitoring site based on the local monitoring data of the roadbed settlement, perform three-dimensional spatial mapping on multiple settlement monitoring time series matrices based on the physical location of the monitoring site, and construct dynamic characteristic fields corresponding to multiple settlement monitoring indicators.

[0050] Specifically, the time series data collected at each monitoring site is constructed to obtain a corresponding settlement monitoring time series matrix, which is used to indicate how multiple settlement monitoring indicators at the monitoring site change over time. According to the physical location of each monitoring site, such as specific coordinate information, the time series matrix is ​​mapped to a three-dimensional space, including three dimensions: space, time, and data. Among them, the spatial 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 characteristic field corresponding to each settlement monitoring indicator, such as pressure and displacement corresponding to pressure characteristic field, settlement characteristic field, etc.

[0051] 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 with respect to multiple settlement monitoring indicators based on the differential features and gradient features.

[0052] Specifically, for each dynamic feature field, the differential features of the corresponding settlement monitoring indicators, that is, the difference between the corresponding feature values ​​in adjacent time steps, are calculated in the time dimension to reflect the dynamic change trend of the data. The gradient features of each monitoring indicator are calculated in the spatial dimension to reflect the spatial change law of the monitoring data. Based on the extracted differential features and gradient features of each settlement monitoring indicator, the settlement feature vector of each monitoring site for multiple settlement monitoring indicators is constructed. The settlement feature vector contains multi-dimensional dynamic feature information, which can be used to divide the construction section into regions.

[0053] Step S4: Divide the target construction section into multiple local monitoring areas according to the settlement characteristic vector, and calculate the settlement risk value of each local monitoring area in the initial state according to the local monitoring data of the roadbed settlement.

[0054] Specifically, based on the settlement feature vectors at the monitoring sites, a clustering algorithm, such as the K-means clustering algorithm or the DBSCAN algorithm, is used to partition the target construction road section. Monitoring sites with similar settlement characteristics are divided into a local monitoring area, thereby generating multiple local areas. The process of data clustering based on feature vectors is a well-known technical method for those skilled in the art and is not specifically limited in this embodiment.

[0055] After dividing the target construction section into multiple local monitoring areas, each local monitoring area contains multiple monitoring sites. Based on the local monitoring data of roadbed settlement at each monitoring site, the roadbed settlement status in the area corresponding to each monitoring site is analyzed, and the settlement risk value of each local monitoring area in the initial state is calculated.

[0056] 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 sites in the target construction section.

[0057] Specifically, based on the collected local monitoring data of roadbed settlement and the soil property-related data in the corresponding area of ​​the monitoring site, the settlement risk propagation coefficient of each local monitoring area is comprehensively determined to characterize the propagation change law of settlement in the area. Based on the determined settlement risk propagation coefficient, the real-time monitoring data of settlement at the monitoring site is analyzed to update the settlement risk value of the local monitoring area and obtain a new settlement risk value corresponding to the real-time data.

[0058] Step S6: 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.

[0059] Specifically, after each risk value update, a comprehensive risk value is calculated for each local monitoring area and used as an important indicator to measure the overall risk level of the region. Based on the results of the comprehensive risk value, appropriate construction optimization strategies can be adopted for different regions. For example, in high-risk areas, the vibration frequency of construction equipment can be reduced, reducing the load. For low-risk areas, construction efficiency can be improved and resource allocation can be optimized. The calculation of comprehensive risk values ​​makes construction optimization more targeted, and personalized construction strategies can be formulated for different regions. This risk update combined with real-time data enables dynamic adjustment of construction plans, which can effectively improve construction safety and efficiency. The hierarchical management of high- and low-risk areas can optimize resource scheduling and avoid unnecessary waste.

[0060] As one implementation process, in step S4, in order to quantify the settlement risk of each local monitoring area in the target construction section in the initial state, it is necessary to calculate the risk value based on the monitoring data. Specifically, the settlement risk value of each local monitoring area in the initial state is calculated based on the local monitoring data of roadbed settlement, using the following method:

[0061] The cumulative pressure parameters and cumulative settlement parameters of each monitoring site are calculated based on the local monitoring data of roadbed settlement, and the regional characteristic weight of each local monitoring area is determined based on the cumulative pressure parameters and cumulative settlement parameters.

[0062] Specifically, the cumulative pressure parameter is used to indicate the magnitude of the pressure accumulated at the monitoring site due to the application of external loads, which can reflect the stress state of the soil. The cumulative settlement parameter is used to indicate the cumulative settlement of the monitoring site during the construction process, which can reflect the degree of compression of the roadbed.

[0063] For the cumulative pressure parameter, the time interval between any two adjacent time steps in the local monitoring data of the subgrade settlement at the monitoring site is determined. The instantaneous pressure value at each time step is multiplied based on the time interval, and the multiple instantaneous pressure values ​​for each time step are accumulated to obtain the cumulative pressure parameter for the monitoring site, reflecting the accumulated pressure over the entire monitoring period. For the cumulative settlement parameter, the instantaneous displacement values ​​corresponding to any two adjacent time steps in the local monitoring data of the subgrade settlement are calculated and the absolute value is taken after the difference is taken to prevent the error influence of the direction of settlement change, such as increase or decrease, on the accumulated settlement. The cumulative settlement parameter for the monitoring site is obtained by accumulating multiple absolute values, reflecting the accumulated subgrade settlement over the entire monitoring period. By accumulating the data of the monitoring site at different time points and calculating the cumulative pressure parameter and cumulative settlement parameter, the comprehensive settlement response characteristics of each monitoring site can be characterized.

[0064] At the same time, based on the actual monitored data, the soil characteristics of the local monitoring area are characterized and the regional characteristic weight of the local monitoring area is calculated to describe the risk sensitivity of soil properties in different areas. The regional characteristic weight of the local monitoring area is calculated using the following formula:

[0065]

[0066] Where, represents the regional characteristic weight of the local monitoring area, 、 Respectively represent the average pressure value and average settlement value of multiple monitoring sites in the local monitoring area, 、 These represent the mean pressure gradient and settlement gradient for multiple monitoring locations within a local monitoring area. Specifically, when the accumulated pressure and settlement within a region are large, but the gradient distribution is small (indicating uniform distribution), the weight is high, indicating that the region is sensitive to construction loads. When the gradient is large (indicating uneven distribution), the weight is lower, indicating that the region is relatively stable.

[0067] After calculating the above parameters, the settlement risk value of each local monitoring area in the initial state is calculated according to the regional characteristic function. Specifically:

[0068]

[0069] Where, Indicates the settlement risk value of the local monitoring area in the initial state, is the regional characteristic function, Indicates monitoring sites in the local monitoring area The cumulative pressure parameter, Indicates monitoring sites in the local monitoring area The cumulative sedimentation parameters, Represents the regional characteristic weight of the local monitoring area.

[0070] In this process, the regional characteristic function The purpose of the metric is to combine previously determined regional characteristic weights and monitoring data from different regions to ensure that the calculated settlement risk value reflects the soil sensitivity and construction response within the region. In this process, the regional characteristic weights and monitoring data are combined in different ways to analyze and calculate the corresponding settlement risk, taking into account the soil properties of the local monitoring area.

[0071] Specifically, if the soil characteristics of the local monitoring area belong to hard soil, the regional characteristic function for:

[0072]

[0073] If the soil characteristics of the local monitoring area belong to soft soil, the regional characteristic function for:

[0074]

[0075] It is worth noting that soil characteristics in different regions can be determined through field testing and regional geological surveys to obtain physical parameters. These physical parameters, combined with specialized knowledge, can then be used to categorize soil characteristics. For example, soil compression modulus can be measured to reflect deformation resistance, void ratio to indicate the proportion of voids in the soil, and liquid index to measure the soil's state of consolidation. Soil characteristics can be categorized based on multiple physical parameters. For example, soil with a low compression modulus, high void ratio, and high liquid index can be classified as soft soil, while soil with a high compression modulus, low void ratio, and low liquid index can be classified as hard soil. In this case, hard soils exhibit slow settlement but limited local bearing capacity. Cumulative settlement can easily lead to stress concentrations. Regional risk primarily depends on the combined effects of pressure and settlement: higher pressures result in greater settlements, and thus, higher risk. Therefore, the regional characteristic function emphasizes the contribution of cumulative pressure to risk, and the ratio of pressure to settlement reflects the risk level of hard soil regions. Soft soils exhibit sensitivity to pressure changes and rapid cumulative settlement. Regional risk primarily depends on the contribution of cumulative pressure to displacement: the lower the pressure required for unit settlement, the higher the risk. Therefore, the regional characteristic function emphasizes the combined effect of cumulative pressure and cumulative settlement. Soft soil areas are highly sensitive to both. In soft soil areas, the risk increases significantly with the increase of pressure and settlement.

[0076] By distinguishing the regional characteristic functions of soft soil and hard soil in soil properties, settlement risk values ​​can be calculated for areas with different soil properties, 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 method of quantifying risk values ​​by comprehensively considering cumulative pressure, settlement and gradient characteristics can better conform to the dynamic response under actual construction environments and achieve more refined construction safety management.

[0077] As one implementation process, in step S5, in order to reflect the dynamic settlement risk propagation pattern within the local monitoring area and between adjacent areas, it is necessary to update the settlement risk value of each local monitoring area based on 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:

[0078] The following formula is used to update the settlement risk value of the local monitoring area:

[0079]

[0080] Where, 、 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 moment The settlement risk value, Represents the monitoring site in the set of neighboring points in the local monitoring area The settlement risk transmission coefficient reflects the impact of the risk of the neighboring point on the risk of the point. Represents a set of neighboring points in the local monitoring area.

[0081] Among them, for the neighboring point set of the local monitoring area , according to the actual setting of monitoring sites in the process of roadbed settlement monitoring, a reasonable division is made. For example, when the division of monitoring sites is discrete, it can be divided based on the center point of the local monitoring area and the pre-set neighborhood radius, and the monitoring sites within a certain range with the center of the local monitoring area as a reference are divided into a set of neighboring points.

[0082] The risk difference between the neighboring point and the current point in the formula determines the direction and intensity of risk propagation. When the risk value of a neighboring point is higher than that of the current point, the risk will spread toward the current point; otherwise, the risk value of the current point will decrease. The sedimentation risk propagation coefficient describes the weight of the risk value propagating from the neighboring point to the current point.

[0083] For the sedimentation risk propagation coefficient , based on the neighboring point set of the local monitoring area Determine, where:

[0084]

[0085] Where, 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 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.

[0086] Specifically, for any local monitoring area, when the local monitoring area is about the central monitoring point of the neighboring point set When it belongs to the local monitoring area, the first propagation coefficient The value is the regional characteristic weight of the local monitoring area. When it does not belong to the local monitoring area, further analysis of the monitoring site The second propagation coefficient is determined by calculating the difference between the corresponding soil characteristics and the soil characteristics of the local monitoring area.

[0087] In this process, the current local monitoring area is recorded as the first area, and the middle monitoring point of the neighboring point set is recorded as If the local monitoring area is the second area, and the soil characteristics of the first area are hard soil and the soil characteristics of the second area are soft soil, 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. In other words, the risk propagation coefficient is 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 are soft soil and the soil characteristics of the second area are hard soil, 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. In other words, the risk propagation coefficient is 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.

[0088] By combining soil characteristics, regional attributes and risk value distribution, the above method enables the propagation coefficient to dynamically adapt to the risk diffusion law in complex construction scenarios. At the junction of soft and hard soils, the dynamic adjustment of the risk propagation coefficient effectively simulates the actual impact of different soil characteristics on risk diffusion. The dynamic adjustment of the propagation coefficient based on the regional risk value ratio enhances the adaptability of the model to cross-regional risk propagation and improves the accuracy of risk propagation prediction.

[0089] As one implementation process, in step S6, in order to optimize the construction plan for the target construction section, it is necessary to calculate and analyze the comprehensive settlement risk value based on the local monitoring area, and identify abnormal construction areas in combination with the risk threshold, and then adjust the construction strategy. Specifically, the comprehensive settlement risk value of multiple local monitoring areas is calculated, and the construction plan for the target construction section is optimized based on the comprehensive settlement risk value, including:

[0090] The comprehensive settlement risk value of the local monitoring area is calculated according to the following formula:

[0091]

[0092] Where, Indicates the comprehensive settlement risk value of the local monitoring area, which is used to quantify the overall risk level of the region. Indicates monitoring sites in the local monitoring area The coverage area parameter is used to weigh the contribution of different monitoring points to the overall regional risk. Each time the settlement risk value of a local monitoring area is dynamically updated, the overall risk level of the local area is globally quantified. A comprehensive settlement risk value is calculated to represent the comprehensive settlement risk situation within the area. This can be directly used to identify high-risk areas and areas with construction anomalies.

[0093] After calculating the comprehensive settlement risk value of each local monitoring area using the above method, multiple construction abnormality 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 a normal settlement state, and if the comprehensive settlement risk value is greater than or equal to the preset risk threshold, it can be marked as a construction abnormality area. For these areas with higher settlement risks, multiple risk sites in the construction abnormality area can be determined based on the settlement risk value of each monitoring site, so as to optimize and adjust the construction plan of the construction abnormality area based on the multiple risk sites. For example, in the area where soft and hard soils meet, the layout of construction equipment can be reasonably adjusted to avoid excessive concentration of equipment in the soft soil area causing additional risks. According to the dynamic changes of the comprehensive risk value, the construction progress and sequence can be flexibly adjusted, such as giving priority to completing construction tasks in low-risk areas and postponing construction in high-risk areas.

[0094] Based on multiple groups of local monitoring data of roadbed settlement collected from target construction sections, the present invention constructs dynamic characteristic fields of different settlement monitoring indicators to extract differential features and gradient features. The dynamic characteristics are analyzed in time and space to reflect the dynamic changes and spatial distribution laws of roadbed settlement. Multiple local monitoring areas are obtained according to the similarity of settlement characteristics. The cumulative pressure parameters and cumulative settlement parameters of each local monitoring area are calculated. The settlement risk values ​​of different areas are calculated by combining the soil sensitivity and construction response of different areas. By introducing the propagation coefficient and combining the soil characteristics and risk value ratios between monitoring points, the settlement risk is analyzed in areas where there are differences in soil characteristics. The propagation law between regions is modeled and the risk values ​​of different regions are updated in real time. This can reflect the risk changes of local areas during the construction process in real time, providing more accurate settlement risk analysis results for construction optimization. The comprehensive risk value of the region is calculated by combining the risk value of the monitoring point, the regional characteristic weight and the coverage area parameter, and the overall risk level of the region is globally quantified. Combined with the risk update and comprehensive evaluation of real-time data, this method of accurate data analysis based on the dynamic changes and propagation differences of regional soil characteristics improves the accuracy of identifying high-risk areas, can dynamically adjust the construction plan based on the risk value, and provide guarantees for the quality and safety of the construction process.

[0095] The foregoing description is merely a detailed description of the present invention, which is intended to enable those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art. Portions not described in detail in this specification are 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. 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 to construct dynamic characteristic fields corresponding to multiple settlement monitoring indicators. The differential features and gradient features of each settlement monitoring indicator in the dynamic feature field are extracted, and the settlement feature vector of each monitoring site with respect to multiple settlement monitoring indicators is constructed based on the differential features and gradient features; The target construction section is divided into multiple local monitoring areas based on the settlement characteristic vector. The settlement risk value of each local monitoring area in the initial state is calculated based on the local monitoring data of the roadbed settlement, including: Calculate the cumulative pressure parameter and cumulative settlement parameter of each monitoring site based on the local monitoring data of roadbed settlement, and determine the regional characteristic weight of each local monitoring area based on the cumulative pressure parameter and cumulative settlement parameter; The settlement risk value of each local monitoring area in the initial state is calculated based on the regional characteristic function, where: Where, Indicates the settlement risk value of the local monitoring area in the initial state, is the regional characteristic function, Indicates monitoring sites in the local monitoring area The cumulative pressure parameter, Indicates monitoring sites in the local monitoring area The cumulative sedimentation parameters, represents the regional characteristic weight of the local monitoring area; 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: Where, represents the regional characteristic weight of the local monitoring area, 、 Respectively represent the average pressure value and average settlement value of multiple monitoring sites in the local monitoring area, 、 They represent the mean pressure gradient and mean sedimentation gradient of multiple monitoring sites in the local monitoring area respectively; 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 real-time settlement monitoring data from multiple monitoring sites in the target construction section; After the settlement risk value of a 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: Based on the settlement risk propagation coefficient and real-time settlement monitoring data from multiple monitoring sites in the target construction section, the settlement risk value for each local monitoring area is updated, including: The following formula is used to update the settlement risk value of the local monitoring area: Where, 、 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 moment The settlement risk value, Represents the monitoring site in the set of neighboring points in the local monitoring area The settlement risk propagation coefficient, represents a set of neighboring points in a local monitoring area; For the sedimentation risk propagation coefficient , based on the neighboring point set of the local monitoring area Determine, where: Where, 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 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.

3. The real-time monitoring method for highway construction project supervision based on big data according to claim 2 is characterized in that: According to the monitoring point of the neighboring point set and the 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, 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, 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.

4. The real-time monitoring method for highway construction project supervision based on big data according to claim 3 is characterized in that: Calculate the comprehensive settlement risk values ​​for 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: Where, Indicates the comprehensive settlement risk value of the local monitoring area, Indicates monitoring sites in the local monitoring area Coverage area parameters; After calculating the comprehensive settlement risk value of each local monitoring area using the above method, 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.

5. The real-time monitoring method for highway construction project supervision based on big data according to claim 4 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 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. The cumulative settlement parameters of the monitoring site are obtained by accumulating multiple absolute values.

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