A rock slope construction risk early warning method and system

Abstract

The present invention discloses a rock slope construction risk early warning method and system, which relates to the field of slope construction early warning technology. The method divides the construction area into at least one sub-monitoring area, obtains the initial risk state of the sub-monitoring area, generates an abnormal coefficient for each sub-monitoring area, dynamically adjusts the coefficient threshold based on the initial risk state of the sub-monitoring area and traffic data, predicts whether the sub-monitoring area will have a safety risk based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and generates a corresponding second management strategy for each sub-monitoring area based on the prediction result. The initial risk state and real-time construction impact are independently evaluated for each sub-monitoring area, and the risk management is refined. After evaluating the risk of the sub-monitoring area, the abnormal coefficient threshold is dynamically adjusted in combination with traffic data to improve the timeliness and accuracy of the early warning, and avoid false alarms or missed alarms caused by too low or too high fixed thresholds.

Description

Technical Field

[0001] The invention relates to the technical field of slope construction early warning, and in particular to a rock slope construction risk early warning method and system. Background Art

[0002] The background of rock slope construction risk warning is usually related to large-scale infrastructure projects such as mountain road construction, mining, and water conservancy projects. These projects involve the excavation, reinforcement, and protection of rock slopes. Due to the complex geological conditions and uncertain stability of rock slopes, there are great risks in the construction process. Therefore, it is very important to establish an effective rock slope construction risk warning system.

[0003] The prior art has the following deficiencies:

[0004] 1. Traditional risk warning systems usually provide unified warnings for the entire construction area, lacking differentiated management of different areas. This approach cannot fully reflect the risk differences caused by different geological conditions and construction progress in the construction area, resulting in the warning coverage being too large or too vague, and unable to accurately locate high-risk areas;

[0005] 2. Risk warning systems usually issue warnings based on fixed thresholds or static models, and are unable to respond in real time to new changes and new risks that arise during the construction process, resulting in poor warning timeliness or a high false alarm rate.

[0006] Based on this, the present invention proposes a rock slope construction risk early warning method and system, which divides the construction area into multiple sub-monitoring areas, independently evaluates the initial risk status and real-time construction impact for each sub-monitoring area, refines the risk management, and after evaluating the risks of the sub-monitoring areas, dynamically adjusts the anomaly coefficient threshold in combination with traffic data to improve the timeliness and accuracy of the early warning and avoid false alarms or missed alarms caused by fixed thresholds that are too low or too high. Summary of the invention

[0007] The purpose of the present invention is to provide a rock slope construction risk early warning method and system to solve the shortcomings of the background technology.

[0008] In order to achieve the above object, the present invention provides the following technical solution: a rock slope construction risk early warning method, the early warning method comprising the following steps:

[0009] Before construction begins, information about the construction area is obtained, the construction area is divided into at least one sub-monitoring area, an initial risk state of the sub-monitoring area is obtained some time before construction begins, and a corresponding first management strategy is generated for each sub-monitoring area according to the initial risk state;

[0010] During the construction process, after obtaining real-time construction impact data, anomaly coefficients are generated for each sub-monitoring area;

[0011] After dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data, it is predicted whether there will be safety risks in the sub-monitoring area based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and a corresponding second management strategy is generated for each sub-monitoring area based on the prediction result.

[0012] In a preferred embodiment, obtaining the initial risk status of the sub-monitoring area some time before the start of construction includes the following steps:

[0013] Some time before the start of construction, the shear strength and porosity of the sub-monitoring area are obtained, and the shear strength and porosity are normalized so that the value range of the shear strength and porosity is mapped to [0,1], and the normalized shear strength value and the normalized porosity value are obtained. The risk coefficient is subtracted from the normalized shear strength value from the normalized porosity value to obtain the risk coefficient. The obtained risk coefficient is compared with the preset risk threshold. The risk threshold is used to determine whether there is a construction risk in the sub-monitoring area. If the risk coefficient is less than or equal to the risk threshold, it is determined that there is no construction risk in the sub-monitoring area. If the risk coefficient is greater than the risk threshold, it is determined that there is a construction risk in the sub-monitoring area.

[0014] In a preferred embodiment, during the construction process, after obtaining real-time construction impact data, an abnormality coefficient is generated for each sub-monitoring area, including the following steps:

[0015] Based on the historical database of the rock slope construction area, all multi-source data that have an impact on construction safety are obtained. The multi-source data includes major impact data and minor impact data. All major impact data are set as gather, The main influencing data in the set are expressed as , n is The number of major influencing data in the set is used to calculate the abnormal coefficient using the Logistic regression analysis method. The expression is: , where is the abnormal coefficient, is a constant term with a value of 1.526, which indicates the influence of the secondary influencing data on the abnormal coefficient when the primary influencing data does not exist. is a variable, is the regression coefficient of each variable. The value of the regression coefficient is set according to the impact of the main influencing data on construction safety. When the main influencing data leads to an increase in construction safety risk, the regression coefficient is greater than 0. When the main influencing data leads to a decrease in construction safety risk, the regression coefficient is less than 0.

[0016] In a preferred embodiment, the main influencing data include: rock displacement rate, crack expansion rate, slope inclination angle growth rate, local stress inside the rock mass, groundwater level rise rate, and accumulated rainfall;

[0017] The secondary impact data include: the rate of increase of air humidity.

[0018] In a preferred embodiment, dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data includes the following steps:

[0019] Obtain traffic data of the sub-monitoring area, including the number of traffic road radiation and vehicle flow;

[0020] The risk coefficient of the sub-monitoring area, the number of traffic road radiation and the traffic flow are comprehensively calculated to obtain the correction index, which is expressed as: , where To correct the index, is the risk factor, For traffic data, , are the adjustment coefficients of risk factor and traffic data respectively, and , are greater than 0, , It is the normalized value of traffic road radiation quantity and the normalized value of traffic flow;

[0021] The obtained correction index is compared with the preset correction threshold. The correction threshold is used to determine whether the coefficient threshold needs to be adjusted. If the correction index is less than or equal to the correction threshold, it is determined that the coefficient threshold does not need to be adjusted. If the correction index is greater than the correction threshold, it is determined that the coefficient threshold needs to be adjusted. The expression is: , where is the coefficient threshold after dynamic adjustment, To dynamically adjust the front coefficient threshold, To correct the index.

[0022] In a preferred embodiment, predicting whether a safety risk will occur in a sub-monitoring area based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold includes the following steps:

[0023] After obtaining the abnormal coefficient and the dynamically adjusted coefficient threshold of each sub-monitoring area, the abnormal coefficient is compared with the dynamically adjusted coefficient threshold. The dynamically adjusted coefficient threshold is used to predict whether there is a construction safety risk in the sub-monitoring area. If the abnormal coefficient is less than or equal to the dynamically adjusted coefficient threshold, it is predicted that there is no construction safety risk in the sub-monitoring area. If the abnormal coefficient is greater than the dynamically adjusted coefficient threshold, it is predicted that there is a construction safety risk in the sub-monitoring area.

[0024] In a preferred embodiment, the logic for obtaining the number of traffic road radiations is as follows: taking the sub-monitoring area as the center and R as the radius, the influence radiation area of ​​the sub-monitoring area is calculated, and all traffic roads passing through the influence radiation area are summed up to obtain the number of traffic road radiations;

[0025] The logic for obtaining the traffic flow is: obtaining the number of vehicles passing through all traffic roads affected by the sub-monitoring area within a monitoring period, and obtaining the traffic flow through comprehensive calculation, the expression is:

[0026] , where For traffic flow, To monitor the duration, is the number of traffic roads affected by the sub-monitoring area, Indicates Traffic roads under monitoring time The number of vehicles passing through.

[0027] A rock slope construction risk early warning system, comprising a regional division module, a foundation assessment module, and a risk prediction module;

[0028] Area division module: obtain construction area information before construction begins and divide the construction area into at least one sub-monitoring area;

[0029] Basic assessment module: before the start of construction, the initial risk status of the sub-monitoring area is obtained, and the corresponding first management strategy is generated for each sub-monitoring area according to the initial risk status;

[0030] Risk prediction module: During the construction process, after obtaining real-time construction impact data, an abnormal coefficient is generated for each sub-monitoring area. After dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data, it is predicted whether there will be safety risks in the sub-monitoring area based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and a corresponding second management strategy is generated for each sub-monitoring area based on the prediction result.

[0031] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0032] The present invention divides the construction area into at least one sub-monitoring area, obtains the initial risk state of the sub-monitoring area, generates a corresponding first management strategy for each sub-monitoring area based on the initial risk state, obtains real-time construction impact data, generates an abnormal coefficient for each sub-monitoring area, dynamically adjusts the coefficient threshold based on the initial risk state of the sub-monitoring area and traffic data, predicts whether a safety risk will occur in the sub-monitoring area based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and generates a corresponding second management strategy for each sub-monitoring area based on the prediction result. The construction area is divided into multiple sub-monitoring areas, and the initial risk state and real-time construction impact are independently evaluated for each sub-monitoring area, which refines the risk management, and after evaluating the risk of the sub-monitoring area, the abnormal coefficient threshold is dynamically adjusted in combination with the traffic data, thereby improving the timeliness and accuracy of the early warning and avoiding false alarms or missed alarms caused by too low or too high fixed thresholds. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0034] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Example 1: Please refer to Figure 1 As shown, this embodiment provides a rock slope construction risk early warning method, the early warning method comprises the following steps:

[0037] Before construction begins, construction area information is obtained, including road information near the construction area and basic slope information, etc. The construction area is divided into at least one sub-monitoring area. The larger the construction area, the more sub-monitoring areas are divided. Some time before construction begins, the initial risk status of the sub-monitoring area is obtained, and a corresponding first management strategy (including slope reinforcement or no management) is generated for each sub-monitoring area based on the initial risk status. During the construction process, after obtaining real-time construction impact data, an abnormal coefficient is generated for each sub-monitoring area. The larger the abnormal coefficient, the more likely it is that the sub-monitoring area will have a safety risk. After dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data, it is predicted whether the sub-monitoring area will have a safety risk based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and a corresponding second management strategy (including advance traffic control and advance road protection, etc.) is generated for each sub-monitoring area based on the prediction result.

[0038] This application divides the construction area into at least one sub-monitoring area, obtains the initial risk status of the sub-monitoring area, and generates a corresponding first management strategy for each sub-monitoring area based on the initial risk status. After obtaining real-time construction impact data, an abnormal coefficient is generated for each sub-monitoring area. After dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data, it predicts whether there will be safety risks in the sub-monitoring area based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and generates a corresponding second management strategy for each sub-monitoring area based on the prediction result. The construction area is divided into multiple sub-monitoring areas, and the initial risk status and real-time construction impact are independently evaluated for each sub-monitoring area, which refines the risk management. After evaluating the risks of the sub-monitoring areas, the abnormal coefficient threshold is dynamically adjusted in combination with traffic data to improve the timeliness and accuracy of the early warning and avoid false alarms or missed alarms caused by too low or too high fixed thresholds.

[0039] Embodiment 2: Before construction begins, obtain construction area information, including road information near the construction area and slope foundation information, etc., divide the construction area into at least one sub-monitoring area. The larger the construction area, the more sub-monitoring areas are divided, including the following steps:

[0040] The construction area is divided into several sub-monitoring areas according to the geological conditions, construction plan and road distribution of the construction area. The division criteria of sub-monitoring areas may include:

[0041] Topographic features: Different slope areas are divided according to slope gradient, slope direction and surface morphology.

[0042] Geological characteristics: Areas with different geological characteristics are divided according to the different composition of rock strata.

[0043] Construction impact scope: According to the impact scope of construction activities (such as blasting, excavation, etc.), the area affected by construction disturbance is divided.

[0044] Road impact: Areas close to traffic arteries or other important facilities will be designated as key monitoring areas to ensure that slope activities have minimal impact on traffic and surrounding facilities.

[0045] The larger the construction area, the more sub-monitoring areas it will be divided into. The size of each sub-monitoring area can be adjusted based on geological complexity, construction risk level, and monitoring equipment layout.

[0046] Some time before construction begins, obtain the initial risk status of the sub-monitoring area, including the following steps:

[0047] Some time before the start of construction, the shear strength and porosity of the sub-monitoring area are obtained, and the shear strength and porosity are normalized so that the value range of shear strength and porosity is mapped to [0,1], and the normalized shear strength value and the normalized porosity value are obtained. The normalized porosity value minus the normalized shear strength value is subtracted to obtain the risk coefficient. The larger the risk coefficient, the greater the construction risk of the sub-monitoring area. The obtained risk coefficient is compared with the preset risk threshold. The risk threshold is used to determine whether there is a construction risk in the sub-monitoring area. If the risk coefficient is less than or equal to the risk threshold, it is determined that there is no construction risk in the sub-monitoring area. If the risk coefficient is greater than the risk threshold, it is determined that there is a construction risk in the sub-monitoring area.

[0048] The calculation expression of shear strength is: , where is the shear strength, To monitor the cohesion of the soil in the sub-area, is the normal stress in the sub-monitoring area, , where is the force acting on the soil surface, represents the surface area on which the force acts, The friction angle is the friction angle between the particles inside the soil. The shear strength of the rock or soil is a key parameter for evaluating slope stability. The lower the shear strength, the more likely the slope will slide and fail.

[0049] The calculation expression of porosity is: , where is the porosity, is the pore volume, i.e. the volume of the voids in the rock or soil mass. It is the total volume of rock or soil. The porosity of rock or soil affects its bearing capacity and stability. The greater the porosity, the greater the risk of instability.

[0050] Generate a corresponding first management strategy (including slope reinforcement or no management) for each sub-monitoring area based on the initial risk status, including the following steps:

[0051] If it is determined that there is no construction risk in the sub-monitoring area, the following management strategies are usually adopted:

[0052] Regular monitoring: Although there is no risk at present, the sub-monitoring area still needs to be monitored regularly to prevent disturbances during subsequent construction or external factors (such as weather changes) from increasing risks. Real-time data collection can be carried out by deploying sensors (such as crack monitors, inclinometers, settlement meters, etc.).

[0053] Maintain the original state: Do not make any intervention or reinforcement on the slope, maintain its existing state.

[0054] Environmental protection measures: Even if there is no direct construction risk, it is still necessary to consider reducing interference with the surrounding environment, especially in terms of vegetation protection and surface soil protection.

[0055] Daily inspection and maintenance: Send personnel to conduct on-site inspections to confirm environmental changes in the area and normal operation of equipment. Increase the inspection frequency, especially when it rains or construction interference is large.

[0056] If it is determined that there is a construction risk in the sub-monitoring area, the following management strategies are usually adopted:

[0057] Anchoring method: Use anchor rods or anchor cables to reinforce the slope. By inserting the anchor rods into the stable rock layer inside the slope, additional shear strength is provided, thereby improving the overall stability of the slope.

[0058] Shotcrete: Cover the slope surface with shotcrete to enhance the slope's weathering resistance and shear strength and prevent the loose rock and soil on the surface from sliding.

[0059] Retaining walls: Retaining walls are built in areas where landslides or soil sliding may occur to increase the slope's resistance to sliding while protecting roads or other infrastructure below the slope.

[0060] Drainage measures: The accumulation of water inside the slope is one of the main causes of landslides. Measures such as building drainage ditches, seepage pipes, and underground drainage systems can be taken to lower the groundwater level and reduce pore water pressure.

[0061] Reduce construction disturbance: In high-risk areas, avoid large-scale excavation, blasting or other high-intensity construction operations that disturb the slope structure. You can choose a more gentle construction process, such as phased and small-scale operations, to reduce disturbance to the slope.

[0062] Adjustment of construction period: Based on weather forecast and geological monitoring results, avoid periods of rainfall, strong winds, etc. that may aggravate slope instability, and choose to carry out construction under relatively stable weather conditions.

[0063] Deployment of monitoring equipment: In sub-monitoring areas where there are construction risks, more intensive monitoring equipment needs to be deployed, such as surface displacement monitors, slope radars, strain sensors, etc., to conduct real-time monitoring of slope deformation, displacement, crack expansion, etc.

[0064] Automatic early warning system: Once the monitoring data shows abnormalities, such as crack expansion, accelerated displacement, and tilt angle exceeding the safety threshold, the system automatically triggers an early warning and immediately notifies relevant management personnel to take emergency measures.

[0065] Pre-planned emergency response plan: In order to deal with sudden slope instability incidents, an emergency response plan must be formulated in advance, including measures such as personnel evacuation, construction suspension, and traffic control.

[0066] Protective nets and rock retaining nets: Protective nets or rock retaining nets are laid above or below the slope to prevent small landslides or falling rocks from threatening construction workers, equipment and the road below.

[0067] Temporary support structures: During the construction process, temporary support structures (such as steel supports and wooden piles) can be used to stabilize the slopes and prevent them from sliding or collapsing due to construction disturbances.

[0068] During the construction process, after obtaining real-time construction impact data, an abnormal coefficient is generated for each sub-monitoring area. The larger the abnormal coefficient, the more likely it is that the sub-monitoring area will have safety risks. The following steps are included:

[0069] Based on the historical database of the rock slope construction area, all multi-source data that have an impact on construction safety are obtained. The multi-source data includes major impact data and minor impact data. All major impact data are set as gather, The main influencing data in the set are expressed as , n is The number of major influencing data in the set is used to calculate the abnormal coefficient using the Logistic regression analysis method. The expression is: , where is the abnormal coefficient, is a constant term with a value of 1.526, which indicates the influence of the secondary influencing data on the abnormal coefficient when the primary influencing data does not exist. are variables (each main effect data), is the regression coefficient of each variable;

[0070] In this embodiment, the value of the regression coefficient is set according to the impact of the main influencing data on construction safety (such as increasing the construction safety risk or reducing the construction safety risk). When the main influencing data causes the construction safety risk to increase, the regression coefficient is greater than 0. When the main influencing data causes the construction safety risk to decrease, the regression coefficient is less than 0. Specifically:

[0071] Regression coefficient is greater than 0: When the main influencing data leads to an increase in construction safety risk, the regression coefficient is positive, which means that there is a positive correlation between the increase in the independent variable and the increase in the dependent variable, that is, as the main influencing data increases, the construction safety risk also increases accordingly;

[0072] Regression coefficient is less than 0: When the main influencing data leads to a decrease in construction safety risk, the regression coefficient is negative, which means that there is a negative correlation between the increase in the independent variable and the decrease in the dependent variable, that is, as the main influencing data increases, the construction safety risk also decreases accordingly;

[0073] For example, the present invention is used for early warning of rock slope construction risks. When the displacement of the rock slope construction area increases during the construction process, the risk of slope instability will increase, and the regression coefficient is greater than 0 at this time;

[0074] When the rock slope construction area is under construction, the longer the cumulative time of no change in soil cracks (that is, the soil cracks initially monitored do not increase during the construction process), the lower the risk of slope instability, and the regression coefficient is less than 0;

[0075] 1) During the construction process in the rock slope construction area, the main influencing data generally include:

[0076] Rock displacement rate: If the displacement rate continues to increase, especially close to a certain threshold, it may indicate that the slope has entered a critical state and the risk of instability has greatly increased;

[0077] Crack expansion rate: The expansion of cracks is a sign of rock stress concentration or structural instability. The increase of cracks (especially sudden expansion) indicates that the rock may be about to become unstable. In this application, the detected soil cracks are monitored in real time, and the cumulative time of no change in cracks during the construction process is obtained (the no change in cracks in this application only means that the cracks do not increase, and does not include changes in the size of cracks). The longer the cumulative time of no change in cracks, the less impact the construction team has on the soil layer, and therefore the lower the construction risk;

[0078] Slope inclination rate: Changes in the slope's inclination usually mean that the slope is deforming or sliding. Monitoring changes in slope surface or deep inside can help identify potential landslide risks;

[0079] Local stress inside the rock mass: As construction progresses, the stress distribution inside the rock mass will change. If the local stress is detected to be too high, it may cause the rock mass to become unstable or rupture;

[0080] Groundwater level rise rate: Changes in groundwater level, especially rise, may increase the pore water pressure in the rock mass, reduce the shear strength of the rock mass, and cause slope sliding or collapse;

[0081] Accumulated rainfall: The stability of the slope is closely related to rainfall. Continuous rainfall will increase the water content of the rock mass and increase the possibility of slope instability. Accumulated rainfall is an environmental factor in the construction process, but it still brings great risks to rock slope construction.

[0082] 2) During the construction process in the rock slope construction area, the secondary impact data generally include:

[0083] Rate of increase in air humidity: In a high humidity environment, the soil or rock surface may absorb more water, reducing its friction and shear strength, thus affecting slope stability;

[0084] The logical factors of the abnormality coefficient when used in the present invention are as follows: taking the impact of the main influencing data on construction safety as an example, the first is the indicator, that is, the factor that causes the risk of construction safety (the present invention refers to the impact of the main influencing data on construction safety); the second is the weight of these indicators, that is, the proportion of each main influencing data when it is generated; the third is the operation equation, that is, what kind of mathematical operation process is used to obtain the result, and the abnormality coefficient is obtained by calculating the indicators with their respective weights through the operation equation.

[0085] The main influencing data obtained from the sample were transformed and processed into a data language recognized by computer software; secondly, these evaluation factors were analyzed by Logistic regression using SPSS software to screen out factors and their weights that are significantly correlated with the results; thirdly, the evaluation factors and weights were brought into the Logistic regression equation for calculation to obtain the results, which are as follows:

[0086] First, ensure the integrity of the main effect data, handle missing values ​​and outliers, and convert the data into a format that SPSS software can recognize. Usually, the data is stored in csv, xlsx and other formats, and then imported into SPSS. Open SPSS software, import the processed data file, and transform the variables as needed. For example, for continuous variables, standardize or normalize them. Select the "Analyze" menu, then select the "Binary Logistic" option under "Regression". In the dialog box, add the dependent variable (outcome) and the independent variable (main effect data) to the corresponding boxes. SPSS will fit the Logistic regression based on the selected variables. Model, in the output results, you will see the coefficients, standard errors, p-values ​​and other information of the model. Check the coefficients and p-values ​​in the output results to determine which variables have a significant correlation with the results. Usually, a p-value less than 0.05 is considered significant. While fitting the model, use variable selection methods, such as stepwise regression, to help screen the most relevant factors. According to the coefficients of the Logistic regression model, the size of the coefficient reflects the degree of influence of each factor on the result, and the positive and negative signs of the coefficients indicate the direction of the influence. After obtaining the significant factors and their coefficients, the Logistic regression equation is obtained, which is used to calculate the probability of each sample and then predict the results.

[0087] Dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data includes the following steps:

[0088] Obtain traffic data of the sub-monitoring area, including the number of traffic road radiation and vehicle flow;

[0089] The logic for obtaining the number of traffic road radiation is as follows: with the sub-monitoring area as the center and R as the radius, the influence radiation area of ​​the sub-monitoring area is calculated (a circular area), and the sum of all traffic roads passing through the influence radiation area is calculated to obtain the number of traffic road radiations. The larger the number of traffic road radiations, the more traffic roads are affected by the sub-monitoring area, and therefore the more monitoring efforts need to be increased;

[0090] The logic for obtaining traffic flow is: obtain the number of vehicles passing through all traffic roads affected by the sub-monitoring area within a monitoring period, and obtain the traffic flow by comprehensive calculation. The expression is:

[0091] , where For traffic flow, To monitor the duration, is the number of traffic roads affected by the sub-monitoring area, Indicates Traffic roads under monitoring time The number of vehicles passing through the sub-monitoring area. The larger the traffic volume, the more vehicles pass through the sub-monitoring area in unit time, and the more monitoring efforts of the sub-monitoring area need to be increased.

[0092] The risk coefficient of the sub-monitoring area, the number of traffic road radiation and the traffic flow are comprehensively calculated to obtain the correction index, which is expressed as: , where To correct the index, is the risk factor, For traffic data, , are the adjustment coefficients of risk factor and traffic data respectively, and , are greater than 0, , It is the normalized value of traffic road radiation quantity and the normalized value of traffic flow;

[0093] The larger the correction index of the sub-monitoring area, the more it is necessary to increase the monitoring intensity of the sub-monitoring area. The obtained correction index is compared with the preset correction threshold. The correction threshold is used to determine whether the coefficient threshold needs to be adjusted. If the correction index is less than or equal to the correction threshold, it is determined that the coefficient threshold does not need to be adjusted. If the correction index is greater than the correction threshold, it is determined that the coefficient threshold needs to be adjusted. The expression is: , where is the coefficient threshold after dynamic adjustment, To dynamically adjust the front coefficient threshold, To correct the index.

[0094] Based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, it is predicted whether the sub-monitoring area will have a safety risk, including the following steps:

[0095] After obtaining the abnormal coefficient and the dynamically adjusted coefficient threshold of each sub-monitoring area, the abnormal coefficient is compared with the dynamically adjusted coefficient threshold. The dynamically adjusted coefficient threshold is used to predict whether there is a construction safety risk in the sub-monitoring area. If the abnormal coefficient is less than or equal to the dynamically adjusted coefficient threshold, it is predicted that there is no construction safety risk in the sub-monitoring area. If the abnormal coefficient is greater than the dynamically adjusted coefficient threshold, it is predicted that there is a construction safety risk in the sub-monitoring area.

[0096] Based on the prediction results, a corresponding second management strategy (including advance traffic control and advance road protection, etc.) is generated for each sub-monitoring area, including the following steps:

[0097] 1) Management strategy for predicting that there is no construction safety risk in the sub-monitoring area

[0098] If the risk prediction results show that there is no obvious construction safety risk in the sub-monitoring area, the management strategy can be relatively relaxed, but certain protective measures must still be maintained to prevent subsequent emergencies. The management strategy includes the following steps:

[0099] 1.1) Maintain routine monitoring

[0100] Continue real-time monitoring: Although no safety risks are currently predicted, key parameters such as slope displacement, crack expansion, and groundwater level still need to be monitored during the construction process to ensure that potential risks can be discovered in a timely manner.

[0101] Regular data analysis: Data collected in real time should be analyzed regularly to detect long-term trend changes in a timely manner. If anomalies are found in the data, the risk status of the sub-monitoring area needs to be reassessed.

[0102] 1.2) No additional reinforcement

[0103] Maintain the existing slope status: If no obvious safety risks are found, no additional slope reinforcement work may be carried out to avoid unnecessary construction interference.

[0104] Reduce construction disturbance: Ensure that construction operations do not generate excessive vibration or disturb the slope structure, and continue to use low-disturbance construction techniques.

[0105] 1.3) Relaxation of traffic management measures

[0106] No traffic control: When the forecast shows that there is no construction safety risk in the sub-monitoring area, traffic control measures may not be implemented or may be relaxed to maintain normal traffic.

[0107] Ensure smooth traffic flow: No road closures or diversions are set up to ensure normal traffic flow near the construction area, while appropriately monitoring driving speed and weight.

[0108] 1.4) Continue patrolling

[0109] Regular inspections: Site managers should conduct regular inspections to ensure that there are no new cracks or other abnormal signs on the slope surface. The inspection frequency should be increased, especially when the weather changes or construction is carried out at night.

[0110] 2) Management strategies for predicting construction safety risks in sub-monitoring areas

[0111] If the risk prediction results indicate that there is a construction safety risk in the sub-monitoring area, timely protection and emergency management measures need to be taken to reduce potential safety hazards. The management strategy includes the following steps:

[0112] 2.1) Strengthen monitoring and early warning

[0113] Increase the density of monitoring equipment: In high-risk areas, add monitoring equipment, such as crack propagation sensors, slope radars, stress strain gauges, etc., to obtain more accurate real-time data.

[0114] Set up an automatic early warning system: Configure an automatic early warning system. Once the monitoring data exceeds the set threshold, an early warning will be issued immediately to notify relevant personnel to take emergency measures.

[0115] Real-time data analysis: Increase the frequency of data analysis and combine factors such as slope stress state, rainfall, groundwater level, etc. to predict whether the slope may become unstable in the short term.

[0116] 2.2) Traffic control in advance

[0117] Closure of high-risk roads: Based on the slope risk prediction results, traffic control is implemented on roads close to the slopes, and sections that may be affected are closed in advance to prevent vehicles and pedestrians from entering dangerous areas.

[0118] Set up traffic guidance measures: Set up temporary roads or guide vehicles to detour according to the on-site conditions to ensure that the traffic around the construction area is not completely blocked. At the same time, set up eye-catching road signs, traffic signs and temporary traffic lights to guide traffic to pass safely.

[0119] Limit vehicle weight and speed: In some high-risk areas, although the road is not completely closed, the weight and speed of vehicles can be limited to reduce disturbance to the slope.

[0120] 2.3) Road protection measures in advance

[0121] Install guardrails or protective nets: Set up temporary guardrails or rock-blocking nets on the roads near the construction area to prevent slope sliding or falling rocks from affecting road safety.

[0122] Set up a temporary buffer zone: Designate a temporary buffer zone beside the road and prohibit non-construction personnel and vehicles from entering to ensure that the direct impact on traffic facilities can be reduced when the slope slides.

[0123] Lay anti-skid materials in advance: If rainfall is predicted to make the road slippery, anti-skid materials can be laid or drainage facilities can be set up in advance to ensure safe use of the road during the risk forecast period.

[0124] 2.4) Construction process adjustment

[0125] Suspend high-intensity construction: In high-risk areas, suspend high-intensity construction activities that may cause additional disturbance to the slope, such as blasting, deep excavation, etc.

[0126] Phased construction: Adjust the construction plan and carry out construction in phases and on a small scale to avoid causing excessive disturbance to large-area slope structures.

[0127] Reduce nighttime construction: Avoid nighttime construction as much as possible, especially when problems are difficult to detect in a timely manner, to avoid exacerbating risks.

[0128] 2.5) Emergency preparedness and response measures

[0129] Plan emergency evacuation routes: If risk prediction indicates that the slope may become unstable, emergency evacuation routes for construction personnel and equipment must be planned in advance to ensure that personnel can be evacuated quickly in the event of an accident.

[0130] Equipped with emergency equipment: Emergency equipment should be prepared on site, such as communication equipment, emergency lights, first aid kits, etc., and ensure that construction workers are familiar with their use.

[0131] Conduct emergency drills: Conduct emergency plan drills regularly to ensure that when an emergency occurs, all personnel can respond quickly to avoid confusion and accidents.

[0132] 2.6) Slope reinforcement and protection

[0133] Carry out emergency reinforcement work: When it is predicted that the slope may become unstable, emergency reinforcement should be carried out immediately on the slope, such as using anchor reinforcement, shotcrete, building retaining walls and other measures to improve the stability of the slope.

[0134] Set up temporary support structures: Set up temporary support structures such as steel brackets or wooden piles in the construction area to prevent slope sliding or soil collapse.

[0135] Drainage measures: If the high risk forecast is related to rainfall, slope drainage measures can be taken to reduce the impact of rainwater on slope stability, such as building drainage ditches and installing seepage pipes.

[0136] Embodiment 3: This embodiment provides a rock slope construction risk early warning system, including a region division module, a foundation assessment module, and a risk prediction module;

[0137] Area division module: before construction begins, the construction area information is obtained, including road information near the construction area and basic slope information, etc. The construction area is divided into at least one sub-monitoring area. The larger the construction area, the more sub-monitoring areas are divided. The sub-monitoring area division information is sent to the basic assessment module and the risk prediction module;

[0138] Basic assessment module: before the start of construction, the initial risk status of the sub-monitoring area is obtained, and the corresponding first management strategy (including slope reinforcement or no management) is generated for each sub-monitoring area based on the initial risk status. The first management strategy is sent to the risk prediction module;

[0139] Risk prediction module: During the construction process, after obtaining real-time construction impact data, an abnormality coefficient is generated for each sub-monitoring area. The larger the abnormality coefficient, the more likely it is that the sub-monitoring area will have safety risks. After dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data, the comparison result between the abnormality coefficient and the dynamically adjusted coefficient threshold is used to predict whether the sub-monitoring area will have safety risks, and based on the prediction results, a corresponding second management strategy (including advance traffic control and advance road protection, etc.) is generated for each sub-monitoring area.

[0140] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0141] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0142] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0143] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0144] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A rock slope construction risk early warning method, characterized by: The early warning method comprises the following steps: Before construction begins, information about the construction area is obtained, the construction area is divided into at least one sub-monitoring area, an initial risk state of the sub-monitoring area is obtained some time before construction begins, and a corresponding first management strategy is generated for each sub-monitoring area according to the initial risk state; During the construction process, after obtaining real-time construction impact data, anomaly coefficients are generated for each sub-monitoring area; After dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data, predict whether the sub-monitoring area will have a safety risk based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and generate a corresponding second management strategy for each sub-monitoring area based on the prediction result; During the construction process, after obtaining real-time construction impact data, anomaly coefficients are generated for each sub-monitoring area, including the following steps: Based on the historical database of the rock slope construction area, all multi-source data that have an impact on construction safety are obtained. The multi-source data includes major impact data and minor impact data. All major impact data are set as set b. Each major impact data in set b is represented by {b1, b2, ..., b n }, n is the number of main influencing data in set b, and the abnormal coefficient is calculated by Logistic regression analysis method, and the expression is: In the formula, gf z is the abnormal coefficient, Q is a constant term with a value of 1.526, which indicates the influence of the secondary influencing data on the abnormal coefficient when the primary influencing data does not exist, {b1, b2, ..., b n } are variables, {∈1,∈2,...,∈ n } is the regression coefficient of each variable. The value of the regression coefficient is set according to the impact of the main influencing data on construction safety. When the main influencing data leads to an increase in construction safety risk, the regression coefficient is greater than 0. When the main influencing data leads to a decrease in construction safety risk, the regression coefficient is less than 0. Dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data includes the following steps: Obtain traffic data of the sub-monitoring area, including the number of traffic road radiation and vehicle flow; The risk coefficient of the sub-monitoring area, the number of traffic road radiation and the traffic volume are comprehensively calculated to obtain the correction index, which is expressed as: CCT = (α·μ+β·ln(θ+e δ +1)) 2 , where CCT is the correction index, μ is the risk coefficient, ln(θ+eδ+1) is the traffic data, α and β are the adjustment coefficients of the risk coefficient and the traffic data, and α and β are both greater than 0, θ and δ are the normalized values ​​of the traffic road radiation quantity and the normalized values ​​of the traffic flow; The obtained correction index is compared with the preset correction threshold. The correction threshold is used to determine whether the coefficient threshold needs to be adjusted. If the correction index is less than or equal to the correction threshold, it is determined that the coefficient threshold does not need to be adjusted. If the correction index is greater than the correction threshold, it is determined that the coefficient threshold needs to be adjusted. The expression is: In the formula, xz new is the coefficient threshold after dynamic adjustment, xz old To dynamically adjust the front coefficient threshold, CCT is the correction index.

2. A rock slope construction risk early warning method according to claim 1, characterized in that: Some time before construction begins, obtain the initial risk status of the sub-monitoring area, including the following steps: Some time before the start of construction, the shear strength and porosity of the sub-monitoring area are obtained, and the shear strength and porosity are normalized so that the value range of the shear strength and porosity is mapped to [0,1], and the normalized shear strength value and the normalized porosity value are obtained. The risk coefficient is subtracted from the normalized shear strength value from the normalized porosity value to obtain the risk coefficient. The obtained risk coefficient is compared with the preset risk threshold. The risk threshold is used to determine whether there is a construction risk in the sub-monitoring area. If the risk coefficient is less than or equal to the risk threshold, it is determined that there is no construction risk in the sub-monitoring area. If the risk coefficient is greater than the risk threshold, it is determined that there is a construction risk in the sub-monitoring area.

3. A rock slope construction risk early warning method according to claim 2, characterized in that: The main influencing data include: rock displacement rate, crack expansion rate, slope inclination angle growth rate, local stress inside the rock mass, groundwater level rise rate, and accumulated rainfall; The secondary impact data include: the rate of increase of air humidity.

4. A rock slope construction risk early warning method according to claim 3, characterized in that: Based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, it is predicted whether the sub-monitoring area will have a safety risk, including the following steps: After obtaining the abnormal coefficient and the dynamically adjusted coefficient threshold of each sub-monitoring area, the abnormal coefficient is compared with the dynamically adjusted coefficient threshold. The dynamically adjusted coefficient threshold is used to predict whether there is a construction safety risk in the sub-monitoring area. If the abnormal coefficient is less than or equal to the dynamically adjusted coefficient threshold, it is predicted that there is no construction safety risk in the sub-monitoring area. If the abnormal coefficient is greater than the dynamically adjusted coefficient threshold, it is predicted that there is a construction safety risk in the sub-monitoring area.

5. A rock slope construction risk early warning method according to claim 4, characterized in that: The logic for obtaining the number of traffic road radiations is as follows: taking the sub-monitoring area as the center and R as the radius, the influence radiation area of ​​the sub-monitoring area is calculated, and the number of traffic road radiations is obtained by summing up all the traffic roads passing through the influence radiation area; The logic for obtaining the traffic flow is: obtaining the number of vehicles passing through all traffic roads affected by the sub-monitoring area within a monitoring period, and obtaining the traffic flow through comprehensive calculation, the expression is: In the formula, Tra vol is the traffic volume, ΔT is the monitoring duration, m is the number of traffic roads affected by the sub-monitoring area, dl i Represents the number of vehicles passing through the i-th traffic road within the monitoring time ΔT.

6. A rock slope construction risk early warning system, used to implement the early warning method according to any one of claims 1 to 5, characterized in that: Including regional division module, basic assessment module and risk prediction module; Area division module: obtain construction area information before construction begins and divide the construction area into at least one sub-monitoring area; Basic assessment module: before the start of construction, the initial risk status of the sub-monitoring area is obtained, and the corresponding first management strategy is generated for each sub-monitoring area according to the initial risk status; Risk prediction module: During the construction process, after obtaining real-time construction impact data, an abnormal coefficient is generated for each sub-monitoring area. After dynamically adjusting the coefficient threshold based on the initial risk status of the sub-monitoring area and traffic data, it is predicted whether there will be safety risks in the sub-monitoring area based on the comparison result between the abnormal coefficient and the dynamically adjusted coefficient threshold, and a corresponding second management strategy is generated for each sub-monitoring area based on the prediction result.

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