Remote automatic monitoring platform for slope deformation based on mountain railway engineering

Abstract

The invention discloses a mountain railway engineering-based slope deformation remote automatic monitoring platform, which comprises a water and soil vector acquisition unit, a current weather acquisition unit and a contribution degree construction subunit, and is used for acquiring a historical weather contribution degree and a future weather contribution degree of a current time point according to a weather type and weather parameters of the current time point; the meteorological vector construction unit is used for constructing the historical meteorological contribution degree, the future meteorological contribution degree, the meteorological type of the current time point and the meteorological parameters of the current time point into a slope meteorological vector of the current time point; the vector splicing unit and the monitoring prediction unit are used for inputting the slope fusion vector into a pre-trained slope deformation prediction model and outputting predefined slope deformation parameters; the method not only can accurately reflect the influence of meteorological conditions on slope deformation in the past, but also can consider the potential influence of upcoming meteorological changes on slope stability, thereby providing more comprehensive and accurate deformation prediction.

Description

Technical Field

[0001] The invention relates to a slope deformation monitoring platform, in particular to a slope deformation remote automatic monitoring platform based on mountain railway engineering. Background Art

[0002] Slope deformation monitoring in mountain railway projects refers to the work carried out on the slopes along the railway (i.e., the earth slopes or rock slopes on both sides of the railway) during the construction and operation of mountain railways. The work mainly monitors the deformation of the slopes under different meteorological conditions, geological conditions, and human activities (such as construction, transportation, etc.) to ensure the stability and safety of the slopes. The patent document with patent publication number CN117606429A discloses a soil slope deformation monitoring and early warning method, which can not only monitor and warn the current slope conditions, but also fully analyze the subsequent trends. Then the existing slope deformation monitoring in mountain railway projects is mainly based on historical meteorological data to monitor slope deformation. It only relies on past meteorological data to evaluate the stability of the slope, lacks consideration of future meteorological conditions, and causes the system to lag in early warning of potential deformation. In addition, the existing calculation models are usually unable to effectively combine historical data with future meteorological forecast data, and often ignore the time series effect of meteorological conditions.

[0003] Therefore, the existing technology lacks the characteristics of fully combining historical data and future weather as current inputs in the prediction process of slope deformation of mountain railway projects, lacks dynamic response to current meteorological conditions, and needs to further improve the monitoring level. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a remote automated monitoring platform for slope deformation based on mountain railway projects, which combines historical actual data with future predicted data to solve the technical problems raised in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A remote automated monitoring platform for slope deformation based on mountain railway engineering, applied to a server, comprising: A water-soil vector acquisition unit, used to acquire the water-soil vector of the slope at the current time point; A meteorological vector construction unit, used to construct a slope meteorological vector at a current time point; The vector feature of the slope meteorological vector includes a future meteorological contribution, which is characterized as a collection of future meteorological instantaneous contributions, and the future meteorological instantaneous contribution is calculated based on the future time weight, the future meteorological weight and the future meteorological instantaneous parameter corresponding to the future time point, and the future time weight decays exponentially and accelerates in a manner away from the current time point; A vector splicing unit, used for splicing the slope water and soil vector and the slope meteorological vector to generate a slope fusion vector; The monitoring prediction unit is used to input the slope fusion vector into a pre-trained slope deformation prediction model and output predefined slope deformation parameters.

[0006] In some of the embodiments, the step of the water-soil vector acquiring unit acquiring the water-soil vector of the slope at the current time point includes: S1-1, obtaining the slope soil type, slope surface moisture content, and slope angle at the current time point; S1-2, defining the slope water permeability at the current time point according to the slope soil type; S1-3. Construct the slope water and soil vector of the current slope according to the slope surface moisture content, slope angle and slope water permeability at the current time point.

[0007] In some of the embodiments, the meteorological vector construction unit has several built-in sub-units, and the several sub-units include: The current weather acquisition subunit is used to obtain the weather type and its weather parameters at the current time point; The contribution construction subunit is used to obtain the historical meteorological contribution and future meteorological contribution at the current time point according to the meteorological type and meteorological parameters at the current time point.

[0008] In some embodiments, the step of obtaining the historical meteorological contribution by the contribution constructing subunit includes: A1-1. Get the starting time point of the current weather type on the time axis; A1-2. Calculate the duration of historical meteorological conditions between the starting time point and the current time point; A1-3, obtaining the instantaneous parameters of historical meteorology at each historical time point in the historical meteorology duration; A1-4. According to the instantaneous parameters of historical meteorology at each historical time point, the instantaneous contribution of historical meteorology at each historical time point is obtained; A1-5. The sum of the instantaneous contributions of all historical meteorological events within the duration of the historical meteorological event is defined as the historical meteorological contribution at the current time point.

[0009] In some embodiments, the instantaneous contribution of historical meteorology at each historical time point is obtained according to the instantaneous parameters of historical meteorology at each historical time point, including: A1-4-1. Calculate the historical time difference between each historical time point and the current time point within the duration of the historical meteorological period; A1-4-2. Calculate the historical time weight of each historical time point based on the historical time difference and historical meteorological duration of each historical time point, in a way that the contribution increases rapidly as it approaches the current time point; The calculation expression of the historical time weight is: ; in, is the total assists in historical time at the i-th historical time point, is the time difference between the i-th historical time point and the current time point; is the standardized historical time difference, indicating the relative proportion of the historical time point to the duration of the historical meteorological event; is the decreasing contribution term, is the decreasing coefficient, which is used to control the decay rate of the impact of historical time points on the current meteorology; A1-4-3. Obtain the historical meteorological weight of each historical meteorological instantaneous parameter within the historical meteorological duration; A1-4-4. Calculate the historical meteorological instantaneous contribution based on the historical time weight, historical meteorological weight and the historical meteorological instantaneous parameters at the corresponding historical time point; The calculation expression of the instantaneous contribution of historical meteorology is: ; in, is the instantaneous contribution of historical meteorology at the i-th historical time point, is the historical meteorological weight, It is the historical meteorological instantaneous parameter.

[0010] In some embodiments, obtaining the historical meteorological weight of each historical meteorological instantaneous parameter within the historical meteorological duration includes: A1-4-3-1. Extract the historical meteorological instantaneous parameters corresponding to each historical time point within the duration of the historical meteorological period; A1-4-3-2. Calculate the total historical meteorological parameters within the duration of the historical meteorological event based on the instantaneous historical meteorological parameters; A1-4-3-3. The ratio of the historical meteorological instantaneous parameters corresponding to each historical time point to the historical meteorological total parameters is defined as the historical meteorological weight of each historical time point.

[0011] In some embodiments, the step of obtaining the future meteorological contribution by the contribution constructing subunit includes: B1-1. Get the end time point of the weather type at the current time point on the time axis; B1-2. Calculate the duration of future weather conditions at the end time and the current time; B1-3, obtaining the instantaneous parameters of future weather at each future time point within the duration of future weather; B1-4, according to the instantaneous parameters of future meteorology at each future time point, obtaining the instantaneous contribution of future meteorology at each future time point; B1-5. The sum of all instantaneous contributions of future weather conditions within the future weather duration is defined as the future weather contribution at the current time point.

[0012] In some embodiments, obtaining the instantaneous contribution of future weather at each future time point according to the instantaneous parameters of future weather at each future time point includes: B1-4-1. Calculate the future time difference between each future time point and the current time point within the future weather duration; B1-4-2. Calculate the future time weight of each future time point based on the future time difference and future weather duration of each future time point in a way that the contribution of the distant time point accelerates the decline; The calculation expression of the future time weight is: ; in, represents the future time weight of the i-th future time point, is the time difference between the i-th future time point and the current time point; is the standardized future time difference, which indicates the relative proportion of the future time point to the duration of the future weather; It means that as the time difference increases, the weight of future time points gradually increases; B1-4-3. Obtain the future meteorological weight of each future meteorological instantaneous parameter within the future meteorological duration; B1-4-4. Calculate the instantaneous contribution of future meteorology based on the future time weight, future meteorological weight and the instantaneous parameters of future meteorology corresponding to the future time point.

[0013] In some of the embodiments, obtaining the future weather weight of each future weather instantaneous parameter within the future weather duration includes: B1-4-3-1. Extract the instantaneous parameters of future weather corresponding to each future time point within the duration of future weather; B1-4-3-2. Calculate the total future meteorological parameters within the duration of the future meteorological event based on the instantaneous future meteorological parameters; B1-4-3-3. Calculate the meteorological parameters of the total duration based on the total future meteorological parameters and the total historical meteorological parameters; B1-4-3-4. Define the inverse ratio of the index of the future meteorological instantaneous parameter corresponding to each future time point and the meteorological parameter of the total duration as the future meteorological weight of each future time point.

[0014] In some embodiments, the modeling step of the slope deformation prediction model includes: S4-1. Mark a first time point and a second time point on the time axis of the slope deformation history database; wherein the first time point is the historical start time point of the meteorological type, and the second time point is the historical end time point of the meteorological type; S4-2, obtaining the slope water and soil vector and the slope meteorological vector at the first time point, and splicing them into a historical slope fusion vector; S4-3, obtaining several slope deformation features at the second time point, and constructing them into a slope historical deformation vector; S4-4, obtaining a number of historical slope fusion vectors and slope historical deformation vectors, and constructing them as a training set; S4-4, receiving the historical slope fusion vector in the training set as an input variable and the slope historical deformation vector as a target variable, and training the slope deformation prediction model through supervision.

[0015] In some of the embodiments, the initial training model of the slope deformation prediction model is a neural network model.

[0016] The present invention provides a remote automated monitoring platform for slope deformation based on mountain railway engineering, which has the following beneficial effects: The present invention defines the future meteorological weight of each future time point as the inverse ratio of the index of the future meteorological instantaneous parameter corresponding to each future time point and the meteorological parameter of the total duration, thereby reflecting the function that the future meteorological data closer to the current time point has a greater impact on the prediction of slope deformation. By accelerating the decay of the time weight and the meteorological weight, it is ensured that the future meteorological data has a stronger effect in the prediction of slope deformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a structural block diagram of a remote automated monitoring platform for slope deformation based on mountain railway engineering of the present invention; Figure 2 A monitoring flow chart of a remote automated monitoring platform for slope deformation based on mountain railway engineering according to the present invention; Figure 3 This is a flow chart for calculating the instantaneous contribution of future meteorology according to the present invention; Figure 4 This is a flow chart for defining the future weather full assist described in the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0019] Example 1: Please refer to Figures 1 to 4 The present invention provides a remote automatic monitoring platform for slope deformation based on mountain railway engineering, which is applied to a server, and the platform includes: A water-soil vector acquisition unit, used to acquire the water-soil vector of the slope at the current time point; A meteorological vector construction unit, used to construct a slope meteorological vector at a current time point; The vector feature of the slope meteorological vector includes a future meteorological contribution, which is characterized as a collection of future meteorological instantaneous contributions, and the future meteorological instantaneous contribution is calculated based on the future time weight, the future meteorological weight and the future meteorological instantaneous parameter corresponding to the future time point, and the future time weight decays exponentially and accelerates in a manner away from the current time point; A vector splicing unit, used for splicing the slope water and soil vector and the slope meteorological vector to generate a slope fusion vector; The monitoring prediction unit is used to input the slope fusion vector into a pre-trained slope deformation prediction model and output predefined slope deformation parameters.

[0020] The slope deformation parameter is a predefined parameter that can be selected from several outputs of the slope deformation prediction model based on platform requirements. It can be: Deformation type: such as horizontal displacement, vertical displacement, rotational deformation, etc.

[0021] Deformation direction: Predict the deformation direction of the slope based on meteorological and land factors.

[0022] Deformation areas: predict which areas are likely to experience large deformations, possibly based on real-time feedback from sensor data (e.g., fiber optic sensors, GPS).

[0023] Deformation amplitude: Based on the predicted meteorological factors and land conditions, the possible deformation amplitude in the future is assessed.

[0024] Risk level: Combined with the stability analysis of the slope, the safety assessment results of the slope are given (such as normal, warning, early warning, critical, etc.).

[0025] In this embodiment, the water and soil vector of the slope at the current time point is obtained by the water and soil vector acquisition unit, including key parameters such as soil type, surface water content and slope angle. Then, the meteorological vector of the slope at the current time point is constructed by the meteorological vector construction unit, wherein the vector characteristics of the slope meteorological vector include the future meteorological contribution, and the future meteorological contribution is the sum of the future meteorological instantaneous contribution, which reflects the potential impact of future meteorological data on the slope deformation within the prediction period of the current time point. In other words, the platform defines the sum of all future meteorological instantaneous contributions as the future meteorological contribution at the current time point, that is, the predicted future meteorological contribution is used as the input of the current time point, and then the future meteorological contribution (i.e., the collection of future meteorological instantaneous contributions) can be combined with historical data, ensuring a comprehensive assessment of the impact of meteorological conditions. Specifically, the platform first predicts the potential impact of future meteorological conditions (such as precipitation, temperature, etc.) on slope deformation, then weights these meteorological data according to the future time weight and the future meteorological weight, and finally calculates the future meteorological instantaneous contribution of each future time point according to these weighted data, ultimately ensuring a comprehensive assessment of the impact of meteorological conditions.

[0026] Furthermore, a slope fusion vector is constructed by the vector splicing unit, combining the slope water and soil vector and the meteorological vector. Finally, the monitoring and prediction unit inputs the fusion vector into the pre-trained slope deformation prediction model and outputs multiple slope deformation parameters. Among them, the multiple slope deformation parameters can be based on predefined deformation type, deformation direction, deformation area, deformation amplitude and risk level.

[0027] The step of the water-soil vector acquisition unit acquiring the water-soil vector of the slope at the current time point includes: S1-1. Obtain the slope soil type, slope surface moisture content, and slope angle (such as clay, sand, rocky soil, etc.) at the current time point Specifically, slope soil type indicates that the stability of the slope is closely related to its soil type. Different types of soil (such as clay, sand, rocky soil, etc.) have different physical properties, which determine the water penetration capacity, expansion, compressibility, etc. The water content of the surface of the slope directly affects the stability of the slope, especially when meteorological factors such as rainfall and drought change. When the water content is high, the soil may be looser and prone to sliding or landslides, especially for clay soils. The angle of the slope directly affects its stability. Steeper slopes are prone to landslides or collapses, especially when precipitation or temperature changes.

[0028] S1-2, defining the slope water permeability at the current time point according to the slope soil type; Water permeability refers to the ability of a soil or rock layer to absorb water, which determines how quickly water moves through a slope. Different soil types have different permeability characteristics. For example, sand has a high permeability and water moves quickly, while clay has a low permeability and water may stay for a longer time.

[0029] S1-3. Construct the slope water and soil vector of the current slope according to the slope surface moisture content, slope angle and slope water permeability at the current time point.

[0030] The slope water-soil vector is a multi-dimensional vector that comprehensively affects the stability of the slope, especially the related characteristics of soil and water. Specifically, the slope water-soil vector represents the comprehensive situation of the soil characteristics, water status and water infiltration process of the slope at the current time point.

[0031] This embodiment can evaluate the stability of the slope in real time by obtaining information such as the slope soil type, surface moisture content, and slope angle at the current time point. Different soil types affect the permeability of water and the expansibility of the soil, which in turn affects the stability of the slope. When the moisture content of the surface of the slope is high, the soil tends to become soft, and the risk of deformation increases, especially under meteorological conditions such as rainfall or drought. The slope angle directly affects the risk of landslide or collapse of the slope. By combining the above factors, the water and soil state of the slope at the current time point is fully described by the slope water and soil vector.

[0032] Furthermore, the meteorological vector construction unit has several sub-units built in, and the several sub-units include: The current meteorological acquisition subunit is used to obtain the meteorological type and its meteorological parameters at the current time point; the meteorological types cover different meteorological conditions such as heavy rain, drought, frost and storm, for example, heavy rain and its instantaneous precipitation, drought and its instantaneous humidity, frost and its instantaneous temperature, storm and its instantaneous wind speed and direction, to ensure that the platform can accurately assess the potential impact of meteorology on slope deformation.

[0033] The contribution construction subunit is used to obtain the historical meteorological contribution and future meteorological contribution at the current time point according to the meteorological type and meteorological parameters at the current time point.

[0034] Specifically, the vector characteristics of the slope meteorological vector include not only the future meteorological contribution, but also the meteorological type and its meteorological parameters at the previous time point, as well as the historical meteorological contribution.

[0035] Furthermore, in this embodiment, the step of the contribution building subunit acquiring the historical meteorological contribution includes: A1-1. Get the starting time point of the current weather type on the time axis; A1-2. Calculate the duration of historical meteorological conditions between the starting time point and the current time point; A1-3, obtaining the instantaneous parameters of historical meteorology at each historical time point in the historical meteorology duration; A1-4. According to the instantaneous parameters of historical meteorology at each historical time point, the instantaneous contribution of historical meteorology at each historical time point is obtained; A1-5. The sum of the instantaneous contributions of all historical meteorological events within the duration of the historical meteorological event is defined as the historical meteorological contribution at the current time point.

[0036] This embodiment defines the historical meteorological contribution, first obtains the starting time point of the meteorological type at the current time point, and determines the starting moment of the historical meteorological impact. Next, the historical meteorological duration between the starting time point and the current time point is calculated to provide a time range for the subsequent meteorological contribution calculation. Then, the meteorological instantaneous parameters of each historical time point within the duration are obtained, and the historical meteorological instantaneous contribution of each historical time point is calculated based on the meteorological instantaneous parameters. Finally, by defining the sum of all historical meteorological instantaneous contributions as the historical meteorological contribution at the current time point, comprehensive historical meteorological impact data is provided for slope deformation prediction.

[0037] Furthermore, the specific steps of steps A1-4 include: A1-4-1. Calculate the historical time difference between each historical time point and the current time point within the duration of the historical meteorological period; A1-4-2. Calculate the historical time weight of each historical time point based on the historical time difference and historical meteorological duration of each historical time point, in a way that the contribution increases rapidly as it approaches the current time point; The calculation expression of the historical time weight is: ; in, is the total historical time assist of the i-th historical time point, indicating the relative time difference of historical time points. The more distant time points contribute less to the current time point. is the time difference between the i-th historical time point and the current time point; The farther the historical time point is from the current time point, the smaller the weight of the historical time will be. is the standardized historical time difference, indicating the relative proportion of the historical time point to the duration of the historical weather. As it increases, the weight will decrease; It is a decreasing contribution term, which means that as the time difference increases, the value of the decreasing contribution term will decrease, thereby reflecting that the influence of historical meteorological data from the current time point is decreasing. is a decreasing coefficient, which is used to control the decay rate of the impact of historical time points on the current weather. =1, the decay rate is linearly decreasing; if >1, the decay rate will accelerate, and the influence of historical meteorology farther from the current time point on the contribution will be smaller; if <1 means slower decay.

[0038] The historical time weight reflects the influence of time in a decreasing manner, ensuring that historical data farther away from the current time have less influence on the forecast contribution, which conforms to the rule that the influence of historical data on the current meteorology gradually weakens.

[0039] A1-4-3. Obtain the historical meteorological weight of each historical meteorological instantaneous parameter within the historical meteorological duration; A1-4-4. Calculate the historical meteorological instantaneous contribution based on the historical time weight, historical meteorological weight and the historical meteorological instantaneous parameters at the corresponding historical time point.

[0040] The calculation expression of the instantaneous contribution of historical meteorology is: ; in, is the instantaneous contribution of historical meteorology at the i-th historical time point, is the historical meteorological weight, which indicates the proportion of the meteorological parameters at the ith historical time point in the entire historical meteorological duration. The proportion of the impact of the meteorological data on the overall historical meteorology is calculated by summing the meteorological instantaneous parameters at that time point and all historical meteorological instantaneous parameters. is the historical meteorological instantaneous parameter; it represents the meteorological data at the ith historical time point, such as precipitation, temperature, etc.

[0041] This embodiment defines the detailed steps of the instantaneous contribution of historical meteorology. First, by calculating the historical time difference of each historical time point within the duration of the historical meteorology, the platform can determine the time difference between each historical time point and the current time point, and then evaluate the impact of the historical meteorological data. Subsequently, according to the historical time difference of each historical time point and the duration of the historical meteorology, the historical time weight is calculated in an accelerated decreasing manner, ensuring that as the time difference increases, the contribution of historical data to the current time point gradually decreases, thereby reflecting the law of the attenuation of the impact of historical meteorological data on the current forecast.

[0042] Next, the platform obtains the historical meteorological weight of each historical meteorological instantaneous parameter within the duration of the historical meteorological event. This weight represents the proportion of the meteorological parameter at each historical time point in the entire duration of the historical meteorological event, and thus reflects the proportion of the impact of each historical meteorological data on the overall historical meteorology. By calculating the historical meteorological instantaneous contribution, the historical time weight, historical meteorological weight and historical meteorological instantaneous parameter are combined to finally calculate the historical meteorological instantaneous contribution of each historical time point.

[0043] Furthermore, the step A1-4-3 specifically includes: A1-4-3-1. Extract the historical meteorological instantaneous parameters corresponding to each historical time point within the duration of the historical meteorological period; A1-4-3-2. Calculate the total historical meteorological parameters within the duration of the historical meteorological event based on the instantaneous historical meteorological parameters; A1-4-3-3. The ratio of the historical meteorological instantaneous parameters corresponding to each historical time point to the historical meteorological total parameters is defined as the historical meteorological weight of each historical time point.

[0044] This embodiment discloses a method for calculating historical meteorological weights. By extracting the historical meteorological instantaneous parameters corresponding to each historical time point within the duration of the historical meteorology, it is ensured that the meteorological data at each historical time point is accurately collected. Then, based on the historical meteorological instantaneous parameters, the total historical meteorological parameters within the duration of the historical meteorology are calculated to obtain the sum of the meteorological data for the entire historical period. Finally, the historical meteorological weight of each historical time point is defined as the ratio of the historical meteorological instantaneous parameters corresponding to each historical time point to the historical meteorological total parameters, reflecting the relative contribution of the meteorological data at each time point during the entire historical meteorological period. This calculation method provides accurate historical meteorological impact data for the slope deformation prediction model by reasonably weighing the relationship between the meteorological data at each historical time point and the total historical meteorological data.

[0045] In this embodiment, the step of obtaining the future meteorological contribution includes: B1-1. Get the end time point of the weather type at the current time point on the time axis; Specifically, the end time point of the weather type at the current time point on the time axis represents the possible end time of the same weather type at the current moment in the future, which can be obtained through weather forecasts or future weather prediction models.

[0046] B1-2. Calculate the duration of future weather conditions at the end time and the current time; B1-3, obtaining the instantaneous parameters of future weather at each future time point within the duration of future weather; B1-4, according to the instantaneous parameters of future meteorology at each future time point, obtaining the instantaneous contribution of future meteorology at each future time point; B1-5. The sum of all instantaneous contributions of future weather conditions within the future weather duration is defined as the future weather contribution at the current time point.

[0047] This embodiment discloses a method for calculating the future meteorological contribution, which further ensures the accuracy of slope deformation prediction. First, by obtaining the end time point of the meteorological type at the current time point on the time axis, the end time of the future meteorological impact is determined. The end time point can be obtained through a weather forecast or a future meteorological prediction model, ensuring an accurate prediction of future meteorological conditions. Next, the future meteorological duration at the end time point and the current time point is calculated to provide a time range for future meteorological data. Then, the platform obtains the future meteorological instantaneous parameters of each future time point within the future meteorological duration, and the parameters include future precipitation, temperature, wind speed and other meteorological data. The platform further calculates the future meteorological instantaneous contribution of each future time point, which reflects the potential impact of the meteorological data on slope deformation during the prediction period. Finally, the platform defines the sum of all future meteorological instantaneous contributions as the future meteorological contribution at the current time point, ensuring a comprehensive assessment of the impact of meteorological conditions.

[0048] It is worth noting that since the calculation of future meteorological contribution depends on data such as future time points and future meteorological instantaneous parameters, the data is not collected in real time, but is based on the forecast data provided by the meteorological forecast model. For example, based on meteorological forecast data, numerical meteorological models, etc., to ensure the accuracy of the calculation of future meteorological contribution. Generally speaking, accurate meteorological forecast data can be obtained through the meteorological department's weather forecast system, numerical weather forecast (NWP) model, etc. The forecast data is usually provided by the meteorological department and covers meteorological parameters such as temperature, precipitation, wind speed, etc. in the future.

[0049] Furthermore, the step B1-4 specifically includes: B1-4-1. Calculate the future time difference between each future time point and the current time point within the future weather duration; B1-4-2. Calculate the future time weight of each future time point based on the future time difference and future weather duration of each future time point in a way that the contribution of the distant time point accelerates the decline; The calculation expression of the future time weight is: ; in, represents the future time weight of the i-th future time point, is the time difference between the ith future time point and the current time point. The farther the future time point is from the current time point, the greater the weight will be. is the standardized future time difference, which indicates the relative proportion of the future time point to the duration of the future weather. As it increases, the weight will gradually increase. It means that as the time difference increases, the weight of future time points gradually increases. If α=1, the increasing speed is linear; if α>1, the increasing speed is faster; if α<1, the increasing speed is slow.

[0050] In order to accurately evaluate the impact of future meteorological conditions on slope deformation, the platform adopts an exponential decay method of future time weights. The core of this method is that as time goes by, the impact of meteorological data far away from the current moment on slope deformation prediction will gradually decrease. This exponential decay ensures that the impact of future meteorological data in the prediction decreases with the distance in time, thereby improving the accuracy and real-time performance of the prediction at the current moment. In other words, future meteorological conditions will decay faster as the distance from the current moment increases, ensuring that the system relies more on the impact of current meteorological conditions on slope deformation, reducing the potential errors of over-reliance on long-term meteorological forecasts.

[0051] The future time weight reflects that the closer the future meteorological data is to the current time point, the greater the impact on the prediction of slope deformation. By accelerating the decay of time weight and meteorological weight, it is ensured that future meteorological data has a stronger role in slope deformation prediction, especially in the near time period, the accuracy and response speed of the prediction will be enhanced.

[0052] B1-4-3. Obtain the future meteorological weight of each future meteorological instantaneous parameter within the future meteorological duration; B1-4-4. Calculate the instantaneous contribution of future meteorology based on the future time weight, future meteorological weight and the instantaneous parameters of future meteorology corresponding to the future time point.

[0053] This embodiment discloses a deformation prediction method based on future meteorological conditions. First, the time difference between each future time point and the current time point is calculated, and the future time weight of the future time point is calculated in an incremental manner according to the time difference and the duration of the future meteorological conditions. As the time difference increases, the influence of future meteorological data gradually increases, ensuring that the meteorological data at nearby time points has a stronger influence on the prediction of slope deformation, thereby improving the accuracy of the prediction.

[0054] Next, the platform calculates the future meteorological weights based on the future meteorological instantaneous parameters, and combines the future time weights with historical meteorological data to calculate the future meteorological instantaneous contribution at each future time point. This method can accurately assess the impact of future meteorological conditions on slope deformation and provide timely deformation prediction and monitoring.

[0055] Furthermore, the step B1-4-3 specifically includes: B1-4-3-1. Extract the instantaneous parameters of future weather corresponding to each future time point within the duration of future weather; B1-4-3-2. Calculate the total future meteorological parameters within the duration of the future meteorological event based on the instantaneous future meteorological parameters; B1-4-3-3. Calculate the meteorological parameters of the total duration based on the total future meteorological parameters and the total historical meteorological parameters; B1-4-3-4. Define the inverse ratio of the index of the future meteorological instantaneous parameter corresponding to each future time point and the meteorological parameter of the total duration as the future meteorological weight of each future time point.

[0056] This embodiment discloses a method for calculating the future weather weight, which first extracts the instantaneous weather parameters at each future time point within the future weather duration, and then calculates the total future weather parameters within the future weather duration, that is, accumulates the future weather data, covering the weather conditions of the entire forecast period. At the same time, the platform also takes into account the total parameters of historical weather, that is, the impact of actual weather in the past on the current situation.

[0057] Through this method, the platform can more accurately incorporate future meteorological changes into slope deformation predictions, taking into account the potential impact of upcoming meteorological changes on slope stability. At the same time, through the exponential attenuation mechanism, it enhances the responsiveness to current meteorological conditions and avoids excessive impact of long-term predictions.

[0058] Next, the platform evaluates the comprehensive impact of meteorological changes on slope deformation by calculating the ratio of future total meteorological parameters to historical total meteorological parameters, and combining the relative impact of historical meteorological conditions and future meteorological conditions. Finally, the platform uses the inverse ratio of the exponential value of the future meteorological instantaneous parameters at each future time point to the meteorological parameters of the total duration as the basis for future meteorological weights. The inverse ratio reflects the accelerating trend of the impact of future meteorology on slope deformation over the entire duration. As time goes by, the future time weight decays rapidly, while the future meteorological weight increases rapidly. The impact of future meteorological conditions will increase rapidly, thus ensuring a comprehensive assessment of future meteorological impacts. Through future meteorological weights, past and future meteorological data are effectively integrated to provide accurate slope deformation predictions.

[0059] Embodiment 2: The technical solution of Embodiment 2 is different from that of Embodiment 1 in that the modeling steps of the slope deformation prediction model disclosed include: S4-1. Mark a first time point and a second time point on the time axis of the slope deformation history database; wherein the first time point is the historical start time point of the meteorological type, and the second time point is the historical end time point of the meteorological type; S4-2, obtaining the slope water and soil vector and the slope meteorological vector at the first time point, and splicing them into a historical slope fusion vector; S4-3, obtaining several slope deformation features at the second time point, and constructing them into a slope historical deformation vector; S4-4, obtaining a number of historical slope fusion vectors and slope historical deformation vectors, and constructing them as a training set; S4-4, receiving the historical slope fusion vector in the training set as an input variable and the slope historical deformation vector as a target variable, and training the slope deformation prediction model through supervision.

[0060] This embodiment discloses the modeling steps of the slope deformation prediction model. First, by marking the first time point and the second time point on the time axis of the slope deformation history database, it helps to determine the historical impact range of meteorological conditions on slope deformation.

[0061] Next, the platform obtains the slope water and soil vector and slope meteorological vector at the first time point, and splices them into a historical slope fusion vector, which integrates the soil, water, meteorological and other factors of the slope, reflecting the overall stability of the slope at that moment. Then, the platform obtains several slope deformation features at the second time point, and constructs them into a slope historical deformation vector to represent the slope deformation state at that time point.

[0062] By collecting several historical slope fusion vectors and slope historical deformation vectors, a training set is constructed. Then, the slope deformation prediction model is trained through supervised training using the historical data of the training set, so that the model can predict future slope deformation based on the input historical meteorological and water and soil data.

[0063] In this embodiment, the initial training model of the slope deformation prediction model is a neural network model.

[0064] Specifically, using the neural network model as the initial training model for the slope deformation prediction model means that the platform uses the powerful nonlinear fitting ability of the neural network to handle complex slope deformation prediction problems. The neural network can automatically learn complex laws and relationships from the input data, especially when there is a complex and nonlinear relationship between slope stability and meteorological, water and soil factors, the neural network can provide higher prediction accuracy.

[0065] As the initial training model, the neural network model can gradually optimize the model parameters through the back propagation algorithm and a large amount of training data, so that it can more accurately predict the deformation trend of the slope. By training on historical data, the neural network can identify the key factors related to slope deformation and learn to make effective predictions when facing new meteorological conditions and water and soil changes. Therefore, using the neural network as the initial training model can improve the adaptability and prediction accuracy of the slope deformation prediction model in complex environments, especially when dynamic meteorological and soil conditions change.

[0066] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means.

[0067] The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., DVD ), or semiconductor media. The semiconductor media may be a solid state drive.

[0068] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division of a waterway underwater terrain change analysis system and method. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0069] The above is only a specific implementation 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 covered by the protection scope of the present application.

Claims

1. A remote automated monitoring platform for slope deformation based on mountain railway engineering, applied to a server, characterized in that: The platform includes: A water-soil vector acquisition unit, used to acquire the water-soil vector of the slope at the current time point; A meteorological vector construction unit, used to construct a slope meteorological vector at a current time point; The vector feature of the slope meteorological vector includes a future meteorological contribution, which is characterized as a collection of future meteorological instantaneous contributions, and the future meteorological instantaneous contribution is calculated based on the future time weight, the future meteorological weight and the future meteorological instantaneous parameter corresponding to the future time point, and the future time weight decays exponentially and accelerates in a manner away from the current time point; A vector splicing unit, used for splicing the slope water and soil vector and the slope meteorological vector to generate a slope fusion vector; The monitoring prediction unit is used to input the slope fusion vector into a pre-trained slope deformation prediction model and output predefined slope deformation parameters.

2. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 1 is characterized in that: The step of the water-soil vector acquisition unit acquiring the water-soil vector of the slope at the current time point includes: S1-1, obtaining the slope soil type, slope surface moisture content, and slope angle at the current time point; S1-2, defining the slope water permeability at the current time point according to the slope soil type; S1-3. Construct the slope water and soil vector of the current slope according to the slope surface moisture content, slope angle and slope water permeability at the current time point.

3. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 1 is characterized in that: The meteorological vector construction unit has several built-in sub-units, and the sub-units include: The current weather acquisition subunit is used to obtain the weather type and its weather parameters at the current time point; The contribution construction subunit is used to obtain the historical meteorological contribution and future meteorological contribution at the current time point according to the meteorological type and meteorological parameters at the current time point.

4. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 3 is characterized in that: The step of obtaining the historical meteorological contribution by the contribution building subunit includes: A1-1. Get the starting time point of the current weather type on the time axis; A1-2. Calculate the duration of historical meteorological conditions between the starting time point and the current time point; A1-3, obtaining the instantaneous parameters of historical meteorology at each historical time point in the historical meteorology duration; A1-4. According to the instantaneous parameters of historical meteorology at each historical time point, the instantaneous contribution of historical meteorology at each historical time point is obtained; A1-5. The sum of the instantaneous contributions of all historical meteorological events within the duration of the historical meteorological event is defined as the historical meteorological contribution at the current time point.

5. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 4 is characterized in that: According to the instantaneous parameters of historical meteorology at each historical time point, the instantaneous contribution of historical meteorology at each historical time point is obtained, including: A1-4-1. Calculate the historical time difference between each historical time point and the current time point within the duration of the historical meteorological period; A1-4-2. Calculate the historical time weight of each historical time point based on the historical time difference and historical meteorological duration of each historical time point, in a way that the contribution increases rapidly as it approaches the current time point; The calculation expression of the historical time weight is: ; in, is the total assists in historical time at the i-th historical time point, is the time difference between the i-th historical time point and the current time point; is the standardized historical time difference, indicating the relative proportion of the historical time point to the duration of the historical meteorological event; is the decreasing contribution term, is the decreasing coefficient, which is used to control the decay rate of the impact of historical time points on the current meteorology; A1-4-3. Obtain the historical meteorological weight of each historical meteorological instantaneous parameter within the historical meteorological duration; A1-4-4. Calculate the historical meteorological instantaneous contribution based on the historical time weight, historical meteorological weight and the historical meteorological instantaneous parameters at the corresponding historical time point; The calculation expression of the instantaneous contribution of historical meteorology is: ; in, is the instantaneous contribution of historical meteorology at the i-th historical time point, is the historical meteorological weight, It is the historical meteorological instantaneous parameter.

6. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 5 is characterized in that: Get the historical meteorological weight of each historical meteorological instantaneous parameter within the historical meteorological duration, including: A1-4-3-1. Extract the historical meteorological instantaneous parameters corresponding to each historical time point within the duration of the historical meteorological period; A1-4-3-2. Calculate the total historical meteorological parameters within the duration of the historical meteorological event based on the instantaneous historical meteorological parameters; A1-4-3-3. The ratio of the historical meteorological instantaneous parameters corresponding to each historical time point to the historical meteorological total parameters is defined as the historical meteorological weight of each historical time point.

7. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 3 is characterized in that: The step of obtaining the future meteorological contribution by the contribution building subunit includes: B1-1. Get the end time point of the weather type at the current time point on the time axis; B1-2. Calculate the duration of future weather conditions at the end time and the current time; B1-3, obtaining the instantaneous parameters of future weather at each future time point within the duration of future weather; B1-4, according to the instantaneous parameters of future meteorology at each future time point, obtaining the instantaneous contribution of future meteorology at each future time point; B1-5. The sum of all instantaneous contributions of future weather conditions within the future weather duration is defined as the future weather contribution at the current time point.

8. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 7 is characterized in that: According to the instantaneous parameters of future meteorology at each future time point, the instantaneous contribution of future meteorology at each future time point is obtained, including: B1-4-1. Calculate the future time difference between each future time point and the current time point within the future weather duration; B1-4-2. Calculate the future time weight of each future time point based on the future time difference and future weather duration of each future time point in a way that the contribution of the distant time point accelerates the decline; The calculation expression of the future time weight is: ; in, represents the future time weight of the i-th future time point, is the time difference between the i-th future time point and the current time point; is the standardized future time difference, which indicates the relative proportion of the future time point to the duration of the future weather; It means that as the time difference increases, the weight of future time points gradually increases; B1-4-3. Obtain the future meteorological weight of each future meteorological instantaneous parameter within the future meteorological duration; B1-4-4. Calculate the instantaneous contribution of future meteorology based on the future time weight, future meteorological weight and the instantaneous parameters of future meteorology corresponding to the future time point.

9. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 8, characterized in that: Obtain the future meteorological weight of each future meteorological instantaneous parameter within the future meteorological duration, including: B1-4-3-1. Extract the instantaneous parameters of future weather corresponding to each future time point within the duration of future weather; B1-4-3-2. Calculate the total future meteorological parameters within the duration of the future meteorological event based on the instantaneous future meteorological parameters; B1-4-3-3. Calculate the meteorological parameters of the total duration based on the total future meteorological parameters and the total historical meteorological parameters; B1-4-3-4. Define the inverse ratio of the index of the future meteorological instantaneous parameter corresponding to each future time point and the meteorological parameter of the total duration as the future meteorological weight of each future time point.

10. The remote automated monitoring platform for slope deformation based on mountain railway engineering according to claim 1, characterized in that: The modeling steps of the slope deformation prediction model include: S4-1. Mark a first time point and a second time point on the time axis of the slope deformation history database; wherein the first time point is the historical start time point of the meteorological type, and the second time point is the historical end time point of the meteorological type; S4-2, obtaining the slope water and soil vector and the slope meteorological vector at the first time point, and splicing them into a historical slope fusion vector; S4-3, obtaining several slope deformation features at the second time point, and constructing them into a slope historical deformation vector; S4-4, obtaining a number of historical slope fusion vectors and slope historical deformation vectors, and constructing them as a training set; S4-4, receiving the historical slope fusion vector in the training set as an input variable and the slope historical deformation vector as a target variable, and training the slope deformation prediction model through supervision.

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