A method and system for monitoring the freezing and thawing process of seasonal frozen ground

Abstract

This invention relates to the field of monitoring system technology, specifically to a method and system for monitoring the freeze-thaw process of seasonal permafrost. The system includes a frost heave monitoring unit, which designates the photovoltaic power station area as the monitoring area and sets multiple sampling points within the monitoring area. Soil data from each sampling point is acquired and analyzed in conjunction with environmental monitoring data to generate a soil frost heave early warning command. A risk assessment unit, upon receiving a soil frost heave early warning command, collects the tilt angle and tilt direction of each photovoltaic support, analyzes the tilt risk level of each photovoltaic support based on the tilt angle and tilt direction, and calculates the offset impact value. A fusion assessment unit determines the impact direction based on the installation posture of the photovoltaic panels in the support model, analyzes and calculates the wind resistance impact value based on the peak wind speed monitored in the affected wind direction and the area value of the photovoltaic panels. The sum of the wind resistance impact value and the offset impact value is calculated to obtain a tilting risk index.

Description

Technical Field

[0001] This invention relates to the field of monitoring system technology, specifically to a method and system for monitoring the freeze-thaw process of seasonal permafrost. Background Technology

[0002] The seasonal frozen soil freeze-thaw process monitoring system is a technological system that integrates sensor technology, data acquisition and transmission, and data management and analysis technology. It is used to automatically, continuously, and in real-time monitor and record changes in key physical parameters of seasonal frozen soil during the freezing and thawing process. This system effectively assists and guides operation and maintenance teams in conducting basic stability checks and leveling for photovoltaic stations located in cold regions.

[0003] While existing monitoring systems can monitor the freeze-thaw process of permafrost, the monitoring data generally only covers the freeze-thaw process itself and is only suitable as an auxiliary indicator for photovoltaic system operation and maintenance. It cannot be directly linked to the stability assessment of photovoltaic equipment, nor can it predict the comprehensive safety status under external forces such as wind loads. This limits the value of the monitoring data and affects the efficiency of operation and maintenance work. Summary of the Invention

[0004] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a method and system for monitoring the freeze-thaw process of seasonal permafrost, which can effectively solve the problem that the freeze-thaw monitoring data in the existing technology cannot establish a direct quantitative correlation with the structural stability of photovoltaic support and operation and maintenance response.

[0005] To achieve the above objectives, the present invention provides the following technical solution: This invention provides a seasonal frozen soil freeze-thaw process monitoring system, comprising at least: The frost heave monitoring unit designates the photovoltaic power station area as the monitoring area. Multiple sampling points are set up within this area to acquire soil data from each point. This data, combined with environmental monitoring data, is used to calculate the frost heave index for each sampling point. When the frost heave indices from multiple sampling points meet the following conditions, a soil frost heave early warning command is generated, where: The driving assessment value, moisture assessment value, and soil assessment value of the soil at the corresponding sampling point are obtained in sequence. The product of the driving assessment value, moisture assessment value, and soil assessment value is calculated to obtain the frost heave index. The risk assessment unit refers to the mounting brackets of photovoltaic panels as photovoltaic brackets. When a soil frost heave warning is received, the tilt angle and tilt direction of each photovoltaic bracket are collected. Based on the tilt angle and tilt direction, the tilt risk level of each photovoltaic bracket is analyzed and the offset impact value is calculated. The integrated evaluation unit determines the direction of influence based on the installation posture of the photovoltaic panels in the support model, and calculates the wind resistance influence value based on the peak wind speed monitored in the direction of influence and the area value of the photovoltaic panels. The tipping risk index is calculated by summing the wind resistance and offset effects.

[0006] Furthermore, the conditions for generating a soil frost heave early warning command include: Condition 1: The average frost heave index of multiple sampling points is greater than or equal to the preset frost heave threshold; Condition 2: The number of sampling points with a frost heave index greater than or equal to the frost heave threshold exceeds the preset threshold.

[0007] Furthermore, the processes for obtaining the driving assessment value, moisture assessment value, and soil assessment value are as follows: The freezing index, freezing depth, and freezing rate of the soil at the corresponding sampling point are obtained and normalized. The normalized freezing index, freezing depth, and freezing rate are then weighted and summed to obtain the driving evaluation value. The soil moisture index, migration index, and recharge index at the corresponding sampling points were obtained and normalized. The normalized moisture index, migration index, and recharge index were weighted and summed to obtain the moisture assessment value. The recharge index is inversely proportional to the groundwater level depth, and the migration index is the product of the groundwater level depth and the soil hydraulic conductivity. The fine particle content, density index, and permeability coefficient of the soil at the corresponding sampling point were obtained and normalized. The soil assessment value was obtained by weighted summation of the normalized fine particle content, density index, and permeability coefficient.

[0008] Furthermore, the freezing index is calculated as follows: When the cumulative temperature value measured by the temperature sensor during the entire freezing period is greater than 0, the freezing index is set to 0. When the cumulative temperature value measured by the temperature sensor during the entire freezing period is less than or equal to 0, the freezing index is set to the absolute value of the cumulative temperature value.

[0009] Furthermore, the tilt angle is obtained as follows: A dual-axis tilt sensor is installed on each photovoltaic support. The dual-axis readings of the dual-axis tilt sensor are recorded before the freezing period and recorded as the initial dataset. The current dual-axis readings of the dual-axis tilt sensor on the photovoltaic support are obtained and recorded as the real-time dataset. The angle change of each axis is calculated by comparing the initial dataset and the real-time dataset. The total spatial tilt angle is synthesized based on the angle change of each axis and recorded as the tilt angle.

[0010] Furthermore, the calculation process for the offset influence value is as follows: A spatial rectangular coordinate system is established, and a three-dimensional model of the photovoltaic support is constructed in the coordinate system, denoted as the support model. The position of the centroid of the support model is determined by analysis based on the three-dimensional modeling software. The support model is adjusted based on the tilt angle and tilt direction of the photovoltaic support, and the coordinates of the centroid position after adjustment are recorded as the centroid coordinates. The offset influence value is obtained by analyzing and calculating the position of the centroid coordinates and the installation support point of the photovoltaic support.

[0011] Furthermore, the coordinates of multiple support points at the bottom of the photovoltaic support are obtained as support point coordinates. The lines connecting the centroid coordinates and the coordinates of multiple support points are recorded as distance lines. The projection length of each distance line on the horizontal plane is recorded as the absolute distance. The support point with the shortest absolute distance to the centroid coordinates is recorded as the target support point. The center point of the coordinates of multiple support points is recorded as the bottom center point. The bottom reference line is obtained by connecting the target support point and the bottom center point. A rectangular coordinate axis is constructed with the target fulcrum as the origin of the coordinate axis and is called the balance reference coordinate axis. The balance reference coordinate axis is perpendicular to the horizontal plane and the target fulcrum and the bottom center point are both located within the balance reference coordinate axis. The horizontal axis of the balance reference axis is on the horizontal plane, and the side of the horizontal axis closer to the bottom center point is the positive half axis. The support model is simplified into a two-dimensional model on the balance reference coordinate axis. The center of mass is represented in the balance reference coordinate axis. The coordinates of the center of mass in the balance reference coordinate axis are obtained, and the horizontal coordinate is extracted and multiplied by a preset gravity constant to obtain the offset influence value.

[0012] Furthermore, the process for determining the direction of influence is as follows: A straight line perpendicular to the surface of the photovoltaic panel is drawn from the center point of the photovoltaic panel in the support model and is called the light-collecting line. The vertical plane where the light-collecting line is located is called the target plane. The projection line of the target plane onto the horizontal plane is called the direction line. The direction corresponding to the direction line is called the influence direction.

[0013] Furthermore, the calculation process for the wind resistance impact value is as follows: The center point of the photovoltaic panel is recorded as the center point of the panel surface, and the vertical distance between the center point of the panel surface and the target support point is recorded as the influence length of the panel surface. The projected area of ​​the photovoltaic panel in the direction of influence is recorded as the wind influence area. A comprehensive coefficient is preset. The wind reference value is obtained by multiplying the square of the maximum wind speed, the wind influence area, and the comprehensive coefficient. The wind resistance effect value is obtained by multiplying the affected length of the plate surface and the wind force reference value.

[0014] A method for monitoring the freeze-thaw process of seasonally frozen soil includes the following steps: Step 1: Set up multiple sampling points in the monitoring area. Based on the soil and meteorological data of each sampling point, calculate the frost heave index by multiplying the driving assessment value, the moisture assessment value, and the soil assessment value. Based on the magnitude and distribution of frost heave index values ​​from multiple sampling points, a soil frost heave early warning command is generated. Step 2: After receiving the soil frost heave warning command, collect the tilt angle and tilt direction of each photovoltaic support; Based on the three-dimensional model of the support, the coordinates of the center of mass are determined, the target fulcrum is selected and the equilibrium reference coordinate axis is established, the model is simplified to a two-dimensional model, and the offset influence value is obtained by extracting the abscissa of the center of mass and multiplying it by the gravity constant. Step 3: Determine the direction of influence based on the installation posture of the photovoltaic panel, obtain the maximum wind speed in that direction over a week, calculate the wind force reference value by combining it with the photovoltaic panel data, and then multiply it by the influence length of the panel to obtain the wind resistance influence value. Step 4: Add the wind resistance impact value and the offset impact value to obtain the tipping risk index. There is a preset risk assessment threshold. When the tipping risk index is greater than or equal to the risk assessment threshold, a tipping warning signal is generated and sent to the staff's handheld terminal to remind the staff to take timely action.

[0015] The technical solution provided by this invention has the following advantages compared with the known prior art: 1. On the one hand, this invention can quantify the complex frost heave process and its impact into comparable indicators by calculating the frost heave index system, providing a foundation for subsequent frost heave risk management and precise maintenance of photovoltaic power plants. On the other hand, by establishing a balance reference coordinate axis and a two-dimensional simplified model, the tilt angle can be converted into an offset impact value based on mechanical analysis, enabling the system evaluation process to directly quantify the degree of mechanical instability. Compared with traditional alarms that only set angle thresholds, this method can identify potential danger points earlier, where the angle change is not significant but the torque increases significantly due to the displacement of the center of mass.

[0016] 2. This invention converts wind speed into wind-induced overturning moment acting on the same target support point by determining the direction of influence and calculating the wind resistance influence value, ensuring the consistency of mathematical characteristics with the offset influence value, and realizing risk coupling assessment: the static instability caused by frost heave and the dynamic load applied by strong wind are linearly superimposed to generate a comprehensive overturning risk index, which solves the limitation of traditional methods that isolate the two types of risks and realizes safety early warning under frost heave and strong wind conditions. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0018] Figure 1 This is an overall module block diagram of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] The present invention will be further described below with reference to embodiments.

[0021] See Figure 1 A seasonal frozen soil freeze-thaw process monitoring system is applicable to seasonal frozen soil areas and is used to monitor the foundation stability of photovoltaic power generation equipment in photovoltaic power stations during the frozen soil frost heave process.

[0022] It should be noted that when water in the soil freezes, it expands by about 9% in volume, generating a huge frost heave force. This force is generally active and upward. For facility foundations, especially shallow foundations or extended foundations located on the ground surface, uneven frost heave forces can cause the ground to bulge and rise, resulting in the facility foundation being lifted, tilted, or even toppled, thus affecting the stability of the equipment and facilities.

[0023] At least including: The frost heave monitoring unit designates the photovoltaic power station area as the monitoring area. Multiple sampling points are set up within this area to acquire soil data from each point. This data, combined with environmental monitoring data, is used to calculate the frost heave index for each sampling point. The frost heave index is used to quantitatively assess the magnitude of frost heave force within the sampling point. A soil frost heave early warning command is generated when the frost heave indices at multiple sampling points meet the following conditions: Condition 1: The average frost heave index of multiple sampling points is greater than or equal to the preset frost heave threshold; Condition 2: The number of sampling points with a frost heave index greater than or equal to the frost heave threshold exceeds the preset threshold.

[0024] It should be noted that the frost heave threshold corresponds to a quantitative value of the degree of frost heave (frost heave at this level will cause soil uplift, soil heave, etc.). Exceeding the frost heave threshold means that the degree of frost heave in the soil at that sampling point will threaten surface facilities. The quantity threshold corresponds to a range of frost heave impact. When the frost heave index of multiple sampling points meets the above conditions, it indicates that the average level of frost heave in the monitoring area is relatively high and the affected area covers a wide range.

[0025] Specifically, the calculation process for the frost heave index is as follows: The freezing index (cumulative absolute value of negative temperature, reflecting freezing intensity), freezing depth (maximum freezing front depth, reflecting freezing range), and freezing rate (freezing front advance speed, reflecting freezing intensity) of the soil at the corresponding sampling point are obtained and normalized. The freezing index, freezing depth, and freezing rate after normalization are weighted and summed to obtain the driving evaluation value. The freezing index is equal to the cumulative absolute value of negative temperature measured by the temperature sensor throughout the entire freezing period, and the specific formula is as follows: , where i is the day number of the freeze period. This represents the average daily temperature measured on day i. The freezing depth is equal to the maximum depth of the 0°C isotherm measured by the ground temperature sensor chain. The freezing rate is equal to the downward displacement of the 0°C isotherm per unit time.

[0026] It should be noted that temperature is the main driving force for frost heave. Therefore, calculating the driving assessment value can quantitatively evaluate the temperature driving effect in the frost heave process. The larger the value, the more obvious the driving effect of temperature on frost heave, and the more likely frost heave will occur under this condition.

[0027] The soil moisture index (corresponding to the initial soil moisture content before freezing), migration index (corresponding to the water migration capacity during freezing), and recharge index (corresponding to the groundwater recharge capacity for frost heave water) at the sampling point are obtained and normalized. The normalized moisture index, migration index, and recharge index are weighted and summed to obtain the moisture assessment value. Among them, the moisture index is the average volumetric water content of the sampling point before freezing in autumn (measured by a soil moisture sensor), the recharge index is inversely proportional to the groundwater level depth, and the migration index is the product of the groundwater level depth and the soil hydraulic conductivity.

[0028] It should be noted that moisture is the material basis of frost heave. Therefore, calculating the moisture assessment value can quantify the impact of moisture on the frost heave process. The larger the value, the more obvious the driving effect of moisture on the occurrence of frost heave, and the more likely frost heave will occur under this condition.

[0029] The soil fine particle content (percentage of particles <0.075mm), density index (density of soil under dry and compacted conditions), and permeability coefficient (measured based on indoor permeability tests or field seepage tests) at the corresponding sampling points were obtained and normalized. The soil assessment value was obtained by weighted summation of the normalized fine particle content, density index, and permeability coefficient. It should be noted that soil properties determine its frost heave sensitivity. By calculating soil assessment values, the influence of soil properties on the frost heave process can be quantitatively evaluated. The larger the value, the more obvious the driving effect of soil properties on the occurrence of frost heave.

[0030] The frost heave index is obtained by multiplying the driving assessment value, the moisture assessment value, and the soil assessment value.

[0031] It should be noted that because frost heave requires multiple conditions to occur simultaneously (such as low temperature, moisture, and frost-susceptible soil), a multiplicative model is used to calculate the frost heave index. A higher frost heave index indicates a greater likelihood of frost heave in the soil at that sampling point and a greater degree of impact after frost heave. By calculating the frost heave index system, the complex frost heave process and its impact can be quantified into comparable indicators, providing a foundation for subsequent frost heave risk management and precise maintenance of photovoltaic power plants.

[0032] The risk assessment unit refers to the mounting brackets of photovoltaic panels as photovoltaic brackets. When a soil frost heave warning is received, the tilt angle and tilt direction of each photovoltaic bracket are collected. Based on the tilt angle and tilt direction, the tilt risk level of each photovoltaic bracket is analyzed and the offset impact value is calculated.

[0033] Specifically, the tilt angle acquisition process is as follows: A dual-axis tilt sensor is installed on each photovoltaic support. The dual-axis readings of the dual-axis tilt sensor are recorded before the freezing period and recorded as the initial dataset. The current dual-axis readings of the dual-axis tilt sensor on the photovoltaic support are obtained and recorded as the real-time dataset. The angle change of each axis is calculated by comparing the initial dataset and the real-time dataset. The total spatial tilt angle is synthesized based on the angle change of each axis and recorded as the tilt angle.

[0034] It should be noted that calculating the tilt angle allows for the estimation of the current attitude of the photovoltaic (PV) support structure, thereby enabling early identification of instability risks caused by frost heave, thaw settlement, foundation settlement, or structural loosening. This helps prevent catastrophic accidents such as support structure twisting and collapse due to excessive tilting, providing early warning and decision support for the operation and maintenance of PV supports. The tilt direction can be obtained during the tilt angle analysis.

[0035] Specifically, the calculation process for the offset impact value is as follows: A spatial rectangular coordinate system is established, and a three-dimensional model of the photovoltaic support is constructed in the coordinate system, denoted as the support model. The position of the centroid of the support model is determined by analysis based on the three-dimensional modeling software. The support model is adjusted based on the tilt angle and tilt direction of the photovoltaic support, and the coordinates of the centroid position after adjustment are recorded as the centroid coordinates. The offset influence value is obtained by analyzing and calculating the position of the centroid coordinates and the installation support point of the photovoltaic support.

[0036] in: Obtain the coordinates of multiple support points at the bottom of the photovoltaic support as support point coordinates, construct the line connecting the centroid coordinates and the coordinates of multiple support points as distance lines, obtain the projection length of each distance line on the horizontal plane as the absolute distance, select the support point with the shortest absolute distance to the centroid coordinates as the target support point, obtain the center point of the coordinates of multiple support points as the bottom center point, and connect the target support point and the bottom center point to obtain the bottom reference line. A rectangular coordinate axis is constructed with the target fulcrum as the origin of the coordinate axis and is called the balance reference coordinate axis. The balance reference coordinate axis is perpendicular to the horizontal plane and the target fulcrum and the bottom center point are both located within the balance reference coordinate axis. The horizontal axis of the balance reference axis is on the horizontal plane, and the side of the horizontal axis closer to the bottom center point is the positive half axis. The support model is simplified into a two-dimensional model on the balance reference coordinate axis. The centroid is represented in the balance reference coordinate axis. The coordinates of the centroid in the balance reference coordinate axis are obtained, and the horizontal coordinate is extracted and multiplied by a preset gravity constant (equal to the gravity of the photovoltaic support) to obtain the offset influence value.

[0037] It should be noted that by transforming the support model into a two-dimensional model on a balance reference coordinate axis, it is easier to analyze the force situation of the support. It can be viewed as a force-bearing object rotating around the target fulcrum and subjected to gravity. The mathematical essence of the offset influence value is the overturning moment of gravity on the target fulcrum. Its absolute value represents the strength of the overturning tendency, and the sign indicates the direction of tilting. The offset influence value is used to quantitatively assess the degree to which the stability of the photovoltaic support is affected after offset; the larger the value, the greater the risk of the support tipping over.

[0038] The integrated assessment unit determines the direction of influence based on the installation posture of the photovoltaic panels in the support model, records the wind speed monitored in the direction of influence as the influence wind speed, obtains the maximum value of the influence wind speed measured in the monitoring area in the most recent measurement cycle (one week in a specific embodiment), analyzes and calculates the wind resistance influence value based on the maximum value of the influence wind speed and the area value of the photovoltaic panels, and calculates the toppling risk index by summing the wind resistance influence value and the offset influence value.

[0039] It should be noted that the overturning risk index, which is calculated by coupling the "static overturning trend caused by gravity" (offset influence value) and the "dynamic overturning trend caused by wind" (wind resistance influence value), is a quantitative representation of the total overturning load and the structure's overturning resistance. It can assess the overturning risk by combining wind interference with the attitude of the photovoltaic support under the influence of frost heave, which is more in line with the actual situation of the photovoltaic support being affected.

[0040] Specifically, the process for determining the direction of influence is as follows: A straight line perpendicular to the surface of the photovoltaic panel is drawn from the center point of the support model (usually a flat and smooth plane) and is called the light-collecting line. The vertical plane containing the light-collecting line is called the target plane. The projection line of the target plane onto the horizontal plane is called the direction line, and the direction corresponding to the direction line is called the influence direction.

[0041] It should be noted that the direction of influence refers to the wind direction that poses the greatest danger to the wind load on the photovoltaic panel. When the wind direction is parallel to this direction (i.e., the wind blows perpendicularly to or against the panel surface), the photovoltaic panel bears the greatest wind pressure and generates the greatest wind load, posing the most significant threat to the stability of the support structure.

[0042] Specifically, the calculation process for the wind resistance impact value is as follows: The center point of the photovoltaic panel is recorded as the center point of the panel surface, and the vertical distance between the center point of the panel surface and the target support point is recorded as the influence length of the panel surface. The projected area of ​​the photovoltaic panel in the direction of influence is recorded as the wind influence area. A comprehensive coefficient (an empirical value used to replace the combined effects of air density, size, height, and pressure difference) is preset. The wind reference value is obtained by multiplying the square of the maximum wind speed, the wind influence area, and the comprehensive coefficient. The wind resistance effect value is obtained by multiplying the affected length of the plate surface and the wind force reference value.

[0043] It should be noted that the wind resistance impact value corresponds to the "overturning moment generated by the maximum wind load on the target support point". It is used to quantify the strength of the wind load at the peak point that drives the support to rotate around the target support point. It can convert the "extreme wind speed" into a mechanical quantity with the same dimension as the "offset impact value" (gravitational moment) through the interaction of the photovoltaic panels. This allows the overturning risk index to reflect both the structural imbalance and the instantaneous impact of the external environment, thus facilitating early warning when the support exhibits a dangerous stability condition (strong wind combined with structural tilt).

[0044] A method for monitoring the freeze-thaw process of seasonally frozen soil includes the following steps: Step 1: Set up multiple sampling points in the monitoring area. Based on the soil and meteorological data of each sampling point, calculate the frost heave index by multiplying the driving assessment value, the moisture assessment value, and the soil assessment value. When the average frost heave index of multiple sampling points is greater than or equal to the frost heave threshold, and the number of sampling points exceeding the threshold exceeds the quantity threshold, a soil frost heave early warning command is generated. Step 2: After receiving the soil frost heave warning command, collect the tilt angle and tilt direction of each photovoltaic support; Based on the three-dimensional model of the support, the coordinates of the centroid are determined, the target fulcrum is selected and the equilibrium reference coordinate axis is established. The model is simplified to a two-dimensional model on this axis, and the offset influence value is obtained by extracting the abscissa of the centroid and multiplying it by the gravity constant. Compared to existing technologies that only alert to the tilt angle, this step quantifies the torsional effect of gravity on the most dangerous fulcrum, directly assessing the urgency of instability and providing a clear mechanical basis for prioritization during maintenance.

[0045] Step 3: Determine the direction of influence based on the installation posture of the photovoltaic panels, and obtain the maximum wind speed in that direction over a week; The vertical distance between the center point of the photovoltaic panel and the target support point is calculated as the influence length of the panel, and the projected area of ​​the photovoltaic panel in the influence direction is calculated as the wind influence area. The wind force reference value is calculated by combining the comprehensive coefficient, the square of the maximum wind speed, and the wind force influence area. Then, the wind resistance influence value is obtained by multiplying it by the influence length of the panel. By determining the "direction of influence" based on the attitude of the photovoltaic panel and analyzing the overturning moment of the wind load on the same target support point, risk assessment under the peak influence wind speed condition is achieved. Compared with the traditional method of directly estimating the wind load using the maximum wind speed, this method considers the coupling effect of wind-receiving area, lever arm and wind direction, making the calculation of wind-induced overturning moment more consistent with the actual stress state.

[0046] Step 4: Add the wind resistance impact value and the offset impact value to obtain the tipping risk index. There is a preset risk assessment threshold. When the tipping risk index is greater than or equal to the risk assessment threshold, a tipping warning signal is generated and sent to the staff's handheld terminal to remind the staff to take timely action.

[0047] This index comprehensively reflects the combined effects of support posture deviation caused by frost heave and extreme wind loads. It is used to conduct a final quantitative assessment and early warning of the risk of photovoltaic support tilting, and to notify when the risk exceeds the set threshold, so as to quickly deal with the risk of tilting and improve the efficiency of operation and maintenance response.

[0048] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

Claims

1. A monitoring system for the freeze-thaw process of seasonally frozen soil, characterized in that, include: The frost heave monitoring unit designates the photovoltaic power station area as the monitoring area. Multiple sampling points are set up within this area to acquire soil data from each point. This data, combined with environmental monitoring data, is used to calculate the frost heave index for each sampling point. When the frost heave indices from multiple sampling points meet the following conditions, a soil frost heave early warning command is generated, where: The driving assessment value, moisture assessment value, and soil assessment value of the soil at the corresponding sampling point are obtained in sequence. The product of the driving assessment value, moisture assessment value, and soil assessment value is calculated to obtain the frost heave index. The risk assessment unit refers to the mounting brackets of photovoltaic panels as photovoltaic brackets. When a soil frost heave warning is received, the tilt angle and tilt direction of each photovoltaic bracket are collected. Based on the tilt angle and tilt direction, the tilt risk level of each photovoltaic bracket is analyzed and the offset impact value is calculated. The integrated evaluation unit determines the direction of influence based on the installation posture of the photovoltaic panels in the support model, and calculates the wind resistance influence value based on the peak wind speed monitored in the direction of influence and the area value of the photovoltaic panels. The tipping risk index is calculated by summing the wind resistance and offset effects.

2. The seasonal frozen soil freeze-thaw process monitoring system according to claim 1, characterized in that, The conditions for generating a soil frost heave early warning command include: Condition 1: The average frost heave index of multiple sampling points is greater than or equal to the preset frost heave threshold; Condition 2: The number of sampling points with a frost heave index greater than or equal to the frost heave threshold exceeds the preset threshold.

3. The seasonal frozen soil freeze-thaw process monitoring system according to claim 1, characterized in that, The processes for obtaining the driving assessment value, moisture assessment value, and soil assessment value are as follows: The freezing index, freezing depth, and freezing rate of the soil at the corresponding sampling point are obtained and normalized. The normalized freezing index, freezing depth, and freezing rate are then weighted and summed to obtain the driving evaluation value. The soil moisture index, migration index, and recharge index at the corresponding sampling points were obtained and normalized. The normalized moisture index, migration index, and recharge index were weighted and summed to obtain the moisture assessment value. The recharge index is inversely proportional to the groundwater level depth, and the migration index is the product of the groundwater level depth and the soil hydraulic conductivity. The fine particle content, density index, and permeability coefficient of the soil at the corresponding sampling point were obtained and normalized. The soil assessment value was obtained by weighted summation of the normalized fine particle content, density index, and permeability coefficient.

4. The seasonal frozen soil freeze-thaw process monitoring system according to claim 3, characterized in that, The calculation process for the freeze index is as follows: When the cumulative temperature value measured by the temperature sensor during the entire freezing period is greater than 0, the freezing index is set to 0. When the cumulative temperature value measured by the temperature sensor during the entire freezing period is less than or equal to 0, the freezing index is set to the absolute value of the cumulative temperature value.

5. The seasonal frozen soil freeze-thaw process monitoring system according to claim 1, characterized in that, The tilt angle acquisition process is as follows: A dual-axis tilt sensor is installed on each photovoltaic support. The dual-axis readings of the dual-axis tilt sensor are recorded before the freezing period and recorded as the initial dataset. The current dual-axis readings of the dual-axis tilt sensor on the photovoltaic support are obtained and recorded as the real-time dataset. The angle change of each axis is calculated by comparing the initial dataset and the real-time dataset. The total spatial tilt angle is synthesized based on the angle change of each axis and recorded as the tilt angle.

6. The seasonal frozen soil freeze-thaw process monitoring system according to claim 5, characterized in that, The calculation process for the offset influence value is as follows: A spatial rectangular coordinate system is established, and a three-dimensional model of the photovoltaic support is constructed in the coordinate system, denoted as the support model. The position of the centroid of the support model is determined by analysis based on the three-dimensional modeling software. The support model is adjusted based on the tilt angle and tilt direction of the photovoltaic support, and the coordinates of the centroid position after adjustment are recorded as the centroid coordinates. The offset influence value is obtained by analyzing and calculating the position of the centroid coordinates and the installation support point of the photovoltaic support.

7. A seasonal frozen soil freeze-thaw process monitoring system according to claim 6, characterized in that, Obtain the coordinates of multiple support points at the bottom of the photovoltaic support as support point coordinates, construct the line connecting the centroid coordinates and the coordinates of multiple support points as distance lines, obtain the projection length of each distance line on the horizontal plane as the absolute distance, select the support point with the shortest absolute distance to the centroid coordinates as the target support point, obtain the center point of the coordinates of multiple support points as the bottom center point, and connect the target support point and the bottom center point to obtain the bottom reference line. A rectangular coordinate axis is constructed with the target fulcrum as the origin of the coordinate axis and is called the balance reference coordinate axis. The balance reference coordinate axis is perpendicular to the horizontal plane and the target fulcrum and the bottom center point are both located within the balance reference coordinate axis. The horizontal axis of the balance reference axis is on the horizontal plane, and the side of the horizontal axis closer to the bottom center point is the positive half axis. The support model is simplified into a two-dimensional model on the balance reference coordinate axis. The center of mass is represented in the balance reference coordinate axis. The coordinates of the center of mass in the balance reference coordinate axis are obtained, and the horizontal coordinate is extracted and multiplied by a preset gravity constant to obtain the offset influence value.

8. A seasonal frozen soil freeze-thaw process monitoring system according to claim 7, characterized in that, The process for determining the direction of influence is as follows: A straight line perpendicular to the surface of the photovoltaic panel is drawn from the center point of the photovoltaic panel in the support model and is called the light-collecting line. The vertical plane where the light-collecting line is located is called the target plane. The projection line of the target plane onto the horizontal plane is called the direction line. The direction corresponding to the direction line is called the influence direction.

9. A seasonal frozen soil freeze-thaw process monitoring system according to claim 8, characterized in that, The calculation process for the wind resistance effect is as follows: The center point of the photovoltaic panel is recorded as the center point of the panel surface, and the vertical distance between the center point of the panel surface and the target support point is recorded as the influence length of the panel surface. The projected area of ​​the photovoltaic panel in the direction of influence is recorded as the wind influence area. A comprehensive coefficient is preset. The wind reference value is obtained by multiplying the square of the maximum wind speed, the wind influence area, and the comprehensive coefficient. The wind resistance effect value is obtained by multiplying the affected length of the plate surface and the wind force reference value.

10. A method for monitoring the freeze-thaw process of seasonal frozen soil, applied to a seasonal frozen soil freeze-thaw process monitoring system according to any one of claims 1 to 9, characterized in that, Includes the following steps: Step 1: Set up multiple sampling points in the monitoring area. Based on the soil and meteorological data of each sampling point, calculate the frost heave index by multiplying the driving assessment value, the moisture assessment value, and the soil assessment value. Based on the magnitude and distribution of frost heave index values ​​from multiple sampling points, a soil frost heave early warning command is generated. Step 2: After receiving the soil frost heave warning command, collect the tilt angle and tilt direction of each photovoltaic support; Based on the three-dimensional model of the support, the coordinates of the center of mass are determined, the target fulcrum is selected and the equilibrium reference coordinate axis is established, the model is simplified to a two-dimensional model, and the offset influence value is obtained by extracting the abscissa of the center of mass and multiplying it by the gravity constant. Step 3: Determine the direction of influence based on the installation posture of the photovoltaic panel, obtain the maximum wind speed in that direction over a week, calculate the wind force reference value by combining it with the photovoltaic panel data, and then multiply it by the influence length of the panel to obtain the wind resistance influence value. Step 4: Add the wind resistance impact value and the offset impact value to obtain the tipping risk index. There is a preset risk assessment threshold. When the tipping risk index is greater than or equal to the risk assessment threshold, a tipping warning signal is generated and sent to the staff's handheld terminal to remind the staff to take timely action.

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