A power tunnel entrance and exit and slope critical danger information alarm monitoring method and system

Abstract

The application relates to the technical field of data management, in particular to a power tunnel entrance and exit and slope critical danger information alarm monitoring method and system. A dynamic deep learning model based on multi-parameter fusion is used to predict the slope stability, and multi-dimensional data such as vegetation, precipitation, stone characteristics and cable protection performance are combined to perform power tunnel risk assessment and early warning. The core advantage lies in that: the neural network is trained by using historical experimental data, the anti-collapse ability of the slope is dynamically evaluated, and the limitation of traditional experience is overcome; the mechanical effect of vegetation, the precipitation load, the stone impact risk and the cable protection performance are comprehensively considered to quantize the criticality and damage abnormality of the danger.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data management, and particularly relates to a power tunnel entrance and exit and slope critical danger information alarm monitoring method and system. BACKGROUND

[0002] As an important infrastructure for power transmission, the stability of the surrounding slope of the power tunnel is directly related to the safe operation of the power system. Compared with general slope engineering, the surrounding slope of the power tunnel faces some special risks:

[0003] On the one hand, the construction and operation of the power tunnel will affect the stress state of the surrounding rock-soil mass, changing the stability conditions of the slope. For example, the tunnel excavation process will cause disturbance and stress redistribution of the rock-soil mass, which may lead to local instability or overall sliding of the slope. On the other hand, the cables and other equipment in the power tunnel have high requirements for the environment, and the instability of the slope may cause damage to the tunnel structure, thereby affecting the normal operation of the cables and causing power outages and other safety accidents.

[0004] In addition, the environmental factors around the power tunnel are also relatively complex, such as vegetation coverage, precipitation, stone rolling, etc., which will affect the stability of the slope. The root system of vegetation can enhance the shear strength of the rock-soil mass, but in some cases, the growth of vegetation may also increase the water content of the rock-soil mass, thereby reducing the stability of the slope. Precipitation is an important factor affecting the stability of the slope. A large amount of rainfall will increase the saturation of the rock-soil mass and increase the pore water pressure, thereby reducing the shear strength of the rock-soil mass and causing slope instability. Stone rolling may directly impact the power tunnel and cables, causing equipment damage and safety hazards.

[0005] In view of this, the present application provides a power tunnel entrance and exit and slope critical danger information alarm monitoring method and system. SUMMARY

[0006] In order to overcome the defects and deficiencies proposed in the background art, the present application provides a power tunnel entrance and exit and slope critical danger information alarm monitoring method and system.

[0007] In order to achieve the above purpose, the present application adopts the following technical solutions:

[0008] In a first aspect, the present application provides a power tunnel entrance and exit and slope critical danger information alarm monitoring method, comprising the following steps:

[0009] Step 1, obtain the cable transmission situation of the tunnel entrance and exit, the stone situation of the slope, and the foundation situation corresponding to the slope, and obtain the precipitation situation estimated by the weather forecast, wherein the foundation situation of the slope includes the vegetation situation and the slope stability situation, wherein the slope stability is obtained by the viscosity of the soil layer corresponding to the slope, the slope of the slope and the crack situation of the slope;

[0010] Step 2, based on the vegetation situation of the slope, the precipitation situation and the slope stability situation, the danger risk assessment is carried out;

[0011] Step 3, based on the slope height, the danger risk assessment result and the corresponding stone danger situation, the danger criticality analysis is carried out;

[0012] Step 4, based on the situation of the tunnel cable, the cable protection performance is evaluated;

[0013] Step 5, based on the danger criticality analysis result and the cable protection performance evaluation result, the cable damage anomaly analysis is carried out;

[0014] Step 6, through the cable damage anomaly analysis result, the maintenance sequence of the power tunnel is sorted, and the power tunnel maintenance warning is carried out.

[0015] In one implementation of this application, the cable transmission situation at the tunnel entrance / exit in step 1 includes the sheath elasticity and sheath thickness of the corresponding cable, used to quantify the protective performance of the cable sheath, obtained through cable information statistics. The rock situation on the slope includes the average size of the rocks, the average number of rocks per unit volume of soil on the slope, the average hardness, and the average edge sharpness data, used to assess the hard damage to the cable sheath caused by rockfall. The average size, average hardness, and average edge sharpness data of the rocks are obtained through statistical analysis of rock information at corresponding locations. The vegetation situation includes the vegetation type and vegetation coverage, used to analyze the protective effect of vegetation on the slope. The slope crack situation includes the length, width, depth, and clustering of slope cracks, with clustering being the number of cracks per unit area. The slope stability analysis includes the following specific steps: obtaining information on collapsed slopes during historical experiments. The critical value of precipitation received is defined as the threshold at which the corresponding slope collapses under experimental conditions. Based on the range of critical precipitation values ​​of collapsed slopes in historical experiments, slope stability is divided into 10 levels from largest to smallest. Level 10 indicates that a large amount of precipitation is required for collapse, indicating the best stability, while Level 1 indicates that collapse occurs with very little precipitation, indicating very weak stability. Based on the slope stability levels of collapsed slopes in historical experiments, as well as the cohesion of the slope soil, slope gradient, and crack conditions of the experimental slope, a deep learning neural network model is constructed. The inputs are the cohesion of the slope soil, slope gradient, and crack conditions, and the output is the slope stability level. The cohesion of the corresponding slope soil, slope gradient, and crack conditions are input into the constructed deep learning neural network model, and the output is the slope stability level. This step constructs the deep learning model using historical experimental data.

[0016] In one implementation of this application, the hazard assessment in step 2 includes the following specific steps:

[0017] Step 21: Obtain the vegetation type and vegetation coverage of the corresponding slope. Obtain the root tensile strength of the corresponding vegetation by the vegetation type. Divide the root tensile strength safety value by the root tensile strength of the corresponding vegetation to obtain the root strength risk. Divide the vegetation coverage safety value by the vegetation coverage to obtain the coverage risk. Obtain the vegetation coverage impact value by multiplying the coverage risk and the root strength risk.

[0018] Step 22: Obtain future periodic precipitation data. Divide the future periodic precipitation data by the precipitation safety value to obtain the precipitation impact value. Compare the future precipitation with the safety threshold to quantify the dynamic threat of external climate loads to slope stability.

[0019] Step 23, obtain the risk situation influence value by weighted summation of the obtained vegetation coverage influence value and the precipitation influence value, obtain the risk situation danger assessment result by multiplication of the risk situation influence value and the reciprocal of the corresponding slope stability level, and obtain the risk situation danger assessment result by weighted summation and stability level linkage, which takes into account the long-term stability state and the short-term triggering factor.

[0020] In an implementation manner of the present application, the risk situation criticality analysis in step 3 comprises the following specific contents:

[0021] Step 31, obtain the slope height, the risk situation danger assessment result and the corresponding stone situation, and perform stone falling danger analysis by the stone situation, wherein the specific manner of the stone falling danger analysis is as follows: obtain the standard deviation of the average size, the average hardness and the average edge sharpness data of the stone from the corresponding standard value, obtain the danger coefficient of a single stone by weighted summation, obtain the stone quantity danger coefficient by the ratio of the average number of stones in the unit volume of soil in the slope to the standard number, and obtain the stone influence coefficient by multiplication of the stone quantity danger coefficient and the danger coefficient of a single stone.

[0022] Step 32, obtain the slope height anomaly by dividing the slope height by the corresponding slope height safety value, obtain the slope falling anomaly by weighted summation of the stone influence coefficient and the slope height anomaly, obtain the risk situation criticality result by multiplication of the slope falling anomaly and the risk situation danger assessment result, and obtain the result by coupling the slope height anomaly, the stone influence coefficient and the risk situation danger, which can be directly used for preferential processing of the risk situation of high and steep slope with sharp stones and optimization of emergency resource allocation.

[0023] In an implementation manner of the present application, the cable protection performance evaluation based on the tunnel cable situation in step 4 comprises the following specific contents:

[0024] Obtain the skin elasticity and the skin thickness situation of the corresponding cable, obtain the elasticity safety value by the ratio of the skin elasticity of the cable to the corresponding skin elasticity safety value, obtain the thickness safety value by the ratio of the skin thickness situation to the corresponding skin thickness safety value, obtain the cable protection performance by multiplication of the elasticity safety value and the thickness safety value, and reflect the protection effect of the skin on the cable by analyzing the ratio of the skin elasticity modulus of the corresponding cable to the safety elasticity modulus.

[0025] In an implementation manner of the present application, the cable damage anomaly analysis in step 5 comprises the following specific contents:

[0026] The obtained tunnel cable risk criticality analysis result and the obtained cable protection performance evaluation result are divided to obtain a cable damage anomaly analysis result corresponding to the tunnel cable, and the external environment threat and the cable self-protection capability are combined to avoid the limitation of single dimension evaluation.

[0027] In an implementation form of the present application, the step 6 comprises the following specific contents:

[0028] The cable damage anomaly analysis result of each power tunnel is compared with a corresponding cable damage anomaly analysis threshold value, a power tunnel with a cable damage anomaly analysis result greater than or equal to the corresponding cable damage anomaly analysis threshold value is set as a dangerous tunnel, and a power tunnel with a cable damage anomaly analysis result less than the corresponding cable damage anomaly analysis threshold value is set as a safe tunnel; the position of the dangerous tunnel and the cable damage anomaly analysis result are obtained, the cable damage anomaly analysis result is arranged in descending order, the dangerous tunnel is maintained and repaired in the descending order arrangement sequence, and a safety warning of the dangerous tunnel is performed, and the position of the dangerous tunnel is published to the maintenance personnel in the descending order arrangement sequence.

[0029] In a second aspect, the present application further provides a power tunnel entrance and exit and slope critical danger alarm monitoring system, comprising:

[0030] A data acquisition module acquires cable transmission conditions of a tunnel entrance and exit, stone conditions of a slope, and foundation conditions of the corresponding slope, and simultaneously acquires a precipitation condition estimated by a weather forecast;

[0031] A risk danger assessment module performs risk danger assessment based on vegetation conditions of the slope, the precipitation condition, and slope stability conditions;

[0032] A risk criticality analysis module performs risk criticality analysis based on the slope height, the risk danger assessment result, and corresponding stone danger conditions;

[0033] A protection performance analysis module performs cable protection performance evaluation based on tunnel cable conditions;

[0034] A damage anomaly analysis module performs cable damage anomaly analysis based on the risk criticality analysis result and the cable protection performance evaluation result;

[0035] A warning module sorts a power tunnel maintenance sequence through the cable damage anomaly analysis result, and performs a power tunnel maintenance warning.

[0036] In a third aspect, the present application provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program that can be invoked by the processor, and the processor executes a power tunnel entrance and slope critical danger information alarm monitoring method by invoking the computer program stored in the memory.

[0037] In a fourth aspect, the present application provides a computer readable storage medium storing instructions, which, when executed on a computer, cause the computer to execute a power tunnel entrance and slope critical danger information alarm monitoring method.

[0038] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0039] The present application predicts the slope stability through a multi-parameter fusion dynamic deep learning model, and performs power tunnel risk assessment and early warning in combination with multi-dimensional data such as vegetation, precipitation, stone characteristics, and cable protection performance. The core advantage is that:

[0040] (1) The neural network is trained using historical experimental data to dynamically evaluate the slope anti-collapse ability, overcoming the limitations of traditional experience;

[0041] (2) The vegetation mechanical effect, precipitation load, stone impact risk, and cable protection performance are comprehensively considered to quantify the criticality and damage abnormality of the cable danger. BRIEF DESCRIPTION OF DRAWINGS

[0042] Other features, objects and advantages of the present application will become more apparent from the following detailed description of the non-limiting embodiments, made with reference to the accompanying drawings:

[0043] Fig. 1 FIG. 1 is a schematic diagram of the overall process of the method embodiment 1 of the present application;

[0044] Fig. 2 FIG. 2 is a schematic diagram of step 2 of the method embodiment 1 of the present application;

[0045] Fig. 3 FIG. 3 is a schematic diagram of the structure of the system embodiment 2 of the present application. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0047] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from the description, and those skilled in the art can make similar generalizations without departing from the scope of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0048] Second, the "one embodiment" or "an embodiment" as used herein means that a particular implementation can include a particular feature, structure, or characteristic. However, such a phrase is not necessarily referring to the same implementation or the same feature, structure, or characteristic, but can refer to a different implementation or a different feature, structure, or characteristic.

[0049] Embodiment 1.

[0050] As shown in Figs. 1-2 The embodiment provides a power tunnel entrance and exit and slope critical danger information alarm monitoring method, and specifically comprises the following steps:

[0051] Step 1, acquire the cable transmission situation of the tunnel entrance and exit, the stone block situation of the slope, and the foundation situation of the corresponding slope, and acquire the precipitation situation estimated by the weather forecast, wherein the foundation situation of the slope includes the vegetation situation and the slope stability situation, wherein the slope stability is acquired by the viscosity of the soil layer corresponding to the slope, the slope of the slope, and the crack situation of the slope;

[0052] In the embodiment, the cable transmission condition of the tunnel entrance and exit in step 1 includes the skin elasticity and the skin thickness condition of the corresponding cable, which is used to quantify the protection performance of the skin of the corresponding cable, and is obtained through cable information statistics. The stone condition of the slope includes the average size of the stone, the average number of the stone in the unit volume of the soil of the slope, the average hardness, and the average edge sharpness data, which are used to evaluate the hard damage of the stone falling to the cable skin. The average size of the stone, the average hardness, and the average edge sharpness data are obtained through the stone information statistics of the corresponding position. The vegetation condition includes the vegetation type and the vegetation coverage condition, which are used to analyze the protection effect of the vegetation on the slope. The crack condition of the slope includes the length, the width, the depth, and the aggregation condition of the crack of the slope. The aggregation condition is the number of cracks per unit area. The slope stability analysis includes the following specific steps: obtaining the critical value of the rainfall borne by the collapsed slope in the historical experiment process. The critical value refers to that the corresponding slope collapses when the corresponding critical value is reached in the experimental environment. The range formed by the critical value of the rainfall borne by the collapsed slope in the historical experiment process is divided into 10 slope stability grades from large to small in average. The 10 grades indicate that a large amount of rainfall is needed to collapse, which indicates the best stability. The 1 grade indicates that the collapse occurs when the rainfall is very small, which indicates very weak stability. A deep learning neural network model is constructed based on the slope stability grade of the collapsed slope in the historical experiment process, and the adhesion of the soil layer of the experimental slope, the slope of the slope, and the crack condition of the slope. The input is the adhesion of the soil layer of the slope, the slope of the slope, and the crack condition of the slope. The output is the slope stability grade. The adhesion of the soil layer of the corresponding slope, the slope of the slope, and the crack condition of the slope are input into the constructed deep learning neural network model, and the output is the slope stability grade. This step constructs a deep learning model through historical experimental data. The specific steps are as follows: collect historical experimental data, including adhesion (such as cohesion c value), slope (angle a), crack condition (such as crack density / depth), and corresponding stability grade label (such as discretized into 1-10 levels), standardize numerical features, and encode crack text description (such as independent encoding or embedding layer); adopt a fully connected network (MLP) or a 1D convolutional network (CNN), the input layer has 3 nodes (adhesion, slope, and crack coding), the hidden layer includes a dense layer with ReLU activation (such as 128→64 nodes), the output layer uses Softmax activation (corresponding to 10 stability levels) and configures a cross-entropy loss function; divide the training set / test set in the ratio of 8:2, adjust the weight through the Adam optimizer, monitor the accuracy and F1 score (handle class imbalance) of the validation set, and use the early stopping method to prevent overfitting;The trained model is integrated into the slope monitoring system, and the real-time sensor data (such as soil detector, inclinometer, crack meter) is input to output the stability warning level, which can dynamically evaluate the slope stability level, avoid the limitations of traditional empirical formula, and combine the key parameters such as soil layer viscosity, slope and crack condition to more accurately predict the slope anti-collapse ability under different rainfall conditions, and provide a scientific basis for subsequent risk assessment; In this step, the historical critical rainfall reflects the hydrogeological response of different slopes under extreme conditions, and quantifies the relationship between water infiltration and soil strength decay; The soil layer viscosity directly affects the shear strength of the soil (such as the cohesion c value), and the higher the viscosity, the stronger the anti-sliding force; The increase of slope will increase the gravity component (downhill force), which follows the Mohr-Coulomb criterion; The crack condition aggravates the water permeability, reduces the effective stress of the soil, and promotes the formation of the sliding surface;

[0053] In this embodiment, the parameters of the application are collected by the corresponding data acquisition module (such as soil detector, inclinometer, crack meter), and the collected data is stored in the corresponding storage component for easy retrieval and use;

[0054] Step 2, based on the vegetation condition, rainfall condition and slope stability condition of the slope, the danger risk assessment is carried out;

[0055] In this embodiment, the danger risk assessment in step 2 includes the following specific steps:

[0056] Step 21, obtain the vegetation type and vegetation coverage rate of the corresponding slope, obtain the root tensile strength of the corresponding vegetation through the vegetation type, obtain the root strength danger by dividing the corresponding root tensile strength safety value by the root tensile strength of the corresponding vegetation, obtain the coverage rate danger by dividing the corresponding vegetation coverage rate by the vegetation coverage rate safety value, and obtain the vegetation coverage influence value by multiplying the coverage rate danger and the root strength danger. This scheme selects the most representative and influential features to reflect the influence of vegetation coverage. Other plant features that affect slope landslide are not represented in this scheme, but they can be considered by weighting. The root tensile strength and coverage rate quantify the protection effect of vegetation, simplify the influence of complex ecological factors, focus on core mechanical indicators, and facilitate rapid engineering evaluation. The root tensile strength directly determines the anchoring ability of the soil, the deep-rooted plant can enhance the anti-sliding torque, the coverage rate is positively correlated with the surface runoff reduction rate, high coverage rate reduces raindrop splash erosion, and the product relationship reflects the synergistic effect of vegetation “mechanical reinforcement” and “coverage root”;

[0057] Step 22, obtain the future period precipitation condition, divide the future period precipitation condition by the precipitation safety value to obtain the precipitation influence value, compare the future precipitation with the safety threshold, and quantify the dynamic threat of external climate load to the slope stability, which is especially suitable for early warning in monsoon regions or rainstorm-prone areas; the increase of precipitation increases the pore water pressure, reduces the effective stress, and causes the anti-sliding force to decrease;

[0058] Step 23, obtain the danger influence value by weighted summation of the obtained vegetation coverage influence value and the precipitation influence value, obtain the danger risk assessment result by multiplying the danger influence value by the reciprocal of the corresponding slope stability grade, and obtain the danger risk assessment result by weighted summation and stability grade linkage, which takes into account the long-term stable state and short-term triggering factors, and the weighted coefficient reflects the contribution weight of vegetation and precipitation to the landslide;

[0059] Step 3, based on the slope height, the danger risk assessment result, and the corresponding stone danger condition, analyze the danger criticality degree;

[0060] In this embodiment, the danger criticality degree analysis in step 3 includes the following specific contents:

[0061] Step 31, obtain the slope height, the danger risk assessment result, and the corresponding stone condition, and analyze the stone falling danger by the stone condition, wherein the specific way of the stone falling danger analysis is as follows: obtain the standard deviation of the average size, the average hardness, and the average edge sharpness data of the stone from the corresponding standard value, obtain the danger coefficient of a single stone by weighted summation, obtain the stone quantity danger coefficient by the ratio of the average number of stones in unit volume of soil to the standard number, and obtain the stone influence coefficient by multiplying the stone quantity danger coefficient by the danger coefficient of a single stone, wherein the stone here refers to hard blocks that can cause damage to the cable skin, including hard soil blocks and stone blocks or concrete blocks mixed in the slope, since the soil collapse only has pulling or pressure effect on the cable, and the stone can cause damage to the cable, this step quantifies the average size, hardness, edge sharpness, and unit volume quantity of the stone to accurately assess the potential damage risk of the stone to the cable skin, solves the problem that the traditional method only focuses on soil collapse and ignores the impact of hard blocks, the larger the volume, the higher the impact kinetic energy, the stronger the penetration, the stone with high Mohs hardness is more likely to scratch the cable insulation layer, the sharp edge stress concentration, and the local pressure is larger, resulting in the risk of puncture, the weighted summation reflects the contribution weight of different characteristics to the damage, and when the unit volume of stone number exceeds the standard value, the collision probability increases significantly;

[0062] Step 32, the slope height is divided by the corresponding slope height safety value to obtain the slope height anomaly, the stone block influence coefficient is weightedly summed with the slope height anomaly to obtain the slope falling anomaly, and the danger criticality result is obtained through the product of the slope falling anomaly and the danger risk assessment result, the coupling of the slope height anomaly, the stone block influence coefficient and the danger risk realizes the multi-dimensional criticality assessment of "geological structure anomaly + local hard block risk + overall stability", the result can be directly used for prioritizing the treatment of danger of high and steep slope with sharp stone blocks, optimizing the allocation of emergency resources, the high safety value is usually determined by the internal friction angle of the soil and the slope foot stability, the gravity potential of the super-high slope is greater, the collapse impact force is stronger, the ratio form is processed by dimensionless, which is convenient for cross-scale comparison, the weighted summation reflects the synergistic effect of stone block influence and height anomaly, the product operation reflects the danger risk amplification of stone block falling consequences, which conforms to the physical mechanism of "chain disaster";

[0063] Step 4, evaluating the cable protection performance based on the condition of the tunnel cable;

[0064] In this embodiment, the evaluation of the cable protection performance based on the condition of the tunnel cable in step 4 includes the following specific contents:

[0065] The skin elasticity and the skin thickness condition of the corresponding cable are obtained, the elastic safety value is obtained by the ratio of the skin elasticity of the cable to the corresponding skin elasticity safety value, the thickness safety value is obtained by the ratio of the skin thickness condition to the corresponding skin thickness safety value, the cable protection performance is obtained by multiplying the elastic safety value and the thickness safety value, and the protection effect of the skin on the cable is reflected by analyzing the ratio of the corresponding cable skin elastic modulus to the safety elastic modulus;

[0066] Step 5, analyzing the cable damage anomaly based on the danger criticality analysis result and the cable protection performance evaluation result;

[0067] In this embodiment, the cable damage anomaly analysis in step 5 includes the following specific contents:

[0068] The obtained danger criticality analysis result of the tunnel cable and the obtained evaluation result of the cable protection performance are obtained, the cable damage anomaly analysis result of the corresponding tunnel cable is obtained by dividing the danger criticality analysis result by the obtained evaluation result of the cable protection performance, the external environmental threat and the cable self-protection ability are combined to avoid the limitation of single-dimensional evaluation, for example, the actual damage risk of high and steep slope danger may be lower than expected if high elasticity and thick sheath cable is used, the static defects of traditional methods of "only focusing on environmental threat or only relying on cable specifications" are solved, and real-time risk dynamic correction is realized;

[0069] Step 6, sorting the power tunnel maintenance sequence through the cable damage anomaly analysis result, and warning the power tunnel maintenance;

[0070] In this embodiment, step 6 includes the following specific contents:

[0071] The cable damage anomaly analysis result of each power tunnel is compared with the corresponding cable damage anomaly analysis threshold value, the power tunnel with a cable damage anomaly analysis result greater than or equal to the corresponding cable damage anomaly analysis threshold value is set as a dangerous tunnel, and the power tunnel with a cable damage anomaly analysis result less than the corresponding cable damage anomaly analysis threshold value is set as a safe tunnel; the position and cable damage anomaly analysis result of the dangerous tunnel are obtained, the cable damage anomaly analysis result is arranged in descending order, the dangerous tunnel is maintained and repaired according to the descending order, and the safety warning of the dangerous tunnel is carried out, the position of the dangerous tunnel is published to the maintenance personnel in descending order, and the publication mode is to publish through wired or wireless mode, and the maintenance personnel maintain the specified dangerous tunnel according to the descending order;

[0072] It should be noted that the setting weight parameter and the setting threshold value of the present application are obtained by historical data experiments, and the specific obtaining steps can be,

[0073] Collect the relevant data of the previous slope stability experiment, cable damage experiment, etc. These data should include various parameters involved in the steps, such as the viscosity of the slope soil layer, the slope, the crack condition, the vegetation type, the vegetation coverage, the precipitation, the average size of the stone, the hardness, the edge sharpness, the number, the cable skin elasticity, the thickness, etc. At the same time, the corresponding experimental results are recorded, such as whether the slope collapses or the cable is damaged; collect the case data of the actual danger and damage of the power tunnel surrounding slope and cable, including the occurrence time, location, related parameter value and consequences, etc. Clean the collected data to remove duplicate, incorrect or missing data. For missing data, interpolation method (such as linear interpolation, spline interpolation) or estimation and supplement according to other related data can be used; take the danger criticality result and the cable damage anomaly analysis result as the dependent variable, and take each influencing factor (such as vegetation coverage influence value, precipitation influence value, stone influence coefficient, etc.) as the independent variable, establish a regression model (such as linear regression, nonlinear regression), estimate the coefficients of the regression model by least squares method, these coefficients are the weights of each influencing factor, and the weights are substituted into each step of the embodiment to calculate the cable damage anomaly analysis result; and the calculation result and the experimental result are imported into matlab fitting software for data fitting, and the threshold value meeting the maximum judgment accuracy is output.

[0074] Embodiment 2.

[0075] As Fig. 3As shown, the embodiment provides a power tunnel entrance and slope critical danger information alarm monitoring system, which is used for implementing the power tunnel entrance and slope critical danger information alarm monitoring method of embodiment 1, and specifically includes: a data acquisition module, which acquires cable transmission conditions of a tunnel entrance, stone block conditions of a slope, and basic conditions of the corresponding slope, and simultaneously acquires precipitation conditions estimated by weather forecasts;

[0076] a danger risk assessment module, which performs danger risk assessment based on vegetation conditions of the slope, precipitation conditions, and slope stability conditions;

[0077] a danger criticality analysis module, which performs danger criticality analysis based on the slope height, the danger risk assessment result, and the corresponding stone block danger conditions;

[0078] a protection performance analysis module, which performs cable protection performance assessment based on tunnel cable conditions;

[0079] a damage anomaly analysis module, which performs cable damage anomaly analysis based on the danger criticality analysis result and the cable protection performance assessment result;

[0080] a warning module, which sorts power tunnel maintenance sequences through the cable damage anomaly analysis result, and performs power tunnel maintenance warning, and the specific steps of each module of the embodiment of the system are the same as the specific steps of the method embodiment of embodiment 1, and will not be repeated here.

[0081] Embodiment 3.

[0082] The electronic device of the embodiment of the present application includes a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a power tunnel entrance and slope critical danger information alarm monitoring method by calling the computer program stored in the memory. It should be noted that all computer programs of the power tunnel entrance and slope critical danger information alarm monitoring method are implemented using C language.

[0083] Embodiment 4.

[0084] The embodiment provides a computer readable storage medium, which stores an erasable computer program;

[0085] When the computer program runs on the computer device, the computer device executes the power tunnel entrance and slope critical danger information alarm monitoring method.

[0086] The above-described embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented by software, the above-described embodiments can 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 according to the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can 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 can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, and the like, which includes one or more available medium collections. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0087] Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed in the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0088] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device, and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0089] In several embodiments provided in the present application, it should be understood that the disclosed system, device, and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of units is only one, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices, or units, which can be electrical, mechanical, or other forms.

[0090] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0091] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit.

[0092] In the description of the specification, the description referring to the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are contained in at least one embodiment or example of the present application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0093] The basic principles and main features of the present application and the advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only illustrative of the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A power tunnel portal and slope critical danger information alarm monitoring method, characterized in that, The method comprises the following steps: Step 1, obtaining cable transmission conditions of a tunnel entrance and exit, stone block conditions of a slope, and foundation conditions of the corresponding slope, and obtaining a rainfall condition estimated by a weather forecast, wherein the foundation conditions of the slope include vegetation conditions and slope stability conditions, and the slope stability is obtained from the viscosity of a soil layer corresponding to the slope, the slope gradient, and the crack conditions of the slope; Step 2, performing a danger risk assessment based on the vegetation conditions of the slope, the rainfall condition, and the slope stability conditions; The danger risk assessment in Step 2 comprises the following specific steps: Step 21, obtaining vegetation types and vegetation coverage conditions of the corresponding slope, obtaining root tensile strength of the corresponding vegetation through the vegetation types, obtaining a root strength risk by dividing the corresponding root tensile strength safety value by the root tensile strength of the corresponding vegetation, obtaining a coverage risk by dividing the corresponding vegetation coverage safety value by the vegetation coverage, and obtaining a vegetation coverage influence value by multiplying the coverage risk and the root strength risk; Step 22, obtaining a future period rainfall condition, and obtaining a rainfall influence value by dividing the future period rainfall condition by a rainfall safety value; Step 23, obtaining a danger influence value by weighted sum of the obtained vegetation coverage influence value and the rainfall influence value, and obtaining a danger risk assessment result by multiplying the danger influence value and the reciprocal of a corresponding slope stability grade; Step 3, performing a danger criticality analysis based on the slope height, the danger risk assessment result, and the corresponding stone block danger conditions; Step 4, performing an evaluation of cable protection performance based on the tunnel cable conditions; Step 5, performing a cable damage anomaly analysis based on the danger criticality analysis result and the cable protection performance evaluation result; Step 6, performing a sorting of power tunnel maintenance sequences through the cable damage anomaly analysis result, and performing a power tunnel maintenance early warning.

2. The power tunnel entrance and side slope critical danger information alarm monitoring method according to claim 1, characterized in that, The cable transmission condition of the tunnel entrance and exit in step 1 includes the skin elasticity and the skin thickness condition of the corresponding cable, the stone condition of the slope includes the average size, the average number of stones in the unit volume of soil, the average hardness and the average edge sharpness data of the stones, the vegetation condition includes the vegetation type and the vegetation coverage condition, and the crack condition of the slope includes the length, the width, the depth and the aggregation condition of the cracks in the slope, the aggregation condition is the number of cracks per unit area. The slope stability analysis includes the following specific steps: obtaining the critical value of the rainfall of the collapsed slope in the historical experiment process, the critical value is that the corresponding slope collapses when reaching the corresponding critical value in the experimental environment, dividing the range formed by the critical value of the rainfall of the collapsed slope in the historical experiment process into 10 slope stability grades from large to small on average, constructing a deep learning neural network model with the input of the soil layer viscosity of the experimental slope, the slope of the slope and the crack condition of the slope and the output of the slope stability grade, and inputting the soil layer viscosity, the slope of the slope and the crack condition of the slope of the corresponding slope into the constructed deep learning neural network model to output the slope stability grade.

3. The power tunnel portal and slope critical danger information alarm monitoring method according to claim 2, characterized in that, The risk criticality analysis in step 3 includes the following specific contents: Step 31, obtaining the slope height, the risk danger assessment result and the corresponding stone condition, and analyzing the stone falling danger through the stone condition, wherein the specific way of the stone falling danger analysis is: obtaining the standard deviation of the average size, the average hardness and the average edge sharpness data of the stones respectively with the corresponding standard value, obtaining the danger coefficient of a single stone after weighted summation, obtaining the stone quantity danger coefficient through the ratio of the average number of stones in the unit volume of soil to the standard number, and obtaining the stone influence coefficient by multiplying the stone quantity danger coefficient and the danger coefficient of a single stone; Step 32, dividing the slope height by the corresponding slope height safety value to obtain the slope height anomaly, weighted summing the stone influence coefficient and the slope height anomaly to obtain the slope falling anomaly, and obtaining the risk criticality result by multiplying the slope falling anomaly and the risk danger assessment result.

4. The power tunnel portal and slope critical danger information alarm monitoring method according to claim 3, characterized in that, The cable protection performance evaluation based on the tunnel cable condition in step 4 includes the following specific contents: Obtaining the skin elasticity and the skin thickness condition of the corresponding cable, obtaining the elasticity safety value through the ratio of the skin elasticity of the cable to the corresponding skin elasticity safety value, obtaining the thickness safety value through the ratio of the skin thickness condition to the corresponding skin thickness safety value, and obtaining the cable protection performance by multiplying the elasticity safety value and the thickness safety value.

5. The power tunnel portal and slope critical danger information alarm monitoring method according to claim 4, characterized in that, The cable damage anomaly analysis in step 5 includes the following specific contents: Obtaining the risk criticality analysis result of the tunnel cable and the evaluation result of the cable protection performance, and obtaining the cable damage anomaly analysis result of the corresponding tunnel cable by dividing the risk criticality analysis result by the evaluation result of the cable protection performance.

6. The power tunnel portal and slope critical danger information alarm monitoring method according to claim 5, characterized in that, The step 6 includes the following specific contents: The cable damage abnormality analysis result of each power tunnel is compared with the corresponding cable damage abnormality analysis threshold value, the power tunnel with the cable damage abnormality analysis result greater than or equal to the corresponding cable damage abnormality analysis threshold value is set as a dangerous tunnel, and the power tunnel with the cable damage abnormality analysis result less than the corresponding cable damage abnormality analysis threshold value is set as a safe tunnel; the position of the dangerous tunnel and the cable damage abnormality analysis result are obtained, the cable damage abnormality analysis result is arranged in descending order, the dangerous tunnel is maintained and repaired according to the descending order, and the safety warning of the dangerous tunnel is performed, and the position of the dangerous tunnel is published to the maintenance personnel according to the descending order.

7. A power tunnel portal and slope critical danger information alarm monitoring system for implementing the power tunnel portal and slope critical danger information alarm monitoring method according to any one of claims 1-6, characterized in that, The system comprises: a data acquisition module, which acquires the cable transmission condition of the tunnel entrance and exit, the stone condition of the side slope, and the foundation condition of the corresponding side slope, and simultaneously acquires the precipitation condition estimated by the weather forecast; a dangerous situation danger assessment module, which performs dangerous situation danger assessment based on the vegetation condition of the side slope, the precipitation condition, and the side slope stability condition; a dangerous situation criticality analysis module, which performs dangerous situation criticality analysis based on the side slope height, the dangerous situation danger assessment result, and the corresponding stone danger condition; a protection performance analysis module, which performs cable protection performance assessment based on the tunnel cable condition; a damage abnormality analysis module, which performs cable damage abnormality analysis based on the dangerous situation criticality analysis result and the cable protection performance assessment result; a warning module, which performs power tunnel maintenance sequence sorting and power tunnel maintenance warning through the cable damage abnormality analysis result.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes a power tunnel entrance and exit and side slope dangerous situation warning monitoring method according to any one of claims 1-6 by calling the computer program stored in the memory.

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