Comprehensive evaluation and prediction method for typical construction risk of deep shaft

Abstract

The invention belongs to the field of construction risk comprehensive evaluation and prediction, and provides a deep shaft typical construction risk comprehensive evaluation and prediction method. Comprising the steps of obtaining a water inrush characteristic value, a rockburst index characteristic value and a heat damage characteristic value, constructing a water inrush index matrix, calculating a water inrush index weight, matching a water inrush risk grade, calculating a rockburst index weight, calculating an attribution degree, matching the rockburst risk grade, calculating heat damage heat dissipating capacity data, matching the heat damage risk grade and controlling signal lamps. According to the method, through the water inrush risk grade, the rockburst risk grade and the heat damage risk grade, comprehensive evaluation and prediction of construction risks and autonomous classification of risk degrees are realized, and the accuracy and reliability of risk prediction are improved.

Description

Technical Field

[0001] The invention relates to the field of comprehensive evaluation and prediction of construction risks, and in particular to a comprehensive evaluation and prediction method for typical construction risks of deep shafts. Background Art

[0002] With the continuous deepening of mineral resource mining, deep metal mining projects are facing more and more risks and challenges. Engineering disasters such as rock bursts, water inrush and heat damage occur frequently, which have a serious impact on the safe production of mines and the safety of personnel. The geological environment faced by deep metal mining is extremely complex, with variable stratum structures and different rock properties. This complex geological environment has brought great challenges to the safe production of mines. Engineering disasters such as rock bursts, water inrush and heat damage are one of the most common risks in deep metal mining. These disasters are often sudden, destructive and unpredictable, and once they occur, they may cause serious casualties and property losses. The occurrence of mining accidents will not only cause casualties and property damage, but also have a profound adverse impact on the normal operation and economic benefits of mines. When a rock burst occurs, the ejected rock fragments may cause direct harm to personnel, and in severe cases may even cause casualties; the shock wave and ejected rock fragments generated by the rock burst may damage the equipment and facilities underground, affecting the normal production of the mine; rock bursts may cause ruptures and deformations in the roof and two sides of the tunnel, and in severe cases may even cause the overall instability and collapse of the tunnel. Working in a high-temperature environment for a long time can cause underground workers to suffer from health problems such as heat stroke and heat stroke. In severe cases, it may even cause chronic diseases such as heart disease and hypertension, which not only affects the miners' quality of life and work efficiency, but may also endanger their lives. In addition, a high-temperature environment can easily make miners feel tired and sleepy, reduce work efficiency and reaction ability, and increase the risk of safety accidents. At the same time, high temperatures may also cause safety hazards such as equipment overheating and electrical fires.

[0003] Patent CN 116910886 A provides an impact energy early warning method and system in karst areas, which realizes the prediction and early warning of risks.

[0004] However, the existing risk prediction models for construction risks are relatively simple, with fewer data sources and poor reliability in predicting risks. Summary of the invention

[0005] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a comprehensive evaluation and prediction method for typical construction risks of deep shafts, which can realize comprehensive evaluation and prediction of construction risks and autonomous classification of risk levels through water inrush risk level, rock burst risk level and thermal damage risk level, so as to improve the accuracy and reliability of risk prediction.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A comprehensive evaluation and prediction method for typical construction risks of deep shafts, including:

[0008] Determine a water inrush risk index, a rock burst risk index, and a heat damage risk index, and assign characteristic values ​​to the water inrush risk index, the rock burst risk index, and the heat damage risk index, respectively, to obtain a water inrush characteristic value, a rock burst indicator characteristic value, and a heat damage characteristic value;

[0009] Constructing a water inrush hierarchy structure, and constructing a matrix of the water inrush risk indicators according to the water inrush hierarchy structure to obtain a water inrush indicator matrix;

[0010] Normalizing the column vectors of the water inrush index matrix and summing the column vectors to obtain the water inrush index weights;

[0011] Calculating a water inrush evaluation index according to the water inrush characteristic value and the water inrush index weight, and classifying the water inrush evaluation index in combination with a natural breakpoint method to obtain a water inrush risk level;

[0012] Based on the random forest algorithm, importance classification and rockburst hierarchy structure are performed according to the rockburst risk indicators to obtain a rockburst indicator matrix, and the weight of the rockburst indicator matrix is ​​calculated to obtain the rockburst indicator weight;

[0013] Based on the cloud model theory, a Gaussian cloud map is generated according to the characteristic value of the rockburst index, and the attribution degree of the rockburst risk index is calculated using the Gaussian cloud map;

[0014] Determining a rockburst risk level according to the rockburst indicator weight and the attribution degree;

[0015] Calculating the heat damage characteristic value to obtain heat damage heat dissipation data;

[0016] According to the preset enthalpy value, the relative humidity and relative temperature of the prediction point are calculated using the heat damage heat dissipation data, and the relative humidity and the relative temperature are compared with the heat damage warning threshold to obtain the heat damage risk level;

[0017] The luminous color of the signal light is controlled according to the water inrush risk level, the rock burst risk level and the thermal damage risk level.

[0018] Preferably, the water inrush risk indicators include: structural fracture zone, fault fracture zone, water richness, water inrush point, water conductivity and stress level; the rock burst risk indicators include: maximum tangential stress of surrounding rock, rock elastic energy index, rock brittleness index and Russenes criterion; the thermal damage risk indicators include: thermal damage warning threshold, initial point wind flow temperature, initial point rock temperature, geothermal gradient around the mine, formation isothermal zone elevation and rock temperature and working face relative humidity gradient.

[0019] Preferably, the water inrush risk levels include: low water inrush risk, medium water inrush risk, relatively high water inrush risk and high water inrush risk; the rock burst risk levels include: no rock burst risk, slight rock burst risk, medium rock burst risk and severe rock burst risk; the heat damage risk levels include: no heat damage risk, slight heat damage risk and severe heat damage risk.

[0020] Preferably, according to the water inrush risk level, the rock burst risk level and the thermal damage risk level, controlling the signal light to change the luminous color comprises:

[0021] When the water inrush risk level is low water inrush risk, or the rock burst risk level is no rock burst risk, or the heat damage risk level is no heat damage risk, controlling the signal light to display green light;

[0022] When the water inrush risk level is a medium water inrush risk or the rock burst risk level is a slight rock burst risk, controlling the signal light to display blue;

[0023] When the water inrush risk level is a high water inrush risk, or the rock burst risk level is a medium rock burst risk, or the heat damage risk level is a slight heat damage risk, controlling the signal light to display purple;

[0024] When the water inrush risk level is a high water inrush risk, or the rock burst risk level is a severe rock burst risk, or the heat damage risk level is a severe heat damage risk, the signal light is controlled to display red.

[0025] Preferably, the calculation formula for the rockburst risk level is: μ i is the i-th attribute degree; w i is the weight of the i-th rockburst indicator; F is the risk parameter corresponding to the rockburst risk level; and n is the number of the rockburst risk indicators.

[0026] Preferably, the formula for judging the heat damage risk level is: t is the relative temperature.

[0027] Preferably, the calculation formula of the water inrush evaluation index is: F w is the water inrush evaluation index; W i is the weight of the water inrush index of the ith item; f i is the i-th water inrush characteristic value; m is the number of water inrush risk indicators.

[0028] Preferably, the formula for judging the water inrush risk level is:

[0029]

[0030] The present invention discloses the following technical effects:

[0031] The present invention provides a comprehensive evaluation and prediction method for typical construction risks of deep vertical shafts. Through water inrush characteristic values ​​and water inrush index weights, the problem of obtaining water inrush evaluation indexes is solved, and the classification of water inrush risk levels is realized; through rock burst index weights and attribution degrees, the problem of rock burst risk level judgment data source is solved, and the judgment of construction rock burst risks is realized; through water inrush risk levels, rock burst risk levels and thermal damage risk levels, the problem of indicator light display is solved, and autonomous control of indicator light display is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0033] Figure 1 A flow chart of a method for comprehensive evaluation and prediction of typical deep shaft construction risks provided by an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of a typical deep shaft construction risk comprehensive evaluation and prediction system provided by an embodiment of the present invention;

[0035] Figure 3 A schematic diagram of the interface of a rockburst engineering risk prediction program provided by an embodiment of the present invention;

[0036] Figure 4 A schematic diagram of the interface of a thermal damage engineering risk prediction program provided by an embodiment of the present invention;

[0037] Figure 5 A schematic diagram of the interface of a water inrush engineering risk prediction program provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] The purpose of the present invention is to provide a comprehensive evaluation and prediction method for typical construction risks of deep shafts. Through the water inrush risk level, rock burst risk level and thermal damage risk level, the comprehensive evaluation and prediction of construction risks and the autonomous classification of risk levels can be achieved to improve the accuracy and reliability of risk prediction.

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0041] Figure 1 A flowchart of a method for comprehensive evaluation and prediction of typical deep shaft construction risks provided by an embodiment of the present invention, Figure 2 A schematic diagram of a typical deep shaft construction risk comprehensive evaluation and prediction system provided by an embodiment of the present invention, such as Figure 1 and Figure 2 As shown, the present invention provides a comprehensive evaluation and prediction method for typical construction risks of deep shafts, comprising:

[0042] Step 100: determining a water inrush risk index, a rock burst risk index, and a thermal damage risk index, and assigning characteristic values ​​to the water inrush risk index, the rock burst risk index, and the thermal damage risk index, respectively, to obtain a water inrush characteristic value, a rock burst indicator characteristic value, and a thermal damage characteristic value;

[0043] Step 200: constructing a water inrush hierarchy structure, and constructing a matrix of the water inrush risk index according to the water inrush hierarchy structure to obtain a water inrush index matrix;

[0044] Step 300: performing column vector normalization and column vector summation on the water inrush index matrix to obtain a water inrush index weight;

[0045] Step 400: Calculating a water inrush evaluation index according to the water inrush characteristic value and the water inrush index weight, and classifying the water inrush evaluation index in combination with a natural breakpoint method to obtain a water inrush risk level;

[0046] Step 500: Based on the random forest algorithm, importance classification and rockburst hierarchy structure are performed according to the rockburst risk indicators to obtain a rockburst indicator matrix, and the weight of the rockburst indicator matrix is ​​calculated to obtain a rockburst indicator weight;

[0047] Step 600: Based on the cloud model theory, a Gaussian cloud map is generated according to the characteristic value of the rockburst index, and the attribution degree of the rockburst risk index is calculated using the Gaussian cloud map;

[0048] Step 700: determining the rockburst risk level according to the rockburst indicator weight and the attribution degree;

[0049] Step 800: Calculate the heat damage characteristic value to obtain heat damage heat dissipation data;

[0050] Step 900: Calculate the relative humidity and relative temperature of the prediction point according to the preset enthalpy value using the heat damage heat dissipation data, and compare the relative humidity and the relative temperature with the heat damage warning threshold to obtain the heat damage risk level;

[0051] Step 1000: Control the luminous color of the signal light according to the water inrush risk level, the rock burst risk level and the thermal damage risk level.

[0052] Specifically, the water inrush risk indicators include: structural fracture zone, fault fracture zone, water richness, water inrush point, water conductivity and stress level; the rock burst risk indicators include: maximum tangential stress of surrounding rock, rock elastic energy index, rock brittleness index and Russenes criterion; the thermal damage risk indicators include: thermal damage warning threshold, initial point wind flow temperature, initial point rock temperature, geothermal gradient around the mine, formation isothermal zone elevation and rock temperature and working face relative humidity gradient.

[0053] Specifically, the water inrush risk levels include: low water inrush risk, medium water inrush risk, relatively high water inrush risk and high water inrush risk; the rock burst risk levels include: no rock burst risk, slight rock burst risk, medium rock burst risk and severe rock burst risk; the heat damage risk levels include: no heat damage risk, slight heat damage risk and severe heat damage risk.

[0054] Further, according to the water inrush risk level, the rock burst risk level and the heat damage risk level, controlling the signal light to change the light color includes:

[0055] When the water inrush risk level is low water inrush risk, or the rock burst risk level is no rock burst risk, or the heat damage risk level is no heat damage risk, controlling the signal light to display green light;

[0056] When the water inrush risk level is a medium water inrush risk or the rock burst risk level is a slight rock burst risk, controlling the signal light to display blue;

[0057] When the water inrush risk level is a high water inrush risk, or the rock burst risk level is a medium rock burst risk, or the heat damage risk level is a slight heat damage risk, controlling the signal light to display purple;

[0058] When the water inrush risk level is a high water inrush risk, or the rock burst risk level is a severe rock burst risk, or the heat damage risk level is a severe heat damage risk, the signal light is controlled to display red.

[0059] Specifically, the calculation formula of the rockburst risk level is: μ i is the i-th attribute degree; w iis the weight of the i-th rockburst indicator; F is the risk parameter corresponding to the rockburst risk level; and n is the number of the rockburst risk indicators.

[0060] Furthermore, the formula for judging the heat damage risk level is: t is the relative temperature.

[0061] Specifically, the calculation formula of the water inrush evaluation index is: F w is the water inrush evaluation index; W i is the weight of the water inrush index of the ith item; f i is the i-th water inrush characteristic value; m is the number of water inrush risk indicators.

[0062] Furthermore, the formula for judging the water inrush risk level is:

[0063]

[0064] Specifically, structural fracture zone: The existence of structural fractures is conducive to the formation of water channels and increases the risk of water inrush. The geological characteristics can be observed through drilling cores, and the sound velocity characteristics can be identified by using acoustic logging technology to determine the development of structural fracture zones. Fault fracture zone: Groundwater often accumulates in fault fracture zones. The rock quality in this area is poor, the water resistance is poor, and the water conductivity is strong, which is very prone to water inrush accidents. The distribution of fault fracture zones can be shown based on the characteristics of drilling cores. Water richness: Abundant groundwater is a prerequisite for water inrush. The presence of water layers will weaken the strength of the rock mass, increase the permeability of the rock mass, and increase the probability of water inrush. The water richness of the formation can be evaluated through drilling and pumping tests. Water inrush point: The water inrush point is identified by using two methods: fluid diffusion method and temperature anomaly zone identification. The fluid diffusion method determines the water outlet location by testing the resistivity change of the fluid in the well, while the temperature anomaly method determines it based on the temperature change before and after the formation is pumped. If both methods determine that the water inrush point is a high water inrush point, otherwise it is determined to be a low water inrush point or no water inrush point. Water conductivity: The velocity and flow rate of groundwater flow are affected by the water conductivity of the rock formation. The water conductivity of the rock formation is evaluated by analyzing the lithology and the thickness of the aquiclude. Stress level: During the stress change process, the permeability of the rock may change, forming a water-conducting channel. The stress level of the formation can be determined based on the ground stress test, rock damage and permeability assessment. Due to the different evaluation criteria of the above indicators, different characteristic values ​​can be assigned to different indicators for the convenience of calculation, and the weights corresponding to different indicators can be obtained through the hierarchical analysis method, as shown in Table 1

[0065] Table 1

[0066]

[0067]

[0068] Specifically, in order to realize the comprehensive evaluation and prediction method of typical deep shaft construction risks, this embodiment designs a rock burst engineering risk prediction program, a thermal damage engineering risk prediction program, and a water inrush engineering risk prediction program through MATLAB software.

[0069] Furthermore, the operation process of the rockburst engineering risk prediction program includes:

[0070] 1) Determine the input indicators as the maximum tangential stress of the surrounding rock, the rock elastic energy index, the rock brittleness index, and the rock Russenes criterion. Construct an analysis matrix based on the importance of the rockburst evaluation indicators determined by the random forest algorithm, solve the weights corresponding to different rockburst indicators, and display the weight values ​​on the interface.

[0071] 2) Combine the cloud model theory to generate Gaussian cloud maps of different rockburst evaluation indicators, calculate the degree of attribution of each benchmark corresponding to different rockburst intensity levels, solve the comprehensive certainty of different rockburst intensity levels, and display the calculation results on the interface.

[0072] 3) The rockburst intensity level corresponding to the maximum value of the comprehensive certainty is taken as the final rockburst intensity level, and the risk level result is output on the interface, indicated by the color of the signal light (green represents no rockburst risk, blue represents slight rockburst risk, purple represents moderate rockburst risk, and red represents strong rockburst risk). In addition to the basic data input and calculation functions, data saving, exporting and printing are also realized. The interface of the deep mine rockburst risk prediction program function module is as follows Figure 3 shown.

[0073] Specifically, the operation process of the thermal damage engineering risk prediction program includes:

[0074] 1) Determine the input indicators as the heat damage warning threshold, the initial point wind flow temperature, the initial point rock temperature, the geothermal gradient around the mine, the elevation of the constant temperature zone of the formation and the rock temperature, and the relative humidity gradient of the working face, and calculate the air humidity, the initial point saturated vapor pressure, the initial point atmospheric pressure, the relative humidity of the prediction point, the initial point space-time density, and the initial point wind flow enthalpy.

[0075] 2) Based on the calculation formulas for different heat release of tunnel types, the heat dissipation of the air inlet shaft between the initial point and the predicted point, the heat dissipation of the tunnel surrounding rock, the heat dissipation of the transported ore, the heat dissipation of the tunnel wall oxidation, the heat dissipation of electromechanical equipment, the heat dissipation of local fans, the heat dissipation of sudden water and the heat dissipation of personnel are obtained, and the heat dissipation values ​​are displayed one by one in the interface.

[0076] 3) Based on the overall heat dissipation value and the enthalpy value of the prediction point, the relative humidity and temperature of the prediction point are solved, and the final degree of heat damage is obtained by comparing with the heat damage warning prefabrication, which is indicated by the color of the signal light (green represents no heat damage risk: t<28℃; purple represents slight heat damage risk 28℃≤t≤32℃, and red represents strong heat damage risk, t>32℃). In addition to basic data input and calculation functions, data saving, exporting and printing are also realized. The deep mine heat damage risk prediction program function modules are as follows: Figure 4 shown.

[0077] Furthermore, the operation process of the water inrush project risk prediction program includes:

[0078] Twenty engineering points in a gold mine were selected to solve the water inrush evaluation index values ​​corresponding to different points, and compared with the actual water inrush point conditions to obtain Table 2. The natural breakpoint method was used to classify the water inrush index and water inrush characteristics.

[0079] Table 2

[0080]

[0081]

[0082] 1) Determine the input indicators as structural fracture zone, fault fracture zone, water richness, water inrush point, water conductivity, and stress level, and assign characteristic values ​​to the water inrush indicators at the calculation points according to Table 1.

[0083] 2) Based on the principle of hierarchical analysis, an analysis matrix is ​​constructed for the water inrush risk index. The corresponding weight value of each index is calculated through the procedures of column vector normalization and column vector summation, and the results are displayed in the interface.

[0084] 3) The water inrush evaluation index F is calculated based on the risk index weight and characteristic value w , combined with the classification of water inrush risk by the Natural Breaks method, the corresponding water inrush level of the predicted point is finally output and indicated by the color of the signal light (green represents low water inrush risk, blue represents medium water inrush risk, purple represents high water inrush risk, and red represents high water inrush risk). In addition to basic data input and calculation functions, data saving, exporting and printing are also realized. Deep mine thermal risk prediction program function modules such as Figure 5 shown.

[0085] The beneficial effects of the present invention are as follows:

[0086] The present invention realizes comprehensive evaluation and prediction of construction risks and autonomous classification of risk degrees through water inrush risk levels, rock burst risk levels and thermal damage risk levels, thereby improving the accuracy and reliability of risk prediction.

[0087] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0088] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A comprehensive evaluation and prediction method for typical construction risks of deep shafts, characterized in that: include: Determine a water inrush risk index, a rock burst risk index, and a thermal damage risk index, and assign characteristic values ​​to the water inrush risk index, the rock burst risk index, and the thermal damage risk index, respectively, to obtain a water inrush characteristic value, a rock burst indicator characteristic value, and a thermal damage characteristic value; Constructing a water inrush hierarchy structure, and constructing a matrix of the water inrush risk indicators according to the water inrush hierarchy structure to obtain a water inrush indicator matrix; Normalizing the column vectors of the water inrush index matrix and summing the column vectors to obtain the water inrush index weights; Calculating a water inrush evaluation index according to the water inrush characteristic value and the water inrush index weight, and classifying the water inrush evaluation index in combination with a natural breakpoint method to obtain a water inrush risk level; Based on the random forest algorithm, the importance of the rockburst risk indicators is graded and the rockburst hierarchy is constructed to obtain a rockburst indicator matrix, and the weight of the rockburst indicator matrix is ​​calculated to obtain the rockburst indicator weight; Based on the cloud model theory, a Gaussian cloud map is generated according to the characteristic value of the rockburst index, and the attribution degree of the rockburst risk index is calculated using the Gaussian cloud map; Determining a rockburst risk level according to the rockburst indicator weight and the attribution degree; Calculating the heat damage characteristic value to obtain heat damage heat dissipation data; According to the preset enthalpy value, the relative humidity and relative temperature of the prediction point are calculated using the heat damage heat dissipation data, and the relative humidity and the relative temperature are compared with the heat damage warning threshold to obtain the heat damage risk level; The luminous color of the signal light is controlled according to the water inrush risk level, the rock burst risk level and the thermal damage risk level.

2. A method for comprehensive evaluation and prediction of typical construction risks of deep shafts according to claim 1, characterized in that: The water inrush risk indicators include: structural fracture zone, fault fracture zone, water richness, water inrush point, water conductivity and stress level; the rock burst risk indicators include: maximum tangential stress of surrounding rock, rock elastic energy index, rock brittleness index and Russenes criterion; the thermal damage risk indicators include: thermal damage warning threshold, initial point wind flow temperature, initial point rock temperature, geothermal gradient around the mine, formation constant temperature zone elevation and rock temperature and working face relative humidity gradient.

3. A method for comprehensive evaluation and prediction of typical deep shaft construction risks according to claim 1, characterized in that: The water inrush risk levels include: low water inrush risk, medium water inrush risk, relatively high water inrush risk and high water inrush risk; the rock burst risk levels include: no rock burst risk, slight rock burst risk, medium rock burst risk and severe rock burst risk; the heat damage risk levels include: no heat damage risk, slight heat damage risk and severe heat damage risk.

4. A method for comprehensive evaluation and prediction of typical construction risks of deep shafts according to claim 1, characterized in that: According to the water inrush risk level, the rock burst risk level and the heat damage risk level, controlling the signal light to change the light color includes: When the water inrush risk level is low water inrush risk, or the rock burst risk level is no rock burst risk, or the heat damage risk level is no heat damage risk, controlling the signal light to display green light; When the water inrush risk level is a medium water inrush risk or the rock burst risk level is a slight rock burst risk, controlling the signal light to display blue; When the water inrush risk level is a high water inrush risk, or the rock burst risk level is a medium rock burst risk, or the heat damage risk level is a slight heat damage risk, controlling the signal light to display purple; When the water inrush risk level is a high water inrush risk, or the rock burst risk level is a severe rock burst risk, or the heat damage risk level is a severe heat damage risk, the signal light is controlled to display red.

5. A method for comprehensive evaluation and prediction of typical deep shaft construction risks according to claim 1, characterized in that: The calculation formula of the rockburst risk level is: μ i is the i-th attribute degree; w i is the weight of the i-th rockburst indicator; F is the risk parameter corresponding to the rockburst risk level; and n is the number of the rockburst risk indicators.

6. A method for comprehensive evaluation and prediction of typical construction risks of deep shafts according to claim 1, characterized in that: The formula for judging the heat damage risk level is: t is the relative temperature.

7. A method for comprehensive evaluation and prediction of typical construction risks of deep shafts according to claim 1, characterized in that: The calculation formula of the water inrush evaluation index is: F w is the water inrush evaluation index; W i is the weight of the water inrush index of the ith item; f i is the i-th water inrush characteristic value; m is the number of water inrush risk indicators.

8. A method for comprehensive evaluation and prediction of typical deep shaft construction risks according to claim 1, characterized in that: The formula for judging the water inrush risk level is:

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