Physical exploration construction safety level classification method and device and storage medium

Abstract

The invention discloses a physical exploration construction safety level classification method and device and a storage medium, and belongs to the field of physical exploration. The construction safety level classification method provided by the invention comprises the steps of collecting and analyzing data, determining risk factors and risk assessment indexes, classifying risk assessment levels and the like, and various factors such as terrain, weather, man-made and equipment are considered in the establishment process of the classification method. And quantifying evaluation indexes such as occurrence probabilities, hazard degrees and exposure time of different risk factors, obtaining risk evaluation scores according to a PTD safety evaluation method, determining construction safety levels, and formulating different construction safety measures and precautionary measures. The method provided by the invention not only can realize automatic processing and analysis of data and improve the efficiency of risk assessment, but also can improve the scientificity and effectiveness of risk assessment, ensures the safety and sustainability of exploration work, and provides a scientific basis for risk management.

Description

Technical Field

[0001] The invention belongs to the field of physical exploration, and relates to a terrain safety level classification method, in particular to a physical exploration construction safety level classification method, equipment and storage medium. Background Art

[0002] The seismic exploration industry is a high-risk industry, and there are many potential risks in its construction process. For example, there may be natural disasters such as debris flow and landslide caused by earthquakes, or accidents such as casualties and equipment damage caused by improper operation of exploration equipment. The degree of these risks varies depending on factors such as terrain, climate, and geological conditions.

[0003] Existing common safety analysis methods such as probabilistic safety analysis (PSA) are often too complex to cope with the diversity of construction projects and are not flexible enough when facing temporary risks. At the same time, other methods lack specific data on construction projects, resulting in inaccurate final results.

[0004] Traditional exploration risk assessment methods are usually based on experience and manual judgment, which are subjective and uncertain, and lack scientific basis and quantitative indicators. Therefore, they often cannot fully and accurately assess the risk situation of the exploration area, making it difficult to accurately assess the risk level of the work area, and are unable to effectively provide corresponding control measures and emergency plans. Summary of the invention

[0005] In order to overcome the shortcomings of traditional exploration risk assessment methods, which lack scientific basis and quantitative indicators and cannot comprehensively and accurately assess the risk situation of the exploration area, or the PSA safety analysis method is not flexible enough or lacks specific data, the present invention proposes a physical exploration construction safety level classification method, which comprehensively considers multiple risk factors such as terrain, meteorology, environment, equipment, etc. and quantifies them, so as to achieve the purpose of comprehensively assessing the risks in the construction process and realize scientific and reasonable safety level classification of different terrains.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A physical exploration construction safety level classification method, the classification method comprises the following steps performed in sequence:

[0008] S1. Collection and analysis of data

[0009] Collect and analyze topographic data, geological data, meteorological data, historical earthquake disaster data, and construction accident data of the target construction area to obtain data analysis results;

[0010] S2. Determination of risk factors and risk assessment indicators

[0011] Based on the data analysis results, determine the risk factors in the construction process;

[0012] Determine corresponding risk assessment indicators based on risk factors;

[0013] Among them, the risk factors include terrain risk, natural risk, man-made risk and equipment risk;

[0014] The risk assessment indicators include the probability of occurrence of risk factors P, construction duration T, and the severity D caused by the occurrence of risk factors;

[0015] S3. Classification of risk assessment levels

[0016] Quantify the risk assessment indicators and calculate the risk assessment score using the PTD safety assessment method;

[0017] Determine the construction safety level according to the safety index risk level classification standard combined with the risk assessment score;

[0018] The calculation formula of the PTD safety assessment method is shown in Formula 1:

[0019]

[0020] In formula 1, R is the risk assessment score. The higher the score, the greater the risk; n is the number of risk assessment indicators; ω i is the weight of the i-th risk assessment indicator; F i is the risk value of a specific risk assessment indicator; the formula contains i The risk assessment indicators in the system are: the mean probability of occurrence of each risk factor The construction duration T and the mean value of the severity of each risk factor after it occurs

[0021] Preferably, after the step S3 is completed, the step S4 is performed, and the step S4 includes formulating corresponding construction safety measures and preventive measures according to the determined construction safety level.

[0022] Preferably, in step S1, the analysis includes: using machine learning algorithms to classify and identify geological and geomorphological data, using deep learning algorithms to perform pattern recognition and prediction on historical earthquake disaster data, using big data analysis technology to analyze and mine meteorological data, and summarizing the company's construction accident data over the past 5 to 10 years.

[0023] Preferably, the use of machine learning algorithms to classify and identify geological and geomorphological data includes extracting the terrain slope, terrain undulation and slope aspect of the target work area through a digital elevation model; and analyzing the geological structure and surface cover of the target work area through a geographic information system (GIS).

[0024] Preferably, in step S2, after obtaining the terrain data and geological information, we need to analyze and determine the risk factors and dangers that may exist in the seismic exploration area, and the terrain risk includes at least one of the stability of the formation, the strength of the rock or the slope;

[0025] The natural risks include geological disasters, soil erosion, soil erosion or surface collapse, such as mudslides, floods, heavy rains or typhoons;

[0026] The human risk includes at least one of misoperation, failure to wear safety gear, or incomplete installation of safety facilities;

[0027] The equipment risk includes at least one of equipment aging or toxic gas leakage.

[0028] Preferably, step S3 comprises the following steps:

[0029] S31. Quantification of risk assessment indicators

[0030] The probability of occurrence P of each risk factor in terrain risk, natural risk, man-made risk and equipment risk is statistically analyzed respectively, the severity D caused by each risk factor after occurrence is statistically analyzed and quantified, and the construction duration T is quantified;

[0031] The severity D caused by the occurrence of the risk factors is divided into 5 levels from high to low, and the different levels are assigned values ​​according to the quintile method;

[0032] The calculation formula of the construction duration T is shown in Formula 2:

[0033]

[0034] In formula 2, t is the duration of construction per day, in hours;

[0035] S32. Determination of parameters in the PTD safety assessment formula

[0036] The mean probability of each risk factor The calculation formula is shown in Formula 3:

[0037]

[0038] In formula 3, A N Represents the probability of a certain risk factor occurring;

[0039] The mean severity of each risk factor after it occurs The calculation formula is shown in Formula 4:

[0040]

[0041] In formula 4, D N An assignment that represents the severity of a risk factor if it occurs;

[0042] The mean probability of occurrence of each risk factor The weight ω P The probability of occurrence of different types of events is evaluated based on historical data and statistical information of the geophysical prospecting industry. It can also be determined by expert analysis based on specific project conditions.

[0043] The weight ω of the construction duration T T The duration of construction of different projects is estimated based on the historical data and complexity of geophysical exploration projects. It can also be determined by expert analysis based on specific project conditions.

[0044] The mean severity of each risk factor after occurrence The weight ω D Based on the type and impact of the accident, historical accident data is used for evaluation and determination; it can also be determined by expert analysis based on specific project conditions;

[0045] S33. Calculation of risk assessment score

[0046] Based on the determined parameters, the risk assessment score is obtained using Formula 1;

[0047] S34. Determination of construction safety level

[0048] According to the safety indicator risk level classification standard combined with the risk assessment score, the safety level of the construction is classified to determine the construction safety level.

[0049] Further preferably, the terrain risk occurrence probability A 1n The calculation formula is shown in Formula 4.

[0050]

[0051] In formula 4, x max represents the maximum value of the event, and x represents the calculation result of a factor in natural risk;

[0052] The probability of natural risk occurring 2n The calculation formula is shown in Formula 5.

[0053]

[0054] In Formula 5, Y represents the total number of construction days in the existing data, and y represents the number of days in the existing data when the risk event occurred in the region during the construction period. For example, the existing data is the data from the China Geological Environment Monitoring Network for the past three years.

[0055] Probability of man-made risk occurrence A 3n The calculation formula is shown in Formula 6.

[0056]

[0057] In Formula 6, Z represents the number of constructions carried out by the company in the existing data, and z represents the number of personnel and property losses caused by human factors in the company in the existing data. The existing data includes the data recorded by the company in the past five years;

[0058] Equipment risk probability A 4n The calculation formula is shown in Formula 7.

[0059]

[0060] In Formula 7, E represents the number of construction operations performed by the company according to the existing data, and E represents the number of times the company suffered personnel and property losses due to equipment problems according to the existing data. The existing data include the data recorded by the company in the past five years.

[0061] More preferably, in step S3, the determined construction safety level result can be visualized by means including map display or chart presentation.

[0062] The present invention also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned physical exploration construction safety level classification method when executing the computer program.

[0063] The present invention also provides a computer-readable storage medium, which stores a computer program for executing the above-mentioned physical exploration construction safety level classification method.

[0064] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0065] ① The present invention comprehensively evaluates the risks in the construction process by considering multiple factors such as topography, weather, human factors, and equipment during the construction process, and adopts data analysis and quantitative evaluation methods to provide a physical exploration construction safety level classification method. This method can objectively and comprehensively evaluate the risk situation in the seismic exploration area, avoid the interference of human factors, improve the accuracy and reliability of the evaluation, and further improve the scientificity and effectiveness of risk management;

[0066] ② The physical exploration construction safety level classification method provided by the present invention can help exploration personnel to more comprehensively understand the risk situation of the exploration area, provide protection for exploration work, and improve the safety of exploration work; at the same time, by timely discovering and identifying risks, corresponding measures can be taken to prevent and control them, thereby improving the sustainability of exploration work;

[0067] ③ The present invention uses artificial intelligence technology to realize automatic processing and analysis of data, reduce manual intervention, and improve the efficiency of risk assessment. At the same time, by visually displaying the assessment results, users can understand the assessment results more intuitively, further improving the efficiency of the assessment;

[0068] ④ In order to make the physical exploration construction safety level classification method established by the present invention more scientific and reasonable, and more universal, the following four aspects are incorporated into the establishment of the method: a. By increasing the number of calculations, the complexity of the model is reduced, so that the influencing conditions can be added or deleted according to actual needs to face the diversity and temporary nature of the project; b. By adopting a database for the geophysical exploration industry, a safety data and risk data set is established to provide input data and improve judgment accuracy; c. Through a large amount of historical data, simulation calculations are performed to improve the statistical stability of the model, reduce randomness, and thus reduce the uncertainty of the model; d. The method is parameterized, and universal parameters are determined through a large number of simulation calculations. At the same time, parameter flexibility is provided. According to the experience of industry experts, project site requirements, etc., the parameter range can be adjusted to make the calculation method more targeted.

[0069] ⑤ The present invention also provides electronic equipment and storage media for executing the physical exploration construction safety level classification method, with complete software and hardware supporting facilities, which facilitates the promotion and use of the classification method.

[0070] In summary, the present invention provides a construction safety level classification method that takes into account multiple factors such as topography, meteorology, human factors, and equipment during the construction process, and quantifies evaluation indicators such as the probability of occurrence of different risk factors, degree of hazard, and exposure time, and obtains the risk score of the construction area according to the PTD safety assessment formula, and classifies the construction project into different safety levels according to the risk score, and formulates different construction safety measures and preventive measures. The physical exploration construction safety level classification method provided by the present invention can not only realize automated processing and analysis of data, improve the efficiency of risk assessment, but also improve the scientificity and effectiveness of risk assessment, ensure the safety and sustainability of exploration work, and provide a scientific basis for risk management.

[0071] The invention is applied to the assessment of the safety level of terrain or construction projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0073] Figure 1 This is a flow chart of the method for classifying the safety level of physical exploration construction in Example 1 of the present invention;

[0074] Figure 2 This is a classification diagram of construction safety levels in a certain exploration area in Example 1 of the present invention. DETAILED DESCRIPTION

[0075] The present invention will be further described in detail below by means of specific embodiments in combination with the accompanying drawings. It should be understood that the described embodiments are preferred examples of the present invention and are only used to explain the present invention and do not limit the present invention.

[0076] Example 1 A physical exploration construction safety level classification method

[0077] This embodiment provides a physical exploration construction safety level classification method, and its flow chart is as follows: Figure 1 As shown, the method includes the following steps performed in sequence:

[0078] S1. Collection and analysis of data

[0079] Collect topographic data, geological data, meteorological data, historical earthquake disaster data and construction accident data of the target construction area;

[0080] The terrain slope, terrain undulation and slope aspect of the seismic exploration area are extracted through the digital elevation model to analyze the terrain characteristics of the seismic exploration area; the geological structure and surface cover of the seismic exploration area are analyzed through the terrain analysis and spatial analysis functions of the geographic information system (GIS);

[0081] Deep learning algorithms are used to identify and predict patterns in historical earthquake disaster data, big data analysis technology is used to analyze and mine meteorological data, and the company's construction accident data over the past 5 to 10 years is summarized.

[0082] S2. Determination of risk factors and risk assessment indicators

[0083] Based on the analysis of the data, the risk factors in the construction process are determined, and corresponding risk assessment indicators are determined for the risk factors, including:

[0084] After analyzing the above data, the risk factors and their dangers such as terrain risks, natural risks, human risks and equipment risks that may exist in the seismic exploration area are analyzed and determined.

[0085] The terrain risk includes stratum stability, rock strength or slope;

[0086] The natural risks include landslides, mudslides, floods, heavy rains or typhoons;

[0087] The human risks include misoperation, failure to wear safety gear or incomplete construction of safety facilities;

[0088] The equipment risks include equipment aging or toxic gas leakage;

[0089] According to the above different risk factors, select corresponding risk assessment indicators, such as:

[0090] Probability of risk factor occurrence P: The probability of risk factor occurrence, which assesses the possibility of the event occurring in the seismic exploration area;

[0091] Construction duration T: assess the exposure of people, property and materials;

[0092] Severity of risk factors after they occur: The degree of harm to people, property and the environment after the risk factors occur;

[0093] S3. Classification of risk assessment levels

[0094] After quantifying the risk assessment indicators and calculating the risk assessment scores using the PTD safety assessment method, the construction safety level is determined according to the safety indicator risk level classification standards, including:

[0095] S31. Quantification of risk assessment indicators

[0096] The probability of occurrence P of each risk factor in terrain risk, natural risk, man-made risk and equipment risk is statistically analyzed respectively, the severity D caused by each risk factor after occurrence is statistically analyzed and quantified, and the construction duration T is quantified;

[0097] The severity D caused by the occurrence of the different risk factors is divided into 5 levels from high to low, and different levels are assigned different values, as shown in Tables 1 and 2.

[0098] Table 1. Grading criteria for severity of risk factors after occurrence

[0099]

[0100]

[0101] Table 2 Probability and level of common risk events

[0102]

[0103] As shown in Table 2, risk types mainly include terrain risk, natural risk, man-made risk and equipment risk. Each type of risk event includes but is not limited to the content in the above table. Its safety level can be adjusted according to actual conditions. The formation stability and rock strength data in terrain risk are derived from the gas exploration and address investigation report. The slope calculation formula is shown in Formula 9.

[0104]

[0105] In Formula 9, θ is the surface slope, dz represents the elevation change, and dx and dy represent the distance changes along the x and y directions.

[0106] Then the probability of occurrence of each factor in terrain risk is A 1n The calculation formula is shown in Formula 5.

[0107]

[0108] In formula 5, x max represents the maximum value of the event, and x represents the calculation result of a factor in terrain risk; taking slope as an example: the maximum value of slope is 90, if the calculated slope result is 9, the slope occurrence probability score is 0.1;

[0109] The probability of natural risk occurring 2n The calculation formula is shown in Formula 6.

[0110]

[0111] In Formula 6, Y represents the total number of construction days in the region in the past three years, and y represents the number of days in which the risk event occurred during the construction period in the region in the past three years. The data comes from the China Geological Environment Monitoring Network;

[0112] Probability of man-made risk occurrence A 3n The calculation formula is shown in Formula 7.

[0113]

[0114] In Formula 7, Z represents the number of constructions carried out by the company in the past five years, and z represents the number of personnel and property losses caused by human factors in the company in the past five years;

[0115] Equipment risk probability A 4n The calculation formula is shown in Formula 8.

[0116]

[0117] In Formula 8, E represents the number of constructions carried out by the company in the past five years, and E represents the number of times the company has suffered casualties and property losses due to any reason in the past five years.

[0118] S32. Determination of parameters in the PTD safety assessment formula

[0119] The PTD safety assessment method is used to calculate the risk assessment score, where the PTD safety assessment calculation formula is shown in Formula 1:

[0120]

[0121] In formula 1, R is the risk assessment score. The higher the score, the greater the risk; n is the number of risk assessment indicators; ω i is the weight of the i-th risk assessment indicator; F i is the risk value of a specific risk assessment indicator;

[0122] The formula contains F i The risk assessment indicators in the system are: the mean probability of occurrence of each risk factor The construction duration T and the mean value of the severity of each risk factor after it occurs

[0123] The parameters in this formula are obtained or determined as follows:

[0124] (1) The calculation formula for construction duration T is shown in Formula 2:

[0125]

[0126] In formula 2, t is the duration of construction per day, in hours;

[0127] (2) Mean probability of occurrence of each risk factor The calculation formula is shown in Formula 3:

[0128]

[0129] In formula 3, A N Represents the probability of a certain risk factor occurring;

[0130] (3) The average severity of each risk factor after it occurs The calculation formula is shown in Formula 4:

[0131]

[0132] In formula 4, D N An assignment that represents the severity of a risk factor if it occurs;

[0133] (4) Mean probability of occurrence of each risk factor The weight ω PThe probability of occurrence of different types of events is evaluated based on historical data and statistical information of the geophysical prospecting industry. It can also be determined by expert analysis based on specific project conditions.

[0134] (5) Weight ω of construction duration T T The duration of construction of different projects is estimated based on the historical data and complexity of geophysical exploration projects. It can also be determined by expert analysis based on specific project conditions.

[0135] (6) The average severity of each risk factor after it occurs The weight ω D Based on the type and impact of the accident, historical accident data is used for assessment and determination; it can also be determined by expert analysis based on the specific project situation.

[0136] S33. Calculation of risk assessment score

[0137] Based on the determined parameters, the risk assessment score is obtained using Formula 1;

[0138] S34. Determination of construction safety level

[0139] According to the safety indicator risk level classification standard combined with the risk assessment score, the safety level of the construction is classified to determine the construction safety level.

[0140] Based on the construction safety level determined above, the construction team further formulates corresponding construction safety measures and preventive measures.

[0141] To facilitate understanding and calculation, one risk is selected from each of the four risk types: terrain risk, natural risk, man-made risk and equipment risk for calculation. The specific process is as follows: Assuming that there is a slope value in a certain work area, the calculated surface slope θ is 40, and the construction time is from March 1 to June 28 of a certain year. During this period, the average number of days with heavy rainstorms over the years is 24 days. According to the production hazard investigation reports of previous years, the probability of misoperation is 5% and the equipment aging rate is 10%.

[0142] The surface slope θ is 40, and the probability of terrain risk occurrence A1 = 0.4 is calculated by formula 5;

[0143] The construction time is 120 days in total. During this period, the average number of days with heavy rainstorms is 24 days. According to formula 3, the probability of heavy rainstorms is A2 = 0.2.

[0144] According to the production hazard investigation reports of previous years, the probability of misoperation is 5%. The probability of human risk factor occurrence is A3 = 0.05 calculated by formula 7;

[0145] The equipment aging rate is 10%, and the equipment risk factor A4 = 0.1 is calculated by formula 8;

[0146] According to formula 2, the construction duration T = 0.5;

[0147] Calculated by formula 3, the mean probability of occurrence of each risk factor is

[0148] Calculated by formula 4, the mean severity of each risk factor after occurrence is

[0149] Assume that the mean probability of each risk factor is The weight ω P Initially set at 6, it can also be adjusted appropriately according to the specific project situation and expert analysis; the weight of the construction duration T ω T Initially set at 7, it can also be adjusted appropriately according to the specific project situation and expert analysis; the average value of the severity caused by each risk factor after it occurs The weight ω D It is initially set at 7, but can be adjusted appropriately based on specific project conditions and expert analysis;

[0150] Using formula 1, we obtain the risk assessment score R=0.4456.

[0151] According to the five-level risk classification method, a risk assessment score of 1 is a level 1 risk area with the highest risk level, and a risk assessment score of 0 is a level 5 risk area with the lowest risk level, which can be a safe area. The above calculated risk assessment score is 0.4456, which is in the range of 0.4 to 0.6, and is a level 3 risk area with a medium risk level. Therefore, it can be determined that the implementation of this type of work in this area is relatively dangerous, and attention should be paid to the implementation of relevant protective measures and safety training.

[0152] For example, the following measures can be taken in exploration areas with medium risk: (1) provide necessary safety training and education to ensure that workers understand potential hazards and correct working practices; (2) mark dangerous areas and set up safety signs when necessary; (3) regularly inspect and maintain work equipment to ensure that it is in safe working condition; (4) formulate and implement safe work processes and procedures, including accident reporting, emergency response, work permit procedures, etc.

[0153] Each construction team can also divide the risk level according to the actual safety indicators, such as level 3, level 5, etc.

[0154] Through data analysis and risk assessment classification methods, the risk assessment classification results of seismic exploration areas can be obtained. These results can be visualized in other ways to help users understand the risk situation of the exploration area more intuitively.

[0155] In terms of presenting risk assessment grading results, ArcMap software can analyze and process relevant information. For example, it can use natural language processing technology to perform semantic analysis and sentiment analysis on risk assessment results to help users better understand the assessment results; it can also use visualization technologies such as map display or chart presentation to visualize the assessment results to help users understand the assessment results more intuitively.

[0156] For example, after applying the method provided by the present invention to classify the construction safety level of a certain exploration area, a visual display is performed, and the construction safety level classification diagram is as follows: Figure 2 As shown. Figure 2 It can enable users to have an intuitive and clear understanding of the distribution of safety levels in the exploration area.

[0157] Embodiment 2 A computer device

[0158] This embodiment provides a computer device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, so as to implement the above-mentioned physical exploration construction safety level classification method.

[0159] The above-mentioned memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0160] The processor may be a central processing unit (CPU) or other processing units having data processing capability and / or instruction execution capability, and may control other components in the electronic device to perform desired functions. The processor is used to execute the computer-readable instructions stored in the memory.

[0161] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0162] Embodiment 3 A computer readable storage medium

[0163] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned physical exploration construction safety level classification method is implemented.

[0164] The computer-readable storage medium stores non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of various embodiments are executed.

[0165] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0166] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present disclosure.

Claims

1. A physical exploration construction safety level classification method, characterized in that: The classification method includes the following steps, which are performed in sequence: S1. Collection and analysis of data Collect and analyze topographic data, geological data, meteorological data, historical earthquake disaster data, and construction accident data of the target construction area to obtain data analysis results; S2. Determination of risk factors and risk assessment indicators Based on the data analysis results, determine the risk factors in the construction process; Determine corresponding risk assessment indicators based on risk factors; Among them, the risk factors include terrain risk, natural risk, man-made risk and equipment risk; The risk assessment indicators include the probability of occurrence of risk factors P, construction duration T, and the severity D caused by the occurrence of risk factors; S3. Classification of risk assessment levels Quantify the risk assessment indicators and calculate the risk assessment score using the PTD safety assessment method; Determine the construction safety level according to the safety index risk level classification standard combined with the risk assessment score; The calculation formula of the PTD safety assessment method is shown in Formula 1: In formula 1, R is the risk assessment score. The higher the score, the greater the risk; n is the number of risk assessment indicators; ω i is the weight of the i-th risk assessment indicator; F i is the risk value of a specific risk assessment indicator; the formula contains i The risk assessment indicators in the system are: the mean probability of occurrence of each risk factor The construction duration T and the mean value of the severity of each risk factor after it occurs 2. A physical exploration construction safety level classification method according to claim 1, characterized in that: In step S1, the analysis includes: using machine learning algorithms to classify and identify geological and geomorphological data, using deep learning algorithms to perform pattern recognition and prediction on historical earthquake disaster data, using big data analysis technology to analyze and mine meteorological data, and summarizing the company's construction accident data over the past 5 to 10 years.

3. A physical exploration construction safety level classification method according to claim 2, characterized in that: The method uses a machine learning algorithm to classify and identify geological and geomorphological data, including extracting the terrain slope, terrain undulation and slope direction of the target work area through a digital elevation model; and analyzing the geological structure and surface cover of the target work area through a geographic information system.

4. A physical exploration construction safety level classification method according to claim 1, characterized in that: In step S2, The terrain risk includes at least one of formation stability, rock strength or slope; The natural risk includes at least one of mudslide, flood, heavy rain or typhoon; The human risk includes at least one of misoperation, failure to wear safety gear, or incomplete installation of safety facilities; The equipment risk includes at least one of equipment aging or toxic gas leakage.

5. A physical exploration construction safety level classification method according to any one of claims 1 to 4, characterized in that: The step S3 comprises the following steps: S31. Quantification of risk assessment indicators The probability of occurrence P of each risk factor in terrain risk, natural risk, man-made risk and equipment risk is statistically analyzed respectively, the severity D caused by each risk factor after occurrence is statistically analyzed and quantified, and the construction duration T is quantified; The severity D caused by the occurrence of the risk factors is divided into 5 levels from high to low, and the different levels are assigned values ​​according to the quintile method; The calculation formula of the construction duration T is shown in Formula 2: In formula 2, t is the duration of construction per day, in hours; S32. Determination of parameters in the PTD safety assessment formula The mean probability of each risk factor The calculation formula is shown in Formula 3: In formula 3, A N Represents the probability of a certain risk factor occurring; The mean severity of each risk factor after it occurs The calculation formula is shown in Formula 4: In formula 4, D N An assignment that represents the severity of a risk factor if it occurs; The mean probability of occurrence of each risk factor The weight ω P The probability of occurrence of different types of events is evaluated based on historical data and statistical information of the geophysical prospecting industry. It can also be determined by expert analysis based on specific project conditions. The weight ω of the construction duration T T The duration of construction of different projects is estimated based on the historical data and complexity of geophysical exploration projects. It can also be determined by expert analysis based on specific project conditions. The mean severity of each risk factor after occurrence The weight ω D Based on the type and impact of the accident, historical accident data is used for evaluation and determination; it can also be determined by expert analysis based on specific project conditions; S33. Calculation of risk assessment score Based on the determined parameters, the risk assessment score is obtained using Formula 1; S34. Determination of construction safety level According to the safety indicator risk level classification standard combined with the risk assessment score, the safety level of the construction is classified to determine the construction safety level.

6. A physical exploration construction safety level classification method according to claim 5, characterized in that: The probability of occurrence of the terrain risk A 1n The calculation formula is shown in Formula 5. In formula 5, x max represents the maximum value of the event, and x represents the calculation result of a factor in terrain risk; The probability of natural risk occurring 2n The calculation formula is shown in Formula 6. In Formula 6, Y represents the total number of construction days in the region according to the existing data, and y represents the number of days in which the risk event occurred in the region during the construction period according to the existing data; Probability of human risk occurrence A 3n The calculation formula is shown in Formula 7. In Formula 7, Z represents the number of constructions carried out by the company in the existing data, and z represents the number of personnel and property losses caused by human factors in the company in the existing data; Equipment risk probability A 4n The calculation formula is shown in Formula 8. In Formula 8, E represents the number of constructions carried out by the company in the existing data, and E represents the number of times the company caused loss of life and property due to reasons in the existing data.

7. A physical exploration construction safety level classification method according to claim 6, characterized in that: In step S3, the determined construction safety level result can be visualized in a manner including map display or chart presentation.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, a physical exploration construction safety level classification method according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for executing a physical exploration construction safety level classification method according to any one of claims 1 to 7.

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