Early warning method and system for construction risk of underground powerhouse cavern of hydropower station

Abstract

The invention provides a hydropower station underground powerhouse cavern construction risk early warning method and system, and the method comprises the steps: obtaining construction environment data, construction technology data, material and equipment data, equipment management data and constructor data of a hydropower station underground powerhouse cavern, and carrying out the normalization processing of the data, the data subjected to normalization processing are obtained; determining a construction environment risk value, a construction technology risk value, a material and equipment risk value, an equipment management risk value and a constructor risk value of the underground powerhouse cavern of the hydropower station; substituting the risk value into a pre-established risk early warning index prediction model to obtain a risk early warning index prediction value of the underground powerhouse cavern of the hydropower station; and judging the construction risk level of the underground powerhouse cavern of the hydropower station based on the risk early warning index predicted value, and performing early warning based on the construction risk level. According to the technical scheme provided by the invention, accurate early warning can be carried out on the cavern construction risk, and the construction safety is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of construction early warning technology, and in particular to a method and system for early warning of construction risks in underground powerhouse caverns of hydropower stations. Background Art

[0002] The construction of underground powerhouse caverns for hydropower stations is a complex and high-risk project, with risks primarily stemming from multiple factors, including geological conditions, construction techniques, and environmental factors. Currently, numerous monitoring instruments are often deployed on projects, and the stability assessment of the surrounding rock mass during underground cavern construction is often data-driven. This approach utilizes monitoring data to assess surrounding rock stability and establishes an early warning system based on this data. However, this evaluation method simply analyzes the stability characteristics of the surrounding rock mass, neglecting environmental and human factors, resulting in low early warning accuracy. Therefore, a highly accurate early warning scheme for the construction risks of underground powerhouse caverns for hydropower stations is urgently needed. Summary of the Invention

[0003] The present application provides a method and system for early warning of construction risks of underground powerhouse caverns in a hydropower station, so as to at least solve the technical problem of low early warning accuracy.

[0004] The first embodiment of the present application provides a method for early warning of construction risks of underground powerhouse caverns in a hydropower station, the method comprising:

[0005] Acquiring construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data of the underground powerhouse cavern of the hydropower station, and normalizing the construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data;

[0006] Determine the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station by using the analytic hierarchy process based on the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data;

[0007] Substituting the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station into a pre-established risk warning index prediction model to obtain a risk warning index prediction value of the underground powerhouse cavern of the hydropower station;

[0008] The construction risk level of the underground powerhouse cavern of the hydropower station is judged based on the predicted value of the risk warning index of the underground powerhouse cavern of the hydropower station, and an early warning is issued based on the construction risk level.

[0009] Preferably, the construction environment data includes: weather data, stability data in the cavern, and sudden water inrush data in the cavern;

[0010] The construction technology data includes: technical solution completeness data, technical support availability data, advanced geological forecast accuracy data, and technology maturity data;

[0011] The material and equipment data include: material and equipment quality inspection data, equipment inspection and maintenance data, equipment normal working status data, and equipment adaptability data;

[0012] The equipment management data includes: inspection and early warning capability data, emergency response measures completeness data, and timeliness of communication and negotiation between all parties involved;

[0013] The construction personnel data include: data on the professional skills proficiency of the construction personnel, data on the strength of the construction personnel's safety awareness, and data on the psychological fatigue level of the construction personnel.

[0014] Furthermore, the process of establishing the risk warning indicator prediction model includes:

[0015] Obtain the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, construction personnel risk value, and the measured value of the risk warning indicators corresponding to the underground powerhouse caverns of each hydropower station in the historical period, and divide them into training and test sets;

[0016] The initial risk warning indicator prediction model is trained using the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse caverns of each hydropower station in the historical period of the training set as input, and the measured value of the risk warning index of the underground powerhouse caverns of each hydropower station in the historical period of the training set as output to obtain a risk warning indicator prediction model after training with the training set;

[0017] The risk warning indicator prediction model trained with the training set is optimized using the test set to obtain a trained risk warning indicator prediction model.

[0018] Furthermore, the determining of the construction risk level of the underground powerhouse cavern of the hydropower station based on the predicted value of the risk warning index of the underground powerhouse cavern of the hydropower station includes:

[0019] When the predicted value of the risk warning indicator is greater than or equal to zero and less than or equal to a first threshold, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a first-level risk level;

[0020] When the predicted value of the risk warning indicator is greater than the first threshold value and less than or equal to the second threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a second-level risk level;

[0021] When the predicted value of the risk warning indicator is greater than the second threshold value and less than or equal to the third threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a third risk level;

[0022] When the predicted value of the risk warning indicator is greater than the third threshold value and less than or equal to the fourth threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a fourth risk level;

[0023] Among them, the risk severity of the first risk level, second risk level, third risk level and fourth risk level decreases in sequence.

[0024] Furthermore, the early warning based on the construction risk level includes:

[0025] When the construction risk level is level one, a red risk warning is issued;

[0026] When the construction risk level is level 2, a yellow risk warning is issued;

[0027] When the construction risk level is level three, an orange risk warning is issued;

[0028] When the construction risk level is level four, a green risk warning is issued.

[0029] The second embodiment of the present application provides a hydropower station underground powerhouse cavern construction risk warning system, comprising:

[0030] an acquisition module, configured to acquire construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data of the underground powerhouse cavern of the hydropower station, and to normalize the construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data;

[0031] a determination module for determining the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station by using the analytic hierarchy process based on the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data;

[0032] A prediction module is used to substitute the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station into a pre-established risk warning indicator prediction model to obtain a risk warning indicator prediction value of the underground powerhouse cavern of the hydropower station;

[0033] The judgment and early warning module is used to judge the construction risk level of the underground powerhouse cavern of the hydropower station based on the risk early warning index prediction value of the underground powerhouse cavern of the hydropower station, and to issue an early warning based on the construction risk level.

[0034] Preferably, the construction environment data includes: weather data, stability data in the cavern, and sudden water inrush data in the cavern;

[0035] The construction technology data includes: technical solution completeness data, technical support availability data, advanced geological forecast accuracy data, and technology maturity data;

[0036] The material and equipment data include: material and equipment quality inspection data, equipment inspection and maintenance data, equipment normal working status data, and equipment adaptability data;

[0037] The equipment management data includes: inspection and early warning capability data, emergency response measures completeness data, and timeliness of communication and negotiation between all parties involved;

[0038] The construction personnel data include: data on the professional skills proficiency of the construction personnel, data on the strength of the construction personnel's safety awareness, and data on the psychological fatigue level of the construction personnel.

[0039] Furthermore, the process of establishing the risk warning indicator prediction model includes:

[0040] Obtain the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, construction personnel risk value, and the measured value of the risk warning indicators corresponding to the underground powerhouse caverns of each hydropower station in the historical period, and divide them into training and test sets;

[0041] The initial risk warning indicator prediction model is trained using the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse caverns of each hydropower station in the historical period of the training set as input, and the measured value of the risk warning index of the underground powerhouse caverns of each hydropower station in the historical period of the training set as output to obtain a risk warning indicator prediction model after training with the training set;

[0042] The risk warning indicator prediction model trained with the training set is optimized using the test set to obtain a trained risk warning indicator prediction model.

[0043] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method described in the first aspect is implemented.

[0044] A fourth embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first embodiment.

[0045] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0046] The present application proposes a method and system for early warning of construction risks of underground powerhouse caverns of a hydropower station, the method comprising: obtaining construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data of the underground powerhouse caverns of the hydropower station, and normalizing the construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data; respectively, according to the normalized construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data, the construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data are obtained. The data of personnel are collected and the analytic hierarchy process is used to determine the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value and construction personnel risk value of the underground powerhouse cavern of the hydropower station; the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value and construction personnel risk value of the underground powerhouse cavern of the hydropower station are substituted into a pre-established risk warning index prediction model to obtain the risk warning index prediction value of the underground powerhouse cavern of the hydropower station; based on the risk warning index prediction value of the underground powerhouse cavern of the hydropower station, the construction risk level of the underground powerhouse cavern of the hydropower station is judged, and an early warning is issued based on the construction risk level. The technical solution proposed in this application can provide accurate early warning of cavern construction risks and ensure the safety of construction.

[0047] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0049] Figure 1 This is a flow chart of a method for early warning of construction risks of underground powerhouse caverns in a hydropower station according to one embodiment of the present application;

[0050] Figure 2 This is a structural diagram of a hydropower station underground powerhouse cavern construction risk warning system provided according to one embodiment of the present application. DETAILED DESCRIPTION

[0051] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0052] The present application proposes a method and system for early warning of construction risks of underground powerhouse caverns of hydropower stations, the method comprising: obtaining construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data of the underground powerhouse caverns of the hydropower station, and normalizing the construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data; respectively, according to the normalized construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data, the construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data are obtained. The data of personnel are collected and the analytic hierarchy process is used to determine the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value and construction personnel risk value of the underground powerhouse cavern of the hydropower station; the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value and construction personnel risk value of the underground powerhouse cavern of the hydropower station are substituted into a pre-established risk warning index prediction model to obtain the risk warning index prediction value of the underground powerhouse cavern of the hydropower station; based on the risk warning index prediction value of the underground powerhouse cavern of the hydropower station, the construction risk level of the underground powerhouse cavern of the hydropower station is judged, and an early warning is issued based on the construction risk level. The technical solution proposed in this application can provide accurate early warning of cavern construction risks and ensure the safety of construction.

[0053] The following describes a method and system for early warning of construction risks of underground powerhouse caverns in a hydropower station according to an embodiment of the present application with reference to the accompanying drawings.

[0054] Example 1

[0055] Figure 1 This is a flow chart of a method for early warning of construction risks of underground powerhouse caverns in a hydropower station according to one embodiment of the present application. Figure 1 As shown, the method includes:

[0056] Step 1: Acquire construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data of the underground powerhouse cavern of the hydropower station, and normalize the construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data;

[0057] It should be noted that the construction environment data includes: weather data, stability data in the cavern, and sudden water inrush data in the cavern;

[0058] The construction technology data includes: technical solution completeness data, technical support availability data, advanced geological forecast accuracy data, and technology maturity data;

[0059] The material and equipment data include: material and equipment quality inspection data, equipment inspection and maintenance data, equipment normal working status data, and equipment adaptability data;

[0060] The equipment management data includes: inspection and early warning capability data, emergency response measures completeness data, and timeliness of communication and negotiation between all parties involved;

[0061] The construction personnel data include: data on the professional skills proficiency of the construction personnel, data on the strength of the construction personnel's safety awareness, and data on the psychological fatigue level of the construction personnel.

[0062] Step 2: Determine the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station using the analytic hierarchy process based on the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data;

[0063] It should be noted that: 1. For the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value and construction personnel risk value, the corresponding judgment matrices are constructed respectively; 2. The eigenvectors and maximum eigenvalues ​​of each judgment matrix are calculated respectively; 3. Consistency is performed; 4. The weights of each data in the construction environment data, construction technology data, material and equipment data, equipment management data and construction personnel data are determined respectively; 5. Based on the weights of each data, the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value and construction personnel risk value are determined respectively.

[0064] Step 3: Substituting the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station into a pre-established risk warning index prediction model to obtain a risk warning index prediction value of the underground powerhouse cavern of the hydropower station;

[0065] In the embodiment of the present disclosure, the process of establishing the risk warning indicator prediction model includes:

[0066] Obtain the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, construction personnel risk value, and the measured value of the risk warning indicators corresponding to the underground powerhouse caverns of each hydropower station in the historical period, and divide them into training and test sets;

[0067] The initial risk warning indicator prediction model is trained using the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse caverns of each hydropower station in the historical period of the training set as input, and the measured value of the risk warning index of the underground powerhouse caverns of each hydropower station in the historical period of the training set as output to obtain a risk warning indicator prediction model after training with the training set;

[0068] The risk warning indicator prediction model trained with the training set is optimized using the test set to obtain a trained risk warning indicator prediction model.

[0069] Step 4: Determine the construction risk level of the underground powerhouse cavern of the hydropower station based on the predicted value of the risk warning index of the underground powerhouse cavern of the hydropower station, and issue an early warning based on the construction risk level.

[0070] In the embodiment of the present disclosure, the determining of the construction risk level of the underground powerhouse cavern of the hydropower station based on the risk warning index prediction value of the underground powerhouse cavern of the hydropower station includes:

[0071] When the predicted value of the risk warning indicator is greater than or equal to zero and less than or equal to a first threshold, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a first-level risk level;

[0072] When the predicted value of the risk warning indicator is greater than the first threshold value and less than or equal to the second threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a second-level risk level;

[0073] When the predicted value of the risk warning indicator is greater than the second threshold value and less than or equal to the third threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a third risk level;

[0074] When the predicted value of the risk warning indicator is greater than the third threshold value and less than or equal to the fourth threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a fourth risk level;

[0075] The risk severity of the first-level risk level, the second-level risk level, the third-level risk level and the fourth-level risk level decreases in order;

[0076] It should be noted that the first threshold may be 0.25, the second threshold may be 0.5, the third threshold may be 0.75, and the fourth threshold may be 1.

[0077] Furthermore, the early warning based on the construction risk level includes:

[0078] When the construction risk level is level one, a red risk warning is issued;

[0079] When the construction risk level is level 2, a yellow risk warning is issued;

[0080] When the construction risk level is level three, an orange risk warning is issued;

[0081] When the construction risk level is level four, a green risk warning is issued.

[0082] It should be noted that sound and light warnings can be used for the above-mentioned risk warnings.

[0083] In summary, the method for early warning of construction risks of underground powerhouse caverns in a hydropower station proposed in this embodiment can provide accurate early warning of cavern construction risks and ensure the safety of construction.

[0084] Example 2

[0085] Figure 2 This is a structural diagram of a hydropower station underground powerhouse cavern construction risk warning system provided according to one embodiment of the present application, such as Figure 2 As shown, the system includes:

[0086] The acquisition module 100 is used to obtain construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data of the underground powerhouse cavern of the hydropower station, and normalize the construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data;

[0087] The construction environment data includes weather data, stability data in the cavern, and sudden water inrush data in the cavern.

[0088] The construction technology data includes: technical solution completeness data, technical support availability data, advanced geological forecast accuracy data, and technology maturity data;

[0089] The material and equipment data include: material and equipment quality inspection data, equipment inspection and maintenance data, equipment normal working status data, and equipment adaptability data;

[0090] The equipment management data includes: inspection and early warning capability data, emergency response measures completeness data, and timeliness of communication and negotiation between all parties involved;

[0091] The construction personnel data include: data on the professional skills proficiency of the construction personnel, data on the strength of the construction personnel's safety awareness, and data on the psychological fatigue level of the construction personnel.

[0092] a determination module 200 for determining, based on the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data, a construction environment risk value, a construction technology risk value, a material and equipment risk value, an equipment management risk value, and a construction personnel risk value of the underground powerhouse cavern of the hydropower station using an analytic hierarchy process;

[0093] The prediction module 300 is used to substitute the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station into a pre-established risk warning indicator prediction model to obtain a risk warning indicator prediction value of the underground powerhouse cavern of the hydropower station;

[0094] The process of establishing the risk warning indicator prediction model includes:

[0095] Obtain the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, construction personnel risk value, and the measured value of the risk warning indicators corresponding to the underground powerhouse caverns of each hydropower station in the historical period, and divide them into training and test sets;

[0096] The initial risk warning indicator prediction model is trained using the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse caverns of each hydropower station in the historical period of the training set as input, and the measured value of the risk warning index of the underground powerhouse caverns of each hydropower station in the historical period of the training set as output to obtain a risk warning indicator prediction model after training with the training set;

[0097] The risk warning indicator prediction model trained with the training set is optimized using the test set to obtain a trained risk warning indicator prediction model.

[0098] The judgment and warning module 400 is used to judge the construction risk level of the underground powerhouse cavern of the hydropower station based on the risk warning index prediction value of the underground powerhouse cavern of the hydropower station, and to issue an early warning based on the construction risk level.

[0099] In the embodiment of the present disclosure, the judgment and warning module 400 is further configured to:

[0100] When the predicted value of the risk warning indicator is greater than or equal to zero and less than or equal to a first threshold, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a first-level risk level;

[0101] When the predicted value of the risk warning indicator is greater than the first threshold value and less than or equal to the second threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a second-level risk level;

[0102] When the predicted value of the risk warning indicator is greater than the second threshold value and less than or equal to the third threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a third risk level;

[0103] When the predicted value of the risk warning indicator is greater than the third threshold value and less than or equal to the fourth threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a fourth risk level;

[0104] Among them, the risk severity of the first risk level, second risk level, third risk level and fourth risk level decreases in sequence.

[0105] Furthermore, the judgment and warning module 400 is further configured to:

[0106] When the construction risk level is level one, a red risk warning is issued;

[0107] When the construction risk level is level 2, a yellow risk warning is issued;

[0108] When the construction risk level is level three, an orange risk warning is issued;

[0109] When the construction risk level is level four, a green risk warning is issued.

[0110] In summary, the hydropower station underground powerhouse cavern construction risk warning system proposed in this embodiment can provide accurate warning of cavern construction risks and ensure construction safety.

[0111] Example 3

[0112] To implement the above embodiments, the present disclosure further proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first embodiment is implemented.

[0113] Example 4

[0114] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first embodiment is implemented.

[0115] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do 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. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0116] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0117] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for early warning of construction risks of underground powerhouse caverns in a hydropower station, characterized in that: The method comprises: Acquiring construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data of the underground powerhouse cavern of the hydropower station, and normalizing the construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data; Determine the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station by using the analytic hierarchy process based on the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data; Substituting the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station into a pre-established risk warning index prediction model to obtain a risk warning index prediction value of the underground powerhouse cavern of the hydropower station; The construction risk level of the underground powerhouse cavern of the hydropower station is judged based on the predicted value of the risk warning index of the underground powerhouse cavern of the hydropower station, and an early warning is issued based on the construction risk level.

2. The method according to claim 1, wherein The construction environment data includes: weather data, stability data in the cavern, and sudden water inrush data in the cavern; The construction technology data includes: technical solution completeness data, technical support availability data, advanced geological forecast accuracy data, and technology maturity data; The material and equipment data include: material and equipment quality inspection data, equipment inspection and maintenance data, equipment normal working status data, and equipment adaptability data; The equipment management data includes: inspection and early warning capability data, emergency response measures completeness data, and timeliness of communication and negotiation between all parties involved; The construction personnel data include: data on the professional skills proficiency of the construction personnel, data on the strength of the construction personnel's safety awareness, and data on the psychological fatigue level of the construction personnel.

3. The method according to claim 2, wherein The process of establishing the risk warning indicator prediction model includes: Obtain the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, construction personnel risk value, and the measured value of the risk warning indicators corresponding to the underground powerhouse caverns of each hydropower station in the historical period, and divide them into training and test sets; The initial risk warning indicator prediction model is trained using the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse caverns of each hydropower station in the historical period of the training set as input, and the measured value of the risk warning index of the underground powerhouse caverns of each hydropower station in the historical period of the training set as output to obtain a risk warning indicator prediction model after training with the training set; The risk warning indicator prediction model trained with the training set is optimized using the test set to obtain a trained risk warning indicator prediction model.

4. The method according to claim 3, wherein The determining of the construction risk level of the underground powerhouse cavern of the hydropower station based on the risk warning indicator prediction value of the underground powerhouse cavern of the hydropower station includes: When the predicted value of the risk warning indicator is greater than or equal to zero and less than or equal to a first threshold, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a first-level risk level; When the predicted value of the risk warning indicator is greater than the first threshold value and less than or equal to the second threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a second-level risk level; When the predicted value of the risk warning indicator is greater than the second threshold value and less than or equal to the third threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a third risk level; When the predicted value of the risk warning indicator is greater than the third threshold value and less than or equal to the fourth threshold value, it is determined that the construction risk level of the underground powerhouse cavern of the hydropower station is a fourth risk level; Among them, the risk severity of the first risk level, second risk level, third risk level and fourth risk level decreases in sequence.

5. The method according to claim 4, wherein The early warning based on the construction risk level includes: When the construction risk level is level one, a red risk warning is issued; When the construction risk level is level 2, a yellow risk warning is issued; When the construction risk level is level three, an orange risk warning is issued; When the construction risk level is level four, a green risk warning is issued.

6. A hydropower station underground powerhouse cavern construction risk warning system, characterized by: The system comprises: an acquisition module, configured to acquire construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data of the underground powerhouse cavern of the hydropower station, and to normalize the construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data to obtain the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data; a determination module for determining the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station by using the analytic hierarchy process based on the normalized construction environment data, construction technology data, material and equipment data, equipment management data, and construction personnel data; A prediction module is used to substitute the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse cavern of the hydropower station into a pre-established risk warning indicator prediction model to obtain a risk warning indicator prediction value of the underground powerhouse cavern of the hydropower station; The judgment and early warning module is used to judge the construction risk level of the underground powerhouse cavern of the hydropower station based on the risk early warning index prediction value of the underground powerhouse cavern of the hydropower station, and to issue an early warning based on the construction risk level.

7. The system according to claim 6, wherein: The construction environment data includes: weather data, stability data in the cavern, and sudden water inrush data in the cavern; The construction technology data includes: technical solution completeness data, technical support availability data, advanced geological forecast accuracy data, and technology maturity data; The material and equipment data include: material and equipment quality inspection data, equipment inspection and maintenance data, equipment normal working status data, and equipment adaptability data; The equipment management data includes: inspection and early warning capability data, emergency response measures completeness data, and timeliness of communication and negotiation between all parties involved; The construction personnel data include: data on the professional skills proficiency of the construction personnel, data on the strength of the construction personnel's safety awareness, and data on the psychological fatigue level of the construction personnel.

8. The system according to claim 7, wherein: The process of establishing the risk warning indicator prediction model includes: Obtain the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, construction personnel risk value, and the measured value of the risk warning indicators corresponding to the underground powerhouse caverns of each hydropower station in the historical period, and divide them into training and test sets; The initial risk warning indicator prediction model is trained using the construction environment risk value, construction technology risk value, material and equipment risk value, equipment management risk value, and construction personnel risk value of the underground powerhouse caverns of each hydropower station in the historical period of the training set as input, and the measured value of the risk warning index of the underground powerhouse caverns of each hydropower station in the historical period of the training set as output to obtain a risk warning indicator prediction model after training with the training set; The risk warning indicator prediction model trained with the training set is optimized using the test set to obtain a trained risk warning indicator prediction model.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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