An underground engineering safety risk identification system and method

Abstract

The present application relates to a kind of underground engineering safety risk identification system and method, including control module, for controlling adjustment risk identification process;Monitoring identification module, for obtaining the risk identification information of monitoring object;Rule repository, for risk identification calculation to risk identification information;Guidance module, for outputting risk identification conclusion.Underground engineering is divided into several node ranges according to node level to form dynamic risk identification network;The calculation rule in rule repository is quantitatively expressed by range table and influence factor, and the risk identification information of each object element of object set is substituted into calculation to obtain risk identification conclusion.Control module can output high accuracy and high timeliness risk identification conclusion for the dynamic identification process of underground engineering safety risk based on the risk identification calculation of qualitative and quantitative combination, which can guide the construction process to take targeted monitoring prevention and construction adjustment.

Description

Technical Field

[0001] This invention relates to the field of underground engineering construction technology, and in particular to underground engineering risk identification and safety management, specifically an underground engineering safety risk identification system and method. Background Technology

[0002] In the fields of urban construction and transportation, underground engineering provides a good way to develop and utilize underground space resources and alleviate the pressure on surface space. It includes underground structures, underground railways, highway tunnels, and civil defense passages. Based on geological characteristics and construction conditions, the construction methods in underground engineering can be divided into shield tunneling, shallow buried tunneling, New Austrian Tunneling Method (NATM), and reverse construction method.

[0003] However, due to the inherent characteristics of underground construction, it inevitably impacts the surrounding natural structures and man-made features, especially in densely built-up urban environments. New underground projects not only affect the geological structure of the construction area but also involve adjacent or overlapping construction with existing railways, tunnels, buildings, bridges, rivers, and pipelines. Therefore, effective risk identification and assessment of the surrounding man-made and natural structures of underground projects, and the adoption of appropriate methods to control the impact of underground construction on the surrounding environment within a safe and reasonable range, are of great significance for ensuring both the safety of the local project and the overall environmental safety.

[0004] Existing technologies for safety management and risk identification in underground engineering include the following methods: (i) Qualitative analysis, which mainly relies on risk classification, evaluation indicators and weight tables to assess risks and determine risk levels; (ii) Quantitative analysis, which is based on statistical data and probability analysis, including decision tree method, Monte Carlo method, Bayesian method, etc.; (iii) Predictive analysis, which is based on the spatiotemporal patterns of data to conduct predictive safety analysis, including artificial neural networks, forecasting models, nonlinear autoregressive methods, etc.

[0005] For example, patent CN114139864A discloses a method, device, equipment, and readable storage medium for identifying environmental risks in subway engineering. The method includes acquiring first information, which includes a set of environmental objects and a subway structural model of the subway project. The set of environmental objects includes at least one environmental subset. A collision model is established based on the first information, and the collision model is solved to obtain collision results, which include the collision set corresponding to each sub-model. The risk level corresponding to each environmental object is obtained by searching a preset collision risk database based on the collision results. This patent's technical solution uses the first information in conjunction with the subway structural model for calculation and analysis to obtain the zoning number information of the surrounding environment of the project, and searches for the risk level of the environmental object corresponding to the first information based on the preset risk database. However, its calculation and analysis are based on the designed underground structural model and do not consider the risk changes and fluctuations brought about by the construction process; that is, there is a dynamic interference error between the predicted risk level and the actual risk level.

[0006] Patent CN103366092B discloses an engineering risk monitoring system and method based on state transition. The system includes a raw data processing module, a state transition visualization module, a graphic feature extraction module, an automatic learning module, and an automatic image recognition module. The state transition visualization module generates state transition diagrams for each state in the project based on the data processed by the raw data processing module. The graphic feature extraction module extracts set features from the state transition diagrams. The automatic learning module calculates the ratio of each feature value to the historical average based on the extracted graphic features and sets a threshold. The automatic image recognition module determines whether the project is in a risky state based on the set features extracted by the graphic feature extraction module and the threshold set by the automatic learning module. This patent's technical solution achieves visualized monitoring of engineering risks based on data processing and image comparison recognition functions. However, the accuracy of risk identification depends on the data image construction rules and the criteria for image change recognition. Furthermore, the risk monitoring points in underground engineering are often non-uniform and variable point, line, and surface arrangements, resulting in a mismatch between the raw data obtained from monitoring and the requirements for image recognition.

[0007] Patent CN102609774B discloses a subway construction safety risk identification and reasoning system and its identification and reasoning method. The system includes a user interface module, an engineering parameter module, a rule module, a reasoning work area module, and a conclusion interpretation module. The identification and reasoning method first receives the work site classification, construction method classification, and safety risk engineering parameters and stores them in the reasoning work area. Then, it performs classification rule base, risk factor matching, and rule reasoning to finally determine the conclusion and interpret the risk. The technical solution of this patent provides a subway construction safety risk identification and reasoning system and its identification and reasoning method, specifically designed to implement a technical solution for subway construction safety risk identification and reasoning based on a rule reasoning (RBR) mechanism and a risk identification rule base. However, the technical solution of this patent mainly relies on design parameters and preset rules to perform rule reasoning on risk factors. In the actual construction process, the relative engineering parameters of each risk identification object and the construction project are in a changing process, so the corresponding risk conclusion should be a set of conclusions that progress over time.

[0008] In summary, existing technologies for risk identification and safety management in underground engineering construction primarily rely on engineering design parameters, risk monitoring object information, and pre-set model databases for qualitative classification or quantitative estimation. While these can serve as preliminary references before construction, the risk identification strategies and processes do not consider the impact of dynamic project progress. In other words, safety risk information cannot be dynamically updated and adjusted according to the progress of the underground engineering construction face. A dynamic risk identification network should be formed based on the relative positional changes between the risk monitoring objects and the underground engineering construction face. Risk identification conclusions for the downstream construction area should be updated based on upstream risk identification conclusions and monitoring data. This would ensure a better temporal and spatial alignment between the risk identification conclusions and the actual construction process. Specifically, the update time of the risk identification conclusions should be shorter than the construction time interval of the corresponding construction area, and the update scope of the risk identification conclusions should be closer to the corresponding construction scope. This would allow risk identification and safety management in underground engineering construction to incorporate dynamic factors such as construction progress, guiding targeted monitoring, prevention, and construction adjustments during the construction process.

[0009] Furthermore, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the inventors studied a large number of documents and patents when making this invention, but due to space limitations, not all details and contents were listed in detail. However, this does not mean that the present invention does not possess the features of these prior art. On the contrary, the present invention already possesses all the features of the prior art, and the applicant reserves the right to add relevant prior art to the background art. Summary of the Invention

[0010] To address at least some of the shortcomings of existing technologies, this application provides an underground engineering safety risk identification system. The system includes: a control module for controlling and adjusting the risk identification process and re-performing the risk identification process based on triggering conditions; a monitoring and identification module for acquiring risk identification information of monitored objects; a rule repository for performing risk identification calculations on the risk identification information; and a guidance module for outputting risk identification conclusions for monitored objects.

[0011] When the control module divides the construction area of ​​the underground project into several node ranges according to the node level, different node ranges are set with differentiated risk identification cycles based on the node level to control the update time interval of risk identification; the calculation rules in the rule repository include at least construction method rules, construction design rules, geological parameter rules and standard criteria. The calculation rules can be quantitatively expressed through the range table and influence factors. The control module substitutes the risk identification information into the risk identification calculation to obtain the risk identification conclusion.

[0012] The risk identification process includes the following steps:

[0013] The monitoring and identification module classifies and summarizes the monitored objects into an object set with at least two nested structures based on multiple identification rules. The object elements in the object set are configured with risk identification information. The nested structure refers to the nested set formed by the object set based on the identification rules. The identification rules include at least the monitoring object category and coordinate information.

[0014] Risk identification calculation is performed by comparing the risk identification information of object elements with the calculation rules in the rule repository. The risk identification calculation includes a matching operation between the object matrix composed of object elements and the rule matrix composed of rule elements.

[0015] The guidance module outputs the risk identification conclusion obtained through risk identification calculation, and associates and sorts the object elements in the object set with the risk identification conclusion, so that the object elements are arranged in ascending or descending order based on at least a part of the information in the risk identification conclusion. The risk identification conclusion includes at least the risk identification level, guidance information, and deformation control indicators.

[0016] The control module changes at least some of the calculation rules in the rule repository based on trigger conditions and re-performs the risk identification process. The guidance module outputs guidance information about the changes in calculation rules and provides a reference for downstream construction design.

[0017] To address the issue that existing risk identification strategies and processes fail to consider the dynamic impact of engineering progress, current risk identification methods cannot incorporate dynamic changes during construction at key points in underground engineering projects. They rely solely on existing design parameters or models of the underground engineering project for correlation analysis with the risk identification targets. Therefore, this application divides the construction scope of the underground engineering project into several key monitoring areas based on the different monitoring targets it passes through. The monitoring targets corresponding to these key monitoring areas are the critical areas for cross-construction or near-construction, serving as the focus for risk identification and safety monitoring. Different risk identification cycles are set for different key areas based on node level to control the update interval of risk identification. The continuous advancement of construction within these key areas alters the structure of the underground engineering project itself, and its relative position to the risk identification monitoring targets also changes accordingly. This is especially true during underground construction with large time or spatial spans, where geological structures and environmental conditions also change as construction progresses, such as groundwater levels and ambient temperature. Therefore, it is necessary to implement a feedback loop in the risk identification process to obtain updated risk identification conclusions, avoiding significant deviations between the static risk identification results of existing technologies and the actual construction process.

[0018] Underground engineering projects have a wide-ranging impact, primarily encompassing the geological and hydrological environment, above-ground or underground structures, and the engineering itself. This is especially true in urban environments where man-made structures are densely packed, and many existing projects are adjacent to or intersect with underground engineering projects. To ensure accurate selection and effective labeling of monitoring objects during the risk identification process, this application categorizes and identifies monitoring objects affected by underground engineering projects using an element set approach, forming an object set with at least two nested layers. The categorization rules include monitoring object categories and coordinate information. The coordinate information includes absolute coordinates referenced to the construction design and relative coordinates relative to the construction surface. Categorizing and arranging specific monitoring objects as element sets clearly demonstrates the degree of impact of underground engineering projects on various major monitoring objects, avoiding information confusion caused by an excessive number of risk identification monitoring objects. Specifically, the first-level object set can be classified according to the category of the monitored object, and the second-level object set can be classified according to the relative positional relationship between the monitored object and the underground project. The relative positional relationship is calculated from coordinate information. The elements of the first-level object set can include high-rise buildings, ground tracks, bridges, subway tunnels, underground pipelines, geological structures, and the project itself, which can be used as the first-level element set. The elements in the first-level object set can be used as the second-level object set, which can include object elements in different relative positions. The object elements are sorted according to the degree of influence.

[0019] The monitoring and identification module categorizes and sorts the acquired risk identification information into object sets. The control module calls the calculation rules in the rule repository to perform risk identification calculations on the object sets. The calculation rules in the rule repository may include construction method rules, construction design rules, geological parameter rules, and standard guidelines. Construction method rules reflect the degree of impact of different construction methods on the monitored objects. Construction design rules use construction design parameters as the basis for judging the degree of impact. Geological parameter rules mainly use the geological structure between the monitored objects and underground engineering as a reference. Standard guidelines use industry standards and guidance documents as references. The above calculation rules can be quantitatively expressed through range tables and influence factors. The risk identification information of each object element in the object set is substituted into the calculation to obtain the risk identification conclusion. The risk identification conclusion may include risk identification level, guidance information, and deformation control indicators. The object elements in the object set are re-associated and sorted based on the risk identification conclusion, so that the updated object set can reflect the impact of changes in risk identification information or calculation rules.

[0020] The guidance module outputs the risk identification conclusions obtained through risk identification calculations. The risk identification level can intuitively display the risk level of the monitored object at the current stage. For monitored objects that exceed a certain risk level, it is necessary to adjust the construction design rules to ensure that the risk level is within a safe and controllable range. Furthermore, it is essential to strictly monitor the development pattern of actual deformation data to ensure that the deformation rate and cumulative deformation of the monitored object do not exceed the deformation control indicators in the risk identification conclusions.

[0021] The control module modifies at least some calculation rules in the rule repository based on trigger conditions and re-performs the risk identification process. Trigger conditions may include the risk level of the monitored object exceeding the warning level or the construction face entering / leaving the node range. The method of setting up the risk identification process to modify some calculation rules based on trigger conditions allows for timely adjustments to the construction design method based on the risk identification conclusions. Furthermore, the risk identification process can reflect the dynamic changes of the underground engineering construction face at different node ranges, ensuring that the risk identification conclusions upstream in time update the risk identification conclusions for the downstream construction area. This makes the risk identification conclusions more aligned with the actual construction process in time and space; that is, the update time of the risk identification conclusions is shortened compared to the construction time interval of the corresponding construction area, and the update range of the risk identification conclusions is closer to the corresponding construction range. This is of great significance for risk identification and safety management of underground engineering projects with large construction time or spatial spans.

[0022] Preferably, the monitoring objects in the risk identification process include existing line tunnels, underground pipelines, above-ground structures, lakes, geological structures, and the engineering body itself; the risk identification information includes at least the category, coordinate information, and structural level of the monitoring object, wherein the coordinate information includes absolute coordinates with reference to the construction design and relative coordinates with the construction surface as the relative origin.

[0023] Preferably, the monitoring and identification module represents risk identification information using an object set that includes at least two nested structures. The first-level object set can be classified according to the category of the monitored object, and the second-level object set can be classified according to the relative positional relationship between the object element and the underground project. The relative positional relationship is calculated from coordinate information.

[0024] Preferably, the coordinate information of the monitored object is calibrated using absolute coordinates and relative coordinates. The coordinate information in the identification rules can be used to calculate the absolute distance and relative distance between the monitored object and the underground project. The absolute distance refers to the shortest distance from the monitored object to the underground project, which can be used to calculate the node level of the corresponding node range of the monitored object. The relative distance refers to the distance from the monitored object to the construction surface, which can be used to classify and summarize the monitored object into an object set.

[0025] Preferably, when the monitoring and identification module sets the acquired object set as a two-level nested structure set, the object set containing X elements can be represented as M(A1, A2, A3, ..., A...). X ), A1 to A X It can be represented as A X (B1, B2, B3, ..., B) Y ), where A1 to A X The elements of the first-level object set, B1 to B, are obtained by classifying the monitored objects according to their categories. Y X and Y are the elements of the second-level object set obtained by classifying the monitoring objects and the underground palace project according to their relative positional relationship. X and Y are positive integers not less than 1.

[0026] Preferably, the object elements configured with risk identification information in the object set are arranged into an object matrix M with at least a two-dimensional structure. The calculation rules in the rule repository are quantified into several range tables / influence factors with matching annotations and conclusion annotations to form rule elements. Several rule elements are classified and summarized into a rule matrix N with at least a two-dimensional structure, wherein the number of columns in matrix M is X, and the number of rows in matrix N is not less than X.

[0027] Preferably, the risk identification calculation process includes: searching and matching the object elements in each column of matrix M with the rule elements in each row of rule matrix N; substituting the risk identification information of the object elements and the matching annotations of the rule elements into the range table / influence factor for calculation to obtain the calculation results and corresponding conclusion annotations. The object elements in the object set can be categorized into several nested sets and object matrices based on the number of identification rules. The risk identification information of each object element is used as the raw data for risk identification calculation. The calculation rules in the rule repository are quantified and expressed as rule elements, forming a rule matrix adapted to the object matrix. The combination of the object matrix and the rule matrix provides the computational foundation and mathematical model for risk identification calculation, facilitating quantitative analysis and data expression in the risk identification calculation process. Furthermore, the object elements in the object matrix are configured with risk identification information, and the rule elements in the rule matrix are configured with matching annotations and conclusion annotations, facilitating qualitative analysis and logical judgment in the risk identification calculation process. Therefore, the risk identification calculation combining qualitative and quantitative methods can output highly accurate and timely risk identification conclusions for the dynamic identification process of underground engineering safety risks.

[0028] Preferably, the control module re-associates and sorts the object elements in at least a portion of the object set based on the risk identification conclusion, so that the ascending or descending order of the object elements can reflect the priority of risk control for various monitoring objects. For example, the higher the risk identification level, the greater the impact of underground engineering on the monitoring object. When the risk identification level exceeds the warning level, the construction design parameters need to be improved so that the impact of the construction process on the monitoring object is within a safe and controllable range.

[0029] Preferably, when a construction area is formed by combining several node ranges and several general ranges, the length of the node range is determined by the node level. The node level is determined at least based on the relative positional relationship between the monitored object and the underground project, and geological parameters. The node range represents the adjacent construction area between the underground project and the monitored object. The length of the node range, determined by the node level, can be linked to the relative positional relationship and geological parameters. The higher the proximity of the underground project—that is, the closer the relative position of the underground project and the monitored object—the longer the corresponding node range should be. This allows the risk identification process to incorporate the dynamic construction process of the node range by increasing the frequency of risk identification, thus better guiding the construction process.

[0030] Preferably, when the construction surface of the underground project moves from the general range into / out of the node range, the trigger control module adjusts and modifies at least some of the calculation rules in the rule repository and changes the risk identification cycle, so that the update rate of risk identification is adapted to the node level of the node range. When the construction surface is in the general range, that is, the key monitoring object is far from the construction surface, the relative positional relationship between the key monitoring object and the construction surface does not change much during the construction process, and the dynamic process of construction has little impact on the key monitoring object, so the update frequency of the risk identification process can be appropriately reduced. When the construction surface is in the node range, the dynamic process of construction has a greater impact on the key monitoring object, so the control module should increase the update frequency of the risk identification process and update and replace at least some of the calculation rules in the rule repository in a timely manner. For example, the construction design rules mainly based on the underground engineering construction model. When the underground project advances in the node range, the relative positional change of the structure in the underground engineering construction model will be relatively significant. Therefore, the timely update of the construction design rules by the control module according to the trigger conditions can ensure the timeliness and accuracy of the risk identification process.

[0031] Preferably, the node range is divided into several segments based on the risk identification cycle. When the construction surface of the underground project is located in the previous segment of the node range, the control module performs risk identification calculations based on the risk identification information of the current segment to obtain risk identification conclusions to guide the next segment. When the construction surface advances to the previous segment of the node range, the risk identification information of that segment, after risk identification calculations, can obtain risk identification conclusions that reflect the changing trends of the next segment. The control module can better simulate the construction impact of the next segment based on the implementation status of the current segment stage, so as to adjust the construction parameters of the next segment in a timely manner.

[0032] Preferably, when the construction surface is located in the previous section of the node range, the control module controls the risk identification process to obtain the risk identification conclusion. If the risk identification level of the monitored object is greater than the warning level, the control module is triggered to adjust at least some of the calculation rules in the rule repository so that the updated risk identification level does not exceed the warning level. The guidance module provides adjustment reference for the actual construction process of the next section by transmitting guidance information.

[0033] Preferably, when the construction surface is located in the previous section of the node range, the control module controls the risk identification process to obtain the risk identification conclusion. If the measured deformation data of the monitored object exceeds the deformation control index, the guidance module provides adjustment reference for the actual construction process of the next section by transmitting guidance information.

[0034] Preferably, when the node ranges corresponding to the monitored objects overlap, overlap information is added to the risk identification information corresponding to the monitored objects and substituted into the risk identification calculation. This makes the change in the risk identification level in the risk identification conclusion positively correlated with the degree of overlap. The change in the risk identification level is the difference between the risk identification level obtained considering the overlap information and the risk identification level obtained without considering the overlap information. Compared to node ranges with only a single key monitored object, when node ranges overlap, the combined influence of multiple key monitored objects and underground engineering should be considered. The closer multiple key monitored objects are in space, the higher the degree of overlap of the node ranges. The overlap of node ranges can be used to characterize the proximity of key monitored objects. Substituting the overlap information of node ranges as risk identification information into the risk identification calculation yields a correction to the risk identification conclusion, thereby more accurately identifying the risk level of the overlapping node range area.

[0035] The present invention also provides a method for identifying safety risks in underground engineering projects. This method can be executed based on the aforementioned underground engineering safety risk identification system and includes one or more of the following steps:

[0036] The control module divides the construction area of ​​the underground project into several node ranges according to the node level. Different risk identification cycles are set for different node ranges based on the node level to control the update time interval of risk identification.

[0037] The monitoring and identification module classifies and summarizes the monitored objects into an object set with at least two nested structures based on multiple identification rules. The object elements in the object set are configured with risk identification information. The nested structure refers to the nested set formed by the object set based on the identification rules. The identification rules include at least the monitoring object category and coordinate information.

[0038] Risk identification calculation is performed by comparing the risk identification information of object elements with the calculation rules in the rule repository. The risk identification calculation includes a matching operation between the object matrix composed of object elements and the rule matrix composed of rule elements.

[0039] The guidance module outputs risk identification calculations to obtain risk identification conclusions, and associates and sorts the object elements in the object set with the risk identification conclusions, so that the object elements are arranged in ascending or descending order based on at least a part of the information in the risk identification conclusions. The risk identification conclusions include at least the risk identification level, guidance information, and deformation control indicators.

[0040] The control module changes at least some of the calculation rules in the rule repository based on trigger conditions and re-performs the risk identification process. The guidance module outputs guidance information about the changes in calculation rules and provides a reference for downstream construction design.

[0041] The method also includes one or more of the following steps:

[0042] The object set acquired by the monitoring and identification module is set as a two-level nested collection. An object set containing X elements can be represented as M(A1, A2, A3, ..., A...). X ), A1 to A X It can be represented as A X (B1, B2, B3, ..., B) Y ), where A1 to A X The elements of the first-level object set, B1 to B, are obtained by classifying the monitored objects according to their categories. Y X and Y are the elements of the second-level object set obtained by classifying the monitoring objects and the underground palace project according to their relative positional relationship. X and Y are positive integers not less than 1.

[0043] Arrange the object elements configured with risk identification information in the object set into an object matrix M with at least a two-dimensional structure. Quantify the calculation rules in the rule repository into several range tables / influence factors with matching annotations and conclusion annotations to form rule elements. Classify and summarize several rule elements into a rule matrix N with at least a two-dimensional structure, where the number of columns in matrix M is X and the number of rows in matrix N is not less than X.

[0044] During risk identification calculation, the object elements in each column of the M matrix are searched and matched with the rule elements in each row of the rule matrix N. The risk identification information of the object elements and the matching annotations of the rule elements are substituted into the range table / influence factor for calculation to obtain the calculation results and corresponding conclusion annotations.

[0045] When a construction area is formed by combining several node ranges and several general ranges, the length of the node range is determined by the node level; when the construction surface of the underground project enters / leaves the node range from the general range, the control module is triggered to adjust and modify at least some of the calculation rules in the rule repository and change the risk identification cycle.

[0046] The node range is set into several segments based on the risk identification cycle. When the construction surface of the underground project is located in the segment above the node range, the control module performs risk identification calculation based on the risk identification information of the current segment to obtain the risk identification conclusion to guide the next segment. If the risk identification level of the monitored object is greater than the warning level, the control module is triggered to adjust at least some of the calculation rules in the rule repository. The guidance module provides adjustment reference for the actual construction process of the next segment by transmitting guidance information.

[0047] When the node ranges of two key monitoring objects overlap, overlap information is added to the risk identification information corresponding to the key monitoring objects, and risk identification calculation is performed with the calculation rules in the rule repository. This results in a positive correlation between the change in risk identification level in the risk identification conclusion and the degree of overlap. The change in risk identification level is the difference between the risk identification level obtained considering overlap information and the risk identification level obtained without considering overlap information. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the system structure of a preferred embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of an underground engineering structure according to a preferred embodiment of the present invention;

[0050] Figure 3 This is a schematic diagram of the underground engineering node range according to a preferred embodiment of the present invention.

[0051] List of reference numerals

[0052] 100: Control module; 200: Monitoring and identification module; 300: Rule repository; 400: Guidance module; 500: Underground engineering route; 501: Node range; 5011: Previous section; 5012: Next section; 502: General range; 503: Construction surface. Detailed Implementation

[0053] The present invention will now be described in detail with reference to the accompanying drawings.

[0054] This application provides a safety risk identification system for underground engineering projects, such as... Figure 1 As shown, the system includes a control module 100, a monitoring and identification module 200, a rule repository 300, and a guidance module 400. The control module 100 is used to control and adjust the risk identification process and store process information. When the control module 100 divides the construction area of ​​the underground engineering line 500 into several node ranges 501 according to node level, different node ranges 501 are set with differentiated risk identification cycles based on node level to control the update time interval of risk identification.

[0055] like Figure 2As shown, this application divides the construction scope of the underground engineering line 500 into several node ranges 501 based on the different monitoring objects that the underground engineering line 500 passes through. The monitoring objects corresponding to the node ranges 501 are the key monitoring objects, and the areas corresponding to the node ranges 501 are the key areas for cross-construction or close-contact construction, which can be used as the focus of risk identification and safety monitoring of underground engineering. Different node ranges 501 are set with differentiated risk identification cycles based on node level to control the update time interval of risk identification. During the advancement of the construction face 503 in the node ranges 501, the structure of the underground engineering itself is continuously changed, and the relative position with the risk identification monitoring objects will also change accordingly. Especially in the underground construction process with a large construction time or spatial span, the geological structure and environmental conditions will also change with the progress of construction, such as groundwater level and ambient temperature. Therefore, it is necessary to conduct a feedback loop in the risk identification process to obtain updated risk identification conclusions and avoid large deviations between the static risk identification results of the prior art and the actual construction process.

[0056] The monitoring and identification module 200 is used to acquire risk identification information of the monitored objects. The monitored objects in the risk identification process include existing line tunnels, underground pipelines, above-ground structures, lakes, geological structures and engineering bodies, etc.; the risk identification information includes at least the category, coordinate information and structural level of the monitored object.

[0057] The rule repository 300 is used to perform risk identification calculations on risk identification information. The calculation rules in the rule repository 300 include at least construction method rules, construction design rules, geological parameter rules, and standard criteria. The calculation rules can be quantitatively expressed through range tables and influence factors. The control module 100 substitutes the risk identification information into the risk identification calculation to obtain the risk identification conclusion.

[0058] The guidance module 400 provides reference information to the downstream construction process based on the risk identification conclusions. The risk identification conclusions include the identification level, guidance information, and deformation control indicators. The risk identification level can intuitively display the risk level of the monitored object at the current stage. For monitored objects exceeding a certain risk level, it is necessary to adjust the construction design rules by transmitting guidance information to ensure that the risk level is within a safe and controllable range. It is also necessary to strictly monitor the development pattern of actual deformation data to ensure that the deformation rate and cumulative deformation of the monitored object do not exceed the deformation control indicators in the risk identification conclusions. The guidance information can be construction guidance information such as the advancing speed, grouting pressure, and support scheme.

[0059] The process of risk identification using the aforementioned underground engineering safety risk identification system includes the following steps:

[0060] (1) The monitoring and identification module 200 classifies and summarizes the monitored objects into an object set with at least two nested structures based on multiple identification rules. The object elements in the object set are configured with risk identification information. The nested structure refers to the nested set formed by the object set based on the identification rules. The identification rules include at least the monitoring object category and coordinate information. The coordinate information includes the absolute coordinates with the construction design as a reference and the relative coordinates with the construction surface 503 as the relative origin.

[0061] To ensure accurate selection and effective labeling of monitoring objects during the risk identification process, this application categorizes and arranges specific monitoring objects into sets of elements. This clearly demonstrates the impact of underground engineering on various major monitoring objects, avoiding information confusion caused by an excessive number of monitoring objects. Specifically, the first-level object set can be classified according to the category of the monitoring object, and the second-level object set can be classified according to the relative positional relationship between the monitoring object and the underground engineering line 500. The relative positional relationship is calculated from coordinate information. For example, the elements of the first-level object set may include high-rise buildings, ground tracks, bridges, subway tunnels, underground pipelines, geological structures, and the engineering body itself. The elements of the second-level object set may include object elements at different relative positions. The object elements are sorted by a combination of relative and absolute distances. The coordinate information of the monitoring object is calibrated using absolute and relative coordinates. The coordinate information in the identification rules can calculate the absolute and relative distances between the monitoring object and the underground engineering line 500. The absolute distance refers to the shortest distance from the monitoring object to the underground engineering line 500, and the relative distance refers to the distance from the monitoring object to the construction surface 503.

[0062] (2) Perform risk identification calculation by comparing the risk identification information of the object elements with the calculation rules in the rule repository 300. The risk identification calculation includes a matching operation between the object matrix composed of object elements and the rule matrix composed of rule elements.

[0063] When the monitoring and identification module 200 sets the acquired object set as a two-level nested structure set, the object set containing X elements can be represented as M(A1, A2, A3, ..., A...). X ), A1 to A X It can be represented as A X (B1, B2, B3, ..., B) Y ), where A1 to A X The first-level object set elements, B1 to B, are obtained by classifying the monitored objects into different categories. Y X and Y are the elements of the second-level object set obtained by classifying the monitoring objects and the underground palace project according to their relative positional relationship. X and Y are positive integers not less than 1.

[0064] For example, in an object set, the first-level object set elements A1 to A... XThe first layer of the object set is categorized by the type of monitored object, including existing underground tunnels, underground pipelines, above-ground railways, bridges, high-rise buildings, geological structure control points, and the main structure of the engineering project. For the case where the first layer of the object set is a high-rise building, the second layer of the object set elements B1 to B... Y The buildings are designated as high-rise 1, high-rise 2, high-rise 3, etc. The sorting rule is determined based on at least one of the absolute distance and relative distance from the high-rise to the underground engineering line 500. The absolute distance represents the closest distance the monitoring object is to the underground engineering construction process, and the relative distance represents the distance of the monitoring object from the construction surface 503. When the monitoring object is located downstream of the construction surface 503, the geological structure around the monitoring object has not changed, so the sorting rule is determined by the relative distance. When the monitoring object is located upstream of the construction surface 503, the geological structure around the monitoring object is still changing, so the sorting rule is determined by a combination of the absolute distance and the relative distance.

[0065] The object elements configured with risk identification information within the object set are arranged into an object matrix M with at least a two-dimensional structure. The calculation rules in the rule repository 300 are quantified into several range tables / influence factors with matching annotations and conclusion annotations, forming rule elements. These rule elements are then classified and summarized into a rule matrix N with at least a two-dimensional structure, where the number of columns in matrix M is X, and the number of rows in matrix N is not less than X. The risk identification calculation process includes: searching and matching each object element in each column of matrix M with the rule elements in each row of rule matrix N; substituting the risk identification information of the object elements and the matching annotations of the rule elements into the range tables / influence factors for calculation based on their compatibility; obtaining the calculation results and corresponding conclusion annotations; and processing the calculation results and conclusion annotations by the guidance module 400 to form the corresponding risk identification conclusion.

[0066] The object matrix M consists of object elements, which are the elements of the second-level object set. All object elements in each column of the object matrix are combined to form the elements of the first-level object set. Therefore, the number of columns in the object matrix is ​​X, and the number of rows is Y. max Y max The maximum value in Y; the rule matrix N is composed of rule elements. All the rule elements in each row of the rule matrix N form the calculation rule for the first-level object set elements of the corresponding column number in the object matrix M. Then the number of rows in the rule matrix is ​​not less than X. The calculation rules in the rule repository 300 may include construction method rules, construction design rules, geological parameter rules, and standard guidelines. Construction method rules can reflect the degree of influence of different construction methods on the monitored object. Construction design rules use construction design parameters as the basis for judging the degree of influence. Geological parameter rules mainly use the geological structure between the monitored object and the underground engineering line 500 as a reference. Standard guidelines use industry standards and guidance documents as references.

[0067] The object elements in the object set can be categorized into object matrices of several dimensions based on the number of identification rules. The risk identification information of each object element is used as the raw data for risk identification calculation. The calculation rules in the rule repository 300 are quantitatively expressed and formed into a rule matrix adapted to the object matrix in the form of rule elements. The combination of the object matrix and the rule matrix provides a computational foundation and mathematical model for risk identification calculation, facilitating quantitative analysis and data expression in the risk identification calculation process. Furthermore, the object elements in the object matrix are configured with risk identification information, and the rule elements in the rule matrix are configured with matching annotations and conclusion annotations, facilitating qualitative analysis and logical judgment in the risk identification calculation process. Therefore, the risk identification calculation combining qualitative and quantitative methods can output highly accurate and timely risk identification conclusions for the dynamic identification process of underground engineering safety risks.

[0068] (3) The guidance module 400 outputs the risk identification calculation to obtain the risk identification conclusion, and associates and sorts the object elements in the object set with the risk identification conclusion, so that the object elements are arranged in ascending or descending order based on at least a part of the information in the risk identification conclusion. The risk identification conclusion includes at least the risk identification level, guidance information, and deformation control indicators. The object elements in the object set can be re-associated and sorted based on the risk identification conclusion, so that the updated object set can reflect the impact of changes in risk identification information or calculation rules. The control module 100 re-associates and sorts the object elements in the object set based on at least a part of the risk identification conclusion, so that the ascending or descending order of the object elements can reflect the priority of risk control for various monitoring objects. For example, the higher the risk identification level, the greater the impact of underground engineering on the monitoring object. When the risk identification level exceeds the warning level, the construction design parameters need to be improved so that the impact of the construction process on the monitoring object is within a safe and controllable range.

[0069] (4) The control module 100 changes at least some of the calculation rules in the rule repository 300 based on trigger conditions and re-performs the risk identification process. The guidance module 400 outputs guidance information on the changes in calculation rules and provides a reference for the construction design downstream. Trigger conditions may include the risk level of the monitored object exceeding the warning level or the construction surface 503 entering / leaving the node range 501. Under this setting, the risk identification process can reflect the dynamic changes of the construction surface 503 of the underground engineering line 500 located in different node ranges 501, ensuring that the risk identification conclusions upstream update the risk identification conclusions of the construction area downstream, making the risk identification conclusions more consistent with the actual construction process in time and space. That is, the update time of the risk identification conclusions and the construction time interval of the corresponding construction area are shortened, and the update range of the risk identification conclusions is close to the corresponding construction range. This is of great significance for risk identification and safety management of underground engineering with large construction time or spatial span.

[0070] When a construction area is formed by combining several node ranges 501 and several general ranges 502, the length of the node range 501 is determined by the node level. The node level is determined at least based on the relative positional relationship between the monitoring object corresponding to the node range 501 and the underground engineering line 500 and geological parameters. When the construction surface 503 of the underground engineering line 500 enters / leaves the node range 501 from the general range 502, the control module 100 is triggered to adjust and modify at least some of the calculation rules in the rule repository 300 and change the risk identification cycle so that the risk identification update rate is adapted to the node level of the node range 501.

[0071] Node range 501 represents the close construction area between the underground engineering line 500 and the monitored object. The length of node range 501 is determined according to the node level and can be linked to the relative position and geological parameters. The higher the proximity of the underground engineering line 500, that is, the closer the relative position of the underground engineering line 500 and the monitored object, the longer the corresponding node range 501 should be. This allows the risk identification process to take into account the dynamic construction process of node range 501 by increasing the frequency of risk identification, so as to better guide the construction process. When the construction surface 503 is in the general range 502, that is, the key monitoring object is far from the construction surface 503, the relative positional relationship between the key monitoring object and the construction surface 503 does not change much during the construction process, and the dynamic process of construction has little impact on the key monitoring object. Therefore, the update frequency of the risk identification process can be appropriately reduced. When the construction surface 503 is in the node range 501, the dynamic process of construction has a greater impact on the key monitoring object. Therefore, the control module 100 should increase the update frequency of the risk identification process and update and replace at least some of the calculation rules in the rule repository 300 in a timely manner. For example, the construction design rules mainly based on the underground engineering construction model. When the underground engineering line 500 advances in the node range 501, the relative positional change of the structure in the underground engineering construction model will be relatively significant. Therefore, the control module 100 can ensure the timeliness and accuracy of the risk identification process by updating the construction design rules in a timely manner according to the triggering conditions.

[0072] For example, the node level is set as K1, and the node level of each node range 501 is determined as level one to nine based on the importance evaluation of the corresponding key monitoring object, relative position relationship, construction design parameters, geological structure parameters, and criteria and specifications; the length of each node range 501 is calculated based on the node level. Specifically, the node range length S is calculated by the following formula: S=(K1*K2*k3*(D / D0)). a ) / ((H / H0) b *(L / L0) cIn this equation, K1 is the node level, with values ​​ranging from 1 to 9; K2 is the geological structure coefficient, used to consider the influence of geological parameters on the length of the node range 501; K3 is the construction method coefficient, used to consider the degree of influence of various underground engineering construction methods on the monitored object; D is the reference dimension of the underground engineering, such as tunnel diameter, cross-sectional reference diameter, etc.; H is the depth of the underground engineering; and L is the minimum distance between the key monitored object and the underground engineering. Considering that the value ranges of D, H, and L are quite different, benchmark numbers D0, H0, and L0 are introduced to make the magnitudes of D / D0, H / H0, and L / L0 close to the same order of magnitude, and changing the benchmark numbers can adjust the influence ratio of D, H, and L on S. At the same time, considering that the node range length S is not simply directly or inversely proportional to the underground engineering reference dimension D, the underground engineering depth H, and the minimum distance L, correction exponents a / b / c are introduced for D / H / L respectively. For example, if the correction index 'a' for the reference dimension D of an underground project is set to 1.2, the difficulty of an underground project increases exponentially with its construction scale. Therefore, when considering the impact of the construction dimension on the surrounding environment and monitoring objects, a correction index should be introduced to correctly evaluate the impact of the increased construction dimension on the node range length S. Similarly, the deeper the underground project (H), the more stable its structure becomes, and the node range length S is negatively correlated with the underground project depth (H). Conversely, the smaller the minimum spacing (L), the closer the underground project is to the key monitoring objects, thus increasing the node range length S that should be prioritized for monitoring, and the node range length S is also negatively correlated with the minimum spacing (L). Quantitatively linking the calculation of the node range length with node level, geological structure coefficient, construction method coefficient, underground project reference dimension, underground project depth, and minimum spacing allows for a comprehensive consideration of various influencing factors in underground project risk identification. This is of great significance for scientifically setting the node range length and improving the accuracy of risk identification.

[0073] Preferably, the risk identification cycle within node range 501 is determined based on the node level. For example, for general areas, the risk identification cycle is set to 7 days / time, meaning that re-identification is performed every 7 days according to the updated calculation rules. The updated calculation rules can be construction design rules for the construction model. For node areas, the risk identification cycle should be adapted to the node level of node range 501, i.e., the node level and the risk identification cycle are negatively correlated. For node levels one to nine, the risk identification cycle is reduced from 6 days / time to 1 day / time. The construction design rules in the calculation rules incorporate the impact of construction face advancement on the construction model into the risk identification calculation process based on the shortened risk identification cycle, which can meet the timeliness requirements of risk identification in areas such as node range 501. When the risk identification conclusion upstream exceeds the safe range, guidance and reference are promptly provided to the construction parameters downstream, such as advancement speed, grouting pressure, and support scheme. Then, risk identification calculation is re-performed based on the updated construction design rules, enabling the upstream risk identification process to effectively control risk factors in downstream construction based on dynamic risk identification calculation, and proactively eliminate safety hazards.

[0074] Preferably, such as Figure 3 As shown, the node range 501 is divided into several segments based on the risk identification cycle. When the construction surface 503 of the underground engineering line 500 is located in the previous segment 5011 of the node range 501, the control module 100 performs risk identification calculations based on the risk identification information of the current segment to obtain risk identification conclusions to guide the next segment 5012. When the construction surface 503 advances to the previous segment 5011 of the node range 501, the risk identification information of that segment can be used to obtain risk identification conclusions that reflect the changing trend of the next segment 5012 after risk identification calculations. The control module 100 can better simulate the construction impact of the next segment 5012 based on the implementation status of the current segment stage, so as to adjust the construction parameters of the next segment 5012 in a timely manner.

[0075] Preferably, when the construction surface 503 is located in the previous section 5011 of the node range 501, the control module 100 controls the risk identification process to obtain a risk identification conclusion. If the risk identification level of the monitored object is greater than the warning level, the control module 100 is triggered to adjust at least some of the calculation rules in the rule repository 300 so that the updated risk identification level does not exceed the warning level. If the measured deformation data of the monitored object exceeds the deformation control index, the guidance module 400 provides adjustment reference for the actual construction process of the next section 5012 by transmitting guidance information, and feeds back the actual construction adjustment measures to the rule repository 300 to change at least some of the calculation rules.

[0076] Preferably, such as Figure 3As shown, when the node ranges 501 corresponding to the monitored objects overlap, overlap information is added to the risk identification information corresponding to the monitored objects and substituted into the risk identification calculation. This makes the change in the risk identification level in the risk identification conclusion positively correlated with the degree of overlap. The change in the risk identification level is the difference between the risk identification level obtained considering the overlap information and the risk identification level obtained without considering the overlap information. Compared to node ranges 501 with only a single key monitored object, when node ranges 501 overlap, the combined influence of multiple key monitored objects and underground engineering should be considered. The closer multiple key monitored objects are in space, the higher the overlap of node ranges 501. Therefore, the overlap of node ranges 501 can be used to characterize the proximity of key monitored objects. Substituting the overlap information of node ranges 501 as risk identification information into the risk identification calculation yields a correction to the risk identification conclusion, thereby more accurately identifying the risk level of the overlapping area of ​​node ranges 501.

[0077] It should be noted that the specific embodiments described above are exemplary, and those skilled in the art can devise various solutions inspired by the disclosure of this invention. These solutions all fall within the scope of this invention and its protection. Those skilled in the art should understand that this specification and its accompanying drawings are illustrative and not intended to limit the scope of the claims. The scope of protection of this invention is defined by the claims and their equivalents.

Claims

1. A safety risk identification system for underground engineering projects, characterized in that, The system includes: The control module (100) is used to control and adjust the risk identification process and re-enact the risk identification process based on triggering conditions; The monitoring and identification module (200) is used to acquire risk identification information of the monitored objects; A rules repository (300) is used to perform risk identification calculations on risk identification information; The guidance module (400) is used to output risk identification conclusions for the monitored objects; When the control module (100) divides the construction area of ​​the underground project into several node ranges (501) according to the node level, different node ranges (501) are set with different risk identification cycles based on the node level to control the update time interval of risk identification. The calculation rules in the rule repository (300) include at least construction method rules, construction design rules, geological parameter rules and standard criteria. The calculation rules are quantitatively expressed through a range table and influence factors. The control module (100) substitutes the risk identification information into the risk identification calculation to obtain the risk identification conclusion. When a construction area is formed by combining several node ranges (501) and several general ranges (502), the length of the node range (501) is determined by the node level; when the construction surface (503) of the underground project enters / leaves the node range (501) from the general range (502), the control module (100) is triggered to adjust and modify at least some of the calculation rules in the rule repository (300) and change the risk identification cycle; The node range (501) is set into several segments based on the risk identification cycle. When the construction surface (503) of the underground project is located in the previous segment (5011) of the node range (501), the control module (100) performs risk identification calculation based on the risk identification information of the current segment to obtain a risk identification conclusion to guide the next segment (5012). If the risk identification level of the monitored object is greater than the warning level, the control module (100) is triggered to adjust at least some of the calculation rules in the rule repository (300), and the guidance module (400) provides adjustment reference for the actual construction process of the next segment by transmitting guidance information. The length S of the node range (501) is calculated using the following formula: ， Wherein, K1 is the node level, K2 is the geological structure coefficient, K3 is the construction method coefficient, D is the reference dimension of the underground project, H is the depth of the underground project, L is the minimum distance between the key monitoring object and the underground project, a is the correction index of the reference dimension D of the underground project, b is the correction index of the depth H of the underground project, c is the correction index of the minimum distance L between the key monitoring object and the underground project; D0 is the baseline number of the reference dimension D of the underground project, H0 is the baseline number of the depth H of the underground project, and L0 is the baseline number of the minimum distance L between the key monitoring object and the underground project.

2. The system according to claim 1, characterized in that, The risk identification process includes the following steps: The monitoring and identification module (200) classifies and summarizes the monitored objects into an object set with at least two nested structures based on multiple identification rules. The object elements in the object set are configured with the risk identification information. The nested structure refers to the nested set formed by the object set based on the identification rules. The identification rules include at least the monitoring object category and coordinate information. The risk identification information of the object elements is compared with the calculation rules in the rule repository (300) to perform risk identification calculation, wherein the risk identification calculation includes a matching operation between the object matrix composed of the object elements and the rule matrix composed of the rule elements; The guidance module (400) outputs the risk identification conclusion obtained by risk identification calculation, and associates and sorts the object elements in the object set with the risk identification conclusion, so that the object elements are arranged in ascending or descending order based on at least a part of the information in the risk identification conclusion, wherein the risk identification conclusion includes at least the risk identification level, guidance information and deformation control index. The control module (100) changes at least some of the calculation rules in the rule repository (300) based on triggering conditions and re-performs the risk identification process. The guidance module (400) outputs guidance information about the changes in calculation rules and provides a reference for downstream construction design.

3. The system according to claim 1 or 2, characterized in that, The monitoring and identification module (200) represents risk identification information with an object set that includes at least two nested structures. The first object set is classified according to the category of the monitored object, and the second object set is classified according to the relative positional relationship between the object element and the underground project. The relative positional relationship is calculated from coordinate information. The coordinate information of the monitored object is calibrated using absolute coordinates and relative coordinates. The coordinate information in the identification rules is used to calculate the absolute distance and relative distance between the monitored object and the underground project. The absolute distance refers to the shortest distance from the monitored object to the underground project, and the relative distance refers to the distance from the monitored object to the construction surface (503).

4. The system according to claim 1 or 2, characterized in that, When the monitoring and identification module (200) sets the acquired object set as a two-level nested structure set, the object set containing X elements is represented as M(A1, A2, A3, ..., A...). X ), A1 to A X Represented as A X (B1, B2, B3, ..., B) Y ), where A1 to A X The elements of the first-level object set, B1 to B, are obtained by classifying the monitored objects according to their categories. Y X and Y are the elements of the second-level object set obtained by classifying the monitoring objects and the underground palace project according to their relative positional relationship. X and Y are positive integers not less than 1.

5. The system according to claim 4, characterized in that, The object elements configured with risk identification information in the object set are arranged into an object matrix M with at least a two-dimensional structure. The calculation rules in the rule repository (300) are quantified into several range tables / influence factors with matching annotations and conclusion annotations and form rule elements. Several rule elements are classified and summarized into a rule matrix N with at least a two-dimensional structure, where the number of columns in matrix M is X and the number of rows in matrix N is not less than X.

6. The system according to claim 5, characterized in that, The risk identification calculation process includes: searching and matching the object elements in each column of the M matrix with the rule elements in each row of the rule matrix N; substituting the risk identification information of the object elements and the matching annotations of the rule elements into the range table / influence factor for calculation to obtain the calculation results and corresponding conclusion annotations.

7. The system according to claim 6, characterized in that, When the node range (501) corresponding to the monitored object overlaps, overlap information is added to the risk identification information corresponding to the monitored object and substituted into the risk identification calculation, so that the change in risk identification level in the risk identification conclusion is positively correlated with the overlap level. The change in risk identification level is the difference between the risk identification level obtained considering the overlap information and the risk identification level obtained without considering the overlap information.

8. A method for identifying safety risks in underground engineering projects, characterized in that, The method employs the system described in any one of claims 1 to 7, and the method includes the following steps: The control module (100) divides the construction area of ​​the underground project into several node ranges (501) according to the node level. Different node ranges (501) are set with different risk identification cycles based on the node level to control the update time interval of risk identification. The monitoring and identification module (200) classifies and summarizes the monitored objects into an object set with at least two nested structures based on multiple identification rules. The object elements in the object set are configured with risk identification information. The nested structure refers to the nested set formed by the object set based on the identification rules. The identification rules include at least the monitoring object category and coordinate information. Risk identification calculation is performed by comparing the risk identification information of the object elements with the calculation rules in the rule repository (300), wherein the risk identification calculation includes a matching operation between the object matrix composed of object elements and the rule matrix composed of rule elements; The guidance module (400) outputs the risk identification calculation to obtain the risk identification conclusion, and associates and sorts the object elements in the object set with the risk identification conclusion, so that the object elements are arranged in ascending or descending order based on at least a part of the information in the risk identification conclusion. The risk identification conclusion includes at least the risk identification level, guidance information and deformation control indicators. When a construction area is formed by combining several node ranges (501) and several general ranges (502), the length of the node range (501) is determined by the node level; when the construction surface (503) of the underground project enters / leaves the node range (501) from the general range (502), the control module (100) is triggered to adjust and modify at least some of the calculation rules in the rule repository (300) and change the risk identification cycle; The node range (501) is set into several segments based on the risk identification cycle. When the construction surface (503) of the underground project is located in the previous segment (5011) of the node range (501), the control module (100) performs risk identification calculation based on the risk identification information of the current segment to obtain a risk identification conclusion to guide the next segment (5012). If the risk identification level of the monitored object is greater than the warning level, the control module (100) is triggered to adjust at least some of the calculation rules in the rule repository (300), and the guidance module (400) provides adjustment reference for the actual construction process of the next segment by transmitting guidance information. The length S of the node range (501) is calculated using the following formula: ， Wherein, K1 is the node level, K2 is the geological structure coefficient, K3 is the construction method coefficient, D is the reference dimension of the underground project, H is the depth of the underground project, L is the minimum distance between the key monitoring object and the underground project, a is the correction index of the reference dimension D of the underground project, b is the correction index of the depth H of the underground project, c is the correction index of the minimum distance L between the key monitoring object and the underground project; D0 is the baseline number of the reference dimension D of the underground project, H0 is the baseline number of the depth H of the underground project, and L0 is the baseline number of the minimum distance L between the key monitoring object and the underground project.

9. The method according to claim 8, characterized in that, The method further includes one or more of the following steps: The control module (100) changes at least some of the calculation rules in the trigger condition rule repository (300) and re-performs the risk identification process, while the guidance module (400) outputs guidance information on the change of calculation rules and provides a reference for the construction design downstream. The object set acquired by the monitoring and identification module (200) is set as a two-level nested structure, and the object set containing X elements is represented as M(A1, A2, A3, ..., A...). X ), A1 to A X Represented as A X (B1, B2, B3, ..., B) Y ); Arrange the object elements configured with risk identification information in the object set into an object matrix M with at least a two-dimensional structure, quantify the calculation rules in the rule repository (300) into several range tables / influence factors with matching annotations and conclusion annotations and form rule elements, classify and summarize several rule elements into a rule matrix N with at least a two-dimensional structure, wherein the number of columns in the M matrix is ​​X and the number of rows in the N matrix is ​​not less than X; During risk identification calculation, the object elements in each column of matrix M are searched and matched with the rule elements in each row of matrix N. Based on the risk identification information of the object elements and the matching annotations of the rule elements, the results are substituted into the range table / influence factor for calculation to obtain the calculation results and corresponding conclusion annotations.

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