Safety risk intelligent assessment system and method for highway tunnel engineering construction

Abstract

The invention relates to the field of highway tunnel engineering, and discloses a highway tunnel engineering construction safety risk intelligent assessment system and method, and the system comprises a data layer which serves as a data warehouse of the system and stores basic index rules, weight calculation rules and work order and index associated data required by assessment. Standardized data and rule support are provided for the whole evaluation; and the data layer is connected with an algorithm layer. Standardized evaluation rules are established through the index dictionary table of the data layer, a unified judgment basis is provided for risk evaluation, and the subjective deviation of'standard determination by experience 'in traditional manual evaluation is avoided; through combination of a dynamic scoring engine and a special risk engine of an algorithm layer, quantitative and hierarchical processing of risk assessment is realized, dependence on artificial experience is thoroughly eliminated, index determination logic consistency under different tunnels and different assessment scenes is ensured, and objectivity and reliability of an assessment result are improved.

Description

Technical Field

[0001] This invention relates to the field of highway tunnel engineering technology, specifically to an intelligent safety risk assessment system and method for highway tunnel construction. Background Technology

[0002] Highway tunnel construction environments are complex, with variable geological conditions, and are susceptible to factors such as surrounding rock stability and hydrological conditions. Risks and accidents such as collapses, water inrushes, and rock bursts are frequent. Therefore, safety risk assessment during construction is a core element in ensuring project progress and personnel safety. As tunnel projects extend to deeper, longer, and more complex geological areas, traditional risk assessment methods are no longer sufficient to meet the demands for precise and dynamic management. There is an urgent need to improve risk control through intelligent technologies.

[0003] Existing risk assessment technologies have significant limitations: First, they are highly subjective, with the selection of assessment indicators and weighting largely relying on expert experience and lacking standardized quantitative models. Different assessors may arrive at vastly different conclusions for the same project, resulting in insufficient objectivity. Second, static assessments are ill-suited to dynamic scenarios. Most systems employ fixed-weight algorithms, failing to respond to sudden geological changes during construction (such as sudden fault fracture zones) or adjustments to work procedures (such as changes in excavation depth), leading to assessment results lagging behind actual risk changes. Third, data and processes are fragmented, with assessment indicator management, work order creation, and result output scattered across independent modules, lacking a comprehensive collaborative mechanism, resulting in low data utilization and inefficient assessment. Fourth, they lack the ability to identify specific risks, failing to stratify risks before and during construction, making it difficult to accurately pinpoint high-frequency specific risks such as collapses and water inrushes, resulting in weak targeted prevention and control.

[0004] The aforementioned problems directly hinder traditional assessment methods from achieving early risk detection and mitigation: subjective biases may mask true risks, static weights may misjudge key hazards, fragmented data prolongs the assessment cycle, and a lack of specific identification leads to indiscriminate and ineffective prevention and control measures. Therefore, developing an intelligent system and method that integrates dynamic weight adjustment of indicators, work order-based assessment processes, and multi-level risk identification to shift from "passive accident response" to "proactive prediction and prevention" has become an essential requirement for solving the challenges of safety risk management in highway tunnel construction. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent safety risk assessment system and method for highway tunnel construction, which solves the problems of strong subjective dependence, limited static assessment, fragmented data, and lack of specialized assessment in the existing highway tunnel construction safety risk assessment process.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a safety risk intelligent assessment system for highway tunnel construction, comprising a data layer, which serves as the system's data warehouse, storing the basic indicator rules, weight calculation rules, and correlation data between work orders and indicators required for the assessment, providing standardized data and rule support for the entire assessment; The data layer is connected to the algorithm layer, which serves as the computing core of the system. Based on the data provided by the data layer, the algorithm layer quickly classifies risk levels through the main control factor identification engine, calculates the total risk score through the dynamic scoring engine, and quantifies specific risks through the specific risk engine, thereby achieving accurate risk assessment. The algorithm layer is connected to the application layer. The application layer serves as the system's interaction interface. It initiates the evaluation process through the work order management module, calls the data layer and algorithm layer to complete the calculation, and then outputs the visualization results through the risk report module. The real-time early warning module monitors the data and triggers alarms, thus realizing a closed loop of the entire process from evaluation initiation, data processing to result output.

[0007] Preferably, the data layer includes: Indicator dictionary table: Stores all basic indicator rules for risk assessment. The basic indicator rules include indicator name, risk category, judgment function, and score range, providing the data and rule foundation for the entire assessment system.

[0008] Preferably, the data layer further includes: Weighting rule table: Stores the calculation rules for weight coefficients. The core is to dynamically generate the weight coefficient for each indicator based on the number of indicators n and the sorting order m. The formula is:

[0009] in: The total number of representative indicators; The index represents the sorting sequence number.

[0010] Preferably, the data layer further includes: Work Order Association Table: Dynamically binds specific evaluation work orders to indicators in the indicator dictionary table, recording the indicator ID and current weight coefficient for each work order.

[0011] Preferably, the algorithm layer includes: Key Control Factor Identification Engine: Focuses on core risk factors in tunnel construction, including surrounding rock grade, tunnel length, and gas content. It quickly classifies risk levels through logical judgment, skips complex calculations, prioritizes the identification of the most critical high-risk scenarios, and significantly shortens the assessment time.

[0012] Preferably, the algorithm layer includes: The logical judgment is as follows: If all core risks meet the criteria for Level I risk, the risk is classified as Level I major risk; otherwise, it is classified as Level II, a relatively large risk. Dynamic scoring engine: based on The formula calculates the total risk score. in: Represents the total score; Representing the The scores of each indicator The weight of the representative indicator; Specialized Risk Engine: This engine addresses specific risks encountered during tunnel construction, including water inrush, mudslides, rock bursts, and collapses. These risks are quantified and assessed using a proprietary formula. The specific formula for quantification and assessment is as follows:

[0013] in: , Representative geological parameters; Representative hydrological indicators; Represents structural factors.

[0014] Preferably, the application layer includes: Work order management module: Enables standardized management of the entire risk assessment process, including: creating work orders, synchronizing indicators, dynamically assigning weights, and performing assessments.

[0015] Preferably, the application layer includes: Risk Reporting Module: Outputs the final assessment results in the form of visual charts, generating a structured report. The assessment results include indicator scores, weights, overall risk level, and details of specific risks. The visual charts include bar charts and level labels.

[0016] Preferably, the application layer includes: Real-time early warning module: Connects to IoT sensors to collect key indicator data in real time. When the data exceeds a preset threshold, it automatically issues an alarm and displays the risk level. The IoT sensor includes: a surrounding rock deformation monitor; The key indicator data includes the relative deformation value of the surrounding rock, u / B.

[0017] A method for using an intelligent safety risk assessment system for highway tunnel construction includes the following steps: S1. Create an assessment work order: Through the work order management module of the application layer, input the tunnel ID, segment ID and assessment type, and the system will automatically generate a unique assessment work order, which will be associated with the basic information of the tunnel, including design parameters and construction stage. S2. Synchronization Indicators and Dynamic Weighting: The system automatically calls the indicator dictionary table and work order association table in the data layer. Based on the assessment type of the work order, it loads the corresponding risk indicators. These risk indicators include "excavation span" and "surrounding rock grade" indicators when assessing collapse risk. Simultaneously, it combines the weighting rule table with the number of indicators... Sorting The dynamic weights of each indicator are automatically calculated using formulas, thus binding the indicators to their weights. S3. Algorithm-level evaluation: The system starts the algorithm-level engine. The main control factor identification engine first quickly judges the core factors and initially classifies the risk level. The dynamic scoring engine combines the actual monitoring value and dynamic weight of each indicator to calculate the total risk score through a formula. The special risk engine calculates the special risk value for the selected evaluation type by substituting the specific formula. S4. Report Generation and Early Warning Activation: The application layer's risk reporting module generates a structured report from the algorithm layer's output in the form of bar charts and level indicators. Simultaneously, the real-time early warning module continuously monitors sensor data. If the threshold is exceeded, a red / yellow warning is immediately triggered, and an alarm is simultaneously pushed to management personnel to assist in formulating prevention and control measures. These measures include suspending construction and strengthening support.

[0018] This invention provides an intelligent safety risk assessment system and method for highway tunnel construction. It has the following beneficial effects: 1. This invention establishes standardized evaluation rules through an indicator dictionary table in the data layer, providing a unified basis for risk assessment and avoiding the subjective bias of "setting standards based on experience" in traditional manual assessment. Combined with the dynamic scoring engine and special risk engine in the algorithm layer, it realizes the quantification and hierarchical processing of risk assessment, completely eliminating the dependence on human experience, ensuring the consistency of indicator judgment logic in different tunnels and different assessment scenarios, and improving the objectivity and reliability of assessment results.

[0019] 2. This invention uses the collaboration of a weight rule table and a work order association table to calculate dynamic weights in real time based on the number of indicators (n) and their order (m), so that the importance of indicators can be automatically adjusted according to dynamic scenarios such as sudden changes in geological conditions and adjustments in procedures during construction. The dynamic scoring engine combines actual monitoring data to ensure that the risk assessment results are updated synchronously with the actual working conditions, breaking through the limitations of traditional fixed weights and accurately adapting to the complex dynamic characteristics of tunnel construction. Attached Figure Description

[0020] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a flowchart illustrating the usage method of the system of the present invention. Detailed Implementation

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example: Please see the appendix Figure 1 - Appendix Figure 2 This invention provides an intelligent safety risk assessment system for highway tunnel construction, comprising a data layer, an algorithm layer connected to the data layer, and an application layer connected to the algorithm layer. The data layer includes: Indicator dictionary table: Stores all basic indicator rules for risk assessment. The basic indicator rules include indicator name, risk category, judgment function, and score range. It provides the data and rule foundation for the entire assessment system, provides a unified and standardized judgment basis for risk assessment, avoids the subjective bias of "setting standards based on experience" in traditional manual assessment, ensures the consistency of indicator judgment logic under different tunnels and different assessment scenarios, and improves the objectivity of assessment. Weighting rule table: Stores the calculation rules for weight coefficients. The core is to dynamically generate the weight coefficient for each indicator based on the number of indicators (n) and the ranking (m). This breaks through the limitations of traditional fixed weights, allowing the importance of indicators to automatically adjust as the number and priority of indicators change in the construction scenario. The formula is:

[0023] in: The total number of representative indicators; Represents the sorting sequence number of the indicator; Work Order Association Table: Dynamically binds specific evaluation work orders to indicators in the indicator dictionary table, records the indicator ID and current weight coefficient corresponding to each work order, realizes flexible matching of "one work order and one set of indicators", and supports the association of different indicators as needed for different evaluation scenarios. The algorithm layer includes: Key Control Factor Identification Engine: Focuses on the core risk factors in tunnel construction, including surrounding rock grade, tunnel length, and gas content. It quickly classifies risk levels through logical judgment, skips complex calculations, prioritizes the identification of the most critical high-risk scenarios, and significantly shortens the assessment time. The logical judgment is specifically as follows: If all core risks meet the criteria for Level I risk, the risk is classified as Level I major risk; otherwise, it is classified as Level II, a relatively large risk. Dynamic scoring engine: based on The formula calculates the total risk score by combining indicator scores with dynamic weights to generate an accurate total risk score, thus avoiding the problem of "key indicators being underestimated" caused by fixed weights. in: Represents the total score; Representing the The scores of each indicator The weight of the representative indicator; Example: Tunnel excavation span: 16.2m → Score R11 = 8; Surrounding rock grade: Grade IV → R31=8; Fault fracture zone width: 35m → R32 = 1.2; The total score is 8 × 0.23 + 8 × 0.20 + ... = 52.6; Specialized Risk Engine: Targeting specific risks in tunnel construction, including water inrush, mudslide, rock burst, and collapse, this engine uses a dedicated formula for quantitative assessment, breaking away from the "one-size-fits-all" generalized assessment and accurately identifying various specialized risks. The specific quantitative evaluation using the proprietary formula is as follows:

[0024] in: , Representative geological parameters; Representative hydrological indicators; Represents structural factors; The application layer includes: Work order management module: This module enables standardized management of the entire risk assessment process. The standardized management includes: creating work orders, synchronizing indicators, dynamically assigning weights, and executing assessments. It simplifies the assessment process from "manual data collection → manual calculation → paper recording" to "one-click work order creation → automatic processing → result entry," reducing manual operation steps by 70% and shortening the assessment cycle from the traditional 3 days to 2 hours, thus significantly improving assessment efficiency. Risk Reporting Module: Outputs the final assessment results in the form of visual charts, generating a structured report. The assessment results include indicator scores, weights, overall risk level, and details of specific risks. The visual charts include bar charts and level labels, allowing construction parties, supervisors, and others to quickly understand the risk situation without having to interpret complex data. Real-time early warning module: Connects to IoT sensors to collect key indicator data in real time. When the data exceeds the preset threshold, it automatically issues an alarm and displays the risk level, upgrading risk monitoring from "periodic manual inspection" to "real-time automatic monitoring" to achieve early detection and early handling of risks. The IoT sensor includes: a surrounding rock deformation monitor; The key indicator data includes the relative deformation value of the surrounding rock, u / B; A method for using an intelligent safety risk assessment system for highway tunnel construction includes the following steps: S1. Create an assessment work order: Through the work order management module of the application layer, input the tunnel ID, segment ID and assessment type, and the system will automatically generate a unique assessment work order, which will be associated with the basic information of the tunnel, including design parameters and construction stage. S2. Synchronization Indicators and Dynamic Weighting: The system automatically calls the indicator dictionary table and work order association table in the data layer. Based on the assessment type of the work order, it loads the corresponding risk indicators. These risk indicators include "excavation span" and "surrounding rock grade" indicators when assessing collapse risk. Simultaneously, it combines the weighting rule table with the number of indicators... Sorting The dynamic weights of each indicator are automatically calculated using formulas, thus binding the indicators to their weights. S3. Algorithm-level evaluation: The system starts the algorithm-level engine. The main control factor identification engine first quickly judges the core factors and initially classifies the risk level. The dynamic scoring engine combines the actual monitoring value and dynamic weight of each indicator to calculate the total risk score through a formula. The special risk engine calculates the special risk value for the selected evaluation type by substituting the specific formula. S4. Report Generation and Early Warning Activation: The application layer's risk reporting module generates a structured report from the algorithm layer's output in the form of bar charts and level indicators. Simultaneously, the real-time early warning module continuously monitors sensor data. If the threshold is exceeded, a red / yellow warning is immediately triggered, and an alarm is simultaneously pushed to management personnel to assist in formulating prevention and control measures. These measures include suspending construction and strengthening support.

[0025] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart safety risk assessment system for highway tunnel construction, characterized in that, The system includes a data layer, which serves as the system's data warehouse, storing the basic indicator rules, weight calculation rules, and correlation data between work orders and indicators required for the assessment, providing standardized data and rule support for the entire assessment. Above the data layer is an algorithm layer, which serves as the system's computational core. Based on the data provided by the data layer, the algorithm layer quickly classifies risk levels through a main control factor identification engine, calculates the total risk score through a dynamic scoring engine, and quantifies specific risks through a specific risk engine, thereby achieving accurate risk assessment. The algorithm layer is connected to the application layer. The application layer serves as the system's interaction interface. It initiates the evaluation process through the work order management module, calls the data layer and algorithm layer to complete the calculation, and then outputs the visualization results through the risk report module. The real-time early warning module monitors the data and triggers alarms, thus realizing a closed loop of the entire process from evaluation initiation, data processing to result output.

2. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The data layer includes: an indicator dictionary table, which stores the basic indicator rules for all risk assessments. The basic indicator rules include the indicator name, the risk category to which it belongs, the judgment function, and the score range, providing the data and rule foundation for the entire assessment system.

3. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The data layer also includes: a weighting rule table: storing the calculation rules for weight coefficients. The core principle is to dynamically generate the weight coefficient for each indicator based on the number of indicators n and the sorting order m. The formula is: ;in: The total number of representative indicators; The index represents the sorting sequence number.

4. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The data layer also includes: a work order association table: dynamically binding specific evaluation work orders with indicators in the indicator dictionary table, recording the indicator ID and current weight coefficient corresponding to each work order.

5. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The algorithm layer includes: a main control factor identification engine: focusing on the core risk factors in tunnel construction, including the surrounding rock grade, tunnel length, and gas content. It quickly classifies risk levels through logical judgment, skips complex calculations, prioritizes the identification of the most critical high-risk scenarios, and significantly shortens the assessment time.

6. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The algorithm layer includes: logical judgment specifically: if all core risks meet the conditions for Level I risk, it is judged as a Level I major risk; otherwise, it is judged as a Level II, relatively large risk; dynamic scoring engine: based on The formula calculates the total risk score, where: Represents the total score; Representing the The scores of each indicator The weights of representative indicators; Specialized risk engine: For specific risks in tunnel construction, including water inrush, mudslides, rock bursts, and collapses, a dedicated formula is used for quantitative assessment. The specific quantitative assessment using this dedicated formula is as follows: ;in: , Representative geological parameters; Representative hydrological indicators; Represents structural factors.

7. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The application layer includes: Work order management module: Enables standardized management of the entire risk assessment process, including: creating work orders, synchronizing indicators, dynamically assigning weights, and performing assessments.

8. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The application layer includes: Risk Reporting Module: Outputs the final assessment results in the form of visual charts, generating a structured report. The assessment results include indicator scores, weights, overall risk level, and details of specific risks. The visual charts include bar charts and level labels.

9. The intelligent safety risk assessment system for highway tunnel construction according to claim 1, characterized in that, The application layer includes: Real-time early warning module: Connects to IoT sensors to collect key indicator data in real time. When the data exceeds a preset threshold, it automatically issues an alarm and displays the risk level. The IoT sensor includes: a surrounding rock deformation monitor; The key indicator data includes the relative deformation value of the surrounding rock, u / B.

10. A method for using the intelligent safety risk assessment system for highway tunnel construction according to claims 1-9, characterized in that, Includes the following steps: S1. Create an assessment work order: Through the work order management module of the application layer, input the tunnel ID, segment ID and assessment type, and the system will automatically generate a unique assessment work order, which will be associated with the basic information of the tunnel, including design parameters and construction stage. S2. Synchronization Indicators and Dynamic Weighting: The system automatically calls the indicator dictionary table and work order association table in the data layer. Based on the assessment type of the work order, it loads the corresponding risk indicators. These risk indicators include "excavation span" and "surrounding rock level" indicators when assessing collapse risk. Simultaneously, it combines the weighting rule table with the number of indicators... Sorting The dynamic weights of each indicator are automatically calculated using formulas, thus binding the indicators to their weights. S3. Algorithm Layer Evaluation: The system starts the algorithm layer engine, and the main control factor identification engine first quickly judges the core factors and initially classifies the risk level. The dynamic scoring engine combines the actual monitoring values ​​and dynamic weights of each indicator to calculate the total risk score using a formula; The specialized risk engine calculates the specialized risk value by inputting a specific formula into the selected assessment type. S4. Report Generation and Early Warning Activation: The application layer's risk reporting module generates a structured report from the algorithm layer's output in the form of bar charts and level indicators. Meanwhile, the real-time early warning module continuously monitors sensor data. If the threshold is exceeded, a red / yellow warning is immediately triggered, and an alarm is simultaneously pushed to the management personnel to assist in the formulation of prevention and control measures. These measures include suspending construction and strengthening support.

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