A method and system for evaluating the construction quality of tunnels using the drill-and-blast method

Abstract

This invention provides a method and system for evaluating the construction quality of drill-and-blast tunnels, belonging to the field of tunnel construction quality evaluation technology. The method involves real-time acquisition of data on borehole drilling, explosive loading, blasting vibration, and tunnel contour, which is then transmitted to a server. The server maintains a dynamically updated tunnel contour benchmark, calculates the contour mass vector through spatial transformation, and integrates construction parameters and geological data to construct a construction state vector. Based on a construction response field constructed from historical data, the system extrapolates expected vibration velocity and contour mass as prediction benchmarks. Through difference analysis between actual data and predicted values, the system generates a current state conflict vector and queries a decision mapping table to output construction parameter adjustment instructions. The equipment control system executes coordinated parameter adjustments and feeds back the new data to the server, forming a closed-loop control for evaluation and optimization, thereby achieving real-time, accurate, and adaptive control of construction quality.

Description

Technical Field

[0001] This invention relates to the field of tunnel construction quality assessment technology, specifically to a method and system for assessing the construction quality of tunnels using the drill-and-blast method. Background Technology

[0002] In the field of drill-and-blast tunnel construction, before construction, engineers determine drilling parameters and explosive charges based on geological survey reports and empirical formulas. After blasting, the excavated cross-section is inspected manually or with portable scanning equipment to assess over-excavation or under-excavation. This method has an inherent lag; its quality control process is separate from the excavation operation in time, making real-time intervention during construction impossible.

[0003] Currently, there is a lack of a benchmark system that can dynamically adapt to continuous changes in surrounding rock conditions. As a result, quality assessment always takes a fixed and idealized design profile as the sole standard, and cannot identify and track the reasonable evolution of the profile morphology caused by geological variations and cumulative blasting effects. This leads to a disconnect between the assessment results and the actual engineering situation. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to provide a method and system for evaluating the construction quality of tunnels using the drill-and-blast method, thereby resolving these issues.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for assessing the construction quality of drill-and-blast tunnels includes:

[0007] S1. During drilling, collect parameters such as hole depth, hole spacing, angle, and charge amount; during blasting, collect vibration velocity data; scan the tunnel excavation section to obtain the tunnel outline data; and transmit the collected data to the server in real time.

[0008] S2. The server maintains a dynamically updated tunnel profile benchmark, the initial value of which is the design profile line; the collected profile line data is compared with the dynamic profile benchmark, and the spatial transformation that minimizes the enclosing area between the two profile lines is solved to calculate the area difference of the overall profile deviation and the over-excavation and under-excavation values; and these are used together as the profile quality vector for this round of excavation.

[0009] S3. The server integrates drilling parameters, charge parameters, and geological condition data into a construction state vector; and uses this as input, with vibration velocity data and profile mass vector as output, to form a construction response field; for the current construction state, the expected vibration velocity and profile mass vector are derived from the construction response field as the prediction benchmark for this round of blasting; the actual monitoring data after blasting is compared with the prediction benchmark, and the construction response field is updated accordingly.

[0010] S4. The server uses the ratio of the actual vibration velocity to the safety threshold and the ratio of each component in the profile mass vector to the allowable deviation to form the current state conflict vector; it establishes a decision mapping table and generates construction parameter adjustment instructions based on the decision mapping table.

[0011] S5. The construction parameter adjustment command is sent to the equipment; according to the association rules defined in the construction parameter adjustment command, the drilling parameter group or the charge parameter group is adjusted in a coordinated manner; and the generated new data is fed back to the contour dynamic benchmark and construction response field.

[0012] As a further technical solution, the integrity and synchronization of data acquisition in step S1 are achieved through an enhanced management process of session identifiers. While generating a unique session identifier, the server creates a data list for that session, listing all data types required for that round of construction, including borehole parameter sets, charge quantities, vibration velocity sequences, and contour point cloud data. When receiving and integrating data, the data acquisition equipment performs strict session identifier verification and checks whether the received data packets match the list items. For data types that fail to be received on time, the system will not wait indefinitely, but will mark the round as an incomplete data session after a predetermined maximum waiting time threshold, such as ten minutes. For incomplete data sessions, the system will not use their data for critical updates to the construction response field, but can use their contour data with lower weight for updating the dynamic contour baseline.

[0013] As a further technical solution, the update mechanism of the dynamic contour benchmark in step S2 is clearly defined. Specifically, after obtaining the actual contour line data of the current round after optimal spatial transformation and alignment, the server performs weighted fusion of this contour line with the current dynamic contour benchmark to generate a new benchmark. The new dynamic contour benchmark is calculated by fusing 70% of the current actual contour line data and 30% of the historical dynamic contour benchmark data. This weighted fusion is performed on the radial coordinates of each corresponding mileage point of the contour line. The dynamic contour benchmark can not only track the long-term trend of the actual excavation contour, but also effectively smooth the random fluctuations caused by a single blast, thus forming a reliable comparison benchmark that is both stable and adaptable to geological changes.

[0014] As a further technical solution, the computational efficiency of solving the spatial transformation process that minimizes the enclosing area between two contour lines is ensured through optimized iteration. After coarse positioning through initial alignment, the server performs translation and rotation adjustments in the horizontal, vertical, and axial dimensions with an initial step size and calculates the enclosing area. When an adjustment direction that reduces the enclosing area is detected, the system immediately locks onto that direction and continuously adjusts with the initial step size until the enclosing area no longer decreases, thus quickly approaching the minimum value region. After finding this region, a fine search is performed within this local range using a reduced step size and angle increment until the change in the enclosing area is less than the convergence threshold. This avoids invalid traversal in non-optimized directions, reduces the number of iterations required to reach the optimal solution, and thus meets the real-time requirements during construction breaks.

[0015] As a further technical solution, the construction and updating logic of the construction response field in step S3 further includes: the construction response field is a historical dataset stored in a server database, each record containing a construction state vector and its corresponding actual vibration velocity data and contour mass vector; the process of extrapolating the expected value is essentially a similar case retrieval and weighted aggregation based on distance metrics; after the server calculates the Euclidean distance between the current construction state vector and the historical state vector, it does not select only one nearest neighbor, but selects the five historical states with the smallest distance as neighboring samples; the weight coefficient assigned to each sample is the normalized value of the inverse of its Euclidean distance with the current state vector, ensuring that the weight of the neighboring sample is proportional to its similarity; the extrapolation of vibration velocity is a weighted average of the historical vibration velocity values ​​of the five samples; the extrapolation of the contour mass vector is a weighted average of the historical values ​​of the area difference and the linear over-excavation and under-excavation values ​​of each mileage point, respectively, to obtain a complete multidimensional prediction vector.

[0016] As a further technical solution, the establishment and operation mechanism of the decision mapping table in step S4 is clearly explained. This decision mapping table is essentially a set of rules that map the conflict vector space to parameter adjustment actions. Its initial rules are based on tunnel construction mechanics principles and expert experience. The decision mapping table first determines the dominant conflict type by comparing the magnitude of the comprehensive vibration conflict value and the comprehensive profile conflict value. For vibration-dominated conflicts, the decision mapping table pre-sets the charge adjustment percentages corresponding to different vibration conflict component ranges; for example, a vibration conflict component between 1.1 and 1.3 corresponds to a 5% reduction in charge. For profile-dominated conflicts, the decision mapping table outputs an adjustment command to reduce the borehole angle by 0.5 degrees based on the distribution characteristics of linear over-excavation and under-excavation values ​​in the profile quality vector; for example, if over-excavation values ​​are concentrated in the arch crown area, the corresponding adjustment is to reduce the borehole angle by 0.5 degrees. These rules are pre-set through simulation and historical data verification before system deployment, ensuring the scientific nature of the initial decision.

[0017] As a further technical solution, the equipment control system does not immediately and unconditionally execute adjustment instructions received from the server. The system pre-stores safety upper and lower limits for various construction parameters, derived from tunnel design specifications and equipment operation manuals. The control system compares the adjusted parameters in the instruction with these safety limits. If the adjusted parameters exceed the safety range—for example, if the calculated charge amount is lower than the minimum critical value for ensuring rock breakage—the control system automatically locks the instruction and sends a warning message to the server, requesting manual intervention for confirmation or modification. This effectively prevents erroneous operations caused by data anomalies or temporary inaccuracies in the prediction model, forming a key safety barrier for the system and improving the overall system reliability and engineering practicality.

[0018] A drill-and-blast tunnel construction quality assessment system includes:

[0019] The data acquisition terminal is used to automatically collect hole depth, hole spacing and angle parameters through intelligent rock drilling equipment during the drilling process, and to record the charge amount through electronic metering device on the charging equipment. At the same time, during the blasting process, vibration velocity data is collected through vibration monitoring instruments placed at key locations. After the blasting, the contour line data is obtained by scanning the tunnel excavation cross section through laser profiler, and all collected data is transmitted to the server in real time.

[0020] The server is configured to maintain a dynamically updated tunnel profile benchmark. The initial value of this benchmark is the design profile line. It compares the received profile line data with the dynamic profile benchmark and calculates the area difference and the linear over-excavation and under-excavation values ​​at each mileage point along the tunnel axis by solving the spatial transformation that minimizes the enclosed area between the two profile lines. This forms the profile quality vector. At the same time, it integrates drilling parameters, charge parameters and geological condition data into a construction state vector. Based on historical data, it constructs a construction response field, derives the expected vibration velocity and profile quality vector as a prediction benchmark, and performs difference analysis to update the construction response field. It also constructs the current state conflict vector by the ratio of the actual vibration velocity to the safety threshold and the ratio of each component in the actual profile quality vector to the allowable deviation. It generates construction parameter adjustment instructions by querying the pre-stored decision mapping table.

[0021] The equipment control system receives construction parameter adjustment instructions sent by the server, coordinates the adjustment of drilling parameter groups or charging parameter groups according to the association rules defined in the instructions, and controls the intelligent rock drilling equipment and charging equipment to operate with the adjusted parameter groups in subsequent construction. At the same time, it feeds back the newly generated data to the server to update the contour dynamic benchmark and construction response field.

[0022] This invention provides a method and system for evaluating the construction quality of tunnels using the drill-and-blast method, which has the following beneficial effects:

[0023] 1. This invention solves the core problems of rigid evaluation benchmarks and inability to adapt to continuous changes in surrounding rock conditions and cumulative blasting effects by establishing and maintaining a tunnel profile benchmark that can dynamically evolve according to changes in actual excavation profile and geological conditions. This improves the fit and accuracy of tunnel construction quality assessment with actual engineering conditions and provides a reliable basis for intelligent decision-making.

[0024] 2. This invention constructs a construction response field based on historical construction data and performs collaborative prediction of blasting vibration velocity and contour forming quality. This solves the problem of decision-making blindness caused by the inability to establish a fast and accurate dynamic correlation mapping between construction parameters and blasting effects before blasting. It improves the scientificity and predictability of construction parameter setting and realizes a fundamental transformation of quality control from passive and lagging detection to proactive and advanced prediction. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0026] The technical solutions in the embodiments of the present invention will be clearly and completely described below. 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.

[0027] This invention provides a method and system for evaluating the construction quality of tunnels using the drill-and-blast method. The implementation of this method relies on an integrated system, including a data acquisition terminal, a server, and an equipment control system. The data acquisition terminal is responsible for collecting various parameters in real time during construction, including drilling parameters, charge parameters, blasting vibration data, geological condition data, meteorological condition data, and construction result data. The server, as the core processing unit, maintains dynamically updated tunnel outline benchmarks and construction response fields, and performs data integration, analysis, and decision generation. The equipment control system receives adjustment instructions from the server, adjusts the parameters of the on-site equipment, and feeds the new data back to the server.

[0028] Before tunnel construction begins, the server initializes system parameters. Based on tunnel design specifications and engineering requirements, thresholds and weights for evaluation indicators are set. For example, the allowable deviation range for over-excavation and under-excavation is set to ±50 mm, and the safe threshold for blasting vibration velocity is set to 2.5 cm / s. The weights of each evaluation indicator in the quality assessment are allocated according to the importance of the project, such as a contour quality weight of 0.6 and a vibration control weight of 0.4. These parameters are input through the system's parameter setting interface and saved to the server. Simultaneously, the server establishes initial rules for the decision mapping table, based on tunnel construction mechanics principles and expert experience. For example, the decision mapping table defines that when the vibration conflict component (i.e., the ratio of actual vibration velocity to safety threshold) is between 1.1 and 1.3, the corresponding charge amount should be reduced by 5%; when the profile conflict component shows that the over-excavation value is concentrated in the crown area, the corresponding output should be an adjustment command to reduce the drilling angle by 0.5 degrees; in addition, the equipment control system has pre-stored safety upper and lower limits for construction parameters, such as the charge amount should not be lower than the minimum critical value of 0.5 kg per hole to ensure rock breakage, and the hole spacing should not be less than 0.8 meters or greater than 1.5 meters. These limits are derived from tunnel design specifications and equipment operation manuals.

[0029] At the start of construction, the server generates a unique session identifier and establishes a data list for the session, listing all data types that need to be collected in this round of construction, including borehole parameter sets, charge quantity, vibration velocity sequence, and contour point cloud data; the data acquisition terminal starts working.

[0030] During drilling, intelligent rock drilling equipment automatically collects hole depth, hole spacing, and angle parameters. For example, using an intelligent rock drilling rig equipped with sensors, it collects hole depth of 3.2 meters, hole spacing of 1.2 meters, and angle of 15 degrees, and sends these parameters, along with a session identifier, to the data acquisition equipment in real time via a wireless transmission module. For manual drilling, workers use a hole depth measuring ruler and an angle meter to measure the hole depth and manually enter the data on the data acquisition terminal, while simultaneously associating it with the current session identifier. During the charging process, the electronic metering device on the charging equipment records the explosive type, charge quantity, and charge structure. For example, it records a charge quantity of 1.0 kg per hole, an emulsion explosive type, and a continuous charge structure, and the data is automatically transmitted to the data acquisition equipment.

[0031] During blasting, vibration monitoring instruments deployed at key locations collect vibration velocity data. For example, high-precision vibration sensors are placed 10 meters behind the tunnel face, 5 meters on both sides of the tunnel, and on the surface of the lining structure to collect vibration velocity, frequency, and duration data. The session identifier and vibration data are then wirelessly transmitted to the data acquisition equipment. After blasting, a laser profiler is used to scan the tunnel excavation cross-section to obtain contour data. For example, a high-precision laser profiler is used to scan along the tunnel axis to obtain a set of point cloud data representing the current excavation contour. This data, along with the session identifier, is transmitted to the server. The data acquisition equipment verifies and integrates all received data using the session identifier to ensure the integrity of data packets within the same session. If a certain data type is not received after a predetermined maximum waiting time threshold of ten minutes, the system marks that round as an incomplete session. Data from such sessions will not be used for critical updates to the construction response field, but contour data can be used with lower weight for updates to the dynamic contour baseline.

[0032] After receiving the data, the server first processes the contour data. The server maintains a dynamically updated tunnel contour reference, initially set to the design contour. The contour data collected by the laser profiler is compared with the dynamic contour reference. The server smooths the collected contour data to remove random noise, and then gradually adjusts the position and orientation parameters of the contour to maximize the overlap area between the adjusted contour and the dynamic contour reference, thus determining the optimal spatial transformation. The specific process includes: initially aligning the collected contour data with the dynamic contour reference as a reference; then translating and rotating the collected contour in the horizontal, vertical, and axial dimensions with a preset initial step size of 0.1 meters and an angle increment of 1 degree; after each adjustment, calculating the enclosing area between the two contours, obtained by discretizing the contour into dense sampling points and calculating their convex hull area; and then iterating through the adjusted parameters... The corresponding enclosed areas are counted and compared to determine the parameter range that minimizes the enclosed area. Within this parameter range, adjustments and calculations are repeated with a reduction step of 0.01 meters and an angle increment of 0.1 degrees until the change in the enclosed area is less than the set convergence threshold of 0.001 square meters. The corresponding translation and rotation parameters are then determined as the optimal spatial transformation parameters. Based on this transformation, the cumulative area of ​​the non-overlapping region between the transformed contour line and the dynamic contour reference is calculated as the area difference, for example, 0.15 square meters. Simultaneously, along the tunnel axis according to a preset mileage point sequence, the radial offset between the transformed contour line and the dynamic contour reference is calculated at each point as the linear over- or under-excavation value, for example, over-excavation of 20 mm at mileage point K1+100 and under-excavation of 10 mm at K1+110. Finally, the area difference and all linear over- or under-excavation values ​​are sequentially combined into a multi-dimensional vector to form the contour quality vector for this round of excavation.

[0033] Next, the server integrates the drilling parameters, charge parameters, and geological condition data of the current cycle into a construction state vector. The geological condition data comes from the pre-construction geological survey report and advanced geological forecasting equipment during construction, such as ground-penetrating radar or TSP systems, to obtain the surrounding rock grade, rock mechanical parameters, and groundwater conditions. For example, the surrounding rock grade is III, the uniaxial compressive strength of the rock is 60 MPa, and the groundwater condition is dry. The construction state vector includes parameters such as borehole depth, borehole spacing, angle, charge quantity, and surrounding rock grade. The server constructs a construction response field based on historical data. The construction response field is a historical dataset stored in the server database. Each record contains a construction state vector and its corresponding actual vibration velocity data and contour mass vector. For the current construction state, the server calculates the Euclidean distance between the current construction state vector and each historical construction state vector in the historical data of the construction response field in multidimensional space. The five historical states with the smallest Euclidean distance are selected as neighboring samples, and their weights are determined based on the reciprocal of their distance from the current state. The weight coefficient is the ratio of the distance between each sample and the current state. The normalized value of the reciprocal of the Euclidean distance to the current construction state vector; for example, if the Euclidean distances between the current state vector and historical samples are 0.5, 0.6, 0.7, 0.8, and 0.9 respectively, then the weighting coefficients are calculated as the normalized values ​​of the reciprocal of the distances, which are 0.28, 0.23, 0.20, 0.17, and 0.12 respectively; then, a weighted average is performed on the historical vibration velocity data and historical profile mass vector corresponding to the selected neighboring samples to deduce the expected vibration velocity and profile mass vector, which serve as the prediction benchmark for this round of blasting; for Vibration velocity is calculated by multiplying the historical vibration velocity values ​​of each neighboring sample by their respective weighting coefficients and then summing them. For example, the expected vibration velocity is 2.2 cm / s. For the profile quality vector, the same operation is performed on its area difference component and the linear over-excavation / under-excavation value component at each mileage point. The corresponding component values ​​of each neighboring sample are multiplied by their respective weighting coefficients and then summed to derive the complete multidimensional expected profile quality vector. For example, the expected area difference is 0.12 square meters, and the expected linear over-excavation / under-excavation value at mileage point K1+100 is 15 mm of over-excavation.

[0034] After blasting, the server compares the actual monitored vibration velocity data and profile mass vector with the prediction benchmark. For example, if the actual vibration velocity is 2.8 cm / s and the area difference in the actual profile mass vector is 0.15 m², the linear over-excavation / under-excavation value at K1+100 is 20 mm over-excavation. The server calculates the relative deviation between the actual data and the prediction benchmark. If the deviation exceeds a set threshold, such as a vibration velocity deviation exceeding 20% ​​or a profile mass vector deviation exceeding 15%, the current construction state vector and the actual monitoring data are added as a new sample point to the historical data to complete the update of the construction response field.

[0035] The server then generates the current state conflict vector; calculates the ratio of the actual vibration velocity to the safety threshold as the vibration conflict component, for example, 2.8 divided by 2.5 equals 1.12; simultaneously, it calculates the ratio of the area difference component in the actual profile mass vector to the allowable area deviation, and the ratio of the linear over-excavation / under-excavation value at each mileage point to the corresponding allowable linear deviation; the allowable area deviation is set to 0.1 square meters, and the allowable linear deviation is set to ±50 millimeters; for example, the area difference ratio is 0.15 divided by 0.1 equals 1.5, and the ratio of the linear over-excavation / under-excavation value at K1+100 is 20 divided by 50 equals 0.4; these ratios are then grouped in sequence. The current state conflict vector is synthesized. The server defines the weight coefficients of each component in the conflict vector. For example, the vibration conflict component has a weight of 0.4, and the contour conflict component has a weight of 0.6. The combined value of vibration conflict and contour conflict is calculated by weighted summation. For example, the combined value of vibration conflict is 1.12 multiplied by 0.4, which equals 0.448. The combined value of contour conflict is 1.5 multiplied by 0.6 plus the weighted sum of the equal components, which is assumed to be 0.9. The magnitude of these two combined values ​​is compared to determine the dominant conflict type. Since the combined value of contour conflict is 0.9, which is greater than the combined value of vibration conflict is 0.448, the system determines that the conflict is contour-dominant.

[0036] Based on the decision mapping table, the server queries the drilling parameter adjustment rules corresponding to the dominant conflict in the profile. According to the distribution characteristics of linear over-excavation and under-excavation values ​​in the profile quality vector, such as the over-excavation values ​​being concentrated in the crown area, the decision mapping table outputs an adjustment instruction to reduce the drilling angle by 0.5 degrees. At the same time, based on the current hole spacing value of 1.2 meters, it outputs an instruction to reduce the hole spacing by 0.05 meters. The server converts these adjustment rules into specific construction parameter adjustment instructions, including the adjusted charge quantity, hole spacing, and angle values, and encapsulates them into executable commands. For example, the adjusted hole spacing is 1.15 meters and the angle is 14.5 degrees.

[0037] After receiving the adjustment command from the server, the equipment control system first performs a safety check. The system stores pre-defined safety limits for construction parameters, such as a hole spacing safety range of 0.8 to 1.5 meters and an angle safety range of 10 to 20 degrees. The control system compares the adjusted parameters in the command with these safety limits. If the adjusted parameters are within the safety range, the command is parsed, and the hole spacing and angle in the drilling parameter group are adjusted synchronously according to the defined parameter association rules. The control system then controls the intelligent rock drilling equipment to perform drilling operations using the adjusted parameter group, for example, setting the hole spacing to 1.15 meters and the angle to 14.5 degrees. Simultaneously, the charge quantity and charge structure in the charge parameter group are modified collaboratively, but the charge quantity remains unchanged due to the contour-dominated conflict. After the operation is completed, a laser profiler is used to collect newly generated contour line data and feed it back to the server to update the contour dynamic benchmark. The server adds the actual construction state vector and corresponding monitoring data of this round as new sample points to the historical database of the construction response field, completing the incremental update of the construction response field.

[0038] The update mechanism of the dynamic contour benchmark is clearly defined. After obtaining the actual contour line data of the current round after optimal spatial transformation and alignment, the server performs a weighted fusion of this contour line with the current dynamic contour benchmark to generate a new benchmark. The new dynamic contour benchmark is calculated by fusing 70% of the current actual contour line data and 30% of the historical dynamic contour benchmark data. This weighted fusion is performed on the radial coordinates of each corresponding mileage point of the contour line. For example, at the current mileage point, the radial coordinate of the historical benchmark is 5.00 meters, and the radial coordinate of the actual contour line is 5.02 meters. Then the radial coordinate of the new benchmark is 5.02 multiplied by 0.7 plus 5.00 multiplied by 0.3, which equals 5.014 meters. In this way, the dynamic contour benchmark can not only track the long-term trend of the actual excavation contour, but also effectively smooth the random fluctuations brought about by a single blast, thus forming a reliable comparison benchmark that is both stable and adaptable to geological changes.

[0039] This invention enables real-time assessment and dynamic adjustment of the construction quality of drill-and-blast tunnels. The system can adaptively update the benchmark and model according to the actual engineering conditions, improving the accuracy of assessment and construction efficiency. For example, after multiple cycles, the construction response field accumulates rich data, improving prediction accuracy, making parameter adjustments more precise, optimizing over-excavation and under-excavation and vibration control, and significantly improving the overall construction quality.

[0040] 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 method for evaluating the quality of construction of a tunnel by the drill-and-blast method, characterized in that, The method comprises the following steps: S1. During drilling, collect hole depth, hole distance and angle parameters, and charge amount; during blasting, collect vibration velocity data; scan the tunnel excavation section to obtain the contour line data of the tunnel; Real-time transmission of the collected data to the server; S2. The server maintains a dynamically updated tunnel contour reference, and the initial value of the reference is the design contour line; compare the collected contour line data with the dynamic contour reference, calculate the area difference of the overall contour deviation degree and the overbreak or underbreak value by solving the spatial transformation that minimizes the enclosed area between the two contour lines, and jointly serve as the contour quality vector of the current round of excavation; S3. The server integrates the drilling parameters, charge parameters and geological condition data into a construction state vector, and constructs a construction response field based on historical data, wherein the construction response field stores historical construction state vectors, corresponding vibration velocity data and contour quality vectors; for the current construction state, the server calculates the Euclidean distance between the current construction state vector and each historical construction state vector in the construction response field, selects a preset number of historical states as neighboring samples in order of increasing Euclidean distance, and determines the weights according to the reciprocal of the distance between each neighboring sample and the current construction state vector; the historical vibration velocity data and historical contour quality vectors corresponding to the selected neighboring samples are weighted and averaged to deduce the expected vibration velocity and contour quality vector as the prediction reference for the current round of blasting; difference analysis is performed between the actual monitoring data after blasting and the prediction reference, and the construction response field is updated; S4. The server constructs a current state conflict vector from the ratio of the actual vibration velocity to the safety threshold and the ratio of each component in the contour quality vector to the allowable deviation; a decision mapping table is established, and construction parameter adjustment instructions are generated based on the decision mapping table; S5. The construction parameter adjustment instructions are sent to the equipment; according to the correlation rules defined in the construction parameter adjustment instructions, the drilling parameter group or the charge parameter group is adjusted coordinately; and the new data generated is fed back to the contour dynamic reference and the construction response field.

2. The quality evaluation method for drill-and-blast tunnel construction according to claim 1, characterized in that: The S1 step further comprises: the construction personnel start a new data collection session, generate a unique session identifier; during the drilling process, the intelligent drilling equipment collects hole depth, hole distance and angle parameters, and sends the session identifier and parameter data to the data collection equipment in real time; for the manual drilling part, the construction personnel measure the parameters using special measuring tools, and associate the current session identifier when entering the data on the data collection terminal; during the charging process, the electronic metering device on the charging equipment records the charging amount, and sends the session identifier and charging amount data to the data collection equipment; during the blasting process, the vibration monitor arranged at the key position collects vibration speed data, and transmits the session identifier and vibration data to the data collection equipment in real time; after blasting, the laser profile gauge is used to scan the tunnel excavation section to obtain the contour line data, and the session identifier and contour line data are transmitted to the server in real time through the data collection equipment; the data collection equipment checks and integrates all received data according to the session identifier, to ensure that the data packets are transmitted to the server completely under the same session.

3. The quality evaluation method for drill-and-blast tunnel construction according to claim 1, characterized in that: The S2 step comprises: when the server compares the contour line data collected by the laser profile gauge with the dynamic contour reference, first, the collected contour line data is smoothed to remove random noise; then, by gradually adjusting the position and direction parameters of the contour line, the area of the overlapping region between the adjusted contour line and the dynamic contour reference is maximized, so as to determine the optimal spatial transformation; based on the transformation, the cumulative area of the non-overlapping region between the transformed contour line and the dynamic contour reference is calculated as the area difference; at the same time, along the tunnel axis according to the preset sequence of mileage points, the offset of the transformed contour line and the dynamic contour reference in the radial direction is calculated at each point as a linear overbreak or underbreak value; finally, the area difference and all linear overbreak or underbreak values are combined in sequence into a multi-dimensional vector to form a contour quality vector of this round of excavation.

4. The quality evaluation method of drill-and-blast tunnel construction according to claim 3, characterized in that: The process of determining the optimal spatial transformation comprises: taking the dynamic contour reference as a reference, the collected contour line data is first aligned; then, in the horizontal, vertical and axial three dimensions, the collected contour line is adjusted in translation and rotation with a preset initial step size and angle increment; after each adjustment, the enclosed area between the two contour lines is calculated, which is obtained by discretizing the contour line into dense sampling points and calculating the convex hull area; by traversing the adjustment parameters and comparing the corresponding enclosed areas, the parameter range that makes the enclosed area present a minimum value is located; then, within the parameter range, the above adjustment and calculation process is repeated with a step size until the change of the enclosed area is less than a set convergence threshold, at which time the corresponding translation and rotation parameters are determined as the optimal spatial transformation parameters.

5. The quality evaluation method for drill-and-blast tunnel construction according to claim 1, characterized in that: The S3 step includes: after the server integrates the drilling parameters, the charging parameters and the geological condition data of the current round into a construction state vector, the server calculates the Euclidean distance between the current construction state vector and each historical construction state vector in the historical data of the construction response field; the server selects a preset number of historical states with the smallest Euclidean distance as the neighboring samples, and determines the weights according to the reciprocal of the distance between the neighboring samples and the current state; the server performs weighted average on the historical vibration speed data and the historical profile quality vector corresponding to the selected neighboring samples, and deduces the expected vibration speed and profile quality vector as the prediction benchmark of the current blasting; after the blasting, the server compares the actual monitored vibration speed data and profile quality vector with the corresponding prediction benchmark values respectively, and calculates the relative deviation; when any deviation exceeds the corresponding set threshold, the server adds the construction state vector and the actual monitoring data of the current round to the historical data as a new sample point, thereby completing the update of the construction response field.

6. The quality evaluation method of drill-and-blast tunnel construction according to claim 5, characterized in that: The process of deducing the expected vibration speed and profile quality vector includes: after the neighboring samples are selected, a weight coefficient is assigned to each sample, which is the normalized value of the reciprocal of the Euclidean distance between the sample and the current construction state vector; for the vibration speed data, the historical vibration speed values of the neighboring samples are multiplied by the corresponding weight coefficients and then summed to obtain the deduced expected vibration speed; for the profile quality vector, the same operation is performed on the area difference components and the linear overbreak and underbreak value components of each mileage point, the corresponding component values of the neighboring samples are multiplied by the weight coefficients and then summed respectively, thereby deducing the complete multi-dimensional expected profile quality vector.

7. The quality evaluation method of drill-and-blast tunnel construction according to claim 5, characterized in that: The S4 step includes: the server first calculates the ratio of the actual vibration speed to the preset safety threshold as the vibration conflict component, and calculates the ratio of the area difference component in the actual profile quality vector to the allowed area deviation, and the ratio of the linear overbreak and underbreak value of each mileage point to the corresponding allowed linear deviation, and combines these ratios in sequence into a current state conflict vector; the server defines the weight coefficients of each component in the conflict vector, and calculates the vibration conflict comprehensive value and the profile conflict comprehensive value by weighted summation, compares the sizes of the two comprehensive values to determine the decision mapping table of the dominant conflict type; when the vibration conflict comprehensive value is large, the server queries the corresponding charging parameter adjustment rule in the decision mapping table, and outputs the reduction percentage of the charge amount or the replacement suggestion of the explosive type according to the specific value range of the vibration conflict component; when the profile conflict comprehensive value is large, the server queries the corresponding drilling parameter adjustment rule in the decision mapping table, and outputs the increase or decrease amount of the hole distance and the fine tuning direction of the drilling angle according to the distribution characteristics of the profile conflict component; the server converts the adjustment rule obtained by the query into specific construction parameter adjustment instructions, including the adjusted charge amount value, hole distance value and angle value, and encapsulates them as executable commands.

8. The method for quality evaluation of drill-and-blast tunneling according to claim 7, characterized in that, The S5 step comprises: the server sends the encapsulated construction parameter adjustment instruction to the control system of the on-site intelligent drilling equipment and charging equipment through a data interface; after the instruction is parsed, the hole distance and angle in the drilling parameter group are synchronously adjusted, or the charging amount and charging structure in the charging parameter group are cooperatively modified according to the parameter association rules defined therein; in the drilling and charging operation, the operation is performed according to the adjusted parameter group; after the operation is completed, the newly generated profile data is collected by the laser profiler and fed back to the server for updating the profile dynamic reference; at the same time, the actual construction state vector of this round and the corresponding monitoring data are added to the historical database of the construction response field as new sample points, and the incremental update of the construction response field is completed.

9. A quality evaluation system for tunnel construction by drill and blast method, for implementing a quality evaluation method for tunnel construction by drill and blast method according to any one of claims 1 to 8, characterized in that, Comprise: a data acquisition terminal, configured to automatically collect hole depth, hole distance and angle parameters through the intelligent drilling equipment during drilling, record the charging amount through the electronic metering device on the charging equipment, collect vibration velocity data through the vibration monitor arranged at the key position during blasting, obtain profile line data through the laser profiler scanning the tunnel excavation section after blasting, and transmit all collected data to the server in real time; a server, configured to maintain a dynamically updated tunnel profile reference, the initial value of which is the design profile line, compare the received profile line data with the dynamic profile reference, calculate the area difference and the linear overbreak and underbreak values of each mileage point along the tunnel axis by solving the spatial transformation that makes the enclosed area between the two profile lines minimum, to form a profile quality vector, integrate the drilling parameters, charging parameters and geological condition data into a construction state vector, construct a construction response field based on the historical data, deduce the expected vibration velocity and profile quality vector as a prediction reference, and perform difference analysis to update the construction response field, and also construct a current state conflict vector from the ratio of the actual vibration velocity to the safety threshold and the ratio of each component in the actual profile quality vector to the allowed deviation, generate a construction parameter adjustment instruction by querying the pre-stored decision mapping table; a device control system, configured to receive the construction parameter adjustment instruction sent by the server, cooperatively adjust the drilling parameter group or the charging parameter group according to the association rules defined in the instruction, and control the intelligent drilling equipment and the charging equipment to operate using the adjusted parameter group in subsequent construction, and at the same time, feed the newly generated data back to the server to update the profile dynamic reference and the construction response field.

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