Tunnel construction progress real-time tracking system

Abstract

The invention relates to the technical field of construction management, in particular to a tunnel construction progress real-time tracking system which comprises an environment monitoring module, a progress acquisition module, an anomaly recognition module, a risk assessment module and a resource allocation module. According to the method, through identification of the time sequence and the change amplitude of the tunnel excavation face environment parameters, pre-screening of potential progress interference factors, enhancement of influence factor perception ability and dynamic comparison of environment data and process progress are achieved, the process disjunction phenomenon can be captured in time, and the aging control precision is improved; through linkage analysis of operation time and equipment operation records, association analysis of abnormal positioning, scheduling response and progress offset section resource data is facilitated, operation node-level dynamic evaluation is achieved, allocation imbalance and high-frequency mismatched resources are avoided, operation time sequences are adjusted preferentially, field bottlenecks are relieved, and operation efficiency is improved. And real-time closed-loop linkage between the construction progress and resource configuration is enhanced through information integration and correlation analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of construction management, and particularly to a real-time tracking system for tunnel construction progress. Background Art

[0002] The technical field of construction management involves the organization, coordination, and control of various resources throughout the entire process of engineering construction, aiming to improve construction efficiency, ensure construction quality, and control construction costs. In this technical field, the core contents include the formulation and implementation of construction plans, the monitoring of construction progress and quality, the management of resource allocation and utilization, the control of work safety, and the collection and processing of construction information. With the continuous expansion of the scale of engineering construction and the increase in project complexity, information technology means have been gradually introduced into construction management technology to conduct systematic and digital management of key elements at the construction site, such as personnel, equipment, materials, construction period, etc., so as to achieve efficient collaboration and scientific decision-making in construction activities. This field also focuses on the real-time collection and analysis of various dynamic data during the construction process, and uses an information integration platform to track and schedule the construction status throughout the whole process.

[0003] Among them, the real-time tracking system for tunnel construction progress refers to a technical solution for the real-time collection, collation, and feedback of the progress status during the construction stage of tunnel engineering, specifically covering the time node records and comparisons of key processes such as tunnel excavation progress, lining operation progress, and construction cycle rhythm. By deploying positioning devices, time recorders, data transmission terminals, etc. at the tunnel site, the time and position data of each operation link are collected, and then automated comparison is carried out based on the planned data in the construction organization design to realize the correlation analysis and dynamic update of the actual construction progress and the planned progress. This system realizes the automatic integration and update of construction progress information by establishing a job process node database and combining the continuous records of the start and completion times of the construction team during each operation stage, thereby forming a real-time tracking system for each key time node during the whole process of tunnel construction.

[0004] In the process of progress monitoring in the prior art, although it relies on time recorders and data terminals to record key processes and compare them with the plan, there is a lack of a real-time warning mechanism for external environmental factors that affect the progress. It is only discovered after anomalies have caused delays, resulting in a lag in response. Although the on-site operation status can be recorded, there is a lack of in-depth linkage analysis between the data. The identification of equipment operation anomalies or operation delays relies on manual inspections or delayed data feedback, delaying the discovery and handling of problems. The operation progress data and the resource status data of equipment, personnel, materials, etc. are managed in a fragmented manner, making it difficult to achieve real-time lag identification under the collaborative state of multiple types of resources. This leads to information islands during the decision-making of resource allocation at construction nodes, affecting the allocation efficiency. There is a lack of a resource attribution mechanism for node progress deviation, and it does not have the ability to classify and count by link, so an effective feedback loop for resource allocation cannot be formed. For example, when material distribution is frequently delayed, the system is difficult to accurately identify the delay frequency and the cumulative impact on construction progress, resulting in the recurrence of resource imbalance problems without being preferentially intervened, affecting the stability of the overall construction rhythm. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art and propose a real-time tracking system for tunnel construction progress.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: The real-time tracking system for tunnel construction progress includes:

[0007] The environmental monitoring module obtains data near the tunnel excavation face, including temperature data, humidity data, soil humidity data, and groundwater level data. After arranging them in chronological order, it identifies the change range of each data item, marks the data items with a range exceeding the threshold as potential progress interference factors, and generates a list of changes in interference factors.

[0008] The progress collection module extracts the operation time period and completion ratio of the processes within the shield section according to the list of changes in interference factors, synchronously compares the real-time progress of the three operations of sectional tunneling, support, and lining, records the operation sections with time lag phenomena, and generates a list of identified operation lags.

[0009] The anomaly identification module calculates the difference between the equipment operation duration and the operation duration under the standard configuration according to the list of identified operation lags, and combines the real-time status of shield propulsion and initial support operations. If the duration is abnormal, it is marked as an offset section, and a set of progress offset marks is generated.

[0010] The risk assessment module extracts the start and stop records of tunneling equipment, personnel scheduling, and material distribution according to the set of progress offset marks, analyzes whether there is a progress lag in the three types of resources, counts the number and duration of lags, classifies them into the corresponding construction links, and generates a frequency table of node resource mismatch.

[0011] As a further solution of the present invention, the interference factor change list includes a data change threshold category, an abnormal data item number, a data item abnormality level, and a time series mark. The operation lag identification list includes a lag time length, a lag process identifier, a comparison progress benchmark, and a lag severity. The progress deviation mark set includes an operation time error range, a device operation deviation degree, a process deviation status identifier, and an abnormal continuous period number. The node resource mismatch frequency table includes a resource type mismatch frequency, a construction link mismatch record, a lag resource category statistic, and a mismatch time period mark.

[0012] As a further solution of the present invention, the environmental monitoring module includes:

[0013] The data capture sub-module acquires data near the tunnel excavation face, including temperature data, humidity data, soil humidity data, and groundwater level data, arranges them in a unified sequence according to the time stamp, combines the data of the time period, and generates a multi-source environmental sequence data set;

[0014] The amplitude calculation sub-module performs a numerical difference operation on the same type of data within a continuous time period based on the multi-source environmental sequence data set, compares the difference with the environmental index fluctuation threshold, screens the data time periods that exceed the standard, and generates a progress impact data segment;

[0015] The interference identification sub-module extracts the time corresponding to the data in the progress impact data segment and matches it with the construction plan time axis of the working face, sets an interference mark for the overlapping time period, summarizes the mark points and the corresponding factor types and frequencies, and generates an interference factor change list.

[0016] As a further solution of the present invention, the progress acquisition module includes:

[0017] The operation time period identification sub-module extracts the time, intensity, and impact section information of the interference event according to the interference factor change list, identifies the process numbers and the original planned arrangement of the shield tunnel section excavation, support, and lining operations, performs an intersection analysis of the interference time period and the planned time period, screens the interfered operation time periods, and generates a set of interfered operation time periods;

[0018] The completion ratio analysis sub-module calls the operation numbers in the set of interfered operation time periods, identifies the real-time progress and the completed quantity of the unit project, analyzes the completion ratio difference at the current time node of the operation, and generates a sub-item operation completion ratio difference sequence;

[0019] The lag section judgment sub-module extracts the progress speed and the synchronous start time according to the ratio differences of the three processes of excavation, support, and lining in the sub-item operation completion ratio difference sequence, performs an offset difference judgment, and uses the formula:

[0020]

[0021] Calculate the increment value of the operation section offset, screen the process sections where the offset increment value is greater than the average value, and generate a list of recognized operation lags;

[0022] Among them, D represents the increment value of the operation section offset, Pt, Ps, and Pc are the current completion ratios of tunneling, support, and lining operations, N is the number of operation nodes of the unit project, E is the event interference intensity, Tt and Ts are the starting times of tunneling and support, and Q is the completed quantity of the unit project.

[0023] As a further solution of the present invention, the anomaly recognition module includes:

[0024] The operation time offset extraction sub-module calls the operation time records and equipment operation data of the lag section according to the list of recognized operation lags, extracts the start and end time points of the propulsion section operation, identifies the corresponding difference between the operation duration and the equipment operation duration, and obtains the operation time difference sequence;

[0025] The progress lag comparison sub-module calls the operation time difference sequence, combines the standard configuration operation duration of each section and the current propulsion footage, extracts the corresponding propulsion state and support state information, and uses the formula:

[0026]

[0027] Combined with the progress time window constraint of each section, obtain the progress lag comparison value;

[0028] Among them, M represents the progress lag comparison value, X i represents the equipment operation duration of the i-th section, Y i represents the standard operation duration of the i-th section, K i represents the fluctuation amplitude of the propulsion state of the i-th section, V i represents the real-time support rate of the i-th section, S i represents the support section spacing of the i-th section, U i represents the cumulative propulsion volume of the i-th section on the construction day, and n represents the total number of propulsion sections;

[0029] The progress anomaly marking sub-module identifies the propulsion sections where the offset value is greater than the construction progress tolerance according to the progress lag comparison value, combines the shield operation trajectory and the construction timeline, marks the sections where the propulsion and support operations have offsets, and generates a progress offset mark set.

[0030] As a further solution of the present invention, the risk assessment module includes:

[0031] The start-stop retrieval sub-module extracts the start-stop records of the tunneling equipment according to the progress offset mark set, matches the shutdown sections and the equipment operation time sections, screens the operation interruption sections within the offset sections, identifies the total equipment stagnation time, and obtains the tunneling equipment stagnation time value;

[0032] The scheduling lag identification sub-module calls the stagnation time value of the tunneling equipment, cross-judges the personnel scheduling shift, the material distribution time and the equipment stagnation section, counts the lag duration and frequency of each type of resource, and obtains the frequency quantity of the lag duration of personnel and materials;

[0033] Based on the frequency quantity of the lag duration of personnel and materials, the resource mismatch statistics sub-module classifies and extracts the lag resource categories corresponding to the construction processes, integrates the lag duration and frequency of the construction nodes, and uses the formula:

[0034]

[0035] Calculate the node resource mismatch degree value, form a mismatch frequency sequence according to the construction nodes, and obtain the node resource mismatch frequency table;

[0036] Among them, ΔG represents the node resource mismatch degree value, λ r is the lag duration of the r-th type of resource, β r is the usage frequency of the r-th type of resource, μ r is the lag frequency of the r-th type of resource, θ r is the number of allocation nodes of the r-th type of resource, ξ r is the lag sensitivity factor of the r-th type of resource, and z represents the total number of resources.

[0037] As a further solution of the present invention, the system further includes a resource allocation module:

[0038] Based on the node resource mismatch frequency table, the resource allocation module identifies the equipment types and work types whose frequencies exceed the set threshold, assigns priorities and adjusts the operation timing sequence, records the changes in key resources, and generates a key resource adjustment list for tunnel construction;

[0039] The key resource adjustment list for tunnel construction includes a list of resources to be adjusted first, the adjustment order of key resources, the operation rhythm after adjustment, and a resource configuration optimization mark.

[0040] As a further solution of the present invention, the resource allocation module includes:

[0041] Based on the node resource mismatch frequency table, the frequency identification sub-module extracts the equipment type and work type information, screens the over-frequency data according to the resource mismatch frequency threshold, identifies the corresponding node positions and time fields, analyzes the frequency fluctuation range through the time fields, and generates a high-frequency mismatch time period sequence;

[0042] The priority sorting sub-module calls the high-frequency mismatch time period sequence, extracts the repeated distribution quantity of the equipment type and work type within the differential time period, evaluates the resource allocation concentration in combination with the allocation times, sorts the distribution priorities of the tunnel operation intervals, and generates a resource interference priority sequence;

[0043] The timing adjustment sub-module extracts the priority device types and work types according to the resource interference priority sequence, identifies the operation numbers and time periods, analyzes the deployment overlap rate of the construction sections, adjusts the operation sequence according to the overlap rate, records the adjusted sections and times, and generates a list of key resource adjustments for tunnel construction.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0045] In the present invention, through the time series arrangement and change amplitude recognition of multi-source environmental parameters around the tunnel excavation face, the pre-screening of potential interference factors of environmental data on the construction progress can be realized, and the active perception ability of construction influencing factors can be improved. By dynamically synchronizing and comparing the environmental parameters with the actual progress of the processes, the time disconnection between processes can be captured at the initial stage of the anomaly, and the fine-grained time control of the construction link can be enhanced. The parallel retrieval and comparative analysis of the operation time and equipment operation records enable the rapid positioning of problems such as equipment operation efficiency and operation persistence deviation, facilitating the scheduling response at the initial stage of the anomaly formation and shortening the response time. The joint analysis of the equipment start-stop, personnel scheduling, and material distribution data corresponding to the progress deviation section enables the dynamic evaluation of the resource allocation status at the operation node level, avoiding the imbalance of resource allocation caused by a single index judgment. Setting priorities for high-frequency mismatched resource items and adjusting the operation timing can effectively alleviate the resource bottleneck problem at the construction site and improve the collaborative efficiency of resource use. The identification logic of each key link is based on dynamic information integration and correlation analysis, enhancing the real-time closed-loop linkage ability between the construction state and resource allocation, and realizing the highly adaptable dynamic management of construction progress and resource scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is the system flow chart of the present invention;

[0047] Figure 2 is the flow chart of the environmental monitoring module in the present invention;

[0048] Figure 3 is the flow chart of the progress collection module in the present invention;

[0049] Figure 4 is the flow chart of the anomaly identification module in the present invention;

[0050] Figure 5 is the flow chart of the risk assessment module in the present invention;

[0051] Figure 6 is the flow chart of the resource allocation module in the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0052] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0053] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality" is two or more, unless otherwise specifically defined.

[0054] Please refer to Figure 1 , the real-time tunnel construction progress tracking system includes:

[0055] The environmental monitoring module obtains data near the tunnel excavation face, including temperature data, humidity data, soil humidity data and groundwater level data. After arranging the data in chronological order, it identifies the change amplitude of each data item, marks the data items with amplitudes exceeding the threshold as potential progress interference factors, and generates a list of changes in interference factors.

[0056] The progress collection module extracts the operation time period and completion ratio of the processes in the shield section according to the list of changes in interference factors, synchronously compares the real-time progress of the three operations of sectional tunneling, support and lining, records the operation sections with time lag phenomena, and generates a list of identified operation lags.

[0057] The anomaly identification module retrieves the operation time and equipment operation records of the lag section according to the list of identified operation lags, calculates the difference between the equipment operation duration and the operation duration under the standard configuration, and combines the real-time states of shield propulsion and initial support operations. If the duration is abnormal, it is marked as an offset section and a set of progress offset marks is generated.

[0058] The risk assessment module extracts the start-stop records of tunneling equipment, personnel scheduling and material distribution records according to the set of progress offset marks, analyzes whether there is a progress lag in the three types of resources, counts the number and duration of lags, classifies them into the corresponding construction links, and generates a frequency table of node resource mismatch.

[0059] The resource allocation module identifies the equipment types and work types with frequencies exceeding the set threshold according to the frequency table of node resource mismatch, assigns priorities and adjusts the operation time sequence, records the content of key resource changes, and generates a list of key resource adjustments for tunnel construction.

[0060] The interference factor change list includes data change threshold categories, abnormal data item numbers, data item abnormal levels, and time series markers. The operation lag identification list includes lag time lengths, lag process identifiers, comparison progress benchmarks, and lag severity levels. The progress deviation marker set includes operation time error ranges, equipment operation deviation degrees, process deviation status identifiers, and abnormal duration numbers. The node resource mismatch frequency table includes resource type mismatch frequencies, construction link mismatch records, lag resource category statistics, and mismatch time period markers. The tunnel construction key resource adjustment list includes a priority adjustment resource list, a key resource adjustment order, an adjusted operation rhythm, and a resource allocation optimization marker.

[0061] Please refer to Figure 2 , the environmental monitoring module includes:

[0062] The data capture sub-module obtains data near the tunnel excavation face, including temperature data, humidity data, soil humidity data, and groundwater level data, arranges them in a unified sequence according to timestamps, combines the data for a period of time, and generates a multi-source environmental sequence data set;

[0063] First, various sensors are deployed at predetermined monitoring points, including temperature, humidity, soil humidity, and groundwater level sensors, to ensure the real-time and accurate acquisition of data. The sensors regularly send the collected data, including timestamps and corresponding environmental data. The data is arranged according to timestamps, and the data at different time points is integrated into a continuous time series. For example, in a specific construction area, if the sensors record data every ten minutes, the data points are connected into a timeline to form a detailed environmental data record. This data is not only used to monitor the environmental conditions but also for analyzing environmental challenges encountered during construction, such as a sudden increase in water level indicating rainfall or groundwater flow changes. After classifying the data into a structured set, it is a detailed record of the changes in various environmental parameters such as temperature and humidity during the entire monitoring period. This data set can be used for further analyzing the impact of construction on the environment and the potential impact of environmental changes on the construction progress, generating a multi-source environmental sequence data set, providing basic data for the real-time tracking of tunnel construction progress, and ensuring that the construction team can adjust the plan in a timely manner to adapt to environmental changes.

[0064] The amplitude calculation sub-module performs numerical difference operations on the same type of data within a continuous time period based on the multi-source environmental sequence data set, compares the differences with the environmental index fluctuation thresholds, screens out the data time periods that exceed the standards, and generates progress impact data segments;

[0065] Calculate the difference between data at different time points. For example, calculate the temperature change for each ten-minute interval. By setting specific thresholds, such as a temperature change threshold of 2°C and a humidity change threshold of 5%, when the difference between two consecutive data points exceeds the threshold, this data segment is marked as abnormal. This kind of analysis helps the project management team identify environmental factors that affect the construction progress. For example, a sudden increase in temperature means that the mechanical equipment is overheating and needs to be suspended to avoid failures, or a sudden increase in soil humidity indicates that there will be rainfall in the near future and the drainage system needs to be adjusted. After calculation, progress impact data segments are generated, allowing the construction management team to respond quickly when environmental factors change, thus maintaining the stability of the construction progress.

[0066] The interference identification sub-module extracts the time corresponding to the data according to the progress impact data segments and matches it with the construction plan time axis of the working face, sets interference marks for overlapping time periods, summarizes the marked points and the corresponding factor types and frequencies, and generates a list of changes in interference factors.

[0067] Refine the analysis of which data in specific time periods exceeds the normal range and compare the data with the construction plan. If the abnormal data in a certain time period overlaps with the key construction activities in the plan, mark this time period as a potential interference factor. For example, if a sudden increase in soil humidity is monitored during late night and underground pipeline installation is planned during this time period, this environmental change will be marked as an interference factor because the increased soil humidity will affect the installation quality or construction speed of the pipeline. By identifying potential interference factors and generating a list of changes in interference factors, the construction team can adjust the construction plan more targeted, such as increasing waterproof measures or adjusting working hours, to ensure that the construction progress is not adversely affected by environmental factors. This real-time environmental monitoring and interference identification mechanism is a key technical means to ensure the timely completion of the tunnel construction project.

[0068] Please refer to Figure 3 , the progress acquisition module includes:

[0069] The operation period identification sub-module extracts the time, intensity, and impact section information of interference events according to the list of changes in interference factors, identifies the process numbers and the original planned arrangements of shield tunneling, support, and lining operations in the shield section, conducts an intersection analysis of the interference period and the planned period, screens the affected operation periods, and generates a set of affected operation periods.

[0070] When implementing a tunnel construction project, considering that the operation area will be interfered by external factors such as geological condition changes and adjacent construction activities, the time, intensity and affected section number of interference events are collected through a data-driven method. For example, during the construction of a subway tunnel, if an unstable formation is encountered, this information will be recorded as an interference event. Subsequently, the interference factors are compared with the planned time period of the shield machine operation. Through comparative analysis, the interfered operation time periods are accurately screened to optimize the subsequent construction plan. Geological monitoring tools are used to record the formation changes, and the data is then input into a centralized management. According to the duration and intensity of the formation instability, the overlapping operation time periods are automatically identified. Through this method, the operation plan can be adjusted in a timely manner to ensure construction safety and efficiency, and finally a set of interfered operation time periods is generated.

[0071] The completion ratio analysis sub-module calls the operation numbers in the set of interfered operation time periods, identifies the real-time progress and the completed quantity of the unit project, analyzes the difference in the completion ratio at the current time node of the operation, and generates a sequence of completion ratio differences for sub-item operations;

[0072] In the completion ratio analysis of tunnel construction, according to the data in the set of interfered operation time periods, the affected operation numbers are determined. For example, if an abnormal rise in the groundwater level is found in a certain operation area, the relevant operation is marked as affected. The real-time progress of this operation is obtained through real-time monitoring, including the completed construction length and the total planned construction length. Using specialized analysis software, the difference in the completion ratio relative to the plan at the current node is calculated. For example, if the planned completion is 100 meters and the actual completion is only 80 meters, the completion ratio is 80%. The data reflects the specific completion situation of each operation unit at the current node through calculation, and generates a sequence of completion ratio differences for sub-item operations, so as to accurately evaluate the impact of interference events on the project progress.

[0073] The lag section judgment sub-module extracts the progress speed and the synchronous start time according to the ratio differences of the three processes of tunneling, support and lining in the sequence of completion ratio differences for sub-item operations, conducts an offset difference judgment, and uses the formula:

[0074]

[0075] Calculate the increment value of the offset of the operation section, screen the process sections with the increment value of the offset greater than the average value, and generate a list of identified operation lags;

[0076] Among them, D represents the increment value of the offset of the operation section, Pt, Ps, and Pc are the current completion ratios of tunneling, support and lining operations, N is the number of operation nodes of the unit project, E is the event interference intensity, Tt and Ts are the start times of tunneling and support, and Q is the completed quantity of the unit project;

[0077] Increment value of the operation section offset: This term is used to measure the increase in the progress deviation of a certain operation section during tunnel construction. Specifically, it calculates the increment value by comparing the deviation of the operation section in the actual construction process with the planned schedule. A larger offset increment value means that the progress deviation of this operation section from the expected progress is more significant, which is used to identify the trend of lagging progress. This value helps the construction team determine which operation sections have a large progress deviation and provides a basis for necessary adjustments;

[0078] During the process of judging tunnel construction lag, it is necessary to integrate the progress data of three operations: tunneling, support, and lining, compare their implementation effects in the affected area, and identify construction delays. Extract the current completion ratio data of each operation from the project schedule. The completion ratio Pt of the tunneling section is recorded as 0.68 (i.e., 68%), the completion ratio Ps of the support section is recorded as 0.74 (i.e., 74%), and the completion ratio Pc of the lining section is recorded as 0.83 (i.e., 83%). The above ratio values are all dimensionless percentage values and are uniformly converted to decimal format for subsequent operations. The dimension processing method uses dimensionless ratio conversion;

[0079] The number of operation nodes N within a unit project is obtained from the operation section plan drawing. If the designed number of nodes in this section is 6, then N = 6;

[0080] The event interference intensity E is quantified by an impact level scoring system. Combining the formation disturbance, groundwater level, and vibration parameters in the monitoring data, a weighted impact score within the range of 0 - 1 is used. In this embodiment, the monitoring result corresponds to E = 0.7;

[0081] Tt is the starting time of tunneling, and Ts is the starting time of support, both in days and recorded through the construction log. Assuming Tt = 12 days and Ts = 9 days, the dimension needs to be unified as days, and the difference is 3 days;

[0082] Q is the cumulative completion volume (in meters) of a unit project, which is statistically calculated from the daily construction report. The current completed construction length of this section is 43 meters, so Q = 43;

[0083] Substituting gives:

[0084] Through actual example calculations, the offset increase value D is obtained as 0.3387, which characterizes the degree of progress lag in this section. If the average value of the normal offset in this type of section is approximately 0.25 based on historical construction data statistics, then the offset value in this section has exceeded the baseline level, is marked as a lagging operation section, and is included in the operation lag identification list for further processing by the project management department. The benefit of the formula is that by integrating the real-time progress data of the three core operations with the degree of interference, construction volume, and time offset, it can quantitatively judge the degree of construction lag, providing a direct quantitative basis for on-site decision-making. The result shows that the current construction progress in this section is affected by interference and constitutes a lagging unit in the overall progress coordination, and needs to be adjusted in the scheduling plan to restore progress balance.

[0085] Please refer to Figure 4 , the anomaly identification module includes:

[0086] The operation time offset extraction sub-module calls the operation time records and equipment operation data of the lagging section according to the operation lag identification list, extracts the start and end time points of the operation in the advancing section, identifies the corresponding difference between the operation duration and the equipment operation duration, and obtains the operation time difference sequence;

[0087] By calling the operation time records and equipment operation data of the lagging section, the start and end time points of each advancing section operation are extracted in detail. The calibration of the time points involved includes the start and end of the work, which is to calculate the difference between the actual operation duration of the equipment and the planned operation duration. The key to the process lies in the use of high-precision time recording equipment. For example, in an actual construction scenario, the operation data of a shield machine can be automatically captured through a recorder connected to the central control. The data includes the daily start and stop times, records of operation interruptions, and the specific time after each advancement is completed. Through the data, engineers can calculate the deviation between the actual working time and the planned time of the shield machine under different geological conditions, thereby obtaining the operation time difference sequence. The final result of this series of data processing is a detailed comparison between the actual operation efficiency and the planned execution efficiency of the shield machine, which not only helps to monitor the current project progress but also provides data support for future project planning.

[0088] The progress lag comparison sub-module calls the operation time difference sequence, combines the standard configuration operation duration of each section and the current advancing footage, extracts the corresponding advancing state and support state information, and uses the formula:

[0089]

[0090] Combined with the progress time window constraint of each section, the progress lag comparison value is obtained;

[0091] Among them, M represents the progress lag comparison value, X i represents the equipment operation duration of the i-th section, Y iRepresents the standard operation duration of the i-th section, K i Represents the fluctuation range of the advancement state of the i-th section, V i Represents the real-time support rate of the i-th section, S i Represents the support section spacing of the i-th section, U i Represents the cumulative advancement amount of the i-th construction day, and n represents the total number of advancement sections;

[0092] Progress lag comparison value: This value is used to measure the difference between the actual operation progress and the planned progress. Specifically, by calculating the difference between the actual completion time of each operation section and the operation time of the standard configuration, and combining parameters such as the shield tunneling and support operation states, the degree of progress lag is further evaluated. The progress lag comparison value can help identify which construction sections have serious progress lags and provide support for progress adjustment;

[0093] Call the sequence of operation time differences, and combine the standard duration of each section operation during shield tunneling and the actual advancement footage data to calculate the difference degree between the current operation advancement rhythm and the theoretical plan. First, a detailed description of the acquisition of parameter items is given;

[0094] X i Is the actual advancement operation duration of the i-th section, in hours. This data is obtained through the equipment operation record system. For example, the shield machine operation console automatically records the start and stop times of each section of advancement operation, and subtracting the pause time in it can obtain the net operation duration. If the operation duration of a certain section of construction is 12.4 hours, then X i = 12.4;

[0095] Y i Is the standard advancement operation duration of the i-th section, also in hours, obtained from the set value under the same type of geology and equipment configuration in the construction progress plan. For example, if the standard advancement time is 10 hours, then Y i = 10;

[0096] K i Is the fluctuation range of the advancement state, dimensionless, estimated through the standard deviation of the daily change range of the advancement rate in the construction record. For example, in the recent 5 working days, the advancement rates of this section are 3.2, 3.4, 3.0, 3.6, 3.3 m / h respectively, and its standard deviation is about 0.22, then K i = 0.22;

[0097] V i Is the support rate of the i-th section, in m / h, collected from the initial support equipment operation log. For example, the support rate of this section is recorded as 2.1 m / h in the shotcreting operation log;

[0098] S i Is the support section spacing, in m, obtained from the design drawings. The length of each support section is 2 m, then Si = 2;

[0099] U i is the current cumulative advancement, in meters, obtained by cumulative measurement of the shield tunneling real-time measurement system. If the current cumulative is 410 meters, then U i = 410;

[0100] Before calculation, it is necessary to unify the dimensions of all parameters. All terms have been adjusted to hours, meters, or dimensionless, and no further conversion is required;

[0101] Substitute the above values into the formula:

[0102] From this calculation, the progress lag comparison value for this section is 5.13. According to the preset judgment interval, if this value exceeds 5, it is regarded as "severe lag". Then the construction of this section needs to be included in the lag warning range and used as the key section for subsequent abnormal marking;

[0103] By introducing the reciprocal square root operation of the advancement state fluctuation amplitude K i , the influence degree of the advancement stability on the overall progress is amplified. At the same time, by using the product of the support rate V i and the support section S i divided by the cumulative advancement U i to form the unit advancement efficiency term, the contribution of the support construction efficiency to the total progress deviation is quantified, effectively avoiding the one-sidedness of evaluation based solely on the time difference. The result shows that the advancement efficiency of the current advancement section is seriously lower than the standard requirements. In the progress control, it needs to be included in the lag warning interval, and targeted adjustments are made to its operation resources and scheduling plan. At the same time, it is used as an important reference value for subsequent abnormal marking.

[0104] The progress anomaly marking sub-module identifies the advancement sections with offset values greater than the construction progress tolerance according to the progress lag comparison value, combines the shield operation trajectory and the construction timeline, marks the sections where there are offsets in the advancement and support operations, and generates a progress offset mark set;

[0105] According to the progress lag comparison value, mark the advancing sections where the construction progress shows deviation. The main operations involved in this process are to use the GIS system to monitor the advancing trajectory in real time and conduct data analysis. By comparing and analyzing the standard progress map and the GIS coverage map of the actual progress, engineers can intuitively see which areas have a construction progress lag or lead. After analysis, the information can be further determined as areas with abnormal progress and marked. An example of the operation is in a certain tunnel project. Through real-time data monitoring, it is detected that the advancing speed of a certain section of construction slows down due to unexpected geological conditions (such as encountering a large amount of groundwater suddenly). At this time, this area will be automatically marked as having abnormal progress, and corresponding warnings and reports will be generated for the project management to make decision support. Finally, a progress deviation mark set is generated, providing a real-time dynamic monitoring tool for project management to ensure that the project progresses according to the established schedule and quality standards.

[0106] Please refer to Figure 5 , the risk assessment module includes:

[0107] The start-stop extraction sub-module extracts the start-stop records of the tunneling equipment according to the progress deviation mark set, matches the shutdown sections with the equipment operation time sections, screens the interrupted operation sections within the deviation sections, identifies the total stagnation time of the equipment, and obtains the stagnation time value of the tunneling equipment;

[0108] By each progress deviation point in the mark set, match the corresponding equipment operation time section of the point, and specifically analyze the non-operation period of the equipment. This operation is of great significance for early detection of potential equipment failures and prevention of project delays. Suppose in an actual engineering project, the tunneling machine has no recorded start during the scheduled working section from T1 to T2. This will trigger a series of inspection and adjustment measures. Through this matching, the non-operation time sections related to the progress deviation can be screened out. For example, within the section from T3 to T4, the tunneling machine stops working unexpectedly for more than the scheduled time. Calculate its total stagnation time and extract the key stagnation time periods, such as from 8:00 AM to 10:00 AM. The progress delay caused by the equipment not operating can clarify the specific stagnation duration of the equipment in each time period. The data will directly reflect the operation efficiency and maintenance requirements of the equipment. Summarize the specific stagnation duration of each time period, and finally obtain the stagnation time value of the tunneling equipment. This value is a key data indicator for equipment management in tunnel construction and is crucial for subsequent equipment scheduling and maintenance plan formulation.

[0109] The scheduling lag identification sub-module calls the stagnation time value of the tunneling equipment, cross-judges the personnel scheduling shifts and material delivery times with the equipment stagnation sections, counts the lag duration and frequency of each type of resource, and obtains the personnel and material lag duration and frequency quantity;

[0110] In tunnel engineering, after obtaining the data on the downtime of tunneling equipment, the data is used for further analysis of the time response of personnel scheduling and material distribution. For example, when the equipment is down, the original planned personnel shifts and material deliveries need to be adjusted to avoid resource waste. This process compares the arrival time of personnel and the arrival time of materials with the downtime of the equipment to detect whether there are delays in personnel arrival or untimely material deliveries during the equipment downtime. Specifically, it includes checking whether there is an overlapping material delivery record during the period from equipment shutdown at T5 to T6. If it is found that materials are still being delivered during the equipment failure downtime, this will be recorded as a lag in resource scheduling. By this method, the lags in personnel and material distribution during all equipment downtimes are identified, and the lag duration and frequency are cumulatively calculated to obtain the personnel and material lag duration and frequency quantity. The quantification result provides data support and improvement directions for subsequent resource reallocation.

[0111] The resource mismatch statistics sub-module extracts the corresponding lagged resource categories for construction processes based on the personnel and material lag duration and frequency quantity, integrates the lag duration and frequency of construction nodes, and uses the formula:

[0112]

[0113] Calculate the node resource mismatch degree value, form a mismatch frequency sequence according to construction nodes, and obtain the node resource mismatch frequency table;

[0114] Among them, ΔG represents the node resource mismatch degree value, λ r is the lag duration of the r-th type of resource, β r is the usage frequency of the r-th type of resource, μ r is the lag frequency of the r-th type of resource, θ r is the number of allocation nodes of the r-th type of resource, ξ r is the lag sensitivity factor of the r-th type of resource, and z represents the total number of resources;

[0115] Node resource mismatch degree value: This value is used to represent the matching situation of resources (such as equipment, personnel, materials, etc.) at each operation node during the construction process. Specifically in the calculation, multi-dimensional data such as the lag duration, usage frequency, lag frequency, and number of allocation nodes of resources are combined to form a comprehensive evaluation index. The higher the node resource mismatch degree value, the more serious the resource allocation mismatch problem at that node, which will affect the overall progress and efficiency of the construction;

[0116] In tunnel construction management, for the resource allocation of construction nodes, it is necessary to comprehensively consider the actual lag behavior of personnel and materials during the construction process. Therefore, based on the obtained frequency of the lag duration of personnel and materials, in order to further analyze the resource matching status of each construction node, it is necessary to match the resource category with the specific construction process, and count the number and duration of lag behaviors by node. First, obtain the lag duration λ of each type of resource at each node r , which is calculated by accumulating the time periods when a certain type of resource fails to arrive in time or is not used in time at a certain node in the construction log. For example, in construction node A, the cable material has 3 lag behaviors, with lag times of 1.5 hours, 1 hour, and 0.5 hours respectively, then λ1 = 3 hours. Subsequently, determine the usage frequency β of this type of resource at this node r , and obtain the frequency information by checking the task volume allocation record in the construction plan. If the usage frequency of the cable at node A is higher than the resource, it is set as β1 = 3 according to the grade division. At the same time, collect the lag times μ of this resource at the current node r , and its value is the independent statistical number of lag behaviors, which is μ1 = 3 in this example. Then determine the number of allocation nodes θ of the resource at this node r , that is, the number of transfer records of this type of resource at this node in the dispatching system. If a total of 4 dispatching operations have been initiated for the cable material at construction node A, then θ1 = 4, and the lag sensitivity factor ξ r is based on the expert experience score of the resource's time-sequence dependence on the construction link, and the value is divided into 1 (low dependence) to 5 (extremely high dependence). For example, the cable material is a core material in the power system node, so it is set as ξ1 = 5. To ensure that each parameter in the formula has a unified dimension, for parameters such as λ r , μ r , θ r with measurement units of "hours" and "times", standardization transformation is adopted to normalize them and unify the dimension to meet the requirements of mixed operations;

[0117] Substitute the above values to get:

[0118] The resource mismatch degree value of this construction node is obtained as 4, and this result reflects that there is a moderate mismatch phenomenon at construction node A in terms of cable materials. It is recommended to further comprehensively analyze in combination with the lag value of the resource. Finally, generate a node resource mismatch frequency table and make further optimization and adjustment to the overall resource allocation system;

[0119] Among them, λ r represents the total lag duration of the resource at the node (unit: hours), β r represents the usage frequency of the resource (dimensionless grade value, level 1–3), μ r is the number of resource lags (unit: times), θr is the number of resource allocation nodes (unit: times), ξ r is the hysteresis sensitivity (unit: experience grade score, value 1-5), and the result obtained after unified operation is a dimensionless comprehensive value.

[0120] By integrating the square of the product of the lag time and the resource usage frequency, and introducing the weighted terms of the resource allocation behavior difference and the lag sensitivity factor, a composite evaluation mechanism is formed to effectively identify the mismatch status of key resources at key nodes. The result shows that there is one over-allocation behavior in the allocation of cable resources in construction node A, which causes the mismatch degree to decrease to 4, and the allocation plan needs to be readjusted.

[0121] See also Figure 6 , the resource allocation module includes:

[0122] The frequency identification submodule extracts the equipment type and work type information according to the node resource mismatch frequency table, filters the overclocking data according to the resource mismatch frequency threshold, identifies the corresponding node position and time field, analyzes the frequency fluctuation amplitude through the time field, and generates a high-frequency mismatch period sequence;

[0123] First, extract the equipment type and work type information in the node resource mismatch frequency table. The equipment type refers to different equipment related to construction, such as excavators, drilling rigs, etc., while the work type refers to specific types of operations, such as electric welding, concrete pouring, etc. Based on the resource mismatch frequency threshold, filter out overfrequency data. Overfrequency data refers to data points where the mismatch frequency exceeds the threshold within a specified time period. For example, if the equipment type is "excavator" and the frequency threshold is set to 5, any mismatch event that exceeds 5 times in this time period will be marked as overfrequency data. The identification process locates the time and location of the specific mismatch through the association between the node position and the time field, analyzes its frequency fluctuation amplitude, and calculates the frequency at different time points to form a high-frequency mismatch period sequence, reflecting the fluctuation of mismatch events within a specific period. For example, assuming that in certain time periods, the fluctuation amplitude of the mismatch frequency is large and the frequency changes frequently, the period will be considered a high-frequency mismatch period, forming a high-frequency mismatch period sequence. The sequence will serve as the basis for subsequent scheduling and resource allocation, helping to formulate a reasonable resource allocation plan and reduce the interference caused by high-frequency mismatch.

[0124] The priority sorting submodule calls the high-frequency mismatch period sequence, extracts the repeated distribution of equipment types and types of work in the differentiated time periods, evaluates the resource allocation concentration based on the number of allocations, sorts the distribution priorities of the tunnel operation intervals, and generates a resource interference priority sequence;

[0125] Call the high-frequency mismatch time period sequence, which reflects the time periods and frequencies of mismatch events. Extract the repeated distribution amounts of equipment types and work types within the differentiated time periods. The process mainly calculates the repeated use of resources for different equipment and work types in different time periods. For example, if within a certain high-frequency mismatch time period, the excavator and the welding work type frequently overlap in operation, it is considered that the distribution amounts of these two resources are large within this time period. Combine the number of deployment operations to evaluate the concentration of resource deployment. The number of deployment operations is the number of times resource deployment operations occur. By counting the resource deployment frequencies within each time period, it is judged whether resources are overly concentrated in certain time periods. Sort the distribution priorities of the tunnel operation sections. The distribution priority of the operation section refers to sorting different operation time periods according to the resource interference situation, and giving priority to processing the sections with serious resource conflicts. For example, within an operation section, if the operation frequencies of multiple equipment and work types are high and the overlaps are frequent, then the priority of this section is high and it needs to be scheduled first, generating a resource interference priority sequence to provide a clear sorting basis for subsequent resource deployment and optimize resource allocation.

[0126] The time sequence adjustment sub-module extracts the priority equipment types and work types according to the resource interference priority sequence, identifies the operation numbers and time periods, analyzes the deployment overlap rate of the construction section, and adjusts the operation sequence according to the overlap rate, records the adjusted sections and times, and generates a key resource adjustment list for tunnel construction;

[0127] Based on the resource interference priority sequence, extract the equipment types and work types with higher priorities. The equipment types and work types with higher priorities are those at the front end of the resource interference priority sequence, that is, the operation time periods and regions have more serious conflicts. Then identify the operation numbers and their corresponding time periods, and compare the overlap situations of the operation deployments. The deployment overlap rate is the degree of resource conflict between different operations within the same time period. For example, if the excavator and the welding work type are arranged for operation within the same time period and the resource requirements of these two work types are similar, then the overlap rate is high. By analyzing the high or low overlap rate, it is decided whether to adjust the operation sequence to avoid conflicts and interferences. If the overlap rate exceeds the preset threshold (for example, the overlap rate is greater than 50%), then the operation sequence needs to be adjusted to reduce conflicts. Finally, record all the adjusted operation sections and times, and generate a key resource adjustment list for tunnel construction to ensure more efficient resource allocation during the operation process, reduce resource conflicts, and ensure the smooth progress of the construction.

[0128] The above are only the preferred embodiments of the present invention, and do not limit the present invention in other forms. Any person skilled in the relevant art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A real-time tracking system for tunnel construction progress, characterized in that, The system includes: The environmental monitoring module obtains data near the tunnel excavation face, including temperature data, humidity data, soil humidity data, and groundwater level data. After arranging the data in chronological order, it identifies the change range of each data item, marks the data items with amplitudes exceeding the threshold as potential progress interference factors, and generates a list of interference factor changes; The progress collection module extracts the operation time period and completion ratio of the processes within the shield section according to the list of interference factor changes, synchronously compares the real-time progress of the three operations of sectional tunneling, support, and lining, records the operation sections with time lag phenomena, and generates a list of identified operation lags; The anomaly identification module calculates the difference between the equipment operation duration and the operation duration under the standard configuration according to the list of identified operation lags, and combines the real-time states of shield propulsion and initial support operations. If the duration is abnormal, it is marked as an offset section and a set of progress offset marks is generated; The risk assessment module extracts the start-stop records of tunneling equipment, personnel scheduling records, and material distribution records according to the set of progress offset marks, analyzes whether there are progress lags in the three types of resources, counts the number and duration of lags, classifies them into corresponding construction links, and generates a frequency table of node resource mismatches.

2. The real-time tunnel construction progress tracking system according to claim 1, characterized in that, The list of interference factor changes includes data change threshold categories, abnormal data item numbers, data item abnormal levels, and time series marks. The list of identified operation lags includes lag time lengths, lag process identifiers, comparison progress benchmarks, and lag severity levels. The set of progress offset marks includes operation time error intervals, equipment operation deviation degrees, process offset status identifiers, and abnormal duration numbers. The frequency table of node resource mismatches includes resource type mismatch frequencies, construction link mismatch records, lag resource category statistics, and mismatch time period marks.

3. The real-time tunnel construction progress tracking system according to claim 1, characterized in that The environmental monitoring module includes: The data capture sub-module obtains data near the tunnel excavation face, including temperature data, humidity data, soil humidity data, and groundwater level data, arranges them in a unified sequence according to timestamps, combines the data of time periods, and generates a multi-source environmental sequence data set; The amplitude calculation sub-module performs numerical difference operations on the same type of data within consecutive time periods based on the multi-source environmental sequence data set, compares the difference with the environmental index fluctuation threshold, filters out the data time periods exceeding the standard, and generates a data segment of progress impact; The interference identification sub-module matches the corresponding time period of the data with the construction plan timeline of the operation face according to the data segment of progress impact, sets interference marks for the overlapping time periods, summarizes the marked points and the corresponding factor types and frequencies, and generates a list of interference factor changes.

4. The real-time tunnel construction progress tracking system according to claim 3, characterized in that, The progress collection module includes: The operation time period identification sub-module extracts the time, intensity, and impact section information of interference events according to the list of interference factor changes, identifies the process numbers and original planned arrangements of the tunneling, support, and lining operations in the shield section, conducts intersection analysis of the interference time period and the planned time period, filters out the affected operation time periods, and generates a set of affected operation time periods; The completion ratio analysis sub-module calls the operation numbers in the set of affected operation time periods, identifies the real-time progress and the completed quantity of the unit project, analyzes the difference in the completion ratio at the current time node of the operation, and generates a sequence of completion ratio differences for sub-operations; The lag segment judgment sub-module extracts the progress speed and synchronous start time based on the proportion differences of the tunneling, support, and lining processes in the piecemeal operation completion proportion difference sequence, performs offset difference judgment, and uses the formula: Calculate the increment value of the operation segment offset, screen the process bid sections with the increment value of the offset greater than the average value, and generate a list of recognized operation lags; Among them, D represents the increment value of the operation segment offset, Pt, Ps, and Pc are the current completion proportions of the tunneling, support, and lining operations, N is the number of operation nodes of the unit project, E is the event interference intensity, Tt and Ts are the start times of tunneling and support, and Q is the completed quantity of the unit project.

5. The real-time tunnel construction progress tracking system according to claim 4, characterized in that, The abnormal recognition module includes: The operation time offset extraction sub-module extracts the start and end time points of the propulsion section by calling the operation time record and equipment operation data of the lag segment according to the list of recognized operation lags, identifies the corresponding difference between the operation duration and the equipment operation duration, and obtains the operation time difference sequence; The progress lag comparison sub-module calls the operation time difference sequence, combines the standard configured operation duration of each section and the current propulsion footage, extracts the corresponding propulsion state and support state information, and uses the formula: Combined with the progress time window constraint of each section, obtain the progress lag comparison value; Among them, M represents the progress lag comparison value, X i represents the operation duration of the i-th section of equipment, Y i represents the standard operation duration of the i-th section, K i represents the fluctuation range of the propulsion state of the i-th section, V i represents the real-time support rate of the i-th section, S i represents the support section spacing of the i-th section, U i represents the cumulative propulsion amount of the i-th construction day, and n represents the total number of propulsion sections; The progress anomaly marking sub-module identifies the propulsion sections with offset values greater than the construction progress tolerance according to the progress lag comparison value, combines the shield operation trajectory and the construction timeline, marks the sections where there are offsets in the propulsion and support operations, and generates a progress offset marking set.

6. The real-time tunnel construction progress tracking system according to claim 5, wherein The risk assessment module includes: The start-stop retrieval sub-module extracts the start-stop records of the tunneling equipment according to the progress offset marking set, matches the shutdown sections with the equipment operation time sections, screens the operation interruption sections within the offset sections, identifies the total equipment stagnation time, and obtains the tunneling equipment stagnation time value; The scheduling lag identification sub-module calls the tunneling equipment stagnation time value, cross-judges the personnel scheduling shifts and material distribution times with the equipment stagnation sections, counts the lag duration and times of each type of resource, and obtains the personnel and material lag duration frequency quantity; The resource mismatch statistics sub-module classifies and extracts the corresponding lag resource categories of the construction processes according to the personnel and material lag duration frequency quantity, integrates the lag duration and times of the construction nodes, and uses the formula: Calculate the node resource mismatch degree value, form a mismatch frequency sequence according to the construction nodes, and obtain the node resource mismatch frequency table; Among them, ΔG represents the node resource mismatch degree value, λ r is the lag duration of the r-th type of resource, β r is the usage frequency of the r-th type of resource, μ r is the number of lag times of the r-th type of resource, θ r is the number of allocation nodes of the r-th type of resource, ξ r is the lag sensitivity factor of the r-th type of resource, and z represents the total number of resources.

7. The real-time tunnel construction progress tracking system according to claim 1, wherein The system also includes a resource allocation module: The resource allocation module identifies the equipment types and work types with frequencies exceeding the set threshold according to the node resource mismatch frequency table, assigns priorities and adjusts the operation timing sequence, records the modified content of the key resources, and generates a list of key resource adjustments for tunnel construction; The list of key resource adjustments for tunnel construction includes a list of resources to be adjusted first, the adjustment order of key resources, the operation rhythm after adjustment, and the resource configuration optimization mark.

8. The real-time tunnel construction progress tracking system according to claim 7, characterized in that The resource allocation module includes: The frequency identification sub-module extracts the equipment type and work type information according to the node resource mismatch frequency table, screens the over-frequency data based on the resource mismatch frequency threshold, identifies the corresponding node positions and time fields, analyzes the frequency fluctuation range through the time fields, and generates a sequence of high-frequency mismatch time periods; The priority sorting sub-module calls the high-frequency mismatch period sequence, extracts the repeated distribution amounts of equipment types and work types within the differential period, evaluates the resource allocation concentration degree in combination with the allocation times, sorts the distribution priorities of the tunnel operation sections, and generates a resource interference priority sequence; The time sequence adjustment sub-module extracts the priority equipment types and work types according to the resource interference priority sequence, identifies the operation numbers and time periods, analyzes the allocation overlap rate of the construction sections, adjusts the operation sequence according to the overlap rate, records the adjusted sections and times, and generates a key resource adjustment list for tunnel construction.

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