Tunnel process realistic management system based on real-time data acquisition and intelligent analysis

Abstract

The invention discloses a tunnel process realistic management system based on real-time data acquisition and intelligent analysis, and belongs to the technical field of tunnel engineering construction management. Comprising a hardware layer, a data layer and an application layer, all the layers cooperatively achieve real-time realistic management of the tunnel process, and the hardware layer is used for collecting data of the whole process and comprises the steps that an Internet of Things terminal with a GPS and a sensor interface is installed on tunnel construction equipment, and equipment start-stop time, working parameters and position information are collected; the data layer is used for data real-time transmission and structured storage; and the application layer realizes a realistic management function and comprises a real-time realistic panel, an intelligent report generation module, a tracing query function module and a permission and collaborative management module. According to the invention, multi-terminal cooperative acquisition of "UWB positioning card + equipment + material" is adopted, and through accurate binding of space positioning and time nodes, process data is upgraded from "manual recording" to "space-time linkage realistic", and the problem that traditional equipment is difficult to accurately associate personnel and processes is solved.

Description

Technical Field

[0001] This invention relates to the field of tunnel engineering construction management technology, and more specifically, to a tunnel process real-time management system based on real-time data acquisition and intelligent analysis. Background Technology

[0002] Tunnel construction involves numerous and closely interconnected procedures, and its management efficiency directly impacts project progress, quality, and cost control. Traditional tunnel procedure management relies primarily on manual records (such as construction logs and paper reports) and post-construction statistics, which presents the following significant problems: Data lag: Information such as process start time, duration, and resource input needs to be manually compiled before it can be fed back to the management end, with a lag time often exceeding 24 hours, making dynamic adjustment difficult; Subjectivity in recording: Manual recording is susceptible to fatigue and negligence, resulting in data omissions (such as failure to indicate the reason for temporary work stoppages) and errors (such as deviations in the estimation of material consumption), leading to low data reliability; Insufficient coordination: Progress data for excavation, support, monitoring and other processes are scattered across various construction teams, lacking a unified real-time sharing platform, which can easily lead to a disconnect in process coordination (such as support equipment failing to be in place in advance according to the excavation schedule). Poor traceability: When quality or safety issues arise, it is necessary to review a large number of paper records to trace the related process parameters, which is time-consuming and makes it difficult to locate the root cause.

[0003] While publicly available construction management systems have achieved partial data digitization, they focus only on schedule management and do not cover detailed data such as real-time resource consumption and personnel operation behavior required for process documentation, thus failing to meet the needs of full-process process documentation management. Therefore, we propose a tunnel process documentation management system based on real-time data acquisition and intelligent analysis. Summary of the Invention

[0004] The purpose of this invention is to provide a tunnel process realistic management system based on real-time data acquisition and intelligent analysis to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A tunnel construction process real-time management system based on real-time data acquisition and intelligent analysis includes a hardware layer, a data layer, and an application layer. These layers work together to achieve real-time real-time management of tunnel construction processes. The hardware layer is used for data acquisition throughout the entire process, including: installing IoT terminals with GPS and sensor interfaces on tunnel construction equipment to collect equipment start-up and shutdown times, working parameters, and location information; equipping construction personnel with UWB positioning cards and deploying UWB base stations in the tunnel to achieve precise positioning of personnel at the work site and automatic association with the process through real-time communication between the two; and deploying high-definition cameras at the work sites of each process to assist in verifying the completion status of the process. The data layer is used for real-time data transmission and structured storage, including: transmitting hardware layer data to the server through a hybrid transmission network; prioritizing the transmission of key process data at the millisecond level; and transmitting UWB positioning data through a separate low-latency channel to ensure synchronization with process node time. The received data is structured in the format of "process ID - timestamp - resource type - parameter value" and associated with UWB positioning coordinates to form a three-dimensional work surface map, showing the spatial distribution and time flow of the process. The application layer implements real-time management functions, including a real-time data visualization panel, intelligent report generation, traceability query function, and a permission and collaboration management module. The real-time data visualization panel displays the real-time status of the process, including progress and exception data. The intelligent report generation module automatically generates process data reports according to preset cycles. The traceability query function supports multi-dimensional retrieval of historical process data. The permission and collaboration management module assigns differentiated permissions to different roles, pushes reminders to subsequent responsible persons and shares key data when a process is completed.

[0006] Preferably, in the hardware layer, the UWB base stations are deployed at intervals of 600 meters in the tunnel, and the positioning accuracy achieved by the UWB positioning card in conjunction with the UWB base station is less than or equal to 30cm.

[0007] Preferably, in the hardware layer, the specific method for using a high-definition camera to assist in verifying the completion status of the process is as follows: using image recognition technology to identify key completion indicators of the process, such as whether the arch frame installation meets the specifications and whether the excavation section meets the standards.

[0008] Preferably, the hybrid transmission network in the data layer is a "4G / 5G + industrial bus" hybrid network; the key process includes blasting operations, and the low-latency transmission channel of UWB positioning data can ensure that the time difference between the positioning information and the process node record is less than or equal to 1 second.

[0009] Preferably, in the real-time progress display panel of the application layer, the progress display includes the name of the currently ongoing process, the duration of the process, and the estimated completion time based on historical data; the anomaly display includes automatically marked process disconnection (the disconnection time between two adjacent processes exceeds X minutes), timed-out processes (process time exceeds the standard duration by 150%), and support processes that are not carried out in a timely manner, where X is the preset maximum allowable interval time for process connection (configured according to the tunnel construction process).

[0010] Preferably, the application layer's intelligent report generation module has preset cycles including daily, weekly, and monthly periods; the process record report includes process efficiency analysis comparing the average excavation progress of each shift, and statistics on abnormal events, including the classification and percentage statistics of reasons for work stoppages.

[0011] Preferably, the traceability query function of the application layer supports retrieval dimensions including time, process type, personnel, and equipment. After the retrieval conditions are entered, the system can display the process parameters and related process data under the corresponding conditions. The process parameters include excavation progress and information of the personnel involved, and the related process data includes support data associated with the excavation process.

[0012] Preferably, in the application layer's permission and collaboration management module, the differentiated permissions for different roles are as follows: team leaders can only view the process data for the work processes they are responsible for, project managers can view the summary information of all tunnel processes, and supervisors can view the quality-related data for each process; the reminder push when a process is completed is implemented based on the responsible person's account bound to the UWB positioning card, and the shared key data includes the geological data and construction dimension data corresponding to the process.

[0013] Preferably, when the 4G / 5G signal is weak in the tunnel, the hybrid transmission network of the data layer is replaced by a "LoRa wireless self-organizing network + fiber optic repeater" network. The coverage distance of this replacement network can reach 5 kilometers, and the transmission rate is 1Mbps.

[0014] Preferably, when the deployment cost of UWB base stations is too high, the hardware layer UWB positioning card and UWB base station are replaced with a Bluetooth beacon positioning combination, which has a positioning accuracy of 1-2 meters; when the image recognition accuracy of the high-definition camera is reduced due to dust, a laser profilometer is added to the process operation surface to assist in measuring the process dimensions, with the measurement accuracy maintained at ±5mm.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) This invention adopts a multi-terminal collaborative acquisition of “UWB positioning card + equipment + materials”. Through the precise binding of spatial positioning and time nodes, the process data is upgraded from “manual recording” to “spatiotemporal linkage and realism”. The real-time performance and spatial correlation of the data are improved to the leading level in the industry. The UWB positioning card not only meets the needs of personnel location tracking, but also undertakes the function of process node recording. The positioning accuracy is within 30cm, which solves the problem that traditional equipment is difficult to accurately associate personnel with processes. A process data association model is constructed to realize the full-process data penetration query of “excavation-support-monitoring”. The problem traceability time is shortened from 2 days to 10 minutes. Built-in intelligent early warning rules (such as disconnection warning, failure to support in time, abnormal process operation time) actively identify management loopholes and reduce the cost of manual intervention.

[0016] (2) Through real-time transmission of “4G / 5G+industrial bus” and spatiotemporal binding with UWB, process data has changed from “manual summarization with a 24-hour delay” to “synchronization within 1 hour at the management end”. Information such as equipment failure and process disconnection can be pushed in real time. Automated collection combined with spatial verification of UWB positioning reduces the data error rate from the traditional 15% to less than 3%. By optimizing equipment and personnel scheduling through resource real-world analysis, the cost loss caused by process disconnection and poor scheduling can be reduced. Two operations in a 1km tunnel can save potential cost losses. Full-process data archiving and correlation analysis enable the accuracy of quality problem traceability to reach 95%, providing a reliable basis for responsibility identification and process improvement. Attached Figure Description

[0017] Figure 1 This is a diagram showing the overall architecture of the system of the present invention; Figure 2 This is a flowchart illustrating the data acquisition and workflow of the processes described in this invention. Figure 3 This is a schematic diagram of the real-time realistic panel interface of the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0019] Example: Please see Figure 1-3 This paper presents a tunnel process real-time management system based on real-time data acquisition and intelligent analysis. The system comprises a hardware layer, a data layer, and an application layer. The hardware layer, acting as the "sensing terminal" for data acquisition, directly addresses the core pain points of traditional tunnel management, such as "lagging data acquisition, large subjective errors, disconnect between personnel and processes, and inefficient quality verification." The data layer undertakes the core function of "data transmission and structured storage," solving the problems of "lagging data transmission, chaotic storage, and lack of spatiotemporal correlation" in traditional management. The application layer, acting as the "management decision-making center," transforms the acquired structured data into management value, solving the inefficiencies of traditional systems where "decision-making relies on experience, reports rely on manual labor, traceability relies on retrieval, and collaboration relies on verbal communication." The collaboration of all levels enables real-time real-time management of tunnel processes. The hardware layer is used for data acquisition throughout the entire process, including: installing IoT terminals (including GPS modules and sensor interfaces) with GPS and sensor interfaces on tunnel construction equipment (excavators, shotcrete machines, etc.) to collect equipment start-up and shutdown times, working parameters (such as shotcrete pressure) and location information; equipping construction personnel (team leaders, operators) with UWB positioning cards and deploying UWB base stations in the tunnel to achieve precise positioning of personnel at the work site and automatic association with the process through real-time communication between the two; and deploying high-definition cameras at the work sites of each process to assist in verifying the completion status of the process.

[0020] Specifically, at the hardware layer, UWB base stations are deployed at 600-meter intervals within the tunnel, and the positioning accuracy achieved by the UWB positioning card in conjunction with the UWB base station is less than or equal to 30cm. By deploying UWB base stations every 600 meters within the tunnel, real-time communication between the base station and the positioning card accurately locates the work surface where personnel are working, achieving automatic association between personnel and work processes. The specific method for using high-definition cameras to assist in verifying the completion status of work processes involves using image recognition technology to identify key completion indicators such as whether the arch frame installation meets specifications and whether the excavation cross-section meets standards. High-definition cameras are deployed at each work surface to assist in verifying the completion status of work processes (such as whether the arch frame installation meets specifications) through image recognition.

[0021] The data layer is used for real-time data transmission and structured storage, including: transmitting hardware layer data to the server through a hybrid transmission network; prioritizing the transmission of key process data at the millisecond level; and transmitting UWB positioning data through a separate low-latency channel to ensure synchronization with process node time. The received data is structured in the format of "process ID - timestamp - resource type - parameter value" and associated with UWB positioning coordinates to form a three-dimensional work surface map, which displays the spatial distribution and time flow of the process.

[0022] Specifically, the hybrid transmission network in the data layer is a "4G / 5G + industrial bus" hybrid network; key processes include blasting operations, and the low-latency transmission channel of UWB positioning data ensures that the time difference between positioning information and process node records is less than or equal to 1 second. The acquisition terminal transmits data to the system server through the "4G / 5G + industrial bus" hybrid network, where data for key processes (such as blasting operations) adopts a millisecond-level priority transmission mechanism; UWB positioning data, because it needs to be associated with process locations in real time, adopts a separate low-latency transmission channel to ensure the time synchronization between positioning and process node records; the server performs structured processing on the data: storing it in the format of "process ID - timestamp - resource type - parameter value" (e.g., "excavation process - 08:30 - excavator - machine time: 2h"), and associating it with the 3D work surface map formed by UWB positioning coordinates, intuitively displaying the spatial distribution and time flow of each process.

[0023] The application layer implements real-time management functions, including a real-time data visualization panel, intelligent report generation, traceability query function, and a permission and collaboration management module. The real-time data visualization panel displays the real-time status of the process, including progress and exception data. The intelligent report generation module automatically generates process data reports according to preset cycles. The traceability query function supports multi-dimensional retrieval of historical process data. The permission and collaboration management module assigns differentiated permissions to different roles, pushes reminders to subsequent responsible persons and shares key data when a process is completed.

[0024] In this application, the real-time progress display panel in the application layer includes the name of the currently ongoing process, its duration, and the estimated completion time based on historical data; the anomaly display includes automatically marked process disconnections (the disconnection time between two adjacent processes exceeds X minutes), time-out processes (process time exceeds 150% of the standard duration), and support processes that are not carried out in a timely manner, where X is the preset maximum allowable interval time for process connection (configured according to the tunnel construction process).

[0025] In this application, the application layer's intelligent report generation module has preset cycles including daily, weekly, and monthly periods; the process record report includes process efficiency analysis comparing the average excavation progress of each shift, and abnormal event statistics on the classification and percentage of reasons for work stoppages.

[0026] In this application, the traceability query function of the application layer supports retrieval dimensions including time, process type, personnel, and equipment. After entering the retrieval conditions, the system can display the process parameters and related process data under the corresponding conditions. The process parameters include excavation progress and information of the personnel involved, and the related process data includes support data associated with the excavation process.

[0027] Specifically, the real-time display panel allows the management system to view the real-time status of each process, including: Progress tracking: Name of the currently ongoing process, duration, and estimated completion time (based on historical data). Abnormalities described: Process disconnect (disconnection time between two adjacent processes exceeds X minutes), automatically marked timed-out processes (e.g., support time exceeds 150% of standard duration), failure to provide timely support. Intelligent report generation: Automatically generates daily / weekly / monthly process report details, including: Process efficiency analysis (such as comparison of average excavation progress of each shift); Statistics on abnormal events (such as the classification and percentage of reasons for work stoppages).

[0028] Traceability query function: Supports searching historical data by multiple dimensions such as "time, process type, personnel, and equipment". For example, entering "excavation process on May 10, 2024" can display all parameters of the excavation on that day (expansion, personnel involved) and related support data.

[0029] In this application, the differentiated permissions for different roles in the application layer's permission and collaboration management module are as follows: team leaders can only view the process data they are responsible for, project managers can view the summary information of all tunnel processes, and supervisors can view the quality-related data for each process; the reminder push when a process is completed is implemented based on the responsible person's account bound to the UWB positioning card, and the shared key data includes the geological data and construction dimension data corresponding to the process.

[0030] Specifically, permissions and collaborative management Different permissions are assigned to different roles (project manager, team leader, supervisor). For example, team leaders can only view the process data of the process they are responsible for, while project managers can view the summary information of all tunnel processes. When a certain process is completed, the system automatically sends a reminder (such as "K1+200 section excavation completed, please prepare support equipment") to the person in charge of the subsequent process (via the account bound to the UWB positioning card), and simultaneously shares key data such as geology and dimensions of that process.

[0031] In one possible implementation, network replacement is used: when 4G / 5G signals are weak within the tunnel, the hybrid data layer transmission network is replaced with a "LoRa wireless self-organizing network + fiber optic repeater" network. This replacement network has a coverage distance of up to 5 kilometers and a transmission rate of 1 Mbps. Traditional systems experience data transmission interruptions in weak signal environments, leading to management disconnection. This solution ensures stable data transmission throughout the entire long tunnel, while balancing the rate and priority of critical data by "reducing the sampling frequency of non-critical data," ensuring the system can still operate normally in long tunnel scenarios.

[0032] Positioning Alternative: When the deployment cost of UWB base stations is too high, the hardware-layer UWB positioning card and UWB base station can be replaced with a Bluetooth beacon positioning combination. This combination provides a positioning accuracy of 1-2 meters. When UWB base station costs are too high, replacing them with Bluetooth beacons with a positioning accuracy of 1-2 meters reduces equipment costs by 50%, making it suitable for scenarios with low positioning accuracy requirements, such as shallow-buried tunnels (depth ≤ 50m). Traditional systems that only support UWB may be too costly for small and medium-sized projects to implement. This solution balances cost-effectiveness and scenario adaptability, expanding the system's application scope.

[0033] Alternative Recognition: When the image recognition accuracy of a high-definition camera decreases due to dust, a laser profilometer is added to the work surface to assist in measuring process dimensions, maintaining a measurement accuracy of ±5mm. When a high-definition camera is affected by dust, the addition of a laser profilometer with a measurement accuracy of ±5mm assists in detecting process dimensions (such as excavation cross-sections). Traditionally, relying solely on cameras reduces recognition accuracy to below 50% in high-dust environments, easily leading to misjudgments of quality. This solution maintains quality verification accuracy above 98% in complex environments, avoiding a reduction in management standards due to environmental factors.

[0034] I. Implementation Details at Each Level of the System (I) Hardware Layer: Deployment and Calibration of Data Acquisition Terminals for the Entire Process The hardware layer is used for data acquisition throughout the entire process. The selection, installation, and calibration methods for core equipment are as follows: IoT terminals for construction equipment Install IoT terminals (model EC200S) with GPS modules (model UBLOX NEO-7M, static positioning accuracy ≤1m, dynamic positioning accuracy ≤3m, data sampling frequency 1 time / 30 seconds) and CAN bus interfaces on equipment such as excavators (model PC360) and shotcrete machines (model TK961). Collect key parameters of the equipment through the CAN bus: for excavators, collect "bucket oil pressure (0~35MPa) and working time", and for shotcrete machines, collect "concrete pressure (0.8~1.2MPa) and spraying volume (5~10m³ / h)". At the same time, record the real-time position of the equipment (accuracy ±2m) through the GPS module.

[0035] UWB positioning system Twelve core personnel, including team leaders and operators, were equipped with UWB positioning cards (model DW1000, 72-hour battery life). One UWB base station (model DWM1001) was deployed every 600 meters along the tunnel. After deployment, a calibration point was set every 300 meters using a laser rangefinder (accuracy ±1mm). The base station coordinates were entered to complete the calibration, ensuring that the positioning accuracy was ≤30cm.

[0036] Automatic personnel and process association logic: When the UWB positioning card detects that personnel have entered the "DK21+160 working face" area (radius 5m, defined by base station coordinates), and the excavator in this area sends a "start signal", the system automatically binds the personnel account to the "excavation process (ID: K1+200 - excavation - 20240510-01)" with the ID encoding rule being "station number - process type - date - work group number".

[0037] Visual and auxiliary measurement equipment High-definition cameras (model DS-2CD3T46WD-I5, resolution 1920×1080, frame rate 25fps, downward angle 45°) are installed 3m directly above the work surface of each process. The completion status of the process is verified by image recognition technology: when identifying the arch frame installation, the standard is "spacing error ≤5cm" and "vertical deviation ≤3°" (based on the "Technical Specification for Highway Tunnel Construction" JTG / T 3660-2020). The edge detection algorithm is used to compare the arch frame outline with the design model. When the dust concentration at the work surface is ≥15mg / m³ (detected in real time by a dust sensor (model GCG1000)) and the camera recognition rate is less than 70%, a laser profilometer (model LJ-V7020) is added 2m to the side of the work surface. The measurement range is 0.5~10m, the sampling frequency is 1 time / 2 minutes, and the laser profilometer is installed to assist in detecting the excavation cross-section size (accuracy ±5mm). The data is fused with the camera data to determine the quality of the process.

[0038] (II) Data Layer: Real-time Transmission and Structured Storage Implementation Hybrid transport network deployment A hybrid network of "4G / 5G + industrial bus (PROFINET protocol, transmission rate 100Mbps)" is adopted: In areas with good signal within 500m of the tunnel entrance, equipment data is transmitted via 4G / 5G (latency ≤50ms); in areas with signal attenuation inside the tunnel (below -90dBm), transmission switches to industrial bus. Specifically, data from critical processes such as blasting operations triggers an "emergency transmission flag," and the server prioritizes allocating 50% of the bandwidth to achieve millisecond-level transmission (latency ≤100ms); UWB positioning data uses a separate low-latency channel (based on UDP protocol) to ensure that the time difference between positioning information and process node records is ≤1 second.

[0039] If the tunnel length is ≥5km (e.g., a super long tunnel is 6km long), and the 4G / 5G signal coverage is insufficient, replace it with a "LoRa wireless self-organizing network + fiber optic repeater" network: deploy one LoRa gateway every 1km (transmission rate 1Mbps), connect the fiber optic repeater in series with the gateway, transmit data in 512-byte / packet packets, and retransmit 3 times; reduce the sampling frequency of non-critical data (e.g., daily personnel positioning) from once / 30 seconds to once / 2 minutes, prioritizing the real-time data of critical processes.

[0040] Structured storage and 3D mapping After receiving the data, the server stores it in a structured format of "Process ID - Timestamp - Resource Type - Parameter Value", for example, "K1+200 - Excavation - 20240510 08:30 - Excavator - Machine Hours: 2h; Cut: 1.2m". Simultaneously, it associates the UWB positioning coordinates (X / Y / Z axes, accuracy 10cm) with the BIM model (based on Revit to create 3D tunnel components) to form a 3D work surface map (as shown in Figure 1): "In-process processes" are marked in blue, "Overdue processes" in red, and "Completed processes" in green, visually displaying the spatial distribution of each process (e.g., the coverage area of ​​the DK21+160 face excavation process) and the time flow (e.g., 08:30-10:30, lasting 2 hours).

[0041] (III) Application Layer: Realistic Management Function Implementation Real-time realistic panel The management panel (as shown in Figure 3) is displayed as follows: Progress report: The current process "DK21+160 excavation" (has been ongoing for 2 hours), based on historical data (average advance of 1.2m / h for Class II surrounding rock excavation in the past 7 days), is predicted to be completed in 1 hour; Abnormal Reality: Automatically mark "DK21+150 Support Procedure Timeout" (standard duration 4 hours, actual duration 6 hours, exceeding 150%) and "DK21+140 Excavation-Support Disconnection" (Class V surrounding rock section preset X=30 minutes, disconnection has lasted 45 minutes), triggering graded warnings: 10% timeout pushes to the team leader (system pop-up), 30% timeout simultaneously pushes to the project manager (SMS + pop-up); for untimely support procedures (such as support not being started 30 minutes after excavation), automatically associate the geological data of the area (Class V surrounding rock, poor stability) and push it to the supervision terminal.

[0042] Intelligent Reports and Traceability Queries The intelligent report generation module automatically generates reports daily, weekly, and monthly: the daily report shows "Team A's average excavation progress is 1.1m / h, Team B's is 1.3m / h" (process efficiency analysis) and "Among the reasons for downtime, 'equipment failure' accounts for 30%, and 'material shortage' accounts for 20%" (abnormal event statistics); the weekly / monthly reports overlay data from multiple days to analyze process efficiency trends (such as a steady increase of 5% in excavation progress over the past 4 weeks).

[0043] The traceability query supports multi-dimensional retrieval: Enter "20240510 Excavation process" and the system will display all excavation parameters for the day (DK21+160 advance 1.2m, 5 participants: Zhang San (operator), Li Si (team leader)) and related support data (DK21+160 support concrete usage 8m³, pressure 1.0MPa), with a traceability time of ≤10 minutes.

[0044] Access Control and Collaboration Management Differentiated access control: Team leaders can only view the process data of "DK21+150~DK21+200" under the responsibility of their team (team A), project managers can view the summary data of the entire tunnel (DK20+403~DK25+210), and supervisors can view the quality data of each process (such as arch frame installation deviation and concrete strength).

[0045] Work process coordination: When “DK21+160 excavation” is completed (equipment stop signal + personnel leave the work face), the system pushes a reminder to the account (support manager Wang Wu) bound to the UWB positioning card: “K1+200 section excavation completed, please prepare support equipment”, and synchronously shares the geological data of this section (Class II surrounding rock, rock stratum dip angle 15°) and excavation dimensions (section width 12m, height 8m).

[0046] II. Case Studies of Technical Effect Verification Using a 1km double-track tunnel (30% of the surrounding rock is Class V and 70% is Class II) with two working faces as the implementation target, the effectiveness of traditional management and this system is compared: Improved management efficiency In traditional management, the average waiting time for the "excavation-support" connection is 4.5 hours. This system reduces it to 3.1 hours (a reduction of 31%) through real-time collaborative reminders; the management decision response time is reduced from 24 hours to 55 minutes (e.g., equipment failure data is uploaded in real time, and scheduling is completed within 1 hour).

[0047] Improved data credibility Selecting the DK21+150~DK21+200 segment, the traditional manual recording of "excavator hours" had an error rate of 16.2% (actually 2 hours recorded as 1.7h or 2.3h). After automated data acquisition and UWB spatial verification, the error rate of this system was 2.8% (less than 3%). A comparison of three sets of continuous construction day data is shown in Table 1. Table 1 Comparison of data from consecutive construction days III. Implementation of Alternative Solutions Location-based alternatives (Bluetooth beacons) If the deployment cost of UWB base stations is too high (8,000 yuan per unit), Bluetooth beacons (3,800 yuan per unit, a 52% cost reduction) can be used in shallow tunnels (depth ≤ 50m, positioning accuracy requirement 1-2m): one Bluetooth beacon is deployed every 100 meters, no calibration is required, and the location of personnel (such as "face / invert arch area") is located through "beacon signal strength (RSSI)", which meets the needs of non-high-precision scenarios.

[0048] Alternative measurement method (laser profilometer) When the dust concentration at the work site is ≥15mg / m³, the laser profilometer and the high-definition camera work together: the profilometer detects the width of the excavation section as "12.1m (design 12m, deviation 0.1m, meets the standard)", and the camera identifies the arch frame as "4.9m (design 5m, deviation 0.1m, meets the standard)". The data from both are merged to determine the process is qualified, avoiding the identification error of a single device.

[0049] IV. System Deployment and Debugging Deployment steps ① Hardware installation: First, deploy UWB base stations (1 unit every 600m) and fiber optic repeaters along the tunnel mileage, then install IoT terminals (CAN bus interface) on the equipment, and finally fix the camera (3m directly above the working face) and the laser profilometer (2m to the side). ② Data Interconnection: The device terminal is networked with the server via the PROFINET protocol, and the UWB positioning card is bound to the personnel account (e.g., Zhang San - Operator - Team A). ③ Parameter calibration: Use a laser rangefinder to calibrate the coordinates of the UWB base station (ensure positioning accuracy ≤30cm), and adjust the camera recognition threshold (arch spacing deviation ≤5cm triggers pass / fail judgment); ④ Trial run: Select the test section from DK21+150 to DK21+250 to simulate the "excavation-slag removal-support" process, verify the data acquisition (excavator time, personnel positioning) and early warning (reminder triggered after 30 minutes of disconnection) functions, and officially go online after 72 hours of trial run without any abnormalities.

[0050] Common Problem Solving UWB positioning drift: Increase base station density (from 600m / unit to 400m / unit), or add aluminum foil anti-interference shielding layer to metal structures such as steel supports, and the drift amount will be reduced from 15cm to 5cm; Data transmission interruption: The industrial bus and LoRa network are redundantly backed up, and automatic switching occurs during interruption (switching time ≤ 3 seconds) to ensure no data loss.

[0051] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A tunnel process realistic management system based on real-time data acquisition and intelligent analysis, characterized in that, Including the hardware layer, data layer, and application layer, each layer works together to achieve real-time, realistic management of tunnel construction processes. The hardware layer is used for data acquisition throughout the entire process, including: installing IoT terminals with GPS and sensor interfaces on tunnel construction equipment to collect equipment start-up and shutdown times, working parameters, and location information; equipping construction personnel with UWB positioning cards and deploying UWB base stations in the tunnel to achieve precise positioning of personnel at the work site and automatic association with the process through real-time communication between the two; and deploying high-definition cameras at the work sites of each process to assist in verifying the completion status of the process. The data layer is used for real-time data transmission and structured storage, including: transmitting hardware layer data to the server through a hybrid transmission network; prioritizing the transmission of key process data at the millisecond level; transmitting UWB positioning data through a separate low-latency channel to ensure synchronization with process node time; and processing the received data in a structured format of "process ID - timestamp - resource type - parameter value" and associating it with UWB positioning coordinates to form a three-dimensional work surface map, displaying the spatial distribution and time flow of the process. The application layer implements real-time management functions, including a real-time real-time dashboard, intelligent report generation, traceability query function, and a permission and collaboration management module. The real-time real-time dashboard displays the real-time status of the process, including progress and exception data. The intelligent report generation module automatically generates process real-time reports according to a preset cycle. The traceability query function supports multi-dimensional retrieval of historical process data. The permission and collaboration management module assigns differentiated permissions to different roles, pushes reminders to subsequent responsible persons and shares key data when a process is completed.

2. The tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: In the hardware layer, the UWB base stations are deployed at intervals of 600 meters in the tunnel, and the positioning accuracy achieved by the UWB positioning card in conjunction with the UWB base station is less than or equal to 30cm.

3. The tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: In the hardware layer, the specific method for using high-definition cameras to assist in verifying the completion status of the process is as follows: key completion indicators of the process, such as whether the arch frame installation meets the specifications and whether the excavation section meets the standards, are identified through image recognition technology.

4. The tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: The hybrid transmission network in the data layer is a "4G / 5G + industrial bus" hybrid network; the key process includes blasting operations, and the low-latency transmission channel of the UWB positioning data can ensure that the time difference between the positioning information and the process node record is less than or equal to 1 second.

5. The tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: In the real-time simulation panel of the application layer, the progress simulation displays the name of the currently ongoing process, its duration, and the estimated completion time based on historical data; the anomaly simulation includes automatically marked process disconnections, time-out processes, and support processes that have not been performed in a timely manner.

6. The tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: The application layer's intelligent report generation module has preset cycles including daily, weekly, and monthly periods; the process record report includes process efficiency analysis comparing the average excavation progress of each shift, and statistics on abnormal events, including the classification and percentage statistics of reasons for work stoppages.

7. The tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: The traceability query function of the application layer supports retrieval dimensions including time, process type, personnel, and equipment. After inputting retrieval conditions, the system can display the process parameters and related process data under the corresponding conditions. The process parameters include excavation progress and information of the personnel involved, and the related process data includes support data associated with the excavation process.

8. The tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: In the application layer's permission and collaboration management module, the differentiated permissions for different roles are as follows: team leaders can only view the process data they are responsible for, project managers can view the summary information of all tunnel processes, and supervisors can view the quality-related data of each process; the reminder push when a process is completed is implemented based on the responsible person's account bound to the UWB positioning card, and the shared key data includes the geological data and construction dimension data corresponding to the process.

9. A tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: When the 4G / 5G signal is weak inside the tunnel, the hybrid transmission network of the data layer is replaced by a "LoRa wireless self-organizing network + fiber optic repeater" network. This replacement network has a coverage distance of up to 5 kilometers and a transmission rate of 1Mbps.

10. A tunnel process realistic management system based on real-time data acquisition and intelligent analysis according to claim 1, characterized in that: When the deployment cost of UWB base stations is too high, the UWB positioning card and UWB base station in the hardware layer are replaced with a Bluetooth beacon positioning combination, which has a positioning accuracy of 1-2 meters. When the image recognition accuracy of the high-definition camera is reduced due to dust, a laser profilometer is added to the process operation surface to assist in measuring the process dimensions, with the measurement accuracy maintained at ±5mm.

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