Tunnel second lining concrete pouring vault anti-disengaging sound-light alarm system

Abstract

The invention specifically relates to an anti-void sound-light alarm system for a tunnel secondary lining concrete pouring vault, and relates to the technical field of tunnel engineering construction monitoring. A data transmission module; an intelligent processing module; an alarm execution module; and an energy supply module. According to the invention, by means of the multi-dimensional data sensing module, various sensors such as a pressure sensor, a flow sensor and a liquid level sensor are comprehensively used, so that all-directional real-time monitoring of the concrete pouring process is realized; the patch pressure sensor can accurately capture the arrival position of concrete, the template pressure strain gauge can monitor the pouring pressure, and the quality problem caused by overpressure or underpressure is avoided; the concrete flow meter is matched with the three-dimensional laser scanner, and the pouring volume deviation is accurately calculated; the ultrasonic flow measurement water sensor can timely find out concrete disintegration or blockage and other abnormalities; and a liquid level area is accurately extracted by combining an optical flow analysis algorithm of the intelligent processing module, the concrete plumpness is accurately evaluated, and the vault void risk is effectively reduced.

Description

Technical Field

[0001] The invention relates to the technical field of tunnel engineering construction monitoring, in particular to an anti-cavitation sound and light alarm system for a tunnel secondary lining concrete pouring arch. Background Art

[0002] In tunnel construction, the quality of secondary lining ("secondary lining") concrete pouring directly affects the durability and safety of the tunnel structure. Vault voids are one of the most common quality hazards. Traditional construction methods rely primarily on experience-based judgment or post-construction testing (such as radar scanning), which presents significant technical flaws:

[0003] Existing liquid level recognition methods often rely on single-point pressure sensors or manual observation, which are not suitable for the complex curved surfaces of tunnel vaults in three-dimensional pouring scenarios. Traditional semantic segmentation algorithms have an accuracy rate of less than 60% for concrete level recognition in tunnel environments with strong dust and backlighting. This accuracy is particularly prone to misjudgment due to dynamic liquid level changes caused by concrete flow.

[0004] Traditional monitoring systems often rely on a single sensor (such as a pressure sensor) to operate independently, without establishing a collaborative analysis model for multiple parameters such as pressure, flow, and temperature. In one tunnel project, relying solely on pressure sensors resulted in a high false alarm rate due to pressure fluctuations caused by concrete segregation, without integrating flow data for cross-validation.

[0005] In traditional construction, treatment plans rely on engineers' experience and lack quantitative analysis tools. For example, after a tunnel project discovered a potential void, the lack of a digital twin model meant that the effectiveness of different treatment options (such as increased vibration or adjustments to the mix ratio) could not be pre-evaluated.

[0006] Therefore, a tunnel secondary lining concrete pouring arch anti-airing sound and light alarm system is needed to deal with the above-mentioned problems. Summary of the Invention

[0007] The purpose of the present invention is to solve the above problems and to propose an anti-cavitation sound and light alarm system for the tunnel secondary lining concrete pouring arch.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] The tunnel secondary lining concrete pouring arch anti-airing sound and light alarm system includes:

[0010] The multi-dimensional data perception module is configured to collect key data from the concrete pouring process in real time through a variety of sensors, providing an accurate information basis for system operation;

[0011] The data transmission module is configured to use signal conditioning, wireless transmission network and data relay processing technology to stably and quickly transmit the sensing data to the processing center;

[0012] The intelligent processing module is configured to conduct in-depth analysis of the transmitted data to achieve dynamic liquid level recognition, threshold judgment prediction, and digital twin deduction;

[0013] The alarm execution module is configured to respond promptly to abnormal situations through on-site sound and light alarms and remote collaborative control;

[0014] The energy supply module is configured to provide support in terms of power supply, equipment protection, human-computer interaction and system integration.

[0015] Preferably, the multi-dimensional data perception module specifically includes:

[0016] The patch pressure sensors are arranged longitudinally and orderly along the center line of the tunnel vault and installed in the gap between the plug template and the waterproof board;

[0017] The sensor and the external indicator light are connected by copper foil tape to form a pathway, and the indicator light color will quickly change from the initial red to green;

[0018] When the concrete pouring pressure acts on the formwork, the resistance value of the strain gauge changes accordingly, and the resistance change is converted into a voltage signal output through the Wheatstone bridge;

[0019] The concrete flow meter is installed at the key position of the concrete delivery pipeline. It uses the electromagnetic induction or ultrasonic measurement principle to accurately measure the concrete flow through the pipeline per unit time and calculate the actual pouring volume.

[0020] The ultrasonic flow sensor is installed on the outside of the trolley near the concrete delivery pipe outlet. It measures the concrete flow velocity by transmitting and receiving ultrasonic signals and using the Doppler effect.

[0021] In addition to estimating the volume of grouting, the 3D laser scanner can also monitor changes in the tunnel lining profile in real time, providing a basis for construction quality assessment.

[0022] Preferably, the data transmission module specifically includes:

[0023] The weak analog signal output by the pressure sensor and the voltage or resistance signal output by the temperature sensor are connected to the signal conditioning circuit to remove high-frequency noise and power frequency interference in the signal and improve the signal-to-noise ratio;

[0024] The analog signal is converted into a digital signal through an analog-to-digital conversion chip.

[0025] Preferably, the intelligent processing module specifically includes:

[0026] The concrete pouring video captured by the surveillance camera is processed using an optical flow dynamic analysis algorithm. Based on the motion information of pixels between adjacent video frames, the optical flow field is calculated to accurately extract the image of the concrete surface area.

[0027] The optical flow analysis results are fused with the pressure, flow, and temperature sensor data; the Kalman filter algorithm is used to optimally estimate multi-source data; cluster analysis is performed on the fused data, dividing it into different categories based on different data characteristics, evaluating the concrete fullness and determining whether the pouring status is normal.

[0028] Preferably, the method further includes:

[0029] For the pixels in the video sequence , the brightness at time t is , at the moment Move to , the brightness is ;

[0030] According to the constant brightness assumption: ;

[0031] Taylor expand the right side of the equation and ignore higher-order infinitesimals: ;

[0032] Substituting the constant brightness assumption and sorting it out, we get: ;

[0033] in ; are the velocity components of the pixel in the x and y directions respectively; 、 and are the gradient of the image in the x and y directions and the rate of change over time respectively;

[0034] Formulate an overdetermined system of equations and solve it using least squares methods: ;

[0035] The solution is: ;

[0036] Where A is a matrix consisting of the gradients of all pixels in the window, and b is a vector consisting of the time change rates of all pixels in the window.

[0037] Preferably, the method further includes:

[0038] For concrete pouring status monitoring, the state vector is defined to include key parameters such as liquid level, pouring speed, and pressure;

[0039] The concrete pouring state estimation is obtained through Kalman filter prediction.

[0040] Preferably, cluster analysis is performed on the fused data, clustering is performed based on the density of data points, and clusters of arbitrary shapes are discovered;

[0041] Density is defined by neighborhood radius and minimum number of points. For each point in the dataset, if its neighborhood radius contains at least the minimum number of points, then the point is called a core point.

[0042] Points that are directly density-reachable from the core point form a cluster, and points that are density-unreachable are considered noise points;

[0043] Built-in construction specification parameter library, automatically matching safety thresholds according to surrounding rock grade, and introducing correction factors for dynamic adjustment; using LSTM neural network to predict deformation trends and provide early warning;

[0044] Build a digital twin of the tunnel based on the BIM model, map data in real time, initiate Monte Carlo simulation when an anomaly occurs, deduce the treatment plan, and generate the optimal solution.

[0045] Preferably, the alarm execution module specifically includes:

[0046] An integrated sound and light alarm is installed at the trolley end template position. When the intelligent processing module determines that the concrete has been poured fully, the sound and light alarm is immediately activated; the buzzer emits a sharp and continuous alarm sound, the LED warning light flashes rapidly, and a voice broadcast is given at the same time;

[0047] A connection is established with the manager's mobile phone APP through the network; once an abnormal situation is detected, detailed alarm information is automatically pushed to the mobile phone APP, including alarm time, alarm location, and abnormal parameters.

[0048] Preferably, the energy supply module specifically includes:

[0049] Connect to the stable mains power supply in the tunnel, and use a high-precision voltage stabilization module to stabilize the mains voltage within the required operating voltage range, providing a clean and stable power supply for all equipment in the system;

[0050] At the same time, it is equipped with a diesel generator and a large-capacity lithium battery pack as a backup power source.

[0051] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0052] 1. The present invention uses a multi-dimensional data perception module and a combination of various sensors, such as pressure, flow, and liquid level, to achieve all-round real-time monitoring of the concrete pouring process. The patch pressure sensor can accurately capture the arrival position of concrete, and the formwork pressure strain gauge can monitor the pouring pressure to avoid quality problems caused by overpressure or underpressure. The concrete flow meter cooperates with the three-dimensional laser scanner to accurately calculate the pouring volume deviation. The ultrasonic flow sensor can promptly detect anomalies such as concrete segregation or blockage. The optical flow analysis algorithm of the intelligent processing module is then combined to accurately extract the liquid surface area and accurately assess the concrete fullness, effectively reducing the risk of vault degassing.

[0053] 2. The present invention has a complete alarm execution and energy supply module. When an abnormal situation is detected, the alarm execution module can promptly notify construction personnel and management personnel through on-site sound and light alarms and remote APP push, and at the same time automatically send a material stop instruction in conjunction with the mixing station to avoid material waste; the high-frequency pneumatic vibration unit is linked with the endoscopic monitoring unit to automatically vibrate the loose areas; the energy supply module ensures the stable operation of the system, and the equipment protection design enables it to adapt to harsh construction environments; in addition, the system can also generate the optimal disposal plan through digital twin deduction, reduce manual decision-making time and cost, realize intelligent closed-loop management of the construction process, significantly improve construction efficiency, reduce construction costs, and improve overall construction benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0055] Figure 1 This is a system structure diagram of the present invention. DETAILED DESCRIPTION

[0056] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and for many different purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0057] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless expressly defined as such herein.

[0058] Example 1

[0059] The specific implementation method is combined with the attached Figure 1 Provide detailed explanation.

[0060] Attachment Figure 1 The structural block diagram of the tunnel secondary lining concrete pouring arch anti-airflow sound and light alarm system provided in an embodiment of the present invention shows the connection relationship between the multi-dimensional data perception module, data transmission module, intelligent processing module, alarm execution module and energy supply module, and marks the main functional interaction process of each module.

[0061] In this embodiment, it includes:

[0062] The multi-dimensional data perception module is configured to collect key data from the concrete pouring process in real time through various sensors such as pressure, flow and liquid level, providing an accurate information basis for system operation;

[0063] Specifically include:

[0064] The patch pressure sensors are arranged longitudinally along the centerline of the tunnel vault and installed in the gap between the plug template and the waterproofing board. These sensors use advanced pressure-sensing materials. When concrete gradually approaches and contacts the sensor, its surface pressure changes instantly, triggering the internal relay sensing device.

[0065] The sensor and external indicator light are connected via copper foil tape to form a pathway. The indicator light quickly changes color from red to green, allowing construction workers to intuitively and clearly know from a distance that concrete has arrived in that area and monitor the pouring progress in real time. The lining trolley formwork is evenly distributed with formwork pressure strain gauges, which operate based on the resistance strain principle.

[0066] When the concrete pouring pressure acts on the formwork, the resistance value of the strain gauge changes accordingly. The Wheatstone bridge converts the resistance change into a voltage signal output. After subsequent circuit processing, the concrete pouring pressure can be accurately monitored, and overpressure or underpressure can be detected in time to prevent the formwork from deforming due to abnormal pressure or causing the vault to become hollow.

[0067] The concrete flow meter is installed at the key position of the concrete delivery pipeline. It uses the electromagnetic induction or ultrasonic measurement principle to accurately measure the concrete flow through the pipeline per unit time and calculate the actual pouring volume.

[0068] At the same time, the 3D laser scanner will periodically scan the lining area in 3D images to obtain spatial information of the tunnel lining. Combined with the design model, it uses professional algorithms to accurately calculate the expected concrete pouring volume. By comparing the two data in real time, deviations between actual pouring and theoretical requirements can be promptly identified, thereby guiding the mixing station to ensure reasonable material supply and avoid material waste or insufficient supply.

[0069] The ultrasonic flow sensor is installed on the outside of the trolley near the concrete delivery pipe outlet. It transmits and receives ultrasonic signals and uses the Doppler effect to measure the concrete flow velocity. If the flow velocity is abnormal, such as too fast a flow velocity may indicate concrete segregation or separation of aggregate and paste, or too slow a flow velocity may indicate blockage or cold joints in the concrete pipe, the system will immediately issue an early warning.

[0070] In addition to estimating pouring volume, the 3D laser scanner can also monitor changes in the tunnel lining profile in real time, providing a basis for construction quality assessment. The temperature sensor is a high-temperature and corrosion-resistant model, installed closely on the back of the formwork near the concrete pouring surface, and can quickly and accurately measure the temperature of the concrete entering the formwork.

[0071] Since temperature changes significantly affect the performance of concrete during pouring and hardening, excessively high or low temperatures entering the mold can cause cracks. Real-time temperature monitoring allows timely implementation of appropriate temperature control measures. The endoscopic monitoring unit consists of a transparent tube and a high-definition endoscopic camera. The transparent tube is installed in an arched structure near the pouring port and is directly connected to the concrete pouring area.

[0072] The camera penetrates the transparent tube and can clearly capture the concrete surface. With the help of advanced image processing algorithms, it analyzes the captured images, identifies the size, number and distribution of bubbles on the concrete surface, and then evaluates the concrete fullness. If problems such as excessive bubbles or loose surface are found, vibration instructions are issued in a timely manner.

[0073] The data transmission module is configured to use signal conditioning, wireless transmission network and data relay processing technology to stably and quickly transmit the sensing data to the processing center to ensure smooth information flow;

[0074] Specifically include:

[0075] The weak analog signal output by the pressure sensor and the voltage or resistance signal output by the temperature sensor are connected to the signal conditioning circuit. The circuit integrates a high-precision amplifier to amplify the weak signal to an amplitude range suitable for subsequent processing. At the same time, a variety of filters such as low-pass and band-pass filters are used to remove high-frequency noise and power frequency interference from the signal, thereby improving the signal-to-noise ratio.

[0076] The analog signal is converted into a digital signal through a high-speed, high-precision analog-to-digital conversion chip, so that it can be processed and transmitted by digital circuits and microprocessors;

[0077] Edge servers are specially deployed near the trolleys, which have powerful data processing capabilities. After receiving the raw data from each sensor, they are first cleaned using algorithms such as sliding window filtering and median filtering to remove outliers and noise data caused by factors such as sensor failure and electromagnetic interference.

[0078] Then, use efficient data compression algorithms, such as those based on wavelet transform, to increase the effective data compression rate, reduce the amount of data transmitted, reduce network bandwidth pressure, and speed up data transmission, so that data can be transmitted to the data processing center more quickly for subsequent analysis;

[0079] The intelligent processing module is configured to conduct in-depth analysis of the transmitted data, realize dynamic liquid level recognition, threshold judgment prediction and digital twin deduction, and provide a scientific basis for system decision-making;

[0080] Specifically include:

[0081] The optical flow dynamic analysis algorithm processes the concrete pouring video captured by the surveillance camera. Based on the motion information of the pixels between adjacent video frames, the optical flow field is calculated to accurately extract the image of the concrete surface area. This effectively solves the problem of inaccurate liquid surface recognition caused by traditional semantic segmentation methods in complex lighting conditions and irregular equipment shapes.

[0082] The optical flow analysis results are integrated with the pressure, flow, and temperature sensor data. The Kalman filter algorithm is used to optimally estimate the multi-source data, remove random noise in the data, and improve data accuracy. The fused data is clustered using the DBSCAN clustering algorithm, which divides the data into different categories based on different data characteristics. This allows for real-time and accurate assessment of concrete fullness and determination of whether the pouring status is normal.

[0083] The optical flow dynamic analysis calculation is based on the assumption of constant brightness, that is, the brightness of the same pixel remains unchanged between adjacent frames;

[0084] For the pixels in the video sequence , the brightness at time t is , at the moment Move to , the brightness is ;

[0085] According to the constant brightness assumption: ;

[0086] Taylor expand the right side of the equation and ignore higher-order infinitesimals: ;

[0087] Substituting the constant brightness assumption and sorting it out, we get: ;

[0088] in ; are the velocity components of the pixel in the x and y directions respectively; 、 and are the gradient of the image in the x and y directions and the rate of change over time respectively;

[0089] Since an equation contains two unknowns, it is impossible to solve u and v directly; the Lucas-Kanade algorithm constructs an overdetermined system of equations and solves it using the least squares method by assuming that all pixels within a window have the same motion: ;

[0090] The solution is: ;

[0091] Where A is a matrix composed of the gradients of all pixels in the window, and b is a vector composed of the time change rates of all pixels in the window;

[0092] By calculating the optical flow field of the entire image, the motion trajectory and shape change of the concrete surface can be obtained, and the surface area can be extracted. Gaussian pyramids are used for multi-scale optical flow calculation to improve the algorithm's robustness to large displacements.

[0093] First, optical flow is calculated on the highest pyramid level. The result is then projected onto the next pyramid level as the initial value, and the calculation continues until the bottom pyramid level is reached. This coarse-to-fine strategy effectively handles large displacements and improves the accuracy of optical flow calculations.

[0094] 6. The tunnel secondary lining concrete pouring arch anti-cavitation sound and light alarm system according to claim 5, characterized in that it also includes:

[0095] The system integrates data from multiple sources, including pressure sensors, flow sensors, temperature sensors, and optical flow analysis results, and uses the Kalman filter algorithm for optimal estimation. The Kalman filter is a recursive estimation algorithm that uses two steps, prediction and update, to optimally estimate the system state.

[0096] For concrete pouring condition monitoring, define the state vector Contains key parameters such as liquid level, filling speed, and pressure;

[0097] The concrete pouring state estimation is obtained through the prediction of Kalman filter;

[0098] The prediction steps of Kalman filter are:

[0099] ;

[0100] ;

[0101] in is the prior state estimate at time k, is the state transition matrix, is the control input matrix, is the control input, is the prior estimation error covariance matrix, is the process noise covariance matrix;

[0102] The update steps are:

[0103] ;

[0104] ;

[0105] ;

[0106] in is the Kalman gain, is the observation matrix, is the observed value at time k, is the observation noise covariance matrix, is the posterior state estimate at time k, is the posterior estimation error covariance matrix;

[0107] In the system, pressure sensors, flow sensors, temperature sensors and optical flow analysis results are used as observation values. Enter the Kalman filter. Through continuous iteration of prediction and update steps, the filter can effectively integrate multi-source data, eliminate the influence of random noise, and obtain a more accurate estimate of the concrete pouring state. The system will determine the optimal state transition matrix based on the actual project situation through historical data training. , observation matrix , process noise covariance matrix and the observation noise covariance matrix To improve the performance of Kalman filtering;

[0108] Perform cluster analysis on the fused data, clustering based on the density of data points, discovering clusters of arbitrary shapes and being insensitive to noise points;

[0109] Density is defined by neighborhood radius and minimum number of points. For each point in the dataset, if its neighborhood radius contains at least the minimum number of points, then the point is called a core point.

[0110] Points that are directly density-reachable from the core point form a cluster, and points that are density-unreachable are considered noise points;

[0111] In concrete fullness assessment, the system uses fused multidimensional data (including pressure, flow, temperature, optical flow features, etc.) as input and divides the data points into different clusters using the DBSCAN algorithm. Each cluster represents a concrete pouring state, such as unpoured, pouring, full, etc.

[0112] The system analyzes the characteristics and data point distribution of each cluster, combines domain expert knowledge, and sets fullness evaluation rules to accurately assess the fullness of concrete in real time and determine whether the pouring status is normal.

[0113] Built-in construction specification parameter library, automatically matching safety thresholds according to surrounding rock grade, and introducing correction factors for dynamic adjustment; using LSTM neural network to predict deformation trends and provide early warning;

[0114] Build a digital twin of the tunnel based on the BIM model, map data in real time, and initiate Monte Carlo simulation when an anomaly occurs to deduce treatment plans and generate the optimal solution;

[0115] The alarm execution module is configured to respond to abnormal situations promptly through on-site sound and light alarms and remote collaborative control, and take effective measures to ensure pouring quality and construction safety;

[0116] Specifically include:

[0117] An integrated sound and light alarm is installed at the end template of the trolley, which integrates a high-decibel buzzer, a high-brightness LED warning light and a clear voice broadcast module;

[0118] When all pressure sensor indicators turn green and the intelligent processing module determines that the concrete has been poured fully, the sound and light alarm will be activated immediately; the buzzer will emit a sharp and continuous alarm, the LED warning light will flash rapidly, and a voice broadcast will clearly prompt "Concrete is full, please stop pouring" at the same time, promptly notifying on-site construction personnel of the pouring status through multiple auditory and visual means;

[0119] The high-frequency pneumatic vibration unit is closely linked to the endoscopic monitoring unit. When the image processing algorithm of the endoscopic monitoring unit detects excessive bubbles on the concrete surface and the presence of looseness, it immediately sends a command to the high-frequency pneumatic vibration unit.

[0120] The vibration unit vibrates the formwork through fast, high-frequency pneumatic impacts, which helps to expel bubbles from the concrete. At the same time, it cooperates with the exhaust and overflow unit to guide the exhausted gas and excess slurry to the designated location, effectively preventing the vault from becoming hollow.

[0121] The system connects to the administrator's mobile app via NB-IoT or 4G networks. Once an abnormality is detected, such as excessive concrete pouring pressure or abnormal pouring volume, the system automatically sends detailed alarm information to the mobile app, including the alarm time, alarm location, and abnormal parameters.

[0122] Managers can use the app to remotely view real-time data and equipment operating status within the tunnel, and can also adjust some system parameters, such as warning thresholds and vibration duration. At the same time, the system is deeply linked with the mixing station. When the actual pouring volume exceeds the volume estimated based on the design model and real-time monitoring data, the system automatically sends a stop-concrete instruction to the mixing station. Upon receiving the instruction, the mixing station immediately stops concrete production and transportation, avoiding concrete waste and reducing construction costs.

[0123] The energy supply module is configured to provide support in terms of power supply, equipment protection, human-machine interaction and system integration to ensure stable and reliable operation of the system;

[0124] Specifically include:

[0125] Connect to the stable mains power supply in the tunnel, and use a high-precision voltage stabilization module to stabilize the mains voltage within the required operating voltage range, providing a clean and stable power supply for all equipment in the system;

[0126] At the same time, it is equipped with a 200kW diesel generator and a large-capacity lithium battery pack as backup power sources. When the mains power is interrupted due to a fault, the automatic switching device can complete the power switch within milliseconds, starting the diesel generator and lithium battery pack, ensuring that the system can continue to operate for more than 8 hours. In the event of an unexpected power outage, the system monitoring and alarm functions are not affected, ensuring construction safety and quality.

[0127] The sensors and communication equipment are housed in aircraft-grade aluminum alloy, specially treated to meet IP68 protection standards. This standard allows the equipment to withstand immersion in water up to 1.5 meters for 72 hours without affecting normal operation. It effectively resists water vapor corrosion in the high humidity of the tunnel, as well as vibration and dust generated during construction.

[0128] The signal cable is wrapped with a tinned copper braided shield to effectively shield against external electromagnetic interference. It also features an integrated TVS tube surge protection circuit. When encountering surge voltages generated by equipment with strong electromagnetic interference, such as welding machines, or severe weather such as lightning, the protection circuit quickly activates to clamp abnormal voltages within a safe range, ensuring stable and reliable signal transmission.

[0129] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factors and specific coefficient values ​​in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0130] The above embodiments can be implemented in whole or in part through software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0131] The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0132] The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more available media. The available medium can be magnetic media, optical media, or semiconductor media. The semiconductor medium can be a solid-state drive.

[0133] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0134] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways.

[0135] For example, the device embodiments described above are merely illustrative. For example, the division of units described herein is merely a logical functional division. Actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through an interface, or indirect coupling or communication connection between devices or units, which may be electrical, mechanical, or other.

[0136] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0137] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0138] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0139] The aforementioned storage media include: USB flash drives, mobile hard disks, read-only memories, random access memories, magnetic disks, optical disks, and other media that can store program codes.

[0140] The above description of the embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system is characterized by: include: The multi-dimensional data perception module is configured to collect key data from the concrete pouring process in real time through a variety of sensors, providing an accurate information basis for system operation; The data transmission module is configured to use signal conditioning, wireless transmission network and data relay processing technology to stably and quickly transmit the sensing data to the processing center; The intelligent processing module is configured to conduct in-depth analysis of the transmitted data to achieve dynamic liquid level recognition, threshold judgment prediction, and digital twin deduction; The alarm execution module is configured to respond promptly to abnormal situations through on-site sound and light alarms and remote collaborative control; The energy supply module is configured to provide support in terms of power supply, equipment protection, human-computer interaction and system integration.

2. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 1 is characterized in that: Multi-dimensional data perception module, specifically including: The patch pressure sensors are arranged longitudinally and orderly along the center line of the tunnel vault and installed in the gap between the plug template and the waterproof board; The sensor and the external indicator light are connected by copper foil tape to form a pathway, and the indicator light color will quickly change from the initial red to green; When the concrete pouring pressure acts on the formwork, the resistance value of the strain gauge changes accordingly, and the resistance change is converted into a voltage signal output through the Wheatstone bridge; The concrete flow meter is installed at the key position of the concrete delivery pipeline. It uses the electromagnetic induction or ultrasonic measurement principle to accurately measure the concrete flow through the pipeline per unit time and calculate the actual pouring volume. The ultrasonic flow sensor is installed on the outside of the trolley near the concrete delivery pipe outlet. It measures the concrete flow velocity by transmitting and receiving ultrasonic signals and using the Doppler effect. In addition to estimating the volume of grouting, the 3D laser scanner can also monitor changes in the tunnel lining profile in real time, providing a basis for construction quality assessment.

3. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 2 is characterized in that: Data transmission module, specifically including: The weak analog signal output by the pressure sensor and the voltage or resistance signal output by the temperature sensor are connected to the signal conditioning circuit to remove high-frequency noise and power frequency interference in the signal and improve the signal-to-noise ratio; The analog signal is converted into a digital signal through an analog-to-digital conversion chip.

4. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 3 is characterized in that: Intelligent processing module, specifically including: The concrete pouring video captured by the surveillance camera is processed using an optical flow dynamic analysis algorithm. Based on the motion information of pixels between adjacent video frames, the optical flow field is calculated to accurately extract the image of the concrete surface area. The optical flow analysis results are fused with the pressure, flow, and temperature sensor data; the Kalman filter algorithm is used to optimally estimate multi-source data; cluster analysis is performed on the fused data, dividing it into different categories based on different data characteristics, evaluating the concrete fullness and determining whether the pouring status is normal.

5. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 4 is characterized in that: Also includes: For the pixels in the video sequence , the brightness at time t is , at the moment Move to , the brightness is ; According to the constant brightness assumption: ; Taylor expand the right side of the equation and ignore higher-order infinitesimals: ; Substituting the constant brightness assumption and sorting it out, we get: ; in ; are the velocity components of the pixel in the x and y directions respectively; 、 and are the gradient of the image in the x and y directions and the rate of change over time respectively; Formulate an overdetermined system of equations and solve it using least squares methods: ； The solution is: ; Where A is a matrix consisting of the gradients of all pixels in the window, and b is a vector consisting of the time change rates of all pixels in the window.

6. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 5 is characterized in that: Also includes: For concrete pouring status monitoring, the state vector is defined to include key parameters such as liquid level, pouring speed, and pressure; The concrete pouring state estimation is obtained through Kalman filter prediction.

7. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 6 is characterized in that: Perform cluster analysis on the fused data, cluster based on the density of data points, and discover clusters of arbitrary shapes; Density is defined by neighborhood radius and minimum number of points. For each point in the dataset, if its neighborhood radius contains at least the minimum number of points, then the point is called a core point. Points that are directly density-reachable from the core point form a cluster, and points that are density-unreachable are considered noise points; Built-in construction specification parameter library, automatically matching safety thresholds according to surrounding rock grade, and introducing correction factors for dynamic adjustment; using LSTM neural network to predict deformation trends and provide early warning; Build a digital twin of the tunnel based on the BIM model, map data in real time, initiate Monte Carlo simulation when an anomaly occurs, deduce the treatment plan, and generate the optimal solution.

8. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 1 is characterized in that: Alarm execution module, specifically including: An integrated sound and light alarm is installed at the end template of the trolley. When the intelligent processing module determines that the concrete has been poured fully, the sound and light alarm is immediately activated; the buzzer emits a sharp and continuous alarm sound, the LED warning light flashes rapidly, and a voice broadcast is given at the same time; A connection is established with the manager's mobile phone APP through the network; once an abnormal situation is detected, detailed alarm information is automatically pushed to the mobile phone APP, including alarm time, alarm location, and abnormal parameters.

9. The tunnel secondary lining concrete pouring arch anti-emptying sound and light alarm system according to claim 1 is characterized in that: Energy supply module, specifically including: Connect to the stable mains power supply in the tunnel, and use a high-precision voltage stabilization module to stabilize the mains voltage within the required operating voltage range, providing a clean and stable power supply for all equipment in the system; At the same time, it is equipped with a diesel generator and a large-capacity lithium battery pack as a backup power source.

Images