Shield tail sealing slurry leakage early warning device, method and system based on multi-source information

Abstract

The application provides a shield tail sealing slurry leakage early warning device, method and system based on multi-source information. The device comprises: a sensor integration module for collecting grease data of multiple monitoring points in a shield tail sealing cavity; an injection pressure obtaining module for reading injection pressure of multiple monitoring points in the shield tail sealing; a slurry leakage early warning module for obtaining predicted shield tail sealing grease pressure according to the grease data, injection pressure and a shield tail sealing slurry leakage early warning algorithm model based on multi-element time series; determining a shield tail sealing slurry leakage risk level according to the predicted shield tail sealing grease pressure and calculated shield tail slurry pressure, and generating early warning information. The application can monitor and predict the grease pressure in the shield tail sealing cavity in real time, and issue a slurry leakage risk early warning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunnel construction, and in particular to a shield tail sealing slurry leakage early warning device, method and system based on multi-source information. BACKGROUND

[0002] The shield tail sealing system is one of the key systems of the shield tunneling machine, and shield tail sealing slurry leakage will cause a large amount of slurry and groundwater in the slurry chamber to flow into the tunnel, causing ground subsidence, personnel casualties and other major disasters. The sealing system commonly used by the shield tunneling machine is composed of three sealing brushes and sealing grease. The sealing brushes are elastic and are installed on the shield body, tightly adhering to the segments. In the gap between the shield tail brushes, the oil is filled by pressure for sealing. During the tunneling process of the shield tunneling machine, it is necessary to monitor the oil change in the shield tail sealing cavity in real time to prevent the slurry and groundwater in the slurry chamber from penetrating the shield tail brushes, causing shield tail sealing slurry leakage.

[0003] The existing shield tail sealing slurry leakage early warning system mainly uses a pressure sensor to monitor the shield tail sealing grease pressure or analyzes the original data of the shield tunneling machine to propose an early warning rule. However, the existing scheme cannot predict the data trend, only realizes alarm, and does not realize early warning.

[0004] Therefore, it is necessary to propose a scheme for real-time monitoring of the oil pressure in the shield tail sealing cavity to issue a slurry leakage risk early warning to the driver. SUMMARY

[0005] The present application provides a shield tail sealing slurry leakage early warning device based on multi-source information to monitor and predict the oil pressure in the shield tail sealing cavity in real time and issue a slurry leakage risk early warning. The device comprises:

[0006] A sensor integration module is configured to collect oil data of multiple monitoring points in the shield tail sealing cavity.

[0007] An injection pressure obtaining module is configured to read the injection pressure of multiple monitoring points in the shield tail sealing cavity.

[0008] A slurry leakage early warning module is configured to obtain a predicted shield tail sealing oil pressure according to the oil data, the injection pressure and a shield tail sealing slurry leakage early warning algorithm model based on multi-element time series, determine a shield tail sealing slurry leakage risk level according to the predicted shield tail sealing oil pressure and a calculated shield tail slurry pressure, and generate early warning information.

[0009] The present application provides a shield tail sealing slurry leakage early warning method based on multi-source information to monitor and predict the oil pressure in the shield tail sealing cavity in real time and issue a slurry leakage risk early warning. The method comprises:

[0010] Collecting oil data of multiple monitoring points in the shield tail sealing cavity.

[0011] read the grease pressure of multiple monitoring points in the shield tail seal;

[0012] According to the grease data, the grease pressure, and the shield tail seal slurry leakage early warning algorithm model based on the multivariate time series, the predicted shield tail seal grease pressure is obtained.

[0013] According to the predicted shield tail seal grease pressure and the calculated shield tail slurry pressure, the shield tail seal slurry leakage risk level is determined, and early warning information is generated.

[0014] The embodiment of the present application proposes a shield tail seal slurry leakage early warning system based on multi-source information, which is used for real-time monitoring and predicting the oil pressure in the shield tail seal cavity, and issuing a slurry leakage risk warning. The system comprises:

[0015] The shield tail seal slurry leakage early warning device based on multi-source information, the shield tunneling machine, the shield tail seal monitoring system cross-section display module, the shield tail seal brush, the segment, and the tail shield shell, wherein,

[0016] The shield tail seal slurry leakage early warning device based on multi-source information is arranged on the shield tunneling machine;

[0017] The shield tail seal brush is arranged on the tail shield shell, and a sensor mounting position is arranged between the shield tail seal brushes, and the sensor mounting position is used for mounting multiple sensors;

[0018] The shield tunneling machine is used for tunneling.

[0019] The shield tail seal brush is used for forming a sealed cavity to isolate the slurry and the underground water.

[0020] The embodiment of the present application further provides a computer device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above-mentioned shield tail seal slurry leakage early warning method based on multi-source information when executing the computer program.

[0021] The embodiment of the present application further provides a computer device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above-mentioned shield tail seal slurry leakage early warning method based on multi-source information when executing the computer program.

[0022] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above-mentioned shield tail seal slurry leakage early warning method based on multi-source information.

[0023] The embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the above-mentioned shield tail seal slurry leakage early warning method based on multi-source information.

[0024] In this embodiment of the invention, a sensor integration module is used to: collect grease data at multiple monitoring points within the shield tail sealing cavity; a grease injection pressure acquisition module is used to: read the grease injection pressure at multiple monitoring points within the shield tail seal; and a grout leakage early warning module is used to: obtain the predicted shield tail seal grease pressure based on the grease data, grease injection pressure, and a shield tail seal grout leakage early warning algorithm model based on multivariate time series; determine the shield tail seal grout leakage risk level based on the predicted shield tail seal grease pressure and the calculated shield tail mud pressure, and generate early warning information. Compared with existing technologies that mainly use pressure sensors to monitor shield tail seal grease pressure or analyze raw shield machine data, achieving only alarms but not early warnings, this embodiment of the invention can collect grease data and grease injection pressure at multiple monitoring points, and predict the shield tail seal grease pressure based on a shield tail seal grout leakage early warning algorithm model based on multivariate time series, generating early warning information to achieve accurate early warning of shield tail seal grout leakage risk. This solves the problem of "difficult monitoring and early warning" of shield tail seals, ensuring safe and efficient shield machine tunneling and promoting the intelligent and unmanned development of tunnel excavation. It can improve work efficiency, save manpower and material resources, and ensure the safe and efficient tunneling of tunnel boring machines. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0026] Figure 1 This is a schematic diagram of a shield tail seal grout leakage early warning system based on multi-source information in an embodiment of the present invention;

[0027] Figure 2 This is a schematic diagram of the shield tail seal grout leakage early warning device based on multi-source information in an embodiment of the present invention;

[0028] Figure 3 This is a flowchart of the shield tail seal grout leakage early warning method based on multi-source information in an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0031] In the description of the present application, "comprising", "including", "having", "containing" and the like are open-ended terms that mean inclusion, but not limited to, whatever follows the term. The description of the terms "one embodiment", "one configuration", "some embodiments", "example" and the like means that the particular feature, structure or characteristic following the term is included in at least one embodiment or example of the present application. The illustrative appearance of the above terms in various places in the description are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures or characteristics can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the embodiments can be modified as appropriate, and the steps involved in the embodiments can be combined in any suitable manner.

[0032] Figure 1 FIG. 1 is a schematic diagram of a shield tail sealing slurry leakage early warning system based on multi-source information in an embodiment of the present application, Figure 1 FIG. 1(a) is a side view of a shield tunneling machine in a shield tail sealing slurry leakage early warning system based on multi-source information in an embodiment of the present application, Figure 1 FIG. 1(b) is a longitudinal section of a shield tunneling machine in a shield tail sealing slurry leakage early warning system based on multi-source information in an embodiment of the present application, Figure 1 FIG. 1(c) is a cross-section of a shield tail sealing monitoring system displayed by a cross-section display module of the shield tail sealing monitoring system in an embodiment of the present application, which includes:

[0033] The shield tail sealing slurry leakage early warning device 2, the shield tunneling machine 1, the shield tail sealing brush 4, and the tail shield shell 7, wherein,

[0034] The shield tail sealing slurry leakage early warning device is arranged on the shield tunneling machine;

[0035] The shield tail sealing brush is arranged on the tail shield shell, and a sensor mounting position is arranged between the shield tail sealing brushes, and the sensor mounting position is used for mounting a plurality of sensors;

[0036] The shield tunneling machine is used for excavating a tunnel;

[0037] The shield tail sealing brush is used for forming a sealing cavity to isolate slurry and underground water.

[0038] In addition, the system further includes:

[0039] The cross-section display module 5 of the shield tail sealing monitoring system is used for viewing the distribution of a plurality of monitoring points;

[0040] The segment 6 is used for supporting a tunnel.

[0041] It can be seen that the structural relationship between the shield tail sealing brush 4, the sensor mounting position 5, the segment 6, and the tail shield shell.

[0042] Figure 1 (c) in the figure shows 8 monitoring points.

[0043] Figure 2 Fig. 1 is a schematic diagram of a seal leakage warning device based on multi-source information in an embodiment of the present application, comprising:

[0044] The sensor integration module 21 is configured to collect grease data of multiple monitoring points in the shield tail sealing cavity.

[0045] The grease pressure obtaining module 22 is configured to read the grease pressure of multiple monitoring points in the shield tail sealing cavity.

[0046] The leakage warning module 23 is configured to obtain the predicted grease pressure of the shield tail sealing cavity according to the grease data, the grease pressure, and the shield tail sealing leakage warning algorithm model based on multi-time series; determine the shield tail sealing leakage risk level according to the predicted grease pressure of the shield tail sealing cavity and the calculated shield tail slurry pressure, and generate a warning information.

[0047] In an embodiment, the device further comprises:

[0048] The data storage module 24 is configured to store the collected grease data and the read grease pressure.

[0049] The wireless communication device 25 is configured to send the warning information to the ground command center and the main driver.

[0050] The ground command center 26 is configured to generate a treatment plan when the warning information is obtained.

[0051] The grease pressure obtaining module can be a PLC, and the data storage module and the leakage warning module are integrated in a high-performance industrial computer. The ground command center is used to monitor various systems of the tunnel boring machine construction to ensure normal tunneling.

[0052] In an embodiment, the shield tail sealing leakage warning algorithm model based on multi-time series takes a long short-term memory neural network as a framework, and comprises a neural network composed of an input layer, a Dropout layer, and a full connection layer. In addition, RNN / Transformer can also be used.

[0053] In an embodiment, the shield tail sealing cavity comprises a front cavity, a middle cavity, and a rear cavity of the shield tail sealing.

[0054] The grease data comprises grease pressure, grease temperature, and grease water content. Of course, other data such as grease resistivity can also be included, and related changes should fall within the protection scope of the present application.

[0055] In an embodiment, the leakage warning module comprises:

[0056] a multivariate time series module, configured to compose the grease data and the grease injection pressure into a multivariate time series;

[0057] a prediction module, configured to input the multivariate time series into a shield tail sealing slurry leakage early warning algorithm model based on the multivariate time series, to obtain a predicted shield tail sealing grease pressure, the predicted shield tail sealing grease pressure being a shield tail sealing grease pressure in a future preset time length;

[0058] a slurry pressure calculation module, configured to calculate a shield tail slurry pressure;

[0059] a differential pressure calculation module, configured to calculate a shield tail sealing inter-cavity differential pressure according to the predicted shield tail sealing grease pressure and the shield tail slurry pressure, the shield tail sealing inter-cavity differential pressure including differential pressures between a front cavity, a middle cavity, a rear cavity and a slurry cavity of the shield tail sealing;

[0060] a risk level determination module, configured to determine a shield tail sealing risk level according to the shield tail sealing inter-cavity differential pressure and a reference interval;

[0061] an early warning information generation module, configured to generate early warning information according to the shield tail sealing slurry leakage risk level.

[0062] In an embodiment, the slurry leakage early warning module further includes a preprocessing module, configured to:

[0063] Before the grease data and the grease injection pressure are composed into the multivariate time series, threshold method and / or moving average filtering method are used to eliminate outliers of the collected grease data and the grease injection pressure, and then the mean value of each minute is selected as a sample;

[0064] the mean value of the grease data with the outliers eliminated is taken;

[0065] the multivariate time series module is specifically configured to compose the mean value into a multivariate time series.

[0066] In an embodiment, the slurry pressure calculation module is specifically configured to:

[0067] assuming that the slurry pressure values at the same horizontal line are the same and the pressure is uniformly and linearly distributed vertically at the horizontal line, the slurry pressure at a plurality of monitoring points is calculated according to the shield tail upper slurry pressure, the shield tail lower slurry pressure and a sensor installation angle.

[0068] In an embodiment, the risk level determination module is specifically configured to:

[0069] if the shield tail sealing inter-cavity differential pressure is less than the lower limit a of the reference interval [a, b], it is determined that the grease overflows;

[0070] If the pressure difference between the shield tail sealing cavities is greater than the upper limit b of the reference interval [a, b], it is determined that the shield tail sealing brush is broken, and according to the situation that the shield tail sealing brush is broken from back to front, it is sequentially divided into low risk, medium risk, high risk, and shield tail sealing has leaked mud.

[0071] In an embodiment, the mud leakage early warning module further comprises:

[0072] The interval determination module is configured to calculate the pressure difference between the shield tail sealing cavities by using the grease pressure when the sealing brush is broken in multiple tests on the shield tail sealing test bench, and determine the reference interval.

[0073] Figure 3 The flowchart of the shield tail sealing mud leakage early warning based on multi-source information in the embodiment of the application comprises:

[0074] Step 301, collecting grease data of multiple monitoring points in the shield tail sealing cavity;

[0075] Step 302, reading the grease injection pressure of multiple monitoring points in the shield tail sealing cavity;

[0076] Step 303, obtaining the predicted shield tail sealing grease pressure according to the grease data, the grease injection pressure, and the shield tail sealing mud leakage early warning algorithm model based on multi-element time series;

[0077] Step 304, determining the shield tail sealing mud leakage risk level according to the predicted shield tail sealing grease pressure and the calculated shield tail mud pressure, and generating early warning information.

[0078] In combination with the above embodiment, a specific process of performing the shield tail sealing mud leakage early warning based on multi-source information is given below.

[0079] (1) determining the shield tail sealing monitoring points;

[0080] (2) The sensor integration module collects the grease data of multiple monitoring points (for example, 8 monitoring points, but not limited to 8, but too many sensors and monitoring points will cause the industrial computer and the upper computer to crash due to too much real-time processing data) in the shield tail sealing cavity, including the grease pressure, grease temperature and water content of the front cavity, middle cavity and rear cavity of the shield tail sealing, and stores them in the data storage module;

[0081] (3) The grease injection pressure acquisition module (PLC) reads the grease injection pressure of multiple monitoring points in the shield tail sealing cavity;

[0082] (4) The threshold method and / or the moving average filtering method are used to eliminate the outliers of the collected grease data and the grease injection pressure, and then the mean value of each minute is selected as the sample; the mean value of the grease data after eliminating the outliers is taken;

[0083] (5) The mean values are arranged according to the monitoring points to form a 60x4 multi-element time series;

[0084] (6) input the multivariate time series into the multivariate time series-based shield tail sealing slurry leakage early warning algorithm model to predict the data trend of the corresponding point in the future 10 minutes;

[0085] (7) the MAE, MSE, MSE, MAPE are used to evaluate the grease pressure trend of each monitoring point to obtain the predicted shield tail sealing grease pressure;

[0086] (8) the same mud pressure value at the same horizontal line and the uniform linear distribution of the pressure perpendicular to the horizontal line are assumed as the premise, and the mud pressure at the 8 monitoring points of the shield tail sealing is calculated according to the upper mud pressure Pt of the shield tail, the lower mud pressure Pb of the shield tail and the installation angle of the sensor;

[0087] (9) according to the predicted shield tail sealing grease pressure and the shield tail mud pressure, the inter-cavity pressure difference of the shield tail sealing is calculated, the inter-cavity pressure difference of the shield tail sealing includes the pressure difference between the front cavity, the middle cavity, the rear cavity and the slurry cavity of the shield tail sealing, and the shield tail sealing slurry leakage risk level (grease overflow, low risk, medium risk, high risk, shield tail sealing has leaked mud) is divided;

[0088] (10) according to the shield tail sealing slurry leakage risk level, the early warning information is generated and transmitted to the PLC, the main driver and the ground command center through the wireless communication device; if the slurry leakage risk occurs, the main driver should increase the shield tail sealing grease injection amount to reinforce the shield tail sealing system, and the ground command center generates a processing scheme, for example, organizes workers to replace the sealing brush;

[0089] Wherein, the processes (1)-(10) are performed once every 1 minute for the shield tail sealing slurry leakage early warning.

[0090] Through the above steps, the real-time monitoring and early warning of the shield tail sealing slurry leakage condition can be realized according to the grease pressure data in the shield tail sealing cavity, and the shield tunneling machine can be ensured to be safe and efficient, which provides technical support for subsequent unmanned tunneling.

[0091] The device, method and system provided by the embodiment of the application have the following beneficial effects:

[0092] Compared with the prior art in which a pressure sensor is mainly used to monitor the shield tail sealing grease pressure or the original data of the shield tunneling machine, only an alarm is realized, and a technical scheme of early warning is not realized, the embodiment of the present application can collect the grease data of multiple monitoring points and the grease injection pressure, and based on a shield tail sealing slurry leakage early warning algorithm model of multiple time series, the shield tail sealing grease pressure is predicted, early warning information is generated, the accurate early warning of the shield tail sealing slurry leakage risk is realized, the problems of difficult monitoring and early warning of the shield tail sealing are solved, the safe and efficient tunneling of the shield tunneling machine is ensured, and the development of the tunneling towards intelligence and unmanned is promoted. The working efficiency can be improved, manpower and material resources can be saved, and the safe and efficient tunneling of the shield tunneling machine is ensured.

[0093] The embodiment of the present application further provides a computer device, Figure 4 For a schematic diagram of the computer device in the embodiment of the present application, the computer device 400 comprises a memory 410, a processor 420, and a computer program 430 stored in the memory 410 and capable of running on the processor 420, and the processor 420 realizes the above-mentioned shield tail sealing slurry leakage early warning method based on multiple source information when the computer program 430 is executed.

[0094] The embodiment of the present application further provides a computer readable storage medium, the computer readable storage medium stores a computer program, and the computer program realizes the above-mentioned shield tail sealing slurry leakage early warning method based on multiple source information when the processor is executed.

[0095] The embodiment of the present application further provides a computer program product, the computer program product comprises a computer program, and the computer program realizes the above-mentioned shield tail sealing slurry leakage early warning method based on multiple source information when the processor is executed.

[0096] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program service system. Therefore, the present application can adopt a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a form of a computer program service system implemented on one or more computer usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer usable program code.

[0097] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks

[0098] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks

[0099] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks Figure 1 one or more flowcharts and / or blocks

[0100] The above-described specific embodiments, the purpose, technical solutions and advantages of the present application are further described in detail, it should be understood that the above-described is only the specific embodiments of the present application, and is not used to limit the protection scope of the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A shield tail seal grout leakage early warning device based on multi-source information, characterized in that, include: The sensor integration module is used to collect grease data at multiple monitoring points within the shield tail sealing cavity; The grease injection pressure acquisition module is used to: read the grease injection pressure at multiple monitoring points inside the shield tail seal; The grout leakage early warning module is used to: obtain the predicted shield tail seal grease pressure based on the grease data, grease injection pressure, and a shield tail seal grout leakage early warning algorithm model based on multivariate time series; determine the shield tail seal grout leakage risk level based on the predicted shield tail seal grease pressure and the calculated shield tail mud pressure, and generate early warning information. The grout leakage early warning module includes: A multivariate time series composition module is used to compose the oil data and injection pressure into a multivariate time series. The prediction module is used to input multivariate time series data into the shield tail seal grout leakage early warning algorithm model based on multivariate time series data to obtain the predicted shield tail seal grease pressure. The predicted shield tail seal grease pressure is the shield tail seal grease pressure for a preset time period in the future. The mud pressure calculation module is used to calculate the mud pressure at the tail of the shield. The differential pressure calculation module is used to calculate the differential pressure between the shield tail sealing cavities based on the predicted shield tail sealing grease pressure and shield tail mud pressure. The differential pressure between the shield tail sealing cavities includes the differential pressure between the front cavity, middle cavity, rear cavity and mud-water cavity of the shield tail seal. The risk level determination module is used to determine the risk level of the shield tail seal based on the pressure difference between the shield tail sealing cavities and the reference range. The early warning information generation module is used to generate early warning information based on the risk level of grout leakage at the tail of the shield.

2. The apparatus as claimed in claim 1, characterized in that, Also includes: The data storage module is used to store the collected oil data and the read injection pressure; Wireless communication device, used to: transmit early warning information to the ground command center and the main driver; The ground command center is used to generate a response plan upon receiving early warning information.

3. The apparatus as described in claim 1, characterized in that, The shield tail seal grout leakage early warning algorithm model based on multivariate time series uses a long short-term memory neural network as its framework, which includes a neural network composed of an input layer, a dropout layer, and a fully connected layer.

4. The apparatus as claimed in claim 1, characterized in that, The shield tail sealing cavity includes a front cavity, a middle cavity, and a rear cavity of the shield tail seal; The oil data includes oil pressure, oil temperature, and oil moisture content.

5. The apparatus as claimed in claim 1, characterized in that, The grout leakage early warning module also includes a pre-processing module, used for: Before assembling the oil data and injection pressure into a multivariate time series, outliers in the collected oil data and injection pressure are removed using a threshold method and / or a moving average filtering method, and then the mean value per minute is selected as the sample. The average value of the oil data after removing outliers was taken; The multivariate time series composition module is specifically used to: compose the mean into a multivariate time series.

6. The apparatus as claimed in claim 1, characterized in that, The mud pressure calculation module is specifically used for: Assuming that the mud pressure values ​​are the same at the same horizontal line and that the pressure is uniformly linearly distributed perpendicular to the horizontal line, the mud pressure at multiple monitoring points is calculated based on the mud pressure at the upper part of the shield tail, the mud pressure at the lower part of the shield tail, and the sensor installation angle.

7. The apparatus as claimed in claim 1, characterized in that, The risk level classification module is specifically used for: If the pressure difference between the shield tail sealing chambers is less than the lower limit of the reference range, grease leakage is confirmed. If the pressure difference between the shield tail sealing chambers is greater than the upper limit of the reference range, it is determined that the shield tail sealing brush has been punctured. Based on the puncture of the shield tail sealing brush from back to front, it is classified as low risk, medium risk, high risk, and shield tail seal leakage.

8. The apparatus as claimed in claim 1, characterized in that, The grout leakage early warning module also includes: The interval determination module is used to calculate the pressure difference between the shield tail sealing cavities and determine the reference interval by repeatedly testing the grease pressure when the sealing brush is punctured using the shield tail sealing test bench.

9. A method for early warning of grout leakage at the tail of a shield based on multi-source information, characterized in that, include: Collect grease data at multiple monitoring points within the shield tail sealing cavity; Read the grease injection pressure at multiple monitoring points inside the shield tail seal; Based on the grease data, grease injection pressure, and the shield tail seal grout leakage early warning algorithm model based on multivariate time series, the predicted shield tail seal grease pressure is obtained. The risk level of shield tail seal leakage is determined based on the predicted shield tail seal grease pressure and the calculated shield tail mud pressure, and early warning information is generated. The risk level of shield tail seal leakage is determined based on the predicted shield tail seal grease pressure and the calculated shield tail mud pressure, and early warning information is generated, including: The oil data and injection pressure were combined into a multivariate time series. The multivariate time series is input into the shield tail seal grout leakage early warning algorithm model based on the multivariate time series to obtain the predicted shield tail seal grease pressure. The predicted shield tail seal grease pressure is the shield tail seal grease pressure for a future preset time period. Calculate the tail mud pressure; Based on the predicted shield tail sealing grease pressure and shield tail mud pressure, the pressure difference between the shield tail sealing cavities is calculated. The pressure difference between the shield tail sealing cavities includes the pressure difference between the front cavity, middle cavity, rear cavity and mud-water cavity of the shield tail seal. The risk level of the shield tail seal is determined based on the pressure difference between the sealing chambers and the reference range. Early warning information is generated based on the risk level of grout leakage at the tail seal.

10. A shield tail seal grout leakage early warning system based on multi-source information, characterized in that, include: The shield tail sealing grout leakage early warning device, shield machine, shield tail sealing brush, and tail shield shell based on multi-source information as described in any one of claims 1 to 8, wherein, A shield tail seal grout leakage early warning device based on multi-source information is installed on the tunnel boring machine; The tail shield sealing brush is located on the tail shield shell, and there are sensor mounting positions between the tail shield sealing brushes. The sensor mounting positions are used to install multiple sensors. Tunnel boring machines (TBMs) are used to excavate tunnels. The tail seal brush is used to form a sealed cavity to isolate mud and groundwater.

11. The system as claimed in claim 10, characterized in that, Also includes: The cross-sectional display module of the shield tail sealing monitoring system is used to view the distribution of multiple monitoring points; Segmentation, used to support the tunnel.

12. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of claim 9.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of claim 9.

14. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of claim 9.

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