Tunnel construction monitoring method based on parallel construction superposition effect analysis

Abstract

The present invention discloses a tunnel construction monitoring method based on the analysis of the superposition effect of parallel construction, which relates to the field of intelligent monitoring technology. The method includes: collecting multiple construction information superimposed in parallel construction, performing stress field analysis respectively, and obtaining multiple stress field information; constructing a tunnel twin model, and dividing to obtain a multi-layer tunnel twin sub-model; performing stress field division, and performing tunnel offset information analysis respectively, obtaining multiple tunnel offset information sets, and performing tunnel offset superposition analysis; performing tunnel construction deformation analysis based on multiple superimposed tunnel offset information, and outputting the tunnel deformation mode with the largest proportion as the construction monitoring result. The present invention solves the technical problems of low accuracy and hysteresis in tunnel deformation monitoring under parallel construction in the prior art, and achieves the technical effect of improving the effectiveness and accuracy of monitoring by performing tunnel offset analysis and tunnel deformation mode monitoring layer by layer.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring, and in particular to a tunnel construction monitoring method based on parallel construction superposition effect analysis. Background Art

[0002] For large-scale engineering projects near subway tunnels, multiple construction activities are often carried out simultaneously during the construction process, such as pile foundation construction, foundation pit excavation, TRD construction, etc. These construction activities have multiple superposition effects on the deformation of nearby tunnels. Therefore, under the influence of multiple superposition effects, tunnel deformation needs to be monitored and processed. However, when multiple construction activities are carried out simultaneously, it is often difficult to conduct timely and accurate tunnel deformation monitoring, and thus it is impossible to take targeted treatment measures. Summary of the invention

[0003] The present application provides a tunnel construction monitoring method based on parallel construction superposition effect analysis, which is used to solve the technical problems in the prior art of low accuracy and hysteresis in tunnel deformation monitoring under parallel construction.

[0004] The first aspect of the present application provides a tunnel construction monitoring method based on parallel construction superposition effect analysis, the method comprising: collecting multiple construction information superimposed in parallel construction, wherein each construction information includes a construction type and construction parameters, and the multiple construction information includes tunnel construction information and near-tunnel construction information; according to the multiple construction information, respectively performing stress field analysis on the tunnel to obtain multiple stress field information; collecting design information of the tunnel, constructing a tunnel twin model, and dividing to obtain a multi-layer tunnel twin sub-model; based on the multi-layer tunnel twin sub-model, performing stress field division on the multiple stress field information, and respectively performing tunnel offset information analysis to obtain multiple tunnel offset information sets; based on the multiple tunnel offset information sets, performing tunnel offset superposition analysis to obtain multiple superimposed tunnel offset information of the multi-layer tunnel twin sub-model; based on the multiple superimposed tunnel offset information, performing tunnel construction deformation analysis to obtain multiple tunnel deformation modes, and outputting the tunnel deformation mode with the largest proportion as the construction monitoring result.

[0005] In a second aspect of the present application, a tunnel construction monitoring system based on parallel construction superposition effect analysis is provided, the system comprising: a plurality of construction information acquisition modules, the plurality of construction information acquisition modules being used to acquire a plurality of construction information superimposed in parallel construction, wherein each construction information comprises a construction type and a construction parameter, and the plurality of construction information comprises tunnel construction information and near-tunnel construction information; a plurality of stress field information acquisition modules, the plurality of stress field information acquisition modules being used to respectively perform stress field analysis on the tunnel according to the plurality of construction information, and acquire a plurality of stress field information; a multi-layer tunnel twin model acquisition module, the multi-layer tunnel twin model acquisition module being used to acquire design information of the tunnel, construct a tunnel twin model, and divide the multi-layer tunnel into a plurality of layers; A tunnel twin model; a tunnel offset information set acquisition module, the tunnel offset information set acquisition module is used to perform stress field division on the multiple stress field information based on the multi-layer tunnel twin model, and perform tunnel offset information analysis respectively to obtain multiple tunnel offset information sets; a superposition tunnel offset information acquisition module, the superposition tunnel offset information acquisition module is used to perform tunnel offset superposition analysis based on multiple tunnel offset information sets to obtain multiple superposition tunnel offset information of the multi-layer tunnel twin model; a construction monitoring result output module, the construction monitoring result output module is used to perform tunnel construction deformation analysis based on multiple superposition tunnel offset information, obtain multiple tunnel deformation modes, and output the tunnel deformation mode with the largest proportion as the construction monitoring result.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] The present application provides a tunnel construction monitoring method based on parallel construction superposition effect analysis, which relates to the field of intelligent monitoring technology. By collecting multiple construction information superimposed in parallel construction, stress field analysis is performed separately to obtain multiple stress field information, a tunnel twin model is constructed, and a multi-layer tunnel twin sub-model is obtained. Stress field division and tunnel offset information analysis are performed to obtain multiple tunnel offset information sets. Tunnel construction deformation analysis is performed based on multiple superimposed tunnel offset information, and the tunnel deformation mode with the largest proportion is output as the construction monitoring result. The technical problems of low accuracy and hysteresis in tunnel deformation monitoring under parallel construction in the prior art are solved, and the technical effect of improving the effectiveness and accuracy of monitoring by performing tunnel offset analysis and tunnel deformation mode monitoring layer by layer to take targeted treatment measures is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic flow chart of a tunnel construction monitoring method based on parallel construction superposition effect analysis provided in an embodiment of the present application;

[0010] Figure 2 A schematic diagram of a flow chart of obtaining multiple tunnel offset information sets in a tunnel construction monitoring method based on parallel construction superposition effect analysis provided in an embodiment of the present application;

[0011] Figure 3 A schematic diagram of a flow chart of outputting construction monitoring results in a tunnel construction monitoring method based on parallel construction superposition effect analysis provided in an embodiment of the present application;

[0012] Figure 4 A schematic diagram of the structure of a tunnel construction monitoring system based on parallel construction superposition effect analysis provided in an embodiment of the present application.

[0013] Explanation of the reference numerals: multiple construction information acquisition modules 11, multiple stress field information acquisition modules 12, multi-layer tunnel twin model acquisition module 13, tunnel offset information set acquisition module 14, superimposed tunnel offset information acquisition module 15, construction monitoring result output module 16. DETAILED DESCRIPTION

[0014] The present application provides a tunnel construction monitoring method based on parallel construction superposition effect analysis, which is used to solve the technical problems in the prior art of low accuracy and hysteresis in tunnel deformation monitoring under parallel construction.

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0016] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices.

[0017] Embodiment 1

[0018] like Figure 1 As shown, the present application provides a tunnel construction monitoring method based on parallel construction superposition effect analysis, the method comprising:

[0019] P10: Collect multiple construction information superimposed in parallel construction, where each construction information includes construction type and construction parameters, and the multiple construction information includes tunnel construction information and near-tunnel construction information;

[0020] It should be understood that during the parallel construction process, information on multiple construction behaviors that are carried out simultaneously is collected, and each construction information includes construction type and construction parameters, such as pile foundation construction, foundation pit excavation, TRD construction, etc. The construction parameters refer to the parameters of each construction behavior, such as pile foundation burial depth, foundation pit size, etc. And the multiple construction information includes tunnel construction information and near-tunnel construction information, that is, construction information inside the tunnel and construction information outside the tunnel. Construction inside the tunnel, such as excavation, support, reinforcement, etc., and construction outside the tunnel, such as on-ground buildings, roads, railways, earthwork accumulation, etc., will cause deformation and displacement of the tunnel due to additional loads.

[0021] P20: According to the multiple construction information, respectively analyze the stress field of the tunnel to obtain multiple stress field information;

[0022] Furthermore, step P20 of the embodiment of the present application also includes:

[0023] P21: Based on multiple sample construction types, multiple sample construction information sets are obtained, and multiple construction stress field sets are obtained;

[0024] P22: Multiple sample construction information sets and multiple construction stress field sets are used to construct multiple stress field analysis branches;

[0025] P23: Integrate multiple stress field analysis branches to obtain stress field analysis channels;

[0026] P24: Obtain the multiple stress field information, wherein the multiple stress field information is obtained by inputting multiple construction information into the stress field analysis channel.

[0027] Optionally, based on tunnel construction experience, multiple sample construction types are collected, such as excavation, support, reinforcement in the tunnel, and earthwork accumulation outside the tunnel, and then construction information is collected for multiple sample construction types to obtain multiple sample construction information sets, and the construction stress field information corresponding to the corresponding sample construction information is collected, that is, according to parameters such as construction type and construction scale, the stress field generated during construction is analyzed to obtain multiple construction stress field sets. Further, multiple sample construction information sets and multiple construction stress field sets are used as training data, combined with machine learning principles, such as BP neural network, to construct multiple stress field analysis branches, and supervised training is performed using the training data until all the multiple stress field analysis branches converge, wherein each stress field analysis branch corresponds to a sample construction type.

[0028] Furthermore, the multiple stress field analysis branches are merged to form a stress field analysis channel, and then the multiple construction information are input into the stress field analysis channel for stress analysis. The multiple stress field information is obtained, which can reflect the stress distribution of multiple construction behaviors currently being carried out simultaneously.

[0029] P30: Collecting the design information of the tunnel, constructing a tunnel twin model, and dividing it to obtain a multi-layer tunnel twin sub-model;

[0030] Furthermore, step P30 of the embodiment of the present application further includes:

[0031] P31: Obtain the structural design information of the tunnel;

[0032] P32: constructing a tunnel twin model of the tunnel according to the structural design information;

[0033] P33: Divide the tunnel twin model according to the radial direction of the tunnel to obtain a multi-layer twin sub-model.

[0034] Exemplarily, the structural design information of the current tunnel is collected, including structural data such as tunnel line selection, longitudinal section design, cross section design, and auxiliary tunnel design. Then, through three-dimensional simulation technology, three-dimensional simulation modeling is performed in combination with the design information to construct a tunnel twin model. Furthermore, according to the radial direction of the tunnel, that is, the extension direction of the tunnel, the tunnel twin model is divided into multiple segmented models to obtain a multi-layer twin sub-model. Through the multi-layer twin sub-model, the influence of stress on tunnel deformation and displacement can be analyzed in different zones.

[0035] P40: Based on the multi-layer tunnel twin model, the multiple stress field information are divided into stress fields, and tunnel offset information is analyzed respectively to obtain multiple tunnel offset information sets;

[0036] Further, such as Figure 2 As shown, step P40 of the embodiment of the present application also includes:

[0037] P41: Dividing the multiple stress field information according to the range of the multi-layer twin model to obtain multiple levels of stress field information sets, each of which includes multiple levels of stress field information received by each layer of the tunnel twin model;

[0038] P42: Building a tunnel offset analyzer;

[0039] Furthermore, step P42 of the embodiment of the present application also includes:

[0040] P42-1: Based on the multi-layer tunnel twin model, multiple sample level stress field information sets are obtained, and multiple sample tunnel offset information sets are obtained;

[0041] P42-2: Use the multiple sample level stress field information sets and the multiple sample tunnel offset information sets respectively to construct multiple tunnel offset analysis branches and obtain a tunnel offset analyzer.

[0042] P43: Based on the tunnel offset analyzer, tunnel offset analysis is performed according to the multiple levels of stress field information sets to obtain multiple tunnel offset information sets.

[0043] Specifically, the multiple stress field information are divided according to the range of the multi-layer twin model, and multiple stress field information of each sub-model under multiple parallel construction behaviors are obtained to form multiple hierarchical stress field information sets, wherein each hierarchical stress field information set contains multiple hierarchical stress field information of each layer of tunnel twin model. Furthermore, for the multi-layer tunnel twin model, multiple sample hierarchical stress field information are collected according to the hierarchy, thereby forming multiple sample hierarchical stress field information sets, and multiple sample tunnel offset information sets are obtained, wherein the tunnel offset information refers to the direction and amplitude of tunnel deformation and displacement, and each sample tunnel offset information set contains multiple tunnel offset information of a tunnel twin model.

[0044] Further, the multiple sample hierarchical stress field information sets and multiple sample tunnel offset information sets are respectively used as construction data, combined with the principle of machine learning, to construct and train multiple tunnel offset analysis branches, each tunnel offset analysis branch corresponds to a tunnel twin model, and then the tunnel offset analyzer is composed of multiple tunnel offset analysis branches. Further, the multiple hierarchical stress field information sets are input into the tunnel offset analyzer, tunnel offset analysis is performed, and multiple tunnel offset information sets corresponding to the multi-layer tunnel twin model are output, and the multiple tunnel offset information sets can reflect the offset deformation of various parts of the current tunnel under the influence of different stress fields.

[0045] P50: Based on multiple tunnel offset information sets, tunnel offset superposition analysis is performed to obtain multiple superimposed tunnel offset information of the multi-layer tunnel twin model;

[0046] Furthermore, step P50 of the embodiment of the present application also includes:

[0047] P51: In a first tunnel twin submodel in the multi-layer tunnel twin submodel, based on a first tunnel offset information set, performing tunnel offset superposition analysis to obtain first superposition tunnel offset information;

[0048] P52: Continue to perform tunnel offset superposition analysis based on multiple tunnel offset information sets to obtain multiple superimposed tunnel offset information.

[0049] It should be understood that based on multiple tunnel offset information sets, tunnel offset superposition analysis is performed, that is, the offset information generated by multiple stress fields on a single tunnel twin model is superimposed and analyzed as the overall tunnel offset information in the single tunnel twin model. For example, any tunnel twin model is randomly selected as the first tunnel twin model in the multi-layer tunnel twin model, and the first tunnel offset information set corresponding to the first tunnel twin model is extracted from multiple tunnel offset information sets, and all offset information in the first tunnel offset information set is superimposed and calculated, such as tunnel displacement superposition, to obtain the first superimposed tunnel offset information, and so on, continue to perform offset superposition analysis of other tunnel twin models based on multiple tunnel offset information sets to obtain multiple superimposed tunnel offset information, which can reflect the offset deformation of various parts of the current tunnel under the joint influence of multiple stress fields.

[0050] P60: Based on multiple superimposed tunnel offset information, tunnel construction deformation analysis is performed to obtain multiple tunnel deformation modes, and the tunnel deformation mode with the largest proportion is output as the construction monitoring result.

[0051] Further, such as Figure 3 As shown, step P60 of the embodiment of the present application also includes:

[0052] P61: Based on the multi-layer tunnel twin model, multiple sample superimposed tunnel offset information sets are obtained, and multiple sample tunnel deformation mode sets are obtained;

[0053] P62: Using the multiple sample superimposed tunnel offset information sets and the multiple sample tunnel deformation pattern sets, construct multiple tunnel deformation pattern classification branches to obtain a tunnel deformation pattern classifier;

[0054] P63: Inputting the multiple superimposed tunnel offset information into a tunnel deformation pattern classifier to obtain multiple tunnel deformation patterns;

[0055] P64: Output the tunnel deformation mode with the largest proportion and obtain the construction monitoring result.

[0056] Optionally, tunnel construction deformation analysis is performed based on multiple superimposed tunnel offset information to obtain multiple tunnel deformation patterns, where the tunnel deformation pattern refers to the tunnel deformation category, and the tunnel deformation category with the greatest possibility of occurrence is selected for construction monitoring. The tunnel construction deformation analysis needs to be processed by a tunnel deformation pattern classifier, and the tunnel deformation pattern classifier can be constructed in the following manner: for a multi-layer tunnel twin model, sample superimposed offset information is collected separately to obtain multiple sample superimposed tunnel offset information sets, and multiple sample tunnel deformation patterns corresponding to the multiple sample superimposed tunnel offset information are obtained to form multiple sample tunnel deformation pattern sets. Furthermore, the multiple sample superimposed tunnel offset information sets and the multiple sample tunnel deformation pattern sets are used as training data, combined with a fully connected neural network, to construct and train multiple tunnel deformation pattern classification branches, and the multiple tunnel deformation pattern classification branches are merged to obtain a tunnel deformation pattern classifier.

[0057] Furthermore, the multiple superimposed tunnel offset information is input into a tunnel deformation pattern classifier for classification to obtain multiple tunnel deformation patterns, the types of the multiple tunnel deformation patterns are counted, and the tunnel deformation pattern with the largest number of occurrences, that is, the largest proportion, is output as the construction monitoring result, and then targeted measures are taken according to the construction monitoring results to carry out tunnel safety processing.

[0058] In summary, the embodiments of the present application have at least the following technical effects:

[0059] The present application collects multiple construction information superimposed in parallel construction, performs stress field analysis respectively, obtains multiple stress field information, constructs a tunnel twin model, and divides a multi-layer tunnel twin sub-model to perform stress field division and tunnel offset information analysis to obtain multiple tunnel offset information sets. The tunnel construction deformation analysis is performed based on multiple superimposed tunnel offset information, and the tunnel deformation mode with the largest proportion is output as the construction monitoring result.

[0060] The technical effect of improving the effectiveness and accuracy of monitoring by performing tunnel deviation analysis and tunnel deformation pattern monitoring layer by layer and taking targeted treatment measures has been achieved.

[0061] Embodiment 2

[0062] Based on the same inventive concept as the tunnel construction monitoring method based on parallel construction superposition effect analysis in the aforementioned embodiment, Figure 4 As shown, the present application provides a tunnel construction monitoring system based on parallel construction superposition effect analysis, and the system and method embodiments in the present application embodiments are based on the same inventive concept. The system includes:

[0063] A plurality of construction information collection modules 11, wherein the plurality of construction information collection modules 11 are used to collect a plurality of construction information superimposed in parallel construction, wherein each piece of construction information includes a construction type and a construction parameter, and the plurality of construction information includes tunnel construction information and near-tunnel construction information;

[0064] A plurality of stress field information acquisition modules 12, wherein the plurality of stress field information acquisition modules 12 are used to respectively analyze the stress field of the tunnel according to the plurality of construction information to obtain a plurality of stress field information;

[0065] A multi-layer tunnel twin model acquisition module 13, wherein the multi-layer tunnel twin model acquisition module 13 is used to collect design information of the tunnel, construct a tunnel twin model, and divide the multi-layer tunnel twin model;

[0066] A tunnel offset information set acquisition module 14, the tunnel offset information set acquisition module 14 is used to perform stress field division on the multiple stress field information based on the multi-layer tunnel twin model, and respectively perform tunnel offset information analysis to obtain multiple tunnel offset information sets;

[0067] A superimposed tunnel offset information acquisition module 15, wherein the superimposed tunnel offset information acquisition module 15 is used to perform tunnel offset superimposed analysis based on multiple tunnel offset information sets to obtain multiple superimposed tunnel offset information of a multi-layer tunnel twin model;

[0068] The construction monitoring result output module 16 is used to perform tunnel construction deformation analysis based on multiple superimposed tunnel offset information, obtain multiple tunnel deformation modes, and output the tunnel deformation mode with the largest proportion as the construction monitoring result.

[0069] Furthermore, the plurality of stress field information acquisition modules 12 are further configured to perform the following steps:

[0070] Based on multiple sample construction types, multiple sample construction information sets are obtained, and multiple construction stress field sets are obtained;

[0071] Multiple sample construction information sets and multiple construction stress field sets are used to construct multiple stress field analysis branches;

[0072] Integrate multiple stress field analysis branches to obtain stress field analysis channels;

[0073] The plurality of stress field information are obtained, wherein the plurality of stress field information are obtained by inputting a plurality of construction information into the stress field analysis channel.

[0074] Furthermore, the multi-layer tunnel twin model acquisition module 13 is also used to perform the following steps:

[0075] Obtain structural design information of the tunnel;

[0076] Constructing a tunnel twin model of the tunnel according to the structural design information;

[0077] The tunnel twin model is divided according to the radial direction of the tunnel to obtain a multi-layer twin sub-model.

[0078] Furthermore, the tunnel offset information set acquisition module 14 is further configured to perform the following steps:

[0079] The multiple stress field information are divided according to the range of the multi-layer twin model to obtain multiple levels of stress field information sets, each of which includes multiple levels of stress field information received by each layer of the tunnel twin model;

[0080] Build a tunnel deviation analyzer;

[0081] Based on the tunnel deviation analyzer, tunnel deviation analysis is performed according to the multiple levels of stress field information sets to obtain multiple tunnel deviation information sets.

[0082] Furthermore, the tunnel offset information set acquisition module 14 is further configured to perform the following steps:

[0083] Based on the multi-layer tunnel twin model, multiple sample level stress field information sets are obtained, and multiple sample tunnel offset information sets are obtained;

[0084] The plurality of sample level stress field information sets and the plurality of sample tunnel offset information sets are respectively used to construct a plurality of tunnel offset analysis branches to obtain a tunnel offset analyzer.

[0085] Furthermore, the superimposed tunnel offset information acquisition module 15 is further configured to perform the following steps:

[0086] In a first tunnel twin submodel in the multi-layer tunnel twin submodel, based on the first tunnel offset information set, tunnel offset superposition analysis is performed to obtain first superposition tunnel offset information;

[0087] Continue to perform tunnel offset superposition analysis based on multiple tunnel offset information sets to obtain multiple superimposed tunnel offset information.

[0088] Furthermore, the construction monitoring result output module 16 is also used to perform the following steps:

[0089] Based on the multi-layer tunnel twin model, multiple sample superimposed tunnel offset information sets are obtained, and multiple sample tunnel deformation mode sets are obtained;

[0090] Using the multiple sample superimposed tunnel offset information sets and multiple sample tunnel deformation pattern sets, construct multiple tunnel deformation pattern classification branches to obtain a tunnel deformation pattern classifier;

[0091] Inputting the multiple superimposed tunnel offset information into a tunnel deformation mode classifier to obtain multiple tunnel deformation modes;

[0092] The tunnel deformation mode with the largest proportion is output to obtain the construction monitoring result.

[0093] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0094] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0095] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A tunnel construction monitoring method based on parallel construction superposition effect analysis, characterized in that: The method comprises: Collecting multiple construction information superimposed in parallel construction, wherein each construction information includes construction type and construction parameters, and the multiple construction information includes tunnel construction information and near-tunnel construction information, and the near-tunnel construction information refers to construction information outside the tunnel; According to the multiple construction information, respectively analyze the stress field of the tunnel to obtain multiple stress field information; Collecting design information of the tunnel, constructing a tunnel twin model, and dividing it to obtain a multi-layer tunnel twin sub-model; Based on the multi-layer tunnel twin model, the plurality of stress field information are divided into stress fields, and tunnel offset information is analyzed respectively to obtain a plurality of tunnel offset information sets; Based on multiple tunnel offset information sets, tunnel offset superposition analysis is performed to obtain multiple superimposed tunnel offset information of a multi-layer tunnel twin model; According to the multiple superimposed tunnel offset information, tunnel construction deformation analysis is performed to obtain multiple tunnel deformation modes, and the tunnel deformation mode with the largest proportion is output as the construction monitoring result, wherein the tunnel deformation mode refers to the tunnel deformation category; Based on the multi-layer tunnel twin model, the plurality of stress field information are divided into stress fields, and tunnel offset information is analyzed respectively to obtain a plurality of tunnel offset information sets, including: The multiple stress field information are divided according to the range of the multi-layer tunnel twin model to obtain multiple levels of stress field information sets, each of which includes multiple levels of stress field information received by each layer of the tunnel twin model; Build a tunnel deviation analyzer; Based on the tunnel deviation analyzer, performing tunnel deviation analysis according to the multiple hierarchical stress field information sets to obtain multiple tunnel deviation information sets; Based on multiple tunnel offset information sets, tunnel offset superposition analysis is performed to obtain multiple superimposed tunnel offset information of the multi-layer tunnel twin model, including: In a first tunnel twin submodel in the multi-layer tunnel twin submodel, based on the first tunnel offset information set, tunnel offset superposition analysis is performed to obtain first superposition tunnel offset information; Continue to perform tunnel offset superposition analysis based on multiple tunnel offset information sets to obtain multiple superimposed tunnel offset information.

2. The method according to claim 1, characterized in that: According to the multiple construction information, stress field analysis of the tunnel is performed respectively to obtain multiple stress field information, including: Based on multiple sample construction types, multiple sample construction information sets are obtained, and multiple construction stress field sets are obtained; Multiple sample construction information sets and multiple construction stress field sets are used as training data respectively, and multiple stress field analysis branches are constructed in combination with machine learning principles, where each stress field analysis branch corresponds to a sample construction type; Integrate multiple stress field analysis branches to obtain stress field analysis channels; The plurality of stress field information are obtained, wherein the plurality of stress field information are obtained by inputting a plurality of construction information into the stress field analysis channel.

3. The method according to claim 1, characterized in that: The design information of the tunnel is collected, a tunnel twin model is constructed, and a multi-layer tunnel twin sub-model is obtained by dividing the model, including: Obtain structural design information of the tunnel; Constructing a tunnel twin model of the tunnel according to the structural design information; The tunnel twin model is divided according to the radial direction of the tunnel to obtain a multi-layer twin sub-model.

4. The method according to claim 1, characterized in that Build a tunnel deviation analyzer, including: Based on the multi-layer tunnel twin model, multiple sample level stress field information sets are obtained, and multiple sample tunnel offset information sets are obtained; The multiple sample level stress field information sets and the multiple sample tunnel offset information sets are respectively used as construction data, and combined with the principle of machine learning, multiple tunnel offset analysis branches are constructed and trained to obtain a tunnel offset analyzer, wherein each tunnel offset analysis branch corresponds to a tunnel twin model.

5. The method according to claim 1, characterized in that Based on multiple superimposed tunnel offset information, tunnel construction deformation analysis is performed to obtain multiple tunnel deformation modes, and the tunnel deformation mode with the highest probability is output as the construction monitoring result, including: Based on the multi-layer tunnel twin model, multiple sample superimposed tunnel offset information sets are obtained, and multiple sample tunnel deformation mode sets are obtained; Using the multiple sample superimposed tunnel offset information sets and the multiple sample tunnel deformation pattern sets as training data, combined with a fully connected neural network, constructing and training multiple tunnel deformation pattern classification branches, and obtaining a tunnel deformation pattern classifier; Inputting the multiple superimposed tunnel offset information into a tunnel deformation mode classifier to obtain multiple tunnel deformation modes; The tunnel deformation mode with the largest proportion is output to obtain the construction monitoring result.

6. A tunnel construction monitoring system based on parallel construction superposition effect analysis, characterized in that: The system comprises: Multiple construction information collection modules, wherein the multiple construction information collection modules are used to collect multiple construction information superimposed in parallel construction, wherein each construction information includes a construction type and a construction parameter, and the multiple construction information includes tunnel construction information and near-tunnel construction information, wherein the near-tunnel construction information refers to construction information outside the tunnel; A plurality of stress field information acquisition modules, wherein the plurality of stress field information acquisition modules are used to respectively analyze the stress field of the tunnel according to the plurality of construction information to obtain a plurality of stress field information; A multi-layer tunnel twin model acquisition module, the multi-layer tunnel twin model acquisition module is used to collect design information of the tunnel, construct a tunnel twin model, and divide the multi-layer tunnel twin model; A tunnel offset information set acquisition module, the tunnel offset information set acquisition module is used to perform stress field division on the multiple stress field information based on the multi-layer tunnel twin model, and respectively perform tunnel offset information analysis to obtain multiple tunnel offset information sets; A superimposed tunnel offset information acquisition module, wherein the superimposed tunnel offset information acquisition module is used to perform tunnel offset superimposed analysis based on multiple tunnel offset information sets to obtain multiple superimposed tunnel offset information of a multi-layer tunnel twin model; A construction monitoring result output module, the construction monitoring result output module is used to perform tunnel construction deformation analysis according to multiple superimposed tunnel offset information, obtain multiple tunnel deformation modes, and output the tunnel deformation mode with the largest proportion as the construction monitoring result, wherein the tunnel deformation mode refers to the tunnel deformation category; The tunnel offset information set acquisition module is also used to perform the following steps: The multiple stress field information are divided according to the range of the multi-layer tunnel twin model to obtain multiple levels of stress field information sets, each of which includes multiple levels of stress field information received by each layer of the tunnel twin model; Build a tunnel deviation analyzer; Based on the tunnel deviation analyzer, performing tunnel deviation analysis according to the multiple hierarchical stress field information sets to obtain multiple tunnel deviation information sets; The superimposed tunnel offset information acquisition module is further used to perform the following steps: In a first tunnel twin submodel in the multi-layer tunnel twin submodel, based on the first tunnel offset information set, tunnel offset superposition analysis is performed to obtain first superposition tunnel offset information; Continue to perform tunnel offset superposition analysis based on multiple tunnel offset information sets to obtain multiple superimposed tunnel offset information.

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