Intelligent bridge pushing analysis method and system based on temperature sensing

Abstract

The present application relates to the technical field of bridge jacking, and discloses a method and system for intelligent bridge jacking analysis based on temperature sensing, which includes obtaining historical temperature data and corresponding historical pad setting strategies, constructing a temperature sensing jacking analysis model, obtaining a first real-time pad setting strategy, and setting the pads based on the first real-time pad setting strategy. The system corresponds to the method. The present application, by obtaining historical temperature data and historical pad setting strategies of different supports, provides a historical reference data basis and data reference for real-time pad setting, reduces the degree of dependence on the experience of designers or construction personnel, and provides targeted pad setting, and optimizes the force analysis and deformation analysis results between the beam body and the support through the analysis of temperature sensing, provides necessary technical means for optimizing pad setting, and also improves the intelligence of bridge jacking analysis through the temperature sensing jacking analysis model, and finally realizes intelligent bridge jacking analysis based on temperature sensing.

Description

Technical Field

[0001] The present application relates to the technical field of bridge jacking, and specifically to an intelligent bridge jacking analysis method and system based on temperature sensing. Background Art

[0002] With the rapid development of bridge technology, the full length of a single bridge is constantly being updated, which brings with it higher requirements for bridge jacking construction. Due to the increase in the full length of the bridge, the construction time of the jacking construction link has also increased significantly, which has led to the impact of the uncertainty factor of temperature on the safe construction of the bridge in the jacking construction link being amplified. Therefore, it is necessary to study the bridge jacking analysis based on temperature sensing.

[0003] During the jacking construction process, the pads set between the beam body and the support play a role in dispersing force and preventing side slipping, which plays an important role in the jacking construction process. At the same time, it is also a factor that is significantly affected by temperature. However, looking at the existing pad setting process, the inventor found the following problems:

[0004] 1. The selection and setting of pads often rely on the experience of designers or constructors, and lack scientific data reference.

[0005] 2. The same pads are often set on a series of supports involved in the jacking process, which is not targeted.

[0006] 3. When setting, only the force analysis between the beam and the support is often considered, and there is a lack of research on the temperature sensitivity variable. In addition, the budget for the labor required for the bridge jacking is only combined, and the reference to historical settings and the degree of intelligence are both poor.

[0007] In summary, the existing technology urgently needs a technical solution for intelligent bridge jacking analysis based on temperature sensing. Summary of the invention

[0008] The purpose of this application is to provide a temperature-sensing-based intelligent bridge jacking analysis method and system to solve the technical problems raised in the above-mentioned background technology.

[0009] To achieve the above objectives, this application discloses the following technical solutions:

[0010] In a first aspect, the present application discloses a temperature sensing-based intelligent bridge pushing analysis method, the method comprising:

[0011] S1: Obtain historical temperature data and corresponding historical pad setting strategies; the temperature data includes moment temperature information and temperature change information; the historical pad setting strategy is specifically an adaptive setting method of the pad caused by the change between the beam body and the support affected by temperature, wherein the change includes a gap change and a pier top horizontal force change, the adaptive setting method includes a pad thickness selection method and a pad material selection method, and the historical pad setting strategy is for different supports;

[0012] S2: constructing a temperature-sensitive jacking analysis model based on the historical temperature data and the corresponding historical pad setting strategy; the temperature-sensitive jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process due to temperature;

[0013] S3: inputting the real-time temperature data into the temperature-sensing push analysis model and running the model to obtain a first real-time cushion block setting strategy;

[0014] S4: Setting pads between the beam and the support during the bridge pushing process based on the first real-time pad setting strategy.

[0015] Preferably, the moment temperature information is specifically the temperature value corresponding to each moment; and the temperature change information is specifically the change of the temperature value with time.

[0016] Preferably, the gap change is used to characterize the change in the gap value between the beam and the support caused by any one or more star marks in the beam and the support due to temperature change; the pier top horizontal force change is used to characterize the change in the pier top horizontal force value between the beam and the support caused by temperature change.

[0017] Preferably, the thickness selection method of the pad block is used to select a pad block of corresponding thickness based on the change in the gap; the material selection method of the pad block is used to select a pad block of corresponding material based on the change in the horizontal force on the pier top.

[0018] Preferably, the construction of the temperature sensing push analysis model based on the historical temperature data and the corresponding historical pad setting strategy specifically includes the following steps:

[0019] A1: Matching the historical temperature data with the historical pad setting strategy based on the time series to obtain a temperature sensing pad execution relationship, wherein the temperature sensing pad execution relationship is used to characterize different pad setting strategies corresponding to temperature sensing corresponding to different temperature data;

[0020] A2: storing the temperature sensing pad execution relationship into a preset temperature sensing push analysis learning model; the temperature sensing push analysis learning model is configured to output a corresponding pad setting strategy based on the input temperature data;

[0021] A3: Generate simulated temperature data and input it into the temperature sensing push analysis learning model, obtain the simulated pad setting strategy and perform manual verification, update the temperature sensing push analysis learning model based on the result of the manual verification, and repeat step A3 until the accuracy of the manual verification is greater than or equal to the preset accuracy threshold;

[0022] A4: Output the temperature sensing push analysis learning model corresponding to the manually verified accuracy greater than or equal to the preset accuracy threshold and define it as the temperature sensing push analysis model.

[0023] Preferably, the intelligent bridge pushing analysis method based on temperature sensing further includes:

[0024] S21: Obtaining the historical pushing length and the corresponding execution relationship of the temperature sensing pad;

[0025] S22: constructing a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding execution relationship of the temperature-sensitive pad; the temperature-sensitive jacking length jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process based on the jacking length and the temperature;

[0026] S23: inputting the real-time temperature data and the real-time jacking length into the temperature-sensitive jacking length jacking analysis model and running the model to obtain a second real-time cushion block setting strategy;

[0027] S24: Setting pads between the beam and the support during the bridge pushing process based on the second real-time pad setting strategy.

[0028] Preferably, the acquired historical jacking length and the corresponding jacking length in the execution relationship of the temperature sensing pad are specifically the length of the jacked beam body completed during the jacking construction process;

[0029] The jacking length is used to characterize the changes between the beam body and the support during the jacking process caused by different jacking lengths for the same temperature sensitivity.

[0030] Preferably, the construction of a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding execution relationship of the temperature-sensitive pad comprises the following steps:

[0031] B1: Matching the historical pushing length with the temperature-sensing pad execution relationship based on the time series to obtain the temperature-sensing pushing length pad execution relationship; the temperature-sensing pushing length pad execution relationship is used to characterize the different pad setting strategies corresponding to the temperature sensing corresponding to different pushing lengths and different temperature data;

[0032] B2: using the temperature-sensing push-pushing length pad execution relationship to update the temperature-sensing push-pushing block execution relationship in the temperature-sensing push-pushing analysis model, obtaining a temperature-sensing push-pushing length push-pushing analysis learning model and performing manual verification, updating the temperature-sensing push-pushing length push-pushing analysis learning model based on the result of the manual verification, and repeatedly executing step B2 until the accuracy of the manual verification is greater than or equal to a preset accuracy threshold;

[0033] B3: Output the temperature-sensing pushing length pushing analysis learning model corresponding to the manually verified accuracy rate being greater than or equal to the preset accuracy rate threshold and define it as the temperature-sensing pushing length pushing analysis model.

[0034] In a second aspect, the present application discloses a temperature-sensing-based intelligent bridge pushing analysis system, which is applicable to the temperature-sensing-based intelligent bridge pushing analysis method as described above, and is characterized in that the system comprises:

[0035] A first historical data acquisition module, wherein the first historical data acquisition module is configured to: acquire historical temperature data and corresponding historical pad setting strategies; the temperature data includes moment temperature information and temperature change information; the historical pad setting strategy is specifically an adaptive setting method of the pad caused by the change between the beam body and the support caused by the temperature, wherein the change includes a gap change and a pier top horizontal force change, and the adaptive setting method includes a pad thickness selection method and a pad material selection method;

[0036] A temperature-sensitive jacking analysis model construction module, wherein the temperature-sensitive jacking analysis model construction module is configured to: construct a temperature-sensitive jacking analysis model based on the historical temperature data and the corresponding historical pad setting strategy; the temperature-sensitive jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process due to temperature;

[0037] A first real-time pad setting strategy generating module, wherein the first real-time pad setting strategy generating module is configured to: input real-time temperature data into the temperature sensing push analysis model and run the model to obtain a first real-time pad setting strategy;

[0038] The first real-time pad setting strategy execution module is configured to: set the pads between the beam and the support during the bridge pushing process based on the first real-time pad setting strategy.

[0039] Preferably, the system further comprises:

[0040] A second historical data acquisition module, wherein the second historical data acquisition module is configured to: acquire a historical pushing length and a corresponding execution relationship of the temperature sensing pad;

[0041] A module for constructing a temperature-sensitive jacking length jacking analysis model, wherein the module is configured to: construct a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding execution relationship of the temperature-sensitive pad; the temperature-sensitive jacking length jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process based on the jacking length and the temperature;

[0042] A second real-time pad setting strategy generating module, wherein the second real-time pad setting strategy generating module is configured to: input the real-time temperature data and the real-time jacking length into the temperature-sensitive jacking length jacking analysis model and run the model to obtain a second real-time pad setting strategy;

[0043] The second real-time pad setting strategy execution module is configured to: set the pads between the beam and the support during the bridge pushing process based on the second real-time pad setting strategy.

[0044] Beneficial effects: The temperature-sensing-based intelligent bridge jacking analysis method and system of the present application, by acquiring historical temperature data and historical pad setting strategies of different supports, provides a historical data basis and data reference for real-time pad setting, reduces the degree of dependence on the experience of designers or construction personnel, and provides targeted pad setting, and optimizes the force analysis and deformation analysis results between the beam and the support through the analysis of temperature sensing, provides the necessary technical means for optimizing the pad setting, and also improves the intelligence of the bridge jacking analysis through the temperature-sensing jacking analysis model, realizing intelligent bridge jacking analysis based on temperature sensing. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 A flowchart of a temperature sensing-based intelligent bridge jacking analysis method provided in an embodiment of the present application;

[0047] Figure 2 Schematic diagram of the calculation of the horizontal force on the top of the pier in the actual jacking construction provided in the embodiment of the present application Figure 1 ;

[0048] Figure 3 Schematic diagram of the calculation of the horizontal force on the top of the pier in the actual jacking construction provided in the embodiment of the present application Figure 2 ;

[0049] Figure 4 This is a structural block diagram of the temperature sensing-based intelligent bridge jacking analysis system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0051] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0052] In a first aspect, this embodiment discloses Figure 1 A temperature sensing-based intelligent bridge pushing analysis method is shown, the method comprising:

[0053] S1: Obtain historical temperature data and corresponding historical pad setting strategies. Temperature data includes moment temperature information and temperature change information. The historical pad setting strategy is specifically an adaptive setting method of pads caused by changes between the beam body and the support caused by temperature, wherein the changes include gap changes and pier top horizontal force changes, and the adaptive setting method includes a pad thickness selection method and a pad material selection method, and the historical pad setting strategy is targeted at different supports.

[0054] S2: Construct a temperature-sensitive jacking analysis model based on historical temperature data and corresponding historical pad setting strategies. The temperature-sensitive jacking analysis model is used to output the corresponding pad setting strategy based on the analysis results of the changes between the beam and the support during the jacking process due to temperature.

[0055] S3: Input the real-time temperature data into the temperature sensing push analysis model and run the model to obtain the first real-time pad setting strategy.

[0056] S4: Setting pads between the beam and the support during the bridge pushing process based on the first real-time pad setting strategy.

[0057] In this embodiment, by obtaining historical temperature data and historical pad setting strategies of different supports, a historical data basis and data reference are provided for real-time pad setting, which reduces the reliance on the experience of designers or construction personnel and provides targeted pad setting. The force analysis and deformation analysis results between the beam and the support are optimized through analysis of temperature sensation, which provides the necessary technical means for optimizing pad setting. The intelligence of bridge pushing analysis is improved through the temperature sensing pushing analysis model, thereby realizing intelligent bridge pushing analysis based on temperature sensing.

[0058] Specifically, the moment temperature information is specifically the temperature value corresponding to each moment. The temperature change information is specifically the change of the temperature value with time.

[0059] The acquisition of the temperature information at each moment provides a data basis for acquiring the temperature change information. In this embodiment, the setting of the cushion block is optimized by the temperature sense corresponding to the temperature change information.

[0060] Specifically, the gap change is used to characterize the change in the gap value between the beam and the support caused by any one or more of the star marks in the beam and the support due to temperature change. The pier top horizontal force change is used to characterize the change in the pier top horizontal force value between the beam and the support due to temperature change.

[0061] During the process of bridge jacking construction, it is well known to those skilled in the art that temperature changes will have a direct impact on the deformation of the beam and the support, and this deformation directly leads to a change in the gap value. The changed gap value causes the support to be unable to provide sufficient support for the beam, so pads are needed to fill it in to prevent construction accidents caused by insufficient support. Furthermore, temperature changes will affect the horizontal force on the pier top between the beam and the support, the most direct impact being the temperature force, which leads to a change in the value of the horizontal force on the pier top. When the changed horizontal force on the pier top is greater than the jacking friction force, the beam will slide, so pads are needed to fill it in to prevent construction accidents caused by insufficient horizontal force on the pier top. In a simple example, Figure 2 and Figure 3 The schematic diagram of the calculation of the longitudinal horizontal force of the pier top steel beam obtained in actual construction shows that the changes in the horizontal force on the pier top show significant differences when the overall temperature rise is different.

[0062] Specifically, the pad thickness selection method is used to select a pad of corresponding thickness based on the gap change. The pad material selection method is used to select a pad of corresponding material based on the pier top horizontal force change.

[0063] In this embodiment, different gap change requirements are met by selecting pads of different thicknesses, and different pier top horizontal force change requirements are met by selecting pads of different materials.

[0064] Specifically, a temperature sensing push analysis model is constructed based on historical temperature data and corresponding historical pad setting strategies, which specifically includes the following steps:

[0065] A1: Match historical temperature data with historical pad setting strategies based on time series to obtain a temperature sensing pad execution relationship, which is used to characterize different pad setting strategies corresponding to temperature sensing corresponding to different temperature data.

[0066] A2: The temperature sensing pad execution relationship is stored in a preset temperature sensing push analysis learning model. The temperature sensing push analysis learning model is configured to output a corresponding pad setting strategy based on the input temperature data.

[0067] A3: Generate simulated temperature data and input it into the temperature sensing push analysis learning model, obtain the simulated pad setting strategy and perform manual verification, update the temperature sensing push analysis learning model based on the results of manual verification, and repeat step A3 until the accuracy of manual verification is greater than or equal to the preset accuracy threshold.

[0068] A4: Output the temperature sensing push analysis learning model corresponding to the manually verified accuracy greater than or equal to the preset accuracy threshold and define it as the temperature sensing push analysis model.

[0069] It should be noted that the model building technology used to construct the temperature-sensitive jacking analysis model in this embodiment is any one of the existing model building technologies, which aims to realize intelligent bridge jacking analysis based on the execution relationship of temperature-sensitive pads and generate a first real-time pad setting strategy.

[0070] The working principle of this embodiment is:

[0071] Based on the historical temperature data and the corresponding historical pad setting strategy, a data basis and data reference are provided for the jacking analysis of this jacking construction. In this embodiment, the real-time temperature data is specifically the temperature data obtained according to the meteorological conditions of the jacking construction environment. The real-time temperature data is used to run the obtained temperature-sensing jacking analysis model to generate the first real-time pad setting strategy, which provides data support for the scientific and targeted pad setting during jacking construction.

[0072] Specifically, the intelligent bridge pushing analysis method based on temperature sensing also includes:

[0073] S21: Obtain the historical pushing length and the corresponding execution relationship of the temperature sensing pad.

[0074] S22: Construct a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding temperature-sensitive pad execution relationship. The temperature-sensitive jacking length jacking analysis model is used to output a corresponding pad setting strategy based on the analysis results of the changes between the beam body and the support during the jacking process based on the jacking length and the temperature.

[0075] S23: inputting the real-time temperature data and the real-time jacking length into the temperature-sensing jacking length jacking analysis model and running the model to obtain a second real-time cushion block setting strategy.

[0076] S24: Setting pads between the beam and the support during the bridge pushing process based on the second real-time pad setting strategy.

[0077] It should be noted that, combined with Figure 2 and Figure 3 The schematic diagram of the calculation of the longitudinal horizontal force of the steel beam on the pier top obtained in the actual construction shows that different pier numbers correspond to different jacking lengths. It is not difficult to find that the jacking length also has a significant effect on the change of the horizontal force on the pier top. Based on the common knowledge in the field, those skilled in the art can deduce in this embodiment that the change of the jacking length directly affects the change of the horizontal force value on the pier top, thereby directly affecting the pad setting strategy. Therefore, as a preferred scheme of this embodiment, by constructing a temperature-sensitive jacking length jacking analysis model and obtaining a second real-time pad setting strategy based on the real-time jacking length, the scientific nature and pertinence of the pad setting are further improved, and the degree of dependence on the experience of designers or construction personnel is reduced and the intelligence of bridge jacking analysis is improved.

[0078] It should be further explained that, in the present embodiment, the construction and working principle of the temperature-sensing pushing length pushing analysis model correspond to the temperature-sensing pushing length pushing analysis model in the previous text. Therefore, the contents not specifically described in the temperature-sensing pushing length pushing analysis model may have, but are not limited to, the same functional definition, working principle and technical effect as the temperature-sensing pushing analysis model in the previous text, and this text will not elaborate on them.

[0079] Specifically, the jacking length in the historical jacking length and the corresponding temperature-sensitive pad execution relationship is obtained, which is specifically the length of the jacking beam body completed during the jacking construction process.

[0080] The jacking length is used to characterize the changes between the beam and the support during the jacking process caused by different jacking lengths for the same temperature sensitivity.

[0081] Specifically, a temperature-sensitive jacking length jacking analysis model is constructed based on the historical jacking length and the corresponding temperature-sensitive pad execution relationship, which specifically includes the following steps:

[0082] B1: Based on the time series, the historical jacking length is matched with the temperature sensing pad execution relationship to obtain the temperature sensing jacking length pad execution relationship. The temperature sensing jacking length pad execution relationship is used to characterize the different pad setting strategies corresponding to the temperature sensing corresponding to different jacking lengths and different temperature data.

[0083] B2: Use the temperature-sensing jacking length pad execution relationship to update the temperature-sensing pad execution relationship in the temperature-sensing jacking analysis model, obtain the temperature-sensing jacking length jacking analysis learning model and perform manual verification, update the temperature-sensing jacking length jacking analysis learning model based on the results of manual verification, and repeat step B2 until the accuracy of manual verification is greater than or equal to the preset accuracy threshold.

[0084] B3: Output the temperature-sensing push-up length push-up analysis learning model corresponding to the manually verified accuracy greater than or equal to the preset accuracy threshold and define it as the temperature-sensing push-up length push-up analysis model.

[0085] In a second aspect, this embodiment discloses Figure 4 The intelligent bridge pushing analysis system based on temperature sensing is shown, and the system is applicable to the intelligent bridge pushing analysis method based on temperature sensing as described above, and is characterized in that the system includes:

[0086] The first historical data acquisition module is configured to: acquire historical temperature data and corresponding historical pad setting strategies. The temperature data includes moment temperature information and temperature change information. The historical pad setting strategy is specifically an adaptive setting method of the pad caused by the change between the beam body and the support caused by the temperature, wherein the change includes the gap change and the pier top horizontal force change, and the adaptive setting method includes the pad thickness selection method and the pad material selection method.

[0087] The module for constructing a temperature-sensitive top-pushing analysis model is configured as follows: constructing a temperature-sensitive top-pushing analysis model based on historical temperature data and corresponding historical pad setting strategies. The temperature-sensitive top-pushing analysis model is used to output corresponding pad setting strategies based on the analysis results of the changes between the beam and the support during the top-pushing process due to temperature.

[0088] The first real-time pad setting strategy generation module is configured to: input the real-time temperature data into the temperature sensing push analysis model and run the model to obtain the first real-time pad setting strategy.

[0089] The first real-time pad setting strategy execution module is configured to: set the pads between the beam and the support during the bridge pushing process based on the first real-time pad setting strategy.

[0090] Specifically, the system also includes:

[0091] The second historical data acquisition module is configured to obtain the historical pushing length and the corresponding temperature sensing pad execution relationship.

[0092] The module for constructing a temperature-sensitive jacking length jacking analysis model is configured as follows: constructing a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding temperature-sensitive pad execution relationship. The temperature-sensitive jacking length jacking analysis model is used to output the corresponding pad setting strategy based on the analysis results of the changes between the beam and the support during the jacking process based on the jacking length and temperature.

[0093] The second real-time pad setting strategy generation module is configured to: input the real-time temperature data and the real-time jacking length into the temperature-sensing jacking length jacking analysis model and run the model to obtain the second real-time pad setting strategy.

[0094] The second real-time pad setting strategy execution module is configured to: set the pads between the beam and the support during the bridge pushing process based on the second real-time pad setting strategy.

[0095] It should be noted that the temperature-sensing-based intelligent bridge pushing analysis system in this embodiment corresponds to the temperature-sensing-based intelligent bridge pushing analysis method in the previous text. Therefore, the contents not specifically described in the temperature-sensing-based intelligent bridge pushing analysis system in this embodiment may have, but are not limited to, the same functional definition, working principle and technical effect as the temperature-sensing-based intelligent bridge pushing analysis method in the previous text, and this text will not go into details here.

[0096] In summary, the temperature-sensing-based intelligent bridge jacking analysis method and system of this embodiment, by acquiring historical temperature data and historical pad setting strategies of different supports, provides a historical data basis and data reference for real-time pad setting, reduces the degree of dependence on the experience of designers or construction personnel, and provides targeted pad setting, and optimizes the force analysis and deformation analysis results between the beam and the support through the analysis of temperature sensing, provides the necessary technical means for optimizing the pad setting, and also improves the intelligence of the bridge jacking analysis through the temperature-sensing jacking analysis model, realizing intelligent bridge jacking analysis based on temperature sensing.

[0097] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to implement the functions described herein, or a combination thereof. For software implementation, part or all of the processes of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a computer. Computer-readable storage media can include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.

[0098] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A temperature-sensing-based intelligent bridge pushing analysis method, characterized in that: The method includes: S1: Acquire historical temperature data and corresponding historical pad setting strategies; the temperature data includes moment temperature information and temperature change information; the historical pad setting strategy is specifically an adaptive setting method of the pad caused by the change between the beam body and the support affected by temperature, wherein the change includes a gap change and a pier top horizontal force change, the adaptive setting method includes a pad thickness selection method and a pad material selection method, and the historical pad setting strategy is for different supports; S2: constructing a temperature-sensitive jacking analysis model based on the historical temperature data and the corresponding historical pad setting strategy; the temperature-sensitive jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process due to temperature; S3: inputting the real-time temperature data into the temperature-sensing push analysis model and running the model to obtain a first real-time cushion block setting strategy; S4: Setting pads between the beam and the support during the bridge pushing process based on the first real-time pad setting strategy; The step of constructing a temperature sensing push analysis model based on the historical temperature data and the corresponding historical pad setting strategy specifically includes the following steps: A1: Matching the historical temperature data with the historical pad setting strategy based on the time series to obtain a temperature sensing pad execution relationship, wherein the temperature sensing pad execution relationship is used to characterize different pad setting strategies corresponding to temperature sensing corresponding to different temperature data; A2: storing the temperature sensing pad execution relationship into a preset temperature sensing push analysis learning model; the temperature sensing push analysis learning model is configured to output a corresponding pad setting strategy based on the input temperature data; A3: Generate simulated temperature data and input it into the temperature sensing push analysis learning model, obtain the simulated pad setting strategy and perform manual verification, update the temperature sensing push analysis learning model based on the result of the manual verification, and repeat step A3 until the accuracy of the manual verification is greater than or equal to the preset accuracy threshold; A4: Outputting the temperature sensing push analysis learning model corresponding to the manually verified accuracy rate being greater than or equal to a preset accuracy rate threshold and defining it as the temperature sensing push analysis model; The intelligent bridge pushing analysis method based on temperature sensing also includes: S21: Obtaining the historical pushing length and the corresponding execution relationship of the temperature sensing pad; S22: constructing a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding execution relationship of the temperature-sensitive pad; the temperature-sensitive jacking length jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process based on the jacking length and the temperature; S23: inputting the real-time temperature data and the real-time jacking length into the temperature-sensitive jacking length jacking analysis model and running the model to obtain a second real-time cushion block setting strategy; S24: Setting pads between the beam and the support during the bridge pushing process based on the second real-time pad setting strategy.

2. The intelligent bridge pushing analysis method based on temperature sensing according to claim 1 is characterized in that: The moment temperature information specifically refers to the temperature value corresponding to each moment; the temperature change information specifically refers to the change of the temperature value with time.

3. The intelligent bridge pushing analysis method based on temperature sensing according to claim 1 is characterized in that: The gap change is used to characterize the change in the gap value between the beam and the support caused by any one or more star marks in the beam and the support due to temperature changes; the pier top horizontal force change is used to characterize the change in the pier top horizontal force value between the beam and the support caused by temperature changes.

4. The intelligent bridge pushing analysis method based on temperature sensing according to claim 1 is characterized in that: The pad block thickness selection method is used to select a pad block of corresponding thickness based on the gap change; the pad block material selection method is used to select a pad block of corresponding material based on the pier top horizontal force change.

5. The intelligent bridge pushing analysis method based on temperature sensing according to claim 1 is characterized in that: The acquisition of the historical jacking length and the corresponding jacking length in the execution relationship of the temperature sensing pad is specifically the length of the jacked beam completed during the jacking construction process; The jacking length is used to characterize the changes between the beam body and the support during the jacking process caused by different jacking lengths for the same temperature sensitivity.

6. The intelligent bridge pushing analysis method based on temperature sensing according to claim 5 is characterized in that: The method of constructing a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding temperature-sensitive pad execution relationship specifically includes the following steps: B1: Matching the historical pushing length with the temperature-sensing pad execution relationship based on the time series to obtain the temperature-sensing pushing length pad execution relationship; the temperature-sensing pushing length pad execution relationship is used to characterize the different pad setting strategies corresponding to the temperature sensing corresponding to different pushing lengths and different temperature data; B2: using the temperature-sensing push-pushing length pad execution relationship to update the temperature-sensing push-pushing block execution relationship in the temperature-sensing push-pushing analysis model, obtaining a temperature-sensing push-pushing length push-pushing analysis learning model and performing manual verification, updating the temperature-sensing push-pushing length push-pushing analysis learning model based on the result of the manual verification, and repeatedly executing step B2 until the accuracy of the manual verification is greater than or equal to a preset accuracy threshold; B3: Output the temperature-sensing pushing length pushing analysis learning model corresponding to the manually verified accuracy rate being greater than or equal to the preset accuracy rate threshold and define it as the temperature-sensing pushing length pushing analysis model.

7. A temperature-sensing-based intelligent bridge pushing analysis system, the system being applicable to the temperature-sensing-based intelligent bridge pushing analysis method as described in any one of claims 1 to 6, characterized in that: The system includes: A first historical data acquisition module, wherein the first historical data acquisition module is configured to: acquire historical temperature data and corresponding historical pad setting strategies; the temperature data includes moment temperature information and temperature change information; the historical pad setting strategy is specifically an adaptive setting method of the pad caused by the change between the beam body and the support caused by the temperature, wherein the change includes a gap change and a pier top horizontal force change, and the adaptive setting method includes a pad thickness selection method and a pad material selection method; A temperature-sensitive jacking analysis model construction module, wherein the temperature-sensitive jacking analysis model construction module is configured to: construct a temperature-sensitive jacking analysis model based on the historical temperature data and the corresponding historical pad setting strategy; the temperature-sensitive jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process due to temperature; A first real-time pad setting strategy generating module, wherein the first real-time pad setting strategy generating module is configured to: input real-time temperature data into the temperature sensing push analysis model and run the model to obtain a first real-time pad setting strategy; The first real-time pad setting strategy execution module is configured to: set the pads between the beam and the support during the bridge pushing process based on the first real-time pad setting strategy.

8. The temperature sensing-based intelligent bridge pushing analysis system according to claim 7 is characterized in that: The system also includes: A second historical data acquisition module, wherein the second historical data acquisition module is configured to: acquire a historical pushing length and a corresponding execution relationship of the temperature sensing pad; A module for constructing a temperature-sensitive jacking length jacking analysis model, wherein the module is configured to: construct a temperature-sensitive jacking length jacking analysis model based on the historical jacking length and the corresponding execution relationship of the temperature-sensitive pad; the temperature-sensitive jacking length jacking analysis model is used to output a corresponding pad setting strategy based on the analysis result of the change between the beam body and the support during the jacking process based on the jacking length and the temperature; A second real-time pad setting strategy generating module, wherein the second real-time pad setting strategy generating module is configured to: input the real-time temperature data and the real-time jacking length into the temperature-sensitive jacking length jacking analysis model and run the model to obtain a second real-time pad setting strategy; The second real-time pad setting strategy execution module is configured to: set the pads between the beam and the support during the bridge pushing process based on the second real-time pad setting strategy.

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