A method, device and equipment for evaluating stability of an extra-large bridge and a readable storage medium

Abstract

The application provides a super-large bridge stability evaluation method, device and equipment and a readable storage medium, relates to the technical field of bridges, and comprises the following steps: obtaining preset depths of at least two stability evaluation points and temperature information collected by two temperature sensor groups of a super-large bridge scale model within preset temperature loading time; calculating a temperature theoretical value of each stability evaluation point according to the preset depth of each stability evaluation point, temperature information of the first temperature sensor group and a preset theoretical temperature formula; calculating a first characteristic value of each stability evaluation point according to each temperature theoretical value and a temperature detection value collected by the corresponding second temperature sensor group; and evaluating the stability of the super-large bridge according to the numerical value of each first characteristic value. The application is based on a super-large bridge scale model, restores the natural temperature environment of the super-large bridge accurately, realizes the stability evaluation of the super-large bridge and provides guidance for engineering design.

Description

Technical Field

[0001] This invention relates to the field of bridge technology, and more specifically, to a method, apparatus, equipment, and readable storage medium for evaluating the stability of extra-large bridges. Background Technology

[0002] In recent years, with the continuous development of high-speed railways in my country, more and more high-speed railways need to use extra-long span bridges to cross major rivers and mountain valleys. Due to the limitations of existing technology, most extra-long bridges still use ballasted track, such as the Wuhan Tianxingzhou Extra-Large Bridge and the Zhenjiang Wufengshan Yangtze River Bridge. Existing technologies lack further in-depth research on laying ballastless track on extra-long bridges. In addition, since temperature is a key factor affecting the stability of extra-long bridges, existing technologies lack quantitative analysis of the effect of temperature on the stability of extra-long bridges. Therefore, there is an urgent need for a stability evaluation method for extra-long bridges, which can study extra-long bridges based on ballastless track and quantitatively evaluate the stability of their overall structure. Summary of the Invention

[0003] The purpose of this invention is to provide a method, apparatus, device, and readable storage medium for evaluating the stability of extra-large bridges, thereby improving the aforementioned problems. To achieve the above objective, the technical solution adopted by this invention is as follows:

[0004] Firstly, this application provides a method for evaluating the stability of extra-large bridges, the method comprising:

[0005] The system acquires the preset depth of at least two stability evaluation points and the temperature information collected by two temperature sensor groups of the scaled-down model of the super-large bridge within a preset temperature loading time. The stability evaluation points are set inside the scaled-down model of the super-large bridge. The first temperature sensor group includes a first temperature sensor and a second temperature sensor. The first temperature sensor and the second temperature sensor are set on the surface of the scaled-down model of the super-large bridge. The second temperature sensor group corresponds one-to-one with the position of the stability evaluation points.

[0006] The theoretical temperature value of each stability evaluation point is calculated based on the preset depth of each stability evaluation point, the temperature information of the first temperature sensor group, and the preset theoretical temperature formula.

[0007] The first characteristic value of each stability evaluation point is calculated based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group.

[0008] The stability of the mega-bridge is evaluated based on the magnitude of each of the first eigenvalues.

[0009] Secondly, this application also provides a stability evaluation device for extra-large bridges, the device comprising:

[0010] The acquisition module is used to acquire the preset depth of at least two stability evaluation points and the temperature information collected by two temperature sensor groups of the scale model of the super bridge within a preset temperature loading time. The stability evaluation points are set inside the scale model of the super bridge. The first temperature sensor group includes a first temperature sensor and a second temperature sensor. The first temperature sensor and the second temperature sensor are set on the surface of the scale model of the super bridge. The second temperature sensor group corresponds one-to-one with the position of the stability evaluation points.

[0011] The first processing module is used to calculate the theoretical temperature value of each stability evaluation point based on the preset depth of each stability evaluation point, the temperature information of the first temperature sensor group, and the preset theoretical temperature formula.

[0012] The second processing module is used to calculate, based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group, to obtain the first characteristic value of each stability evaluation point.

[0013] The judgment module is used to evaluate the stability of the super-large bridge based on the numerical value of each of the first feature values.

[0014] Thirdly, this application also provides a stability evaluation device for extra-large bridges, comprising:

[0015] Memory, used to store computer programs;

[0016] A processor is used to implement the steps of the stability evaluation method for the super-large bridge when executing the computer program.

[0017] Fourthly, this application also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the steps described above based on the stability evaluation method for super-large bridges.

[0018] The beneficial effects of this invention are as follows:

[0019] This invention, based on the layout of stability evaluation points, calculates the theoretical temperature value for each stability evaluation point and then obtains the first characteristic value corresponding to that point. This invention can be used to study large bridges with ballastless track, and simultaneously quantitatively analyzes the impact of temperature on the stability of these bridges.

[0020] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the process for evaluating the stability of a super-large bridge as described in an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram of the structure of the super-large bridge stability evaluation device described in this embodiment of the invention;

[0024] Figure 3 This is a schematic diagram of the structure of the third processing module in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of the fourth processing module in an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of the structure of the super-large bridge stability evaluation equipment described in this embodiment of the invention;

[0027] Figure 6 This is a schematic diagram of the scaled-down model of the super-large bridge in an embodiment of the present invention;

[0028] Marked in the image:

[0029] 901. Acquisition Module; 902. First Processing Module; 903. Second Processing Module; 904. Judgment Module; 905. Third Processing Module; 906. Fourth Processing Module; 9041. First Calculation Unit; 9042. Second Calculation Unit; 9043. Third Calculation Unit; 9044. Fourth Calculation Unit; 9045. First Judgment Unit; 9051. First Acquisition Unit; 9052. Fifth Calculation Unit; 9053. Sixth Calculation Unit; 9054. Seventh Calculation Unit; 90541. Eleventh Calculation Unit; 90542. Twelfth Calculation Unit; 90543. Thirteenth Calculation Unit Calculation unit; 90544, Fourteenth calculation unit; 90545, Second judgment unit; 9061, Second acquisition unit; 9062, Eighth calculation unit; 9063, Ninth calculation unit; 9064, Tenth calculation unit; 90641, Fifteenth calculation unit; 90642, Sixteenth calculation unit; 90643, Seventeenth calculation unit; 90644, Eighteenth calculation unit; 90645, Third judgment unit; 800, Extra-large bridge stability evaluation equipment; 801, Processor; 802, Memory; 803, Multimedia component; 804, I / O interface; 805, Communication component. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0031] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0032] Example 1:

[0033] This invention first manufactures a scaled-down model of a super-large bridge with ballastless track. The model platform can be produced as a single unit, and its dimensions should be determined according to experimental requirements, specifically:

[0034] The model length is: original total bridge length / scale ratio + 1m to 2m;

[0035] The model width is: original total width of the bridge / scale reduction ratio + 1m to 2m;

[0036] The model height is: original total bridge height / scale ratio + 0.5m to 1m.

[0037] like Figure 6 As shown, a long-span cable-stayed bridge will be briefly described as an example. A long-span cable-stayed bridge includes pier bases, main towers, main beams, and cable stays connecting the main beams and tower columns. Ballastless track structures are laid on the surface of the main beams. Different types of ballastless track structures can be laid according to the test requirements.

[0038] The scaled-down model must be surrounded by transparent, heat-insulating glass with a transparency of no less than 70% and a heat transfer coefficient of less than 1 W / (m²). 2 •k) can adopt a vacuum composite hollow glass structure to achieve good heat insulation effect. The glass can be closed. The bottom of the model platform is a base. The height of the model base can be adjusted according to the test requirements.

[0039] In this invention, the model base can be equipped with a hot air inlet and a heating air outlet to simulate the high-temperature environment of the super-large bridge; the side of the model can be equipped with a cold air inlet and a cooling air outlet to simulate the low-temperature environment of the super-large bridge; the side of the model can also be equipped with a humidifier inlet to simulate the humidity environment of the super-large bridge. This scaled-down model is equipped with an intelligent temperature and humidity control system for precise parameter control.

[0040] In this invention, a sliding groove can also be provided on the model base. The length of a single sliding groove is 0.02m narrower than the internal length of the test platform, and the width of a single sliding groove is 0.05m to 0.1m. The sliding groove is used for the longitudinal movement of the loading device on the model base.

[0041] This embodiment provides a method for evaluating the stability of extra-large bridges. (See also...) Figure 1 The figure shows that this method includes steps S1 to S4, specifically:

[0042] Step S1: Obtain the preset depth of at least two stability evaluation points and the temperature information collected by two temperature sensor groups of the scaled-down model of the super bridge within a preset temperature loading time. The stability evaluation points are set inside the scaled-down model of the super bridge. The first temperature sensor group includes a first temperature sensor and a second temperature sensor. The first temperature sensor and the second temperature sensor are set on the surface of the scaled-down model of the super bridge. The second temperature sensor group corresponds one-to-one with the position of the stability evaluation points.

[0043] In step S1, using pre-collected meteorological data such as solar radiation, ambient wind speed, and relative humidity, a 24-hour temperature and humidity field is simulated using CFD numerical simulation based on the principle of thermal radiation, realistically reproducing the real-time temperature and humidity changes on site. Real-time intelligent loading is achieved through an intelligent temperature and humidity control system. Two temperature sensor groups collect corresponding data. This invention can simulate special climatic conditions such as extreme large temperature differences, sustained high temperatures, sudden temperature rises, and sudden temperature drops.

[0044] The first temperature sensor is used to collect the initial surface temperature of the scaled-down model of the super-large bridge, and the second temperature sensor is used to collect the surface temperature of the scaled-down model of the super-large bridge after a preset temperature loading time.

[0045] Step S2: Calculate the theoretical temperature value of each stability evaluation point based on the preset depth of each stability evaluation point, the temperature information of the first temperature sensor group, and the preset theoretical temperature formula.

[0046] In step S2, the formula for calculating the theoretical temperature value at each stability evaluation point is:

[0047]

[0048] In the above formula, Ti represents the theoretical temperature value corresponding to the position of stability evaluation point i; T I This represents the initial surface temperature of the scaled-down model of the super-large bridge, as collected by the first temperature sensor; T S λ represents the surface temperature of the scaled model of the super bridge collected by the second temperature sensor after time t; hi represents the preset depth h when the stability evaluation point is i; λ represents the thermal conductivity; t represents the preset temperature loading time; c represents the unit specific heat capacity; ρ represents the density.

[0049] Step S3: Calculate the first characteristic value of each stability evaluation point based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group;

[0050] In step S3, the calculation formulas are:

[0051] Ti-Ti′=K1i

[0052] In the above formula, Ti represents the theoretical temperature value corresponding to the position of stability evaluation point i; Ti′ represents the temperature detection value collected by the second temperature sensor group corresponding to the position of stability evaluation point i; and K1i represents the first characteristic value corresponding to the position of stability evaluation point i.

[0053] Step S4: Evaluate the stability of the super-large bridge based on the numerical value of each of the first feature values.

[0054] Step S4, which involves evaluating the stability of the super-large bridge, includes S41-S45, specifically:

[0055] S41: Divide the scaled model of the super-large bridge into sections based on the location of all stability evaluation points to obtain the sectioning information of the scaled model of the super-large bridge.

[0056] S42: Based on the partition information of the scaled-down model of the super-large bridge, calculate all the first feature values ​​in each partition information;

[0057] S43: Fit all the first feature values ​​in each partition information to obtain the first feature curve in each partition information;

[0058] S44: Extract the peak-to-peak value of each first feature curve based on the first feature curve in each partition information;

[0059] S45: Compare the peak-to-peak value of each first characteristic curve with a preset first threshold. When the peak-to-peak value of all first characteristic curves is less than the preset first threshold, the bridge is in a stable state. When the peak-to-peak value of some first characteristic curves is greater than the preset first threshold, the bridge is in a sub-stable state. When the peak-to-peak value of all first characteristic curves is greater than the preset first threshold, the bridge is in an unstable state.

[0060] To clarify the impact of load on the stability of the super-large bridge, a step S5 is set after step S3. Step S5 includes S51 to S54, specifically:

[0061] S51: Obtain load loading information and load information collected by the load sensor group of the scaled model of the super bridge within the preset load loading time, wherein the position of the load sensor group corresponds one-to-one with the stability evaluation point, and the load loading information includes preset dynamic load and preset static load.

[0062] In step S51, a train load intelligent loading system needs to be set outside the scaled model to simulate the train load conditions of different trains under different operating speeds. After the train load intelligent loading system is working, it can obtain the preset dynamic load and preset static load.

[0063] S52: Calculate the theoretical load value for each stability evaluation point based on the load loading information and the preset theoretical load formula;

[0064] In step S52, the calculation formula is:

[0065] Fi(t)=(Psinωt+P0)·S F

[0066] In the above formula, Fi(t) represents the theoretical load value corresponding to the position of stability evaluation point i within the preset load loading time t; P represents the preset dynamic load; P0 represents the preset static load; ω represents the vibration frequency; S F This represents the train load similarity constant.

[0067] S53: Calculate the second characteristic value of each stability evaluation point based on the theoretical value of each load and the load detection value collected by the corresponding load sensor group;

[0068] In step S53, the calculation formula is:

[0069] Fi-Fi′=K2i

[0070] In the above formula, Fi represents the theoretical load value corresponding to the position of stability evaluation point i; Fi′ represents the load detection value collected by the load sensor group corresponding to the position of stability evaluation point i; and K2i represents the second characteristic value corresponding to the position of stability evaluation point i.

[0071] S54: Evaluate the stability of the super-large bridge based on the numerical values ​​of each of the first and second eigenvalues.

[0072] In step S54, to clearly evaluate the stability of the super-large bridge using the first and second eigenvalues, step S54 includes S541-S545, specifically:

[0073] S541: Divide the scaled model of the super-large bridge into sections based on the location of all stability evaluation points to obtain the sectioning information of the scaled model of the super-large bridge.

[0074] S542: Based on the partition information of the scaled-down model of the super-large bridge, calculate all the first and second feature values ​​in each partition information;

[0075] S543: Fit all the first and second feature values ​​in each partition information to obtain the first feature curve and the second feature curve in each partition information;

[0076] S544: Calculate the peak-to-peak value of each characteristic curve based on the first and second characteristic curves in each partition information;

[0077] S545: Compare the peak-to-peak value of each first characteristic curve with a preset first threshold, and compare the peak-to-peak value of each second characteristic curve with a preset second threshold to determine the stability of the super-large bridge.

[0078] To clarify the impact of deformation on the stability of the super-large bridge, a step S6 is set after step S3. Step S6 includes S61 to S64, specifically:

[0079] S61: Obtain the stroke displacement of the electric push rod and the displacement information collected by the laser displacement sensor group of the scaled-down model of the super bridge within the preset deformation loading time, wherein the electric push rod and the laser displacement sensor group are set at the bottom of the scaled-down model of the super bridge.

[0080] In this step, the electric actuator is used to adjust the bridge alignment, enabling synchronous lifting and lowering.

[0081] S62: Calculate the theoretical deformation value of each stability evaluation point based on the stroke displacement of the electric actuator and the preset theoretical deformation formula;

[0082] In step S62, the theoretical deformation value of each stability evaluation point can be simplified to the stroke displacement of the electric actuator, and the data can be displayed through the electric actuator;

[0083] S63: Calculate the third characteristic value of each stability evaluation point based on each of the theoretical deformation values ​​and the deformation detection values ​​collected by the corresponding laser displacement sensor group;

[0084] In step S63, the calculation formula is:

[0085] Ii-Ii′=K3i

[0086] In the above formula, Ii represents the theoretical deformation value corresponding to the stability evaluation point i; Ii′ represents the deformation detection value collected by the laser sensor group corresponding to the stability evaluation point i; and K3i represents the third characteristic value corresponding to the stability evaluation point i.

[0087] S64: Evaluate the stability of the super-large bridge based on the magnitude of each of the first and third eigenvalues.

[0088] In step S64, to clearly evaluate the stability of the mega-bridge using the first and second eigenvalues, step S64 includes S641-S645, specifically:

[0089] S641: Divide the scaled model of the super-large bridge into sections based on the location of all stability evaluation points to obtain the sectioning information of the scaled model of the super-large bridge.

[0090] S642: Based on the partition information of the scaled-down model of the super-large bridge, calculate all the first and third feature values ​​in each partition information;

[0091] S643: Fit all the first and third feature values ​​in each partition information to obtain the first feature curve and the third feature curve in each partition information;

[0092] S644: Calculate the peak-to-peak value of each characteristic curve based on the first and third characteristic curves in each partition information;

[0093] S645: Compare the peak-to-peak value of each first characteristic curve with a preset first threshold, and compare the peak-to-peak value of each third characteristic curve with a preset third threshold to determine the stable state of the super-large bridge.

[0094] This invention can reproduce the test conditions of a super-large bridge under various combined working conditions under service conditions through a data loading system composed of an intelligent temperature and humidity control system, a train load intelligent loading system, and a bridge alignment intelligent control system.

[0095] Example 2:

[0096] like Figure 2 As shown, this embodiment provides a stability evaluation device for a super-large bridge. The device includes an acquisition module 901, a first processing module 902, a second processing module 903, and a judgment module 904, specifically comprising:

[0097] The acquisition module 901 is used to acquire the preset depth of at least two stability evaluation points and the temperature information collected by two temperature sensor groups of the scale model of the super bridge within a preset temperature loading time. The stability evaluation points are set inside the scale model of the super bridge. The first temperature sensor group includes a first temperature sensor and a second temperature sensor. The first temperature sensor and the second temperature sensor are set on the surface of the scale model of the super bridge. The second temperature sensor group corresponds one-to-one with the position of the stability evaluation points.

[0098] The first processing module 902 is used to calculate the theoretical temperature value of each stability evaluation point based on the preset depth of each stability evaluation point, the temperature information of the first temperature sensor group, and the preset theoretical temperature formula.

[0099] The second processing module 903 is used to calculate, based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group, to obtain the first characteristic value of each stability evaluation point.

[0100] The judgment module 904 is used to evaluate the stability of the super-large bridge based on the magnitude of each of the first feature values.

[0101] In one specific embodiment of the present invention, the judgment module 904 includes a first calculation unit 9041, a second calculation unit 9042, a third calculation unit 9043, a fourth calculation unit 9044, and a first judgment unit 9045, specifically comprising:

[0102] The first calculation unit 9041 is used to partition the scaled model of the super-large bridge according to the location of all stability evaluation points, and obtain the partition information of the scaled model of the super-large bridge.

[0103] The second calculation unit 9042 is used to calculate all the first feature values ​​in each partition information based on the partition information of the scaled-down model of the super-large bridge.

[0104] The third calculation unit 9043 is used to fit all the first feature values ​​in each partition information to obtain the first feature curve in each partition information;

[0105] The fourth calculation unit 9044 is used to extract the peak-to-peak value of each first feature curve based on the first feature curve in each partition information;

[0106] The first judgment unit 9045 is used to compare the peak-to-peak value of each first characteristic curve with a preset first threshold. When the peak-to-peak value of all first characteristic curves is less than the preset first threshold, the bridge is in a stable state. When the peak-to-peak value of some first characteristic curves is greater than the preset first threshold, the bridge is in a sub-stable state. When the peak-to-peak value of all first characteristic curves is greater than the preset first threshold, the bridge is in an unstable state.

[0107] In one specific embodiment of the present invention, after the second processing module 903, a third processing module 905 is further included, such as... Figure 3 As shown, the third processing module 905 includes a first acquisition unit 9051, a fifth calculation unit 9052, a sixth calculation unit 9053, and a seventh calculation unit 9054, specifically comprising:

[0108] The first acquisition unit 9051 is used to acquire load loading information and load information collected by the load sensor group of the scaled model of the super bridge within a preset load loading time. The load sensor group corresponds one-to-one with the position of the stability evaluation point. The load loading information includes preset dynamic load and preset static load.

[0109] The fifth calculation unit 9052 is used to calculate the theoretical load value for each stability evaluation point based on the load loading information and the preset theoretical load formula.

[0110] The sixth calculation unit 9053 is used to calculate the second characteristic value of each stability evaluation point based on the theoretical value of each load and the load detection value collected by the corresponding load sensor group.

[0111] The seventh calculation unit 9054 is used to evaluate the stability of the super-large bridge based on the numerical values ​​of each of the first and second feature values.

[0112] In one specific embodiment of the present invention, the seventh calculation unit 9054 includes an eleventh calculation unit 90541, a twelfth calculation unit 90542, a thirteenth calculation unit 90543, a fourteenth calculation unit 90544, and a second judgment unit 90545, specifically comprising:

[0113] The eleventh calculation unit 90541 is used to partition the scaled model of the super-large bridge according to the location of all stability evaluation points, and obtain the partition information of the scaled model of the super-large bridge.

[0114] The twelfth calculation unit 90542 is used to calculate all the first and second feature values ​​in each partition information based on the partition information of the scaled model of the super bridge.

[0115] The thirteenth calculation unit 90543 is used to fit all the first feature values ​​and second feature values ​​in each partition information to obtain the first feature curve and second feature curve in each partition information.

[0116] The fourteenth calculation unit 90544 is used to calculate the peak-to-peak value of each characteristic curve based on the first and second characteristic curves in each partition information.

[0117] The second judgment unit 90545 is used to compare the peak-to-peak value of each first characteristic curve with a preset first threshold, and the peak-to-peak value of each second characteristic curve with a preset second threshold, to determine the stable state of the super-large bridge.

[0118] In one specific embodiment of the present invention, after the second processing module 903, a fourth processing module 906 is further included, such as... Figure 4 As shown, the fourth processing module 906 includes a second acquisition unit 9061, an eighth calculation unit 9062, a ninth calculation unit 9063, and a tenth calculation unit 9064, specifically comprising:

[0119] The second acquisition unit 9061 is used to acquire the stroke displacement of the electric push rod and the displacement information collected by the laser displacement sensor group of the scaled model of the super bridge within a preset deformation loading time. The electric push rod and the laser displacement sensor group are set at the bottom of the scaled model of the super bridge.

[0120] The eighth calculation unit 9062 is used to calculate the theoretical deformation value of each stability evaluation point based on the stroke displacement of the electric actuator and the preset theoretical deformation formula.

[0121] The ninth calculation unit 9063 is used to calculate the third characteristic value of each stability evaluation point based on each of the theoretical deformation values ​​and the deformation detection values ​​collected by the corresponding laser displacement sensor group.

[0122] The tenth calculation unit 9064 is used to evaluate the stability of the super-large bridge based on the numerical values ​​of each of the first and third feature values.

[0123] In one specific embodiment of the present invention, the tenth calculation unit 9064 includes: a fifteenth calculation unit 90641, a sixteenth calculation unit 90642, a seventeenth calculation unit 90643, an eighteenth calculation unit 90644, and a third judgment unit 90645, specifically comprising:

[0124] The fifteenth calculation unit 90641 is used to partition the scaled model of the super-large bridge according to the location of all stability evaluation points, and obtain the partition information of the scaled model of the super-large bridge.

[0125] The sixteenth calculation unit 90642 is used to calculate all the first and third feature values ​​in each partition information based on the partition information of the scaled model of the super bridge.

[0126] The seventeenth calculation unit 90643 is used to fit all the first feature values ​​and third feature values ​​in each partition information to obtain the first feature curve and third feature curve in each partition information.

[0127] The eighteenth calculation unit 90644 is used to calculate the peak-to-peak value of each characteristic curve based on the first and third characteristic curves in each partition information.

[0128] The third judgment unit 90645 is used to compare the peak-to-peak value of each first characteristic curve with a preset first threshold, and the peak-to-peak value of each third characteristic curve with a preset third threshold, to determine the stable state of the super-large bridge.

[0129] It should be noted that the specific manner in which each module performs its operation in the apparatus described in the above embodiments has been described in detail in the embodiments of the method, and will not be elaborated here.

[0130] Example 3:

[0131] Corresponding to the above method embodiments, this embodiment also provides a stability evaluation device for super-large bridges. The stability evaluation device for super-large bridges described below and the stability evaluation method for super-large bridges described above can be referred to in correspondence.

[0132] Figure 5 This is a block diagram illustrating a stability evaluation device 800 for a large bridge according to an exemplary embodiment. Figure 5 As shown, the stability evaluation device 800 for the super-large bridge may include: a processor 801 and a memory 802. The stability evaluation device 800 for the super-large bridge may also include one or more of the following: a multimedia component 803, an I / O interface 804, and a communication component 805.

[0133] The processor 801 controls the overall operation of the bridge stability evaluation device 800 to complete all or part of the steps in the aforementioned bridge stability evaluation method. The memory 802 stores various types of data to support the operation of the bridge stability evaluation device 800. This data may include, for example, instructions for any application or method operating on the bridge stability evaluation device 800, and application-related data such as contact data, sent and received messages, images, audio, video, etc. The memory 802 can be implemented using any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 802 or transmitted via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. I / O interface 804 provides an interface between processor 801 and other interface modules, such as keyboards, mice, and buttons. These buttons can be virtual or physical. Communication component 805 is used for wired or wireless communication between the bridge stability evaluation device 800 and other devices. Wireless communication includes Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination thereof. Therefore, the corresponding communication component 805 may include a Wi-Fi module, a Bluetooth module, or an NFC module.

[0134] In an exemplary embodiment, the super-large bridge stability evaluation device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the super-large bridge stability evaluation method described above.

[0135] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the above-described method for evaluating the stability of a major bridge. For example, the computer-readable storage medium may be the memory 802 including the program instructions, which may be executed by the processor 801 of the major bridge stability evaluation device 800 to complete the above-described method for evaluating the stability of a major bridge.

[0136] Example 4:

[0137] Corresponding to the above method embodiments, this embodiment also provides a readable storage medium. The readable storage medium described below can be referred to in conjunction with the above-described method for evaluating the stability of a super-large bridge.

[0138] A readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method embodiment for evaluating the stability of a large bridge.

[0139] Specifically, the readable storage medium can be a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, or any other readable storage medium capable of storing program code.

[0140] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0141] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating the stability of extra-large bridges, characterized in that, include: The system acquires the preset depth of at least two stability evaluation points and the temperature information collected by two temperature sensor groups of the scaled-down model of the super-large bridge within a preset temperature loading time. The stability evaluation points are set inside the scaled-down model of the super-large bridge. The first temperature sensor group includes a first temperature sensor and a second temperature sensor. The first temperature sensor and the second temperature sensor are set on the surface of the scaled-down model of the super-large bridge. The second temperature sensor group corresponds one-to-one with the position of the stability evaluation points. The theoretical temperature value of each stability evaluation point is calculated based on the preset depth of each stability evaluation point, the temperature information of the first temperature sensor group, and the preset theoretical temperature formula. The first characteristic value of each stability evaluation point is calculated based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group. The stability of the mega-bridge is evaluated based on the magnitude of each of the first eigenvalues.

2. The method for evaluating the stability of extra-large bridges according to claim 1, characterized in that... The evaluation of the stability of the mega-bridge based on the numerical value of each of the first eigenvalues ​​includes: The scaled model of the super-large bridge is divided into partitions based on the location of all stability evaluation points to obtain the partition information of the scaled model of the super-large bridge. Based on the partition information of the scaled-down model of the super-large bridge, all the first feature values ​​in each partition information are calculated. Fit all the first feature values ​​in each partition information to obtain the first feature curve in each partition information; The peak-to-peak value of each first feature curve is extracted based on the first feature curve in each partition information; The peak-to-peak value of each first characteristic curve is compared with a preset first threshold. When the peak-to-peak value of all first characteristic curves is less than the preset first threshold, the bridge is in a stable state. When the peak-to-peak value of some first characteristic curves is greater than the preset first threshold, the bridge is in a sub-stable state. When the peak-to-peak value of all first characteristic curves is greater than the preset first threshold, the bridge is in an unstable state.

3. The method for evaluating the stability of extra-large bridges according to claim 1, characterized in that... After calculating the first characteristic value of each stability evaluation point based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group, the process includes: The load loading information and the load information collected by the load sensor group of the scale model of the super bridge within the preset load loading time are obtained. The load sensor group and the position of the stability evaluation point are in one-to-one correspondence. The load loading information includes preset dynamic load and preset static load. The theoretical load value for each stability evaluation point is obtained by calculating based on the load loading information and the preset theoretical load formula. The second characteristic value of each stability evaluation point is calculated based on the theoretical value of each load and the load detection value collected by the corresponding load sensor group. The stability of the mega-bridge is evaluated based on the magnitude of each of the first and second eigenvalues.

4. The method for evaluating the stability of extra-large bridges according to claim 1, characterized in that, After calculating the first characteristic value for each stability evaluation point based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group, the calculation includes: The electric actuator's stroke displacement and the displacement information collected by the laser displacement sensor group of the scaled-down model of the super-large bridge within a preset deformation loading time are obtained. The electric actuator and the laser displacement sensor group are set at the bottom of the scaled-down model of the super-large bridge. The theoretical deformation value of each stability evaluation point is obtained by calculating the stroke displacement of the electric actuator and the preset theoretical deformation formula. The third characteristic value of each stability evaluation point is calculated based on the theoretical deformation value and the deformation detection value collected by the corresponding laser displacement sensor group. The stability of the super-large bridge is evaluated based on the magnitude of each of the first and third eigenvalues.

5. A stability evaluation device for a super-large bridge, characterized in that, include: The acquisition module is used to acquire the preset depth of at least two stability evaluation points and the temperature information collected by two temperature sensor groups of the scale model of the super bridge within a preset temperature loading time. The stability evaluation points are set inside the scale model of the super bridge. The first temperature sensor group includes a first temperature sensor and a second temperature sensor. The first temperature sensor and the second temperature sensor are set on the surface of the scale model of the super bridge. The second temperature sensor group corresponds one-to-one with the position of the stability evaluation points. The first processing module is used to calculate the theoretical temperature value of each stability evaluation point based on the preset depth of each stability evaluation point, the temperature information of the first temperature sensor group, and the preset theoretical temperature formula. The second processing module is used to calculate, based on each theoretical temperature value and the temperature detection value collected by the corresponding second temperature sensor group, to obtain the first characteristic value of each stability evaluation point. The judgment module is used to evaluate the stability of the super-large bridge based on the numerical value of each of the first feature values.

6. The stability evaluation device for extra-large bridges according to claim 5, characterized in that, The judgment module includes: The first calculation unit is used to partition the scaled model of the super-large bridge according to the location of all stability evaluation points, and obtain the partition information of the scaled model of the super-large bridge. The second calculation unit is used to calculate all the first feature values ​​in each partition information based on the partition information of the scaled-down model of the super-large bridge. The third calculation unit is used to fit all the first feature values ​​in each partition information to obtain the first feature curve in each partition information; The fourth calculation unit is used to extract the peak-to-peak value of each first feature curve based on the first feature curve in each partition information; The first judgment unit is used to compare the peak-to-peak value of each first characteristic curve with a preset first threshold. When the peak-to-peak value of all first characteristic curves is less than the preset first threshold, the bridge is in a stable state. When the peak-to-peak value of some first characteristic curves is greater than the preset first threshold, the bridge is in a sub-stable state. When the peak-to-peak value of all first characteristic curves is greater than the preset first threshold, the bridge is in an unstable state.

7. The stability evaluation device for super-large bridges according to claim 5, characterized in that, Following the second processing module, a third processing module is also included, the third processing module comprising: The first acquisition unit is used to acquire load loading information and load information collected by the load sensor group of the scaled model of the super bridge within a preset load loading time. The load sensor group corresponds one-to-one with the position of the stability evaluation point. The load loading information includes preset dynamic load and preset static load. The fifth calculation unit is used to calculate the theoretical load value for each stability evaluation point based on the load loading information and the preset theoretical load formula. The sixth calculation unit is used to calculate the second characteristic value of each stability evaluation point based on the theoretical value of each load and the load detection value collected by the corresponding load sensor group. The seventh calculation unit is used to evaluate the stability of the super-large bridge based on the numerical values ​​of each of the first and second feature values.

8. The stability evaluation device for extra-large bridges according to claim 5, characterized in that, Following the second processing module, a fourth processing module is also included, the fourth processing module comprising: The second acquisition unit is used to acquire the stroke displacement of the electric push rod and the displacement information collected by the laser displacement sensor group of the scaled model of the super bridge within a preset deformation loading time. The electric push rod and the laser displacement sensor group are set at the bottom of the scaled model of the super bridge. The eighth calculation unit is used to calculate the theoretical deformation value of each stability evaluation point based on the stroke displacement of the electric actuator and the preset theoretical deformation formula. The ninth calculation unit is used to calculate the third characteristic value of each stability evaluation point based on each of the theoretical deformation values ​​and the deformation detection values ​​collected by the corresponding laser displacement sensor group. The tenth calculation unit is used to evaluate the stability of the super-large bridge based on the numerical values ​​of each of the first and third feature values.

9. A stability evaluation device for extra-large bridges, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the stability evaluation method for extra-large bridges as described in any one of claims 1 to 4.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program that, when executed by a processor, implements the steps of the stability evaluation method for extra-large bridges as described in any one of claims 1 to 4.

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